Update Pinot Site from dev branch 7d94757781f6ab627905ddf9e2e82fa87c9c9bbd
commit 7d94757781f6ab627905ddf9e2e82fa87c9c9bbd
Merge: 6c30a73 243803e
Author: Mayank Shrivastava <mayanks@apache.org>
Date: Thu Sep 2 07:10:52 2021 -0700
Merge pull request #58 from joshigaurava/who-uses-pinot
Moved Who Uses section to an independent page
commit 243803e829c00ef40cec57f8a36b97730401cbac
Author: Gaurav Joshi <68965367+joshigaurava@users.noreply.github.com>
Date: Thu Sep 2 07:00:30 2021 -0700
Moved Who Uses section to an independent page
diff --git a/content/404.html b/content/404.html
index a4a801d..742663f 100644
--- a/content/404.html
+++ b/content/404.html
@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,14 +11,14 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
<link rel="search" type="application/opensearchdescription+xml" title="Apache Pinot™" href="/opensearch.xml">
<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Ubuntu|Roboto|Source+Code+Pro">
-<link rel="stylesheet" href="https://at-ui.github.io/feather-font/css/iconfont.css"><title data-react-helmet="true">Page Not Found | Apache Pinot™</title><meta data-react-helmet="true" property="og:title" content="Page Not Found | Apache Pinot™"><meta data-react-helmet="true" property="og:url" content="https://pinot.apache.org/404.html"><meta data-react-helmet="true" name="docsearch:language" content="en"><meta data-react-helmet="true" name="docsearch:docusaurus_tag" content="default"><meta data-react-helmet="true" name="description" content="Apache Pinot"><meta data-react-helmet="true" name="description" content="Real-time Analytics"><meta data-react-helmet="true" name="description" content="User-facing Analytics"><meta data-react-helmet="true" name="description" content="user facing analytics"><meta data-react-helmet="true" name="description" content="Olap"><meta data-react-helmet="true" name="description" content="Consumer-facing facing analytics"><meta data-react-helmet="true" name="description" content="Fast Analytics"><meta data-react-helmet="true" name="description" content="Who uses Apache Pinot?"><link data-react-helmet="true" rel="shortcut icon" href="/img/favicon.ico"><link data-react-helmet="true" rel="canonical" href="https://pinot.apache.org/404.html"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/404.html" hreflang="en"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/404.html" hreflang="x-default"><link data-react-helmet="true" rel="preconnect" href="https://BH4D9OD16A-dsn.algolia.net" crossorigin="anonymous"><link rel="stylesheet" href="/assets/css/styles.f8c6b66d.css">
-<link rel="preload" href="/assets/js/runtime~main.59053854.js" as="script">
-<link rel="preload" href="/assets/js/main.5e591844.js" as="script">
+<link rel="stylesheet" href="https://at-ui.github.io/feather-font/css/iconfont.css"><title data-react-helmet="true">Page Not Found | Apache Pinot™</title><meta data-react-helmet="true" property="og:title" content="Page Not Found | Apache Pinot™"><meta data-react-helmet="true" name="twitter:card" content="summary_large_image"><meta data-react-helmet="true" property="og:url" content="https://pinot.apache.org/404.html"><meta data-react-helmet="true" name="docsearch:language" content="en"><meta data-react-helmet="true" name="docsearch:docusaurus_tag" content="default"><meta data-react-helmet="true" name="description" content="Apache Pinot"><meta data-react-helmet="true" name="description" content="Real-time Analytics"><meta data-react-helmet="true" name="description" content="User-facing Analytics"><meta data-react-helmet="true" name="description" content="user facing analytics"><meta data-react-helmet="true" name="description" content="Olap"><meta data-react-helmet="true" name="description" content="Consumer-facing facing analytics"><meta data-react-helmet="true" name="description" content="Fast Analytics"><meta data-react-helmet="true" name="description" content="Who uses Apache Pinot?"><link data-react-helmet="true" rel="shortcut icon" href="/img/favicon.ico"><link data-react-helmet="true" rel="canonical" href="https://pinot.apache.org/404.html"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/404.html" hreflang="en"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/404.html" hreflang="x-default"><link data-react-helmet="true" rel="preconnect" href="https://BH4D9OD16A-dsn.algolia.net" crossorigin="anonymous"><link rel="stylesheet" href="/assets/css/styles.14a15550.css">
+<link rel="preload" href="/assets/js/runtime~main.664acf57.js" as="script">
+<link rel="preload" href="/assets/js/main.a1de4389.js" as="script">
</head>
<body>
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stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper"><main class="container margin-vert--xl"><div class="row"><div class="col col--6 col--offset-3"><h1 class="hero__title">Page Not Found</h1><p>We could not find what you were looking for.</p><p>Please contact the owner of the site that linked you to the original URL and let them know their link is broken.</p></div></div></main></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a 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class="footerLogoLink_qW4Z"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
-<script src="/assets/js/runtime~main.59053854.js"></script>
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+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img 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class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener noreferrer" class="footer__link-item">Getting Started</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Pinot Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/users" target="_blank" rel="noopener noreferrer" class="footer__link-item">User Guide</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Administration</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Community</h4><ul class="footer__items"><li class="footer__item"><a href="https://join.slack.com/t/apache-pinot/shared_invite/zt-5z7pav2f-yYtjZdVA~EDmrGkho87Vzw" target="_blank" rel="noopener noreferrer" class="footer__link-item">Slack</a></li><li class="footer__item"><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Github</a></li><li class="footer__item"><a href="https://twitter.com/ApachePinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Twitter</a></li><li class="footer__item"><a href="mailto:dev-subscribe@pinot.apache.org?Subject=SubscribeToPinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Mailing List</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Apache</h4><ul class="footer__items"><li class="footer__item"><a 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class="margin-bottom--sm"><a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footerLogoLink_qW4Z"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
+<script src="/assets/js/runtime~main.664acf57.js"></script>
+<script src="/assets/js/main.a1de4389.js"></script>
</body>
</html>
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diff --git a/content/assets/css/styles.14a15550.css b/content/assets/css/styles.14a15550.css
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+++ b/content/assets/css/styles.14a15550.css
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diff --git a/content/assets/js/4300.db52424e.js b/content/assets/js/4300.72f4995f.js
similarity index 99%
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"})),I.createElement("image",{x:370,y:82,width:51,height:83,xlinkHref:"data:image/png;base64,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"}))),I.createElement("image",{x:342,y:60,width:51,height:83,xlinkHref:"data:image/png;base64,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"})),I.createElement("image",{x:370,y:82,width:51,height:83,xlinkHref:"data:image/png;base64,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N0XvlcsBNRuvjlDGTleo5WRoJOQ2VDN1N1JQNhoA2T8SWdG4igRWMw8koEEAAAQQQQAABBBBAAIGCCEgiQieUdu4I579NF38B9/4odZ2d18iC7pcFfEF3Z9hhSQ6+ozdRZUhX9X8f8Lx4AsbWdzutS/KUDQEEEEAAAQQQQAABBBBAAIG9AlsurYnJo6P96GFMada/6mvjLOhulHW57COr0xeGxwgUSMAY+xanKRJYBQKlGQQQQAABBBBAAAEEEEAgCAKZtOXP2VeCL9eyPVaOYyBrQ62W2UlLytE3fSIQcIHHJtzS9TdnjCSwAn6kGR4CCCCAAAIIIIAAAggg4EbAVsqf61/JDKjd1vCDFhl3M+58y6ZT4f8nbezItx3qI4BAHwGjf7n/GQms/RJ8RQABBBBAAAEEEEAAAQQQcAT8msBqn9Sy6aVyHUJnQXe5hvDKcvVPvwgEUODfw9LdN+0fFwms/RJ8RQABBBBAAAEEEEAAAQQQkLXIfZvAKsvlg33fMnWp5DWSxPp73308RgCB3ASMVteMbdu+a39tElj7JfiKAAIIIIAAAggggAACCFS4wCOLpkSE4CRfMmjzz3LHrdtURhnrExIHC7qX+2DQv98FXq7qSV/TdxAksPpq8BgBBBBAAAEEEEAAAQQQqGCBMTu3nyjDr/YjgbHLs4B7fytnQXel9M399/McAQSyF5DZV98b37Z1e98aJLD6avAYAQQQQAABBBBAAAEEEKhgAa2NX9e/Usa2H/fKoUub3gXdX/RKPMSBgM8EnutRw77XP2YSWP1FeI4AAggggAACCCCAAAIIVKqAtk/16dC765/dstErsR+/dPOz2qiveiUe4kDAVwLafGWgGzKQwPLVUSRYBBBAAAEEEEAAAQQQQKCIAsY6vYitF7Fp/S+9QqWL2IHrpqPp5M9Y0N01GxUQeDTW03ndQAwksAZSYR8CCCCAAAIIIIAAAgggUJECxq8zsMq+gHv/t0vvgu7avlz2s6B7fxyeIzCwQFpp/dHe750BXieBNQAKuxBAAAEEEEAAAQQQQACBShPY1jBmhIx5gi/Hrb2xgHt/u/qWrjWSv/p1//08RwCBQwUk0/vNupbEXw59Ze8eEliDybAfAQQQQAABBBBAAAEEEKgggZ6qKmf2lfbjkI2tH/Nq3D2h9BUS2wtejY+4EPCIwKPbR4z75uFiIYF1OB1eQwABBBBAAAEEEEAAAQQqRMAo7ds7ENppyzN3IOz/djnh5me3SVaQBd37w/AcgQMCL1sZ03TmtY+mDuw69BEJrENN2IMAAggggAACCCCAAAIIVJyArZRfE1jPTWxr3+rlAxZNJX8uSay/eTlGYkOgXAJaq89Eb+3cMFT/JLCGEuJ1BBBAAAEEEEAAAQQQQKASBIzy5QLukhjy7OWD+982zqLU2piPy3MWdN+PwlcE9gr8LtaSHPCug/2BSGD1F+E5AggggAACCCCAAAIIIFCBApII8mUCyxjvrn/V920UXdq5TvJXN/bdx2MEKllAPnOe3KOHfSBbAxJY2UpRDgEEEEAAAQQQQAABBBAIqED7gvrxMrQxvhyepTy7/lV/TyusPi/7nu+/n+cIVKDAC8pS509q2fRStmMngZWtFOUQQAABBBBAAAEEEEAAgYAKWMb26/pXzhHxTQIrelPn80rrKwP6NmJYCGQrYMvsqwWxJclN2VZwypHAcqNFWQQQQAABBBBAAAEEEEAgmAJ+TWDZVVbPv/x0SGKTEj+XeB/2U8zEikBhBfQVsdbkH9y2SQLLrRjlEUAAAQQQQAABBBBAAIGgCRh7sk+H9PRxNz/7sp9i14uVbWnzKYlZbvzIhkClCeib6loT381l1CSwclGjDgIIIIAAAggggAACCCAQKAF9uh+HI7f08/wdCAdyjbZ0/ln2/+9Ar7EPgeAKmNV7XqhelOv4SGDlKkc9BBBAAAEEEEAAAQQQQCAAAqZBhWQYp/hxKHJC65v1r/r7WmFzhex7rv9+niMQUIFnIqnMRZOWbdqT6/hIYOUqRz0EEEAAAQQQQAABBBBAIAACnVbta2UYR/hyKEb905dxS9B7F3Q3X/Fr/MSds8AumTn4B1nM/3PaqIU5t+Kviv+2Mmbe+Lat2/MJmwRWPnrURQABBBBAAAEEEEAAAQR8LmAs7dcF3JXS/ryEcP9bJtbTeZ08fnT/c74GUqBHRrVS7rq32Bhr1rYR40bXtybfWdeS+J68f53kcdC3Hm2p90Zv7dyQ70DD+TZAfQQQQAABBBBAAAEEEEAAAf8KyP3sT5OTaz9ur0RPTD7tx8D3x6zbVCYxX33cWGqt7GOCyX4Yf3+Vxfn135Uy98sMq/si4dSqg280EO8d3eaGCccZlb7c30PNInqjPxJbkliRRckhi5DAGpKIAggggAACCCCAAAIIIIBAoAVO9eno/unc0c+nsb8aduyW5EMdTdEbJIn4oVd38sBvAjK7yNxntLo/FFIPRG9KPn+4AcglhDoRSd8gZY49XDm/v6a1ujrWmijYzQpIYPn9HUH8CCCAAAIIIIAAAggggEAeApI44Q6EefgVoqqVUleYiHqPtBXohEYhrLzRhnlWK2ulrczyjMr86fjWLR1u4ko0xb4hCa95bur4rawk6X4bm5T8UiHjJoFVSE3aQgABBBBAAAEEEEAAAQR8JNC1qOaI9C51vI9C7huqbxdw7zsI53GsLfnvjsbaL2utf9H/NZ57QuBFiWKFLLy+3E6n759w65Ynco2qo7n2/cqYL+Za3yf1Hpak7MJCz5AkgeWTo0+YCCCAAAIIIIAAAggggEChBdIvhV6nLBMqdLulaC+kzGOl6KdUfdSd1HldYmP0A8qoqaXqk34GFUjLK/+Q2YnLbWUv3z5i/INnXvtoatDSWb4QXxCbpWzzyyyL+7OYUZ06oi6KtSZ3F3oAJLAKLUp7CCCAAAIIIIAAAggggIBfBCzl1/WvVCiVCcwMLOft4sxW6WiyPq6V/bA8ZUH30n8PPbM3YWWW9+jhf5rUsumlAyF0HXiY46OOprrjlW3/VqpX59iE56vJZYM75Y37jthNyc5iBEsCqxiqtIkAAggggAACCCCAAAII+ELAPk1SJ76ItF+QXePbtm7vt8/3T+tb448mmqLXSyJgke8H4/0BbNFKr3bWsbLC6vfFSro4DImG6Gij7GXycIz3WXKOMKOM3Rxb2lW0mZEksHI+NlREAAEEEEAAAQQQQAABBHwvIAksX26P+zLqbIJOqS8ouQRLirKgezZe2ZfZJcnaPxtJWMkEt+VOsjD7qrmXfGTRlIja9WybtHBi7q14v6akwT9dt7Tr7mJGSgKrmLq0jQACCCCAAAIIIIAAAgh4WUDr02TNJd9tRquizfIoN0bvgu5N0S9JQiDYayUVH7oo61i5DXvcrmevkW+xc93W81N5ea/+WNa8uqbYMZPAKrYw7SOAAAIIIIAAAggggAACHhToaqw5Nm3UcR4MbeiQjAnuDCwZfd2JyetlQfcPsqD70G+FfiVeXcfqiGF7/jjmhud2Hng9/3WsDrSV3aN4Y+xLMuMr2JeDavXHaGfys9mJ5FeKBFZ+ftRGAAEEEEAAAQQQQAABBHwpYDuzr3y6yW0TA53A6rOg+0NyiHx5l8gSvbVeXcdK2/qeulsSpc9SDTLQjuba9yljvj7Iy0HZvT7VUzVfr1DObLeibySwik5MBwgggAACCCCAAAIIIICA9wQySr/Zl8u3K5VOVUWe9J5oYSNy1miKN8eulyTIfxa2ZV+39rwsvH6/s/D6vnWsnvHiaBLzo1ONUTdJbHJTvsBuW0K2Pa+u7ZkdpRohCaxSSdMPAggggAACCCCAAAIIIOAhAW3U2/15A0K1YeKN7d0eoixaKLrHfNHsXdA9yHevO5zfbll4fc3+hdfrToz/zZmddrgK5X7tmabx9RLvnRL38HLHUsT+d2tbXVh7S1eiiH0c0jQJrENI2IEAAggggAACCCCAAAIIBFsguaD2DNtWM/05ymCvf9X3mDgLuicao1+UReuv67s/wI+d5NRftVbLnVlWdiSyxk/Jyo3NJ4wK2933SGJ4XJCPkSS/F8ZuSTqXt5Z0I4FVUm46QwABBBBAAAEEEEAAAQTKK5BoiI6W5NWvJAp/ng8aK9DrX/V/d0RPSt4gC7p/KMALum+S2UrLjbbvs3r0/U7Srr+BH56bOSqcUN23SvLqVD/Em2uMckfFL9YtTf421/r51PPnB1Y+I6YuAggggAACCCCAAAIIIFCBAmaxsuJP1bzTaPNjSRhM8C1BKNgLuPc/LgFc0H27UuZ+bfTytAkvn3hLe3v/MfvxeaK29keSZHy7H2PPOmajbqhfmvzvrMsXuCAJrAKD0hwCCCCAAAIIIIAAAggg4BUBmS2hE/NjU2Qp6QsTG+wmrfUEr8SWaxy2rqwZWI5T74LuTbXXyuH8aK5uZaz3ivS9ypllZduZ++pP7vqH19excmvV0RT9lCSvPua2np/Ky2fJA9tHjvuIUsmyhe3Tm06UzYuOEUAAAQQQQAABBBBAAAFPC5gGFYqH66ZZ2m6Qk84LJdiYpwN2F9xLsdbk0XIiK0OrrK2jqe4YreynZNReX9A9IzH+XY6RrGNlL7erqlb7aR0rt++qRHN0ntxx8G6pF3Jb1y/l5ZtN3nfWNEmkvlDOmElglVOfvhFAAAEEEEAAAQQQQACBAgjIulbD7bA919LWu+QOaBfIbJeALiKt19S1Jny6+Hz+BzrRFP0PSSZcn39LBW/hmb0JK7PcSun7/LqOlVuVjsa6yVrba6TeUW7r+qj883Jsp0nieGO5Y+YSwnIfAfpHAAEEEEAAAQQQQAABBHIQ6F2MPWLOs5Q+35lppZU1Yu+0pCDPU7Afy4EqMFWirckb4pLEchIKZR7Udq30it47Bdrhe4OyjpUb0/YF9eO1nfmD1Aly8iplKdMQbe0se/LKOTYksNy8QymLAAIIIIAAAggggAACCJRRoHN+TSxtWfMspZyk1dskiRDZm7QqY1Al7bry1r/qyyuJK9Nu2Zdr23pY9pfykjVZx0qvldl9y+VSsuV1J8b/FrR1rPo6D/XYmfFoTOZ2KVc3VFkfvy5XRpr/kOTVA14ZAwksrxwJ4kAAAQQQQAABBBBAAAEEBhCQtY+OV8o+X5JVDRllpksSQ1dW0uoAijH68QPPKvPRhCVdf4031/5SGV3MRcMPWseq54UjVk1atmlPZYofPGrnbp6Jp1SLrMI29eBXgvXMaHVVfUvnzV4aFQksLx0NYkEAAQQQQAABBBBAAIGKF3BOkOMb6t7Qm7TS5mJl7FP2olRq2urVt4Sxq61/vvqsgh8YE/qyvD/eJ8nMsQVkeHUdK5nctbzcC3YXcFwFbSq+MXq11r03Ryhou15qTJLlbbGWxGIvxeTEIu93NgQQQAABBBBAAAEEEEAAgXIKHHTnQKPeK2dqteWMx6N9x+tak/Ueja3kYcWbYx9Uxvwq144lHbpN1k970FnHKqMyfzq+dUtHrm1VSr18zX3i9Eh4hH12zbVdctmotzYSWN46HkSDAAIIIIAAAggggAACFSKw/YPHjnxld/U8ben3yOVI75BhB3kx6LyPqsx6+X2sJfmuvBsKSAOSgNKyoPt9clJ/TpZD2iWGvQkrbck6VjcnmM2WJZxTrKO59jxt9DJ5GHFRzW9FN/eEUmedcPOz27wYOJcQevGoEBMCCCCAAAIIIIAAAggEUmDTwnFjq9ORdytLvWd3tzpPEgrDJHnFlp1Axa9/1ZdJElcmqc2lttJ/kffQcX1f2/c4LTmuh5yF1yVJet+2I8b++cxrH00NUI5dQwhsbqw5WZJXbVIsyMmrHUZb7/Jq8so5RCSwhnij8jICCCCAAAIIIIAAAgggkI+Aswi7NuY9km94j8qo6bI4coikVU6iJLD6sUVbOpPx+bEpyjLfkZfOkPdYlzLWeqMy9x8xvGfFmBue23mgSuLAQx5lLdDVWHNsWlv3SIVjsq7kv4JppfXF9S3xf3k5dC4h9PLRITYEEEAAAQQQQAABBBDwpUBHY91kpe13yWLI50tSYboMgnOvPI+kMdap9Uvj6/NshuoIZC2wvmFy1cjwjj/Jd++crCv5saDRH69bmviZ10NnBpbXjxDxIYAAAggggAACCCCAgOcFeu8c+FTddEuSVnJF4IVyh7gT9wbN9YEFOng9u9IjNxaoLZpBYEgBZ42xZGTH9fJ1zpCF/VzAmO/VLU16PnnlEJPA8vMbjdgRQAABBBBAAAEEEECgbAKbL5swzOrpmWkp6/zEBtWgtT2edFWRDodRT0xuW99TpNZpFoFDBGSB/Ctl2uTCQ14I0A75vPpDXbrzCr8MiQSWX44UcSKAAAIIIIAAAggggEDZBbYuHHfknnToXEtbDaYnfYFS1iiSVsU/LMZSrH9VfGZ62CfQ0Vh7sSSvvhpkEBnf34al9lwiS9Nn/DJOElh+OVLEiQACCCCAAAIIIIAAAmUR2NJw3JieSGiepXRDT0a9Ve4cWEXSqrSHwlIksEorXrm9tc+vma61/rUISI4nsNsWy7YvGNu2fZefRkgCy09Hi1gRQAABBBBAAAEEEECgJALxS2Kv1Za5SO4YeFFKqTfLmaxF0qok9IN1wgyswWTYXzCB3juGKvsOaXBYwRr1XkMv25b9rrrWLt/dlpIElvfeTESEAAIIIIAAAggggAACZRDof+dASVgFeQZGGYTz6DKkHsujNlURGFJgY/MJo7Tdfad8148ZsrB/C9jK6AUTlnT91Y9DIIHlx6NGzAgggAACCCCAAAIIIFAQgX1JK1mA3VysjH3K3kaZa1UQ3MI18u/YTcnOwjVHSwgcLPDIoimR6l1bb1Nan3rwKwF7ZvTn65YmnBlmvtxIYPnysBE0AggggAACCCCAAAII5CJgFisr/lTddEvb75I01fuUsl/b245cK8jmUQHD7CuPHpnAhDV219YfyYTLtwRmQAMP5FeSvPr+wC/5Yy8JLH8cJ6JEAAEEEEAAAQQQQACBHAVMgwrFw3XTJGnVkNioLtbaPo45VjlilqEadyAsA3oFdZlojH5ePg8+GughG7ViZ/qojymV9PUwSWD5+vARPAIIIIAAAggggAACCAwk0LWo5ojMTmueswi7rFT8Tq3so3qTVmSuBuLy9D7uQOjpw+Pr4OKNsfcYba729SCGDv5fmerwhZOXru8Zuqi3S5DA8vbxIToEEEAAAQQQQAABBBDIUmDzZROOtnpSb7GUPj+9S10oizGPyLIqxTwsYBvLlwtOe5iU0ESgfX7NG5Q2S+Sh5EgDuz2nLXXBxBvbXwzCCElgBeEoMgYEEEAAAQQQQAABBCpUIHlp7WsyafVOSVo1mJ70W2UdmyomWQXqzZCyq6z1gRoRgym7QHx+rEZZ5i4J5MiyB1O8ALpt275gQmvXpuJ1UdqWSWCV1pveEEAAAQQQQAABBBBAIE+Brktr6lJp6+0ybeJ8O63eLsuvh0la5Ynq0epyXNfL7JFuj4ZHWD4U2NYwZsRuy/xePjeiPgw/25Cd21J8aMItXWuzreCHciSw/HCUiBEBBBBAAAEEEEAAgQoX2NxYc7Jl6Qu10Rel0+pM556BJK2C/6bQyvw9+KNkhKUScG7okIgMa5X31etL1Wc5+tFGLY4tTbaUo+9i9kkCq5i6tI0AAggggAACCCCAAAI5C3Q01k1WcudASVa9SxqZQsYqZ0rfVtRaP+Hb4AnccwKJcOy7kvo+33OBFTQgc2t0aedVBW3SI42RwPLIgSAMBBBAAAEEEEAAAQQqXcAsVlZ8Q90blLLPl6RVo3w9sdJNGL/aiAEChRBINEY/JHcc/HQh2vJuG2b1nheGv18+PwM5QZUElnffeUSGAAIIIIAAAggggEDgBZxLeuLhummWzLRKbFDv08quCfygGWDWAsbSJLCy1qLgYALxptjbjDI/H+z1gOzf3BNKv3fSsk17AjKeQ4ZBAusQEnYggAACCCCAAAIIIIBAMQU2XzZhWCideavKqIsS2shsK3t0IKcLFBOxMtq2dbd5ujKGyiiLJdB7KbKyb5X2g5z/eCFj7HeccPOz24rl6IV2g3wAveBLDAgggAACCCCAAAIIICACXYtqjkjtVOdZ2mowPekLZNco5azEzobA4ALrY23J3YO/zCsIHF6gq7Hm2LS275RSRx2+pK9fTcmlkQ0TW7ue9PUosgieBFYWSBRBAAEEEEAAAQQQQAAB9wLJS2tfY2esC7QxF6Z3qbdoraqZaeXesXJr6OWVO3ZGnq9AoiE6PK3V3dLOa/Nty8v15e8AH61r6bzPyzEWKjYSWIWSpB0EEEAAAQQQQAABBBBQcnng0aFU5iJZQrjRTptzZC3hEEkr3hjuBUx7pir8dff1qIFA7wrmOlGlb1TGnBVkD2PU/9QtTf4qyGPsOzYSWH01eIwAAggggAACCCCAAAKuBZyZDnaVeae2dZPqSb9DGqh23QgVENgr0C3Jz1ad1p+f2Nr+IigI5CKQaK69SpJXF+dS10d1fld3UvILPoo371C56jxvQhpAAAEEEEAAAQQQQKAyBRLN0dOMMR9VSjeLwKjKVGDUBRDokfXQ7pfZJLdbKXWbrHv17wK0SRMVKtDRVHupVvrXAR/+I+ER9tk113a9EvBxHjQ8ElgHcfAEAQQQQAABBBBAAAEEDiewvmFy1YjIixdoZS2SC3XOk7KcUxwOjNcGE3hF3jj328q0pVPVd7627ZkdgxVkPwLZCsgdB2dqbTtrpwV5FmiXpc3UaEtnMluXoJTjh01QjiTjQAABBBBAAAEEEECgiAJymeBoO6I+KV18VE4ixhaxK5oOrsB2Gdpdcse0O+xIZPnEG9u7gztURlZqgURTdJKst7dO+n1NqfsuVX8yvp0hy8yKLun8R6n69FI/rIHlpaNBLAgggAACCCCAAAIIeEzAuQ19SluXy4nTpyRxdbTHwiMc7wvE5X3zR9vY92wfOf6PZ177aMr7IROh3wR6E+xK3S3vtcAmr+SY2NrSC6JLkhWZvHLekySw/PadSbwIIIAAAggggAACCJRAoH1B/XjLtj+fVmaRnBQeWYIu6SIoAkb9U2lzu22ZOyYs6frrgWF1HXjIIwQKJOBc1mzCO34rn1MnFahJTzYjf0T4TP2SxF2eDK5EQZHAKhE03SCAAAIIIIAAAggg4AeBvWtc7fiosjNXSbwj/RAzMZZdwJYI/iYn2PfITKtbJi7terLsERFAxQiMiuz4ibz35gR5wHKDg+vqlyZ/HOQxZjM2EljZKFEGAQQQQAABBBBAAIEKEOhorDlf6x0/lKEeXwHDZYj5CWRk/f4/G1mE3QrLnQNvSnbm1xy1EXAvEG+q/aIkr+SGEoHe/lS3JfmxQI8wy8GRwMoSimIIIIAAAggggAACCARVoP2S8adYobD8dd/MDeoYGVdBBF7WRi2T+07eka4K/14WYX+xIK3SCAI5CHQ0175PGe3MFA3y9vgePexivUKlgzzIbMcml4myIYAAAggggAACCCCAQCUKyMwFHW+KflhOCn4g4z+iEg0Y85AC/5b3x+9tZe4enupZNrZt+64ha1AAgSILdDTVTdHKXindBPdzS6utaZM56/jWLR1F5vRN8ySwfHOoCBQBBBBAAAEEEEAAgcIJbG6YcFwokr5BWpxXuFZpKSACCTlRXMadAwNyNAM2jMSl0VqTUg/JTMDagA2t73C6LW3OibZ0/rnvzkp/zCWElf4OYPwIIIAAAggggAACFSeQaIy+3ej0Uhn40RU3eAY8mMC/nDsHqox1R+yWxKOSwJIJes7GnQP3OvC/FwQ2Np8wyqS7nctYg5y8kjXbzaUkrw59x5HAOtSEPQgggAACCCCAAAIIBFagoym6SDIT18gAI4EdJAPLVuBf8l5oM5nMrRNu3fJEtpUoh0A5BEyDCiXMniXS92nl6L9UfRptvlTf0tlWqv781A8JLD8dLWJFAAEEEEAAAQQQQCBHgd6Tv0jUucPg5Tk2QTX/C6Rk2bMHZW7V7Tpi7uTOgf4/oJU0gkQk+iOZGHh+sMdsbpTk1beDPcbcR0cCK3c7aiKAAAIIIIAAAggg4AuB3sXaI9FfyGVhH/JFwARZSIHdctzvs5W6OxVK3XHCzc9uK2TjtIVAKQRk5uinpJ+Pl6KvsvVh1Ko9Lw7/SNn690HH8lnGhgACCCCAAAIIIIAAAkEVcJJXiabYz2TmAidGQT3Ih47rBa30clvZ98idA3/HnQMPBWKPfwQSzdF5sijUXRJxkCfgPBNJpc8a37Z1u3+OTOkjDfIboPSa9IgAAggggAACCCCAgMcEEk3RH5O88thBKU44SWn2Dlk/5466zs4H9QqVLk43tIpA6QSSC2rPyNjqVpl5E+TcxfMyvreTvBr6fRXkN8HQo6cEAggggAACCCCAAAIBFog3xT4qySvWvAruMX5GTnzvsY3VVrc0vkYey4Q7NgSCIbC5YcJxtp2+S97XI4MxogFHkbKNuXjC0s6NA77KzoME5L3AhgACCCCAAAIIIIAAAkETSDbXnmUbmYejVHXQxlbh4+m9c6BS1t31rfFHK9yC4QdUINEQHW6q1AOSkp0a0CH2DktrtSjWkrwuyGMs5NiYgVVITdpCAAEEEEAAAQQQQMADAslLa19jp/RtSpO88sDhyDeEtMw6WCmN3K7l8sBoS6dzqSAbAoEVMIuVldiglgQ9eaW0+WaspZPklYt3MgksF1gURQABBBBAAAEEEEDADwJ2yvqenBzV+iFWYhxQoFuSVrIIu7o7YyJ3Hr9087MDlmInAgEUiD8V/bbMTLoogEN7dUjaqNuiJ3Z+9dUdPMhKgEsIs2KiEAIIIIAAAggggAAC/hBINEbPNlouvZG7D/ojYqLcJ/DqnQOPGLbn9jE3PLcTGQQqTSDeGPuAJN9vCPi4HwmPsM+uubbrlYCPs+DD44dawUlpEAEEEEAAAQQQQACB8gg8smhKZOyuZ/8pvZ9Yngjo1aVAl6y7fqcxodu3jxyz4sxrH025rE9xBAIj0N5Ye66l9R9lQJHADOqQgZj2tKk6i1mVh8BktYNLCLNiohACCCCAAAIIIIAAAt4XGLtz2wKZd0XyytuHarPMIri7986BJ8XX6sVKrhR0tvjeL/yPQAUKdC6oOSljy7p9AU5eyS1Cd1pGX0DyKvc3OAms3O2oiQACCCCAAAIIIICAZwSchY/jG8wVXGLhmUPSNxDuHNhXg8cI9BFwbjqRSeu7ZdcxfXYH7WFGLo1sirV2Pha0gZVyPCSwSqlNXwgggAACCCCAAAIIFEkgvqH2vZK8OqlIzdOsO4GM3EFtlaxFdnskbN9Rc1MX06vc+VG6QgQ2zjuh2k7vvkOGOynQQzb6k/WtyXsCPcYSDI4EVgmQ6QIBBBBAAAEEEEAAgWILaK0/KEkTtvIJdMu6+auNMvfYqfCtE9vat5YvFHpGwPsC8nGlk8d0X2eUnun9aPOI0Ogf1i1N/CyPFqi6T4AEFm8FBBBAAAEEEEAAAQR8LtDVWHNs2qjzfD4MP4b/ssx6e8BWpq1HD79jUsuml/w4CGJGoBwCyaboVyWJtbAcfZewz2WxdOJzJewv0F2RwAr04WVwCCCAAAIIIIAAApUgkNLWRZJICfCduzx1FJ8T62W2sdt2pY/50+S29T2eio5gEPCBQEdTbYMkr670Qaj5hLg+lapq1G0qk08j1D0gQALrgAWPEEAAAQQQQAABBBDwpYAkVN7my8B9E7Rp10rfZSv77rqurhV6hUrvDb3LNyMgUAS8IhBvjr1JGXOjxCMfXYHdtoRse15d2zM7AjvCMgyMBFYZ0OkSAQQQQAABBBBAAIECC7y5wO3RnFLcOZB3AQIFFtg8f8IEZVJyx0F9RIGb9lJzuyUz957aW7oSXgoqCLGQwArCUWQMCCCAAAIIIIAAAhUr0L6gfryyM9GKBSjcwG05qV4ni7DfHcqY26O3dm4oXNO0hAACG5tPGBUy3XfJ99m4AGvYWqvmWEvy4QCPsWxDI4FVNno6RgABBBBAAAEEEEAgf4FQJnOGCfKFOPkTHa6FPXKyuVzu3nh7OJW+a3zb1u2HK8xrCCCQm8Aji6ZEqndtvU2SV6fl1oI/ammj/ivWmrzdH9H6L0oSWP47ZkSMAAIIIIAAAggggMCrAnIL+vFKMjBsWQs461fdY4xZesTwPcvG3PDczqxrUhABBHISGLfr2Wvks+otOVX2SSX5FL6+bmnyOz4J15dhksDy5WEjaAQQQAABBBBAAAEE9grIJW/jmICV1buhW2Z/fF/Z6qd1tyRYpQ4XEgAAQABJREFUfT0rMgohkL+ALNr+WUkYL8q/Je+2IJ/B920bMe5jSiW9G2QAIiOBFYCDyBAQQAABBBBAAAEEKldAaz2WGVhDHv+NRlvvqW+J/2vIkhRAAIGCCcSbYhfIHQf/p2ANerEhbZ5IRyLvO/PaR1NeDC9IMVlBGgxjQQABBBBAAAEEEECg0gS0MvxOP8RBl0t7ZIH2zFsTDdHRQxTlZQQQKJBA+4KaN0pyvUWaC/Jn1HaVts6feGP7iwVio5nDCAT5jXSYYfMSAggggAACCCCAAAKBEZBL49gOJyCX95ykjf6BiaiuRFPsNx1NNXMlqcWVl4dD4zUE8hDY1jBmhGVbt0gTR+bRjNer9mhLXVx3a+JprwcalPi4hDAoR5JxIIAAAggggAACCFSkgEwt6iYTk/Whr5Y1wxq0shriTdGn4lpfF7Yzv65Z2vVc1i1QEAEEhhTYHan+gXwuTRqyoI8LyB0HPxdbklzh4yH4LnRmYPnukBEwAggggAACCCCAAAIHCbxw0DOeZCXgzMqStXm+m9ZWMt5Uu7S9sfZcZmVlRUchBA4r0NVYc6x8f1122EI+f1HGd190afIanw/Dd+EzA8t3h4yAEUAAAQQQQAABBBA4IGBss0lbcjrFlqtAtVxNOF8I5yeaohsTWl2/x0rdeMLNz27LtUHqIVDJAulQ6BRlm0DnGmxlXy2fupLzZiulQKDfVKWEpC8EEEAAAQQQOCAwc+bMY4wJy5oz5hT5/W6sXLIzSis9QkoMk+e75GTxJbml9g45YUxkVOTva9fe/4y8xi+CBwh5hEDWAiFLb+CbJ2uuoQpOMkb9d1UmclWiMXqXraxr606K36cXO4vAsyGAQFYCWgV+VqiVsv6alQWFCirAn2oKykljCCBQLIFp06aNDlmRb8nprfvPLaOXr173YFuxYitHuzOmzfq03DZdEgMF29LS3vPyV/zntTbPG8s88cILLzy+fv36noL14IOGZk6b/Sl5h70uh1B3r1678tM51AtMldlTZ0/KhM152ljnSR5qhgxsvMvB7ZTyj0hS666ICd2x4s8r2l3WL2nxWdNnzZePo3PcdGoZ9YuV61b+zU2dXMvOnD77S1K3zk39VGbP5x966KGX3NQpRdk5b5pzXDpif60UfQ3Vh9GZz61Zs8Z5r3pqe2TRlMjYXc9KYlhVeSqw4ATzjNHmeqPDN05Y0rElOMNiJAgUR8AsVlZiQ/Qpaf2E4vRQ/lYtbWLRls5k+SOprAjcnwhWlg+jRQABjwjMmjH7O/IX0c/lFo6+Z/XaB8/Pra43a82YPnuzfIBPKHJ0u6WPB+Qk/bYjdlX/5t7H7n25yP2Vtflp0+acHNL24xJETrOTbZUet3bt2oq63GTatHNrQzq9QMwuk38ny7+CbfLe+4uRO4aFq3XbihUr0gVruEANzZo++08y4+WtbpqTmRynrV274p9u6uRYVksCy7md9ygX9XdKEvYoKe+5iTwzZ559vlyKcpeLsRSr6A4xOsaLRs6A443RlZKAn1WswdNur0BKvkPukc+na6MnJe9lVhbvCgQGF5B15T4js62/P3gJv7+iP1DXmrjR76PwW/ws4u63I0a8CFSggHOSLMmrj+U+dHNG7nW9V3Pq1KlyKZaqL0Fkw+VM9h1yPnvDKyO6k7NmnP3VOXPmOJeABXILa/u/ZWA5Ja8cEMuuOj2QMAMMavr0s6fNnH723ZK86pCXr5Z/BU1eOV3Ke+9NSpvWdI/91KyzZjkzujy1SXynuQyoZ8eO7Rtc1smp+OzZsydIRTfJK6cfJ3krw/LeJnd5cmtdnEFo5SQfPWnkDNhodX9xBk6rfQQikiS8UKyXJZ6KxmW9rKufaRpf3+d1HiKAwD6BYame6+ST6dmggmhlPhnUsXl5XCSwvHx0iA0BBHoF5CT56/LgiDw4Ym9+83mvyaO+p6pWW9WnSkCSwyrpdrRc2vU1SSasn3nWnLkl7bkEncl6TVPlrDS/WXqWHahE6UDsM2acPUtm9iy3lFkrv5S+S8qEBipX4H3HG23VFLjNvJpzLmmWBlxeIqmfKNUluSZt3CdTdW8CKy+XYlWWP2B4IoGlbe8a9doba3mxjgHtDiCgVa383LgirEKb4o21d7bPr32naSjJZ+IAwbALAe8JjG3bvktm8X/be5EVJiL5/n+Dc+fSwrRGK9kKkMDKVopyCCBQFoEZM2acJB1fmm/nVVUZT5wA5TsOp37GyuHktBAd722jTqYa/XHGtNk5Xs5ZuEAK2lJGO7OI8ksKauU+aVDQQRSvMWcNopnTZ90kC7I/KL3IGlel3Wyt2kvb4+F7C4WqczjW9mOHb7Vwr8oJg/vPO28nZ9yPp3Ccr7YkJyuluPzz1f7cPtg+csxDUme723qUz1sgrLR+t2XpexKR6OaOpujizvk1sbxbpQEEAiDQ88KwX8gvVx0BGMqAQ5Dv+2/Jz4b8fn8csGV2DiZAAmswGfYjgIAnBLQJO4mFnC/renUQdlmTPq+GUYgHcic3ZwZWObeQ1uo7spD8V8oZRKH6njlt5rvk5GNO3u0ZHcQZWHrGjFkfkQW0n5DfzxaKUVl+SctkwvG8j08BG9C2+4S4fM84l+iVZsthxpLcDbJ08blQmDx5sixKbia5qFK0ol412j/gM699VNZn0i37n/O1LAIx+ZC8MmNZ7fGm2P91NNU2OAvslyUSOkXAAwKTlm3aI39UWeyBUIoTglFTE02xdxencVodSIAE1kAq7EMAAU8IzJo2681y4nJBQYIxwUlgyQosOcz+KIjiQY3IXQu/Lnfty3t23EGNlv6JpbR1VWG6NafsPdkuTGvlbsVZa02O7y3a6J9LLEeXMZ7dDz10n6cWx5e/trqeEWTsUOkSRDnMBuxOR9aX8RgP2vXoEaOd9dUkiVX+zatGB8mE1a8Oes6TcgnIOZaZK39w+o3cHbLDWSurfWH9xHIFQ78IlFMglkrcLP3/q5wxFLdv800uHy6ucN/WSWD11eAxAgh4SsDoAlzWtX9EWgVpdky5Z2DtV3Xm4/xU1o+qO7DDX48kQePcQe/1BYq6at/JdoGaK18zsmj6GyOh6r/J8b24fFG82nOHPJKckYc2o10nkY2VKsklhHKjhWEidYJLreTDD9/3vMs6pSke8kbCXgbb6VmjPkei7uaEc5njI3128bD8AuPlA+wKK5PZFG+OLks0Ry9kVlb5DwoRlE5At6mMzEwMxKz9QdQmxyO1zYO8xu4CC5DAKjAozSGAQGEEZsyYLXe/U+cUprXeVibLiV3+lyIWMKBcmpozdU5U6jm3cffKNkLZoe95JRg3cfTOltLqSjd1hizrnZPtIUMdrIAs1H6OsfQD8vrxg5Up6X5t2kva39CdyaQK9bqhix1U4t9r1qzpOmhPkZ6k0+nJ0rS7zzrjzcsHHSI58Xc9260otNqUbgZdngMw2jh3VGXznoDc/0K9XW5K8LuxLz/bewfD+CWx13ovTCJCoPACsdbk76TVPxe+ZW+0KAm6r22cd0K1N6IJdhQksIJ9fBkdAn4VcH7J+0aBgx9ud9ueWEcln3GlwrbrmR/59JddXfPe6dPneGdWWHZBq6NHjf6YFC1oksY2lgePT5YgUmzmtLMvlIXa/yAPR2Vfq9gltTMDyzObzDicKMGMdBnQP1yWz7m4tnNYwN3LyRmTw3hy1hu8orEt3ySw6lo6fysjKcmMv8HFeOWwAkYd58zKUiGzYf9aWesbnPXe2BAIroA26r8CPLoJ1aP3fCi44/POyEhgeedYEAkCCOwTmDV9VpP8JeMNhQbJBGB2jGXKvoD7QIdFW8r+6EAveHWfzMYbIWt4faHQ8Vna+PZSVfm+m6+0uU1MnEvQPLMZZTyVwMopQVTCZEIuM5bk89a7yRntjRlYJV2EP8/vPjmeMsnHFPqPQHlGRfVBBORcbO9aWSMjO7bKWlm/7Gisc2ZRsiEQOIHY0uSDsvbE8sANbN+AjDFf3f7BY93+gSuoHEUbFwmsotHSMAII5CLgXNYlJ2CLc6k7VB3L9v9d4myvXE5zKPb7ZJdvfqZkUub/SbxjDx1GfnvkvVuo9bTyC8Rlbblhwnlyl6AbpZrnjqEkjDyVwBIn15e0mVLe4S+HBdyN5c3L4yTR7Nw8oNbl27koxS1jnLWlfLPVndg7C+th3wRMoI7AMfIzZJHW9uOSyLpPZmbN55Ik3hhBE9DKfEnGJG/14G3yx4Oxu7urPxG8kXlrRGFvhUM0CCBQ6QLHHHXsR+TnWlHWhJB1QXx9eZfz3pAfjq5PnqXaX6XmIL8sGOeShdHyL9+TxLFyadVpq1evLtmlUhJzTtusWbPGmIz5dE6Vh640durU88bJXfOeHbqoN0rMmDHnTGPsOySaQq/d8Ix8Lz+ktfVPW5lOaX+n/EvLv+HKNuNlBtwk+RV2irypp8i+QX8fkUsaPZXAkphPc74R3WyWXcIEkftL7tIjR4580s14SlU2lTKnCbVLbfWcVCnwe8YYq9p6olTjLkQ/ctN6O9GoPizJ00elvUG/vwrRF20UXMD5gX2ufH6eW31M94uSzPqNfBdcE2tJenemZMEJaDCoArIW1sPxpujtMr6LgjlG/flEQ/QXsbbkv4M5vvKPih9o5T8GRIAAAvsEnMu60j32F4sI4tvLuxyTKVOmROQX2pNd+mxbvXalkyA47DbnTXOOS1VlPqCN/rIUPOKwhQd50WSss+QlzyewjK2vlDhHDjKMvHeHw2knUfp/eTdUggamTZs2WpuMXDaoRxSmO/O0Mvr6jLJuW7duxaZs2pw6deqocLjaWXvrQxLHzP510jrS3n9fWZ+7v6TNHv7y8PWliHlvclaNc9WXURuWLVu2x1WdEhWWs3jXCXtJjP5k1ZoHv16iED3djVyu81i8MXaN/P2iWAl7T48/IMEdLcmsRZI4XyQn/Y/K42sjI+wlNdd2vRKQ8TGMChQIWfYXM7b1bhl6EHMRR6sq9XkZW8GXqajAt8qAQ/bcpQIDRslOBBCoCAFJXn1OBuru5MudTPTNbz7vNe6qeKf0sGHDTpRo3M6Syeovtiv+smLrmjWrvq0se7b0sSuXUcsaMZ5fJH/27NkT5UTgw7mML+s6tm/WwdJhHflfSRrVZz22wQv+U2Z6vHf12lWTVq9beXW2ySunuYceeuilNWtW/lrqzpJfSs6WXTJj8NWtZ926+7e8+qzMD+bNm+d8/7l9nz9972P3vlyK0E0q5DpJ7+W1nSSp6TqBpYzt+SR6Kd4L+/sYlu7+ikxhK/CMtP2t87XEAlPkWP4yvctKSGLyBx3NdW7vhlricOkOgYEFapd0PSV/kL154Ff9v1cWIfxk+4L68f4fiTdHQALLm8eFqBCoOAFn5oAM+jPFHnhVVcb9CVGxg8qyfctYrmN3e3IqlwA+Kj94v5ZlSAcVk1+sowft8OATO22+KWEV9U5P2ieXqs6cfvYn5K/5zl9A89kk2ak/JbP8zpAk1O+kIWky923l2pUrx9eOe7O08BX5l5HmEvJVln7zxvbyiy87J4yu/mIsIKW7G5zl/jJpiS+rJHc5joCxcpiBFdal8y4Hiss+x7Zt3yXfQZdItR6XVSnuXYHRzqw6bez1MivrkY6m6KKtC8cd6d1wiQyBQwXCYbNY9npy9u+h0brec4Rl0s4VDWxFECCBVQRUmkQAAfcCdqb3hHWU+5oua2Rs1zMUXPZQvOLGOt1t48a4P5lLZZxZOe6TBrK4tad/gZ41dZb4aedErrib9v7NAuZMnSPJxvzuUiaJj79ZYXX66rUP/lhAC5Zkamtry0hC7Bsyk+Y9Wmn5K613Nhmk+yRyCRNEckxcx6cs958RJToistavcns3tpdWrlzZXqL4fNNN7JakrEXX+zPWNzETaNYCvbOyejKRTucOhsmm2tdnXZOCCJRRoOamrrgsOfDzMoZQ3K6N/nD8klhR1vQtbuDeb50ElvePEREiEHgB57IuOVFd5H6g2v26Mto3l3cdyqGN25M5+d1Au55d8fDD9z0vJ445XHJiIocG7Z09xtJXSzRuf+7JLCD1hKtRGHWyczdNV3VKXDgVsn8oXY7MtVuZbXerbVIzJFmwOdc2hqq3et3qe0JV1vuHKlfK13UOM4Lkm7BkM4LkuLhOYIXT7j8jSmE+ffq5ddLP0e76Mo615PHY+gtEW5LfkX139t/P88AIHCVv/EW20n/bPytrW8OYAq1tGBgjBuIxgbDKOLPiX/JYWIUKJ2L2zjIrVHu0s0/A7S/ywCGAAAIFFzBpdZU06nZtJzkvVJ+Qei+6C8j9LCZ37RevtFza5/bkNNPdvfNfOUWk1Q7X9YwqyTo/ruOSCrOnz54td3Ga57auJARukfPhZS7rVR1zzDGnuKxTsuIzZpz9FhnXe3PtUGbaXX9c7bjmdevW7c61jWzrrVixQu4o550th+9BuQ6yNAmihoaGkLxX3a6Js3PFn1d0eEf4QCSW6XH7eSeVS5csPBCpPx7J97y8fa0PyKVn7hLy/hgeUR4s0DsrqztSnYw31/6UWVkH4/DMOwI1S7uek8TrD7wTUWEjkRuRNCWaozn8LCtsHEFrjQRW0I4o40HAZwKzp80+TX54NboP26xes+bBB+Rv7S4vMTKnyt0OXa1h4z62wtdw7tQmCZgJ7lrWmx599NEc71RkjnHXl5wdae3Zv6LJe8yZfeV2y6SN9Q2ZtOXyPSbd2CHXl3u6DS7X8rJuyldzrSvfb79Zs/bB/3Qu88u5DX9XdPeLqCR1161b8UwphpxMbp8k/Qx305ckNf4p5eXbw3ubzJh0Z+0MxJRwvTHvkQ0ZUX1r/AX5xf+tUjA5ZGEKBEHgKPnB/DFmZQXhUAZ3DMNTe74rP4S2BXSElrHzW64hoC55DYsEVl58VEYAgXwFZE2Z/5Y2XH8WyV81ehdHlBOwJ13GUJ3JZE50Wafsxaut6lMlCBmuq8315YNO63svf9PjXPXkFDZ23HWdElSYNX3We+WXo2muu9KqRZIPT1rKuH2PORieXGtNZqKdK2+jma4t9lZYO/LoIy+Vh/JtW3nbtGnTRsuoa1yO3EkQlcTLsmzXSVP5vsjpM8KlQU7F5TPefQJLMwNrKOxoS2fStuwLpFxOd5sdqn1e96xA76ys3ZHqLmetrI7Gulx/Dnh2gATmTwHnRhPaaOdcIJib1u9un18zPZiDK8+oXJ80lidMekUAgSAKyKVMs3K5rEtOuu5ftW7Vg46JbRn3s2MyyvWJXrn9ZbqL+5M5YzvrwbjeRo8a7SR7hrmtqLW1yW2dYpd3LquSS96cS1TdbhmjMt9yKqVVOocEljffY5JJ+aJbiH3lX7BVuGnZsmV7cqzv+2qhULX7zw3duyZTScaeW8LHeDaBJYlWt595JpPpdr8uYkmOjrc6mbCk66/GWPPkZ+lOb0VGNMUWkL+CjZTjvkhre5WslbVe7mB4RaIh6iTn2RAom0CmOvQz6TxRtgCK3LGlrVyuAihyVP5tngSWf48dkSPgewFtTE4f6LLQy9f2D17bluvkglzq5snZMfvHNNBX+bB2ZmC52rSynNkfrjfxaXJdSSpYxvw9l3rFrLO1a+sHpH3X61FJ0uvmNWvW9CZH165d60xt/7fLOF/vsnzRi8ui2K+VTmQGVg6bUZ9eu/b+jhxqBqaKtjNuEyrOlMmSJYjkpNR1fJZduvjcvBH23QTB1UxZsX76oYce8uxlzG7GX4qy9Uvjq5W2SWKVAtu7fbxOvm+ultuvyB0MY7/paKqZ691QiSzIAhNvbO+WP8J8PbBj1GqWzHp8S2DHV+KBkcAqMTjdIYDAXoFZ02a9Rx65n1KrzfKVa1eu3O+ow7brGVjyQ9L9TIr9HZbpqyxY7/rk1NYh1zOwZk+d7ayjc1kOw/z3ynUrPTX7QdY6G2aM/moOY8loK/PtvvXkl3y377Mxc94057i+bZT7cUhn3i8xyFBcb6tWr1t5s+taAauQS4JIVpdy/T2YK1sun2t7MlU5JblzjTHbeqNHjD5ZylZlW94px/pXbrT2lq1v6VrjJLHkmcubobjvixqeFhhmlGmQP3r9X7wx+vd4Y+xjTzccf5SnIya4wAlEtyRvlJ+zbn/X8o2DzHr8lowvl9/BfDPGUgXqu4WMSwVDPwggUDwB57KuLZ3bZHFs+Sh3ucldlA76C80rr7yycXj1kSlpJpJtU9Kr72ZgydjcJrB2yYyZzdmaOOUk4TMi3WP/Vh66OnHs7UOr++RrSdb66e0vi/8yPeaTUiyWRdH+RX69evXqDX13yi/3MtNPT+u7b6jHmXDGeZ9tHapciV6XCXL2pbn87qRt8wWJ0f03a4kGVqputNKnukXIaF09c+bMKcWO0cpY1bbrmzyorocfvu/5YseWS/uygLvrGadyWvBiIa3lM+BvErunPtNysRyqjpPEctZD0jpzj3w+TBiqPK8HXEA7vx+Zn0YiPd+TWVl32ypzbX1r1/KAj5rheUBAr1DpjibzFfkc+o0HwilGCGcmG6MXqaVJ5/dstjwESGDlgVcpVeWkNtzTY9XKLzd18hfeCVrZRyttjTTGOHdFO1ocRsqveCPlB95IZ/9+Fznh26Hldlf7nztfZZG+V2QmyYtyKvSi1H9R1sx53mjTLmsxxI3ZE5fbsru9TKdv8zz2icCW5LPvl/fOZLfhyp8t7l295sFVfevJXfZSM6fPdhI1bi43qZX39bErVqx4rm9bXn08bdq5tbISk9s1KpyZFQd9/x1ufHLid2I6ZbdJmdMOV26w1+Ry0FsHe60c++X4Hi3JuCty6DulLPubh9bT7v8qaPXO9PvToW2Vfo/c7fMMeTPU59Dzg6v+vGpNDvWCVkV+/Ln/zJJp7n+ShfqKbiHJK/dbCdfnch2czmmW7AfF+oOu+xq4wguy2+1n7sAt+WCvXE64vqux5k1pbd0hv8vN8EHIhFh8gf2zshpk0fcn5efHjRFj/6pmaZcvfm8qPg89FEOgrrXztkRz9CE5T5xajPbL3aacA3/LzFF3Osm6csfi5/5JYPn56BUwdmdGjHML7rDOvF4Z63TJNNVJAkpOdnS9nATWWHJP+P1/f5e1YeT3G/lV3tn2fXF2Sdk+O/Y+k9v3Oi+8uvUW31dH673lnbMCSYrJfxEliYiXZO96qfaY1H1Mvj7e3b1LchSPvvJqIzzwtYAkFobJe+rKXAZhLOuqgerJe+ZJeRu5SWCpVMo4iZoHBmrPa/tCys4hqTT04sxvPf2tR+4a0T1DTq8vkW/BhTLurGex9TN6Lm3Sf+i3r6xP5T32XxJADieg5kaZefFM/+C1zMDq/ezr/8LhnhvvrLVmLDO3/+fx4ULf/5p8BjsLq1b8Nnv27Al2Wo0KEoSxrZKtz+XWTT7TT5PP9LJt0rdnbYqF4iQmuhbVvDW9UxZT1ub9xeqHdv0nIN8PJ8v35NWS4LxSklm32ca6tncNNf8NhYg9LiDvMxNXztIPxhN//CsC14mJ2tilsl79DUVou2KaJIFVMYf6wED3zqgyb5AZE2+UE9fXywnK62VGzGkhrY7sPUFzMkq9m3yMlH4bJb1Pk8TYNCc75oTiXB4mia2/SCir5CRy1fBdw1fc+9i9L5c+NHoshEBqj3255C7rXLdl1LLVq1esHqjevsu73j3Qa4Pus23n8q4HBn3dQy/ITMbT939XZh+WXijfN+87TPnIK6p7RCHmhkgy+ifr1q7bfZi+SvrSjBkzauTj4xM5dJqywvqgta/2t2Fr+0ltQvufZvVVjtnpWRUsQSGJ5dwcunkxErHuyqFe4KqYtJFjWZafiUWzlM9hzyZp5P2aQ9K+cFRetincKA9tqebaLuePhZdJkmKVHIOfyOPhh5ZiTwULDJf3xUJZy2ehrJW1SqfV22JtSc/87K/g4xKoode1JO6Vu2M+ID9xzwnUwPYPxpgrN847oWXSsk179u/iqzsBEljuvHxbWi4POl4mUc2VjNBcmZkwV05aj3F+F5cfRHs3b/9e7swKcRb7ni4prSteGdHdPXPGrNXK1vdYEfW7lStXJvaNgi8eF5g7Ze5Re3TPf736vnMTb8j+2qDFjVze5fI9LCconkkuDDqufS8YZct6MC4HqNQwqe78K+omUT2ftnuuKWonLhvXxlosVY5wWc0hvkE+TzYPVC8SiTwtn5098pqb9cFOmTdvXvWyZcvK/UuK5P51DpcF6eVymW33QB6Vtk9+9pQ1oVIMb1tpTyawnJ8T3aonWowxZ9um/FHEuQS7YrdYa/JXicboX+QPnEsEIXDv/Yo9sIUb+KNpnVl4fNsWkleFM6WlPgIhbb5oG72uz64gPayrGr37ozKgHwZpUKUcSyH++F7KeOkrS4Fp06aNnjlt9gdnTZ99i8zC2CbrQjwt6apfSsaqQZo4JstmvFpsmJyMSTJO/VAu6eiYOX3WqlkzZn3I+aXXqwET116BPVWpKyR59ZocPH4vl3U9NFg9+SCTBbbdbt65vGvoyOWyXo9utjZf9tLadc5aXpKJ+kAOXKlwxrp6sHqSyHHWK5DPUVdbeMeO3ae4qlGEwmISk2ZHum3aaPs+t3UCW94E7iQ+XVWVy+dm8Y9w9/C0kzBxnbEvZGRWxruz0wo5zsO1FVuafGxn6qgz5Q+fzpqArNdyOKzKec2Wof40UxWeeXzrlo7KGTYjLbVAtKXzz9LnnaXut2T9Gf2F7R881vXvZSWLz+MdkcDy+AFyE55cGnj0rOmzLpPE1R9COrJVfv37lSQLLpE2xrhpx2dl5ZdcPdMYfV13dc8WSWa1zpw5Z6bPxlAR4c6aNWu8/FX7k7kMVi53/frh6qVUKocElpo8ZcqUXNd8Olw4BX3NueRXks8nF7TRAjUmny/3r1mz6toCNVeQZmRdn29JQznMLjbXr/jzivbDB+F+IXe51MK5VLWsm87onJJocnONR8sauJc61wFLYBm1wbOz62zncs3ybqFhofXljcAbvU9uW99T19L5Zbn771nyu9ZfvREVUZRDQH7ePyU/E86ua01ePvHGdmbmluMgVFif8n77kgw5E8Rhy8nr2O7dwz4TxLGVYkwksEqhXMQ+5AT8CElaLZCk1V1yectWuczhfyVxNU+69PyJeRFYhssvWI3Ktlc5a2bNmDG7efLkyW4u9ylCSDS5X8DY+kp5bx65/3nWX426e9W6VQ8frvy+GUDbD1dmgNeqhw37/9m7Evioqut975uZhJAAAgICCQEUNxCXqDgzmUmKiMWlrbWpQtXaxaXqX22r1VaraF1rV9tqta0LCqhpa60LrSINWUXFHXfZkrCICztJZubd/3dDwBCyzHvz3sx9d879/QIz79177jnffe/Nu98959x+8NZRuyQSCaljrnJacrYuEDO+Bb3kiqwSJRQqOwYvBV+3oUybyQK399mOC8tEKcjXjE/G8btghwAViUTLe31ikgUVZBgozJygk6kq53jCPSM9sDJZGkHubcykAqr1XTxv9dKiAxuPwSLUt6Gb1d9a1cwhfawhEMfv6p2BAvMoStxuDTiqnRoCcndUzOvmpiZF3dbYPfiKD88eMVxdDdXVjAgsdcemV82CwfID4G30ayQ4b8Lk5CEQA6eigXqT3F6tcPXk0UgA//DgQUM/ioTKfkBElqtY9yk8OiU6AeGr3+2zYjcVTM673Xmwm6rWyQXTn3FyoRs79jyUUDJX12aeECdXvVS1bk9lM/vNYOJWaIB3bYuFs7/U1y9a1VcrTKytEzoK5FrjjI/oy7Zuzm9esmTJ5m6OZ92hjjBQG1596kIFbwol819JxISRWW83PECUxSaTVxSfzcziec1zDL84BLmx/gBdZE5AKlojwF/B7+oxyIl2WUeCf62tJePUQyBh+q6HVlo+a/BbMyAnEbhSPdTV14gILPXHqLOGBrytTt4ZImhiIsV/hJNez2fV2T43PhdixfCuwYOGvC/zZHkhZMwNEDIt0/Szm6FDwLoe/F/19YvlDpRJFOveMcjtkfHwrr4MA0E9sa86aT7/OTOMk2teqFEqnCQSjJwIHI63gUWLP95z7qvO8kzus0ySIl9fxq8xYYiBne1I8vOWJOtpX80QpvpEt8VRAAGhKkmDDQdYRp95KpN7FofZleqFc5o/LZ7bdKnfb07ABEyGkGsZ4uMKeN4R2oL74IYtsYHBwnnNr7mkNi4fKoRA7wiMe2TlSvxe3dN7LU+fvaT5zFEyTykVCwgQgWUBrExVleELIK7+D2FxH2Ay+1RHiCCNnaUB4cUyTxY81l4PhaLTLTWlyikhEA6XH40JyTdsCBHYJeuG5NtZz08EvZSfmOINTyEdxUcJYYRqa6tqkx+XtNTkgvNbbPZ0b9WSqqZk2gYCtpJeD5P535KR72Idy4lCMXmhpM0dA8Iz7BHkxnXh86lJYHVsOLCPGzYnKxMMWlbvQJgsTqPmrFkNz5wLBDcm43fqIbSjZ0ay4Kldr9pIiMOL5zXNljnQnFR1ypQpA8PBsl9iIX55OBwucFI2ydIXgYQZkIvg2zS1sJ9pGNdqaptrZhEJ4hq0qQuW3kJ4yJ+zZeO2d0Bc3QmJ41OXmvUSDsFF/9/ScOS56HFRW4mNsx5BiwBwlrAX1iXY4/X1VUmv/GHSYd07hrOMe8f0BScSTKlBYHFW6c/xHd3QUGUd576MTPF8abDsTIg4yoaYloTw/zLZdu15cZD7K9n6u+qJuC+z15ng/Xfpkuz/mJAOTbau7vWEfjsQbq2url6p4rhxk2c6/xVCGIWq3mkqDhkrnrv6bRBZ5yRM/wQo+Cf87VBSUVKqLwQQMs4vwliWFz7a/H5fla2eR17akwK+3Dc5F1diIX5AXV0deflaBTFL64+fv2I9gst/q6v5WDD8buOsQvn8pJIkAlrldEjSZuWrSeIqLyd/JsKbroOy+yuvsBcVFHyaabBX4NV2+47WbTcvXbo05kUzVNe59LjyaUyY0+zoCY+azRifq5Jtawo+Ai9GyVbfVW8UdvnbF8TEJ7sOqPQ/VigHwKTijOok2NvISXNlXV31MxnVo4fO28OCuYk8aaBcLBf+kY/Hz8J1lnxLwSw/K3BdShLyP8l34nBNLtrgbWi1DMC90U/ZneqsWpNa/YyTKqmpv1dr6WFk/YrYS4zzB+ApfZitW9k5VeIDBgxQjqR3zjz3JMlQH0i/5KOK8df4A23n4rdLEhWj3euRJDuIwAKEhF4oveoclNkuCl6Vg5mJMH3Bzu8ke3mnz/SREOgTgVgs91eBQNsPUFHHxTU/0t3cCNtm9gkEVWhHgAgsxS4EeBKAuJKTMUlc2ZmQKWaQ2ur0g3rX98/NPwlEwXewGoTdLqg4iABnhrjNrjx4VJ1rpa0N8qpdvNnWnt9mkZW+0lVXCP8k4JCJBwGcTtj/8Aj6fV199VOw10yXzVb7AdkvX4ptEv1C5tqxfY0mq6vIdK41IeB6b+MyamH7wcaVydqpY71gMDgEdo2yZBtIX7jxXGapjc3Kwkh8CUn6f2atuboeRtgdcZJVZg32X4Rdbj+whkH3tYVPtC5YsKC1+7N0NBkE9q9cvgn1fr+sYuLdBYGNZ2J8rsB33UjgZKDwQp3Pcb9djXDBe91QFnOaCmYK6ZU3bE/5nAisPQGhb30gIJ8rjTMLb8cbcdJe832IVOw0P2PlmaN+OfaRNa8qppiS6hCBpciwgECZyE3jj/C6Krc10VDEDi+qgR/vY7jwLYUXxjW19dW/gQ1W35+9aLbrOsNd/JtMiBLXO0qxgw5yQUkCC+Gu6Xzp34grvwFw/pf5zMframsdX4lNcaj2aj598vT87UbLtcrfsRnOtcY53yQZSaslzs0Q2qy02k6n+n7mP8wydFwsqW2oWpgOHPC7VWq1H1CZyobIAWurIdPgruIP171A4UhWrwO363fkT5qDfuasmjmm1ODmVRjfk/HdBpvutrbZJx/EYqU/Frt4ZOW6DU5bL/M+4sb8E94BT+tONrzzVnR3nI4RAr0hEM/1/8HXFr8UdQp7q+fRc5wbxk3QXT4jqfSBABFYfQDk9mmEv/RHYvGfYAL2U/yk57jdH8nvEYFcnPkVcmN92d/mO7vqpSrLeW56lJyFJ2RYF15QpCeh8sUUhtUJU9psEsyEB5bFd33BHkOTvl4O4zBiC2RvRsjOCsM0P6peUv0RjinradUd6Nvyd/wI2dull5Dq5eCMhuMJATLS4nUkEeWsDP/OUx1cN/VDqPlheJZZKvAiSh9BJPNzWR1awd6wZFCaKreHAzN2kMXuVlAuHYuIZaB68fzVtei2tiPPyyW4pb6P75Zz82VAdR27XItn1MVFcxsfd8E4XhoqO08kxB2QPbBH+X2/o/TYlE5kLwLjHljZsmrm6JuwKPdnHVHAT/lJjWcVlhc93FSlo31O2kQElpNoWpQFD5Uz8GL8azSjHAEWsXOtOnJjxQPmy+Fw2cy6usU1rvWjueD+uQXfRzy3RxISisPVHQ5uWbcEM65pqK/6UF2bnNFM5i6Lt5kyNMULxW+2mnLTiEy5htsN15gGnSU9YpHC8cKQJKcjCFLLXpAi4UsfgcWte2m2JnJkDizlSn5O/sFg0C0t5OHCTB/WyiHmPYWQIFyGel62tmK/m9oC/u/i4SK9KayF6HrPbFU0lvkIHkYWx8uLKps+c1qpUGjq/pzFEYoopvYpW5h2f5P6FE0V9EZgTLz5r02Bwsvx7D9YR0vhuXgT7LLsWa0jFr3ZZPR2ks65gwBca4eFQ9F/gbx6BD0QeeUOzKlIHc2FWBQJRf4vFSHZ2hY5Y/JAXl3jFfvxQndox8q/cirjAT3RolLbGxqqsuLFMBEz5TXW8wqvReDcrp7JPFjYVe0dm/aNx3PwJJttdWk22aohMZEeAks+a6HbeIv6rXnxxec/tdgmLdVBXlkmC/H8JgIrLaPjbCcybA15l25v/bzfeLwvfBsUuZKkqrNWZ1TacvwGnSB3i3SavMJikh87pl9miPjruB/7Jq8AA3LNrcgoGtS5ZxHglSwhGL/Bswb0qbgIw1M129+7+kSJCKw+IXK2QigUnS4S/DU85L/qrGSS5jAC2BGC34n8IveoSm44bK9j4nw88CMI8xIxm5ubO8Bq2IpjePUkKBicOhorTEN7Ot/DcTkJwDxQ74KV3mLkdJK70XimZDJUtba2VpKa6+2AZTIu7+dsLfipZodaNP6TJUuet4W1xX6Yz+eTuvkstlOX8EG4pkVb5BYXRHxYBU2h+hMWfNhaPK95zpj5TYcJYURwwz0F9fDTR8UhBOLA9M4cX2xy8dzm5x2SuVtMZEpkMjyhG+Cn+zv85e8+0fuH+I4dOxp7r0JnCYGeESia1/gonMNf6bmGt8/gAXibmM2Io+llGAmcXsBx8hRIkP6RYPRuAP4fyCV3aSfBdVfW+Xn9+j+DJPsD3O1GD+nt2yUz9mOvWWOI9p0IlVLbx0zLkzm89qs7OXUQXYPHb4Q4mbfOOyXjOxGyF+2AhcnP1Egwcrydtl5vE41Gx8IGS15+ePFMW34pbloPb0xrfi6rF4DM52WxGIa6OypaNCXrq8s8WfAQOtVIiIMl6QJAdmQ9KKkB8CbjPARML9vvofXYida5InM6YoF3tvDxlyD1aEuSBWtcunRpzFIbqkwIdEIAzweBncev7XRIt4+HNb5f9E3djHLSHiKwnESzB1nhcPnRebkFr2Cl8EJUwX1HxVMIIC8WF/7/hUKh4Z7SOxPKmlz+oAzORNcp9ZlpcqEb5bmRsDyZgxjtCaxQqHwSiLpvdQOZ0ofwY2s5n5mTBiHp6QK78vCm+OCxxx4/1G57r7ZLJKwTKviBT5tHEMgyy88IYSr9jLBqT+v27ds/8Or1RXp3j0Dho83vS9IlEfOPxzxV5oP5pPuadLQHBFowvb/244IRJWPmNkqCydESOS4ShteVzOd4Pf4s5axrV4SzrEhz4CjoJGwvBIrmNsl3muq9TmhzQNz48vklAW3McdgQIrAcBrSruAh24+DCrMOPsHIhSl11pe+9ISBKDOF/IRgsP6C3Wtl8Toa8gZ/1VFjX7vHilrdu393UrQ8IkbM6mWNGOnc/c8vwPuQaTNyKKlbDpvqQ6v5pkA1D4cmZOe9bn/kvWGk3vHR0jj/+V7R37Z0BK/oF2DxjhvsjkXwPyFNp+R7EqnAaSWTrHlgYwDTqlzzW00qmDULtouRbyJr8XfLksIaYl2qPq1y5bsy85p8jT1Zhe54sxt72kv6Z0BUelvVmInHUmPmNNx99r7NeTtMnT8+H19VtwuCSNLCdQBvpOVZkAhvqUz8EBDd/pp9Vuy2aMGzr+u/s/kYf9kDAtZfRPXrJwi8yb1JpOPpH/OhiRw4bKxRZiJnyJnM2zsfNxZiEEhnZzWAZPCFXSvO6OaX+IWF9tz/3jTIsJ4+Os3javD/ct3/vHkpLy7Ezizhl7zNeOeLPmBdWTU3NWqBUYx8p8TVMXv5SUVHhOHkYDUWjWNFfiheSY+zr53xLeFNZJrCQKDmdBNEki1bHjVzDbkJ/i11Zq96SF5dYW/JQBymcTqytGUS1HUNgV54seGVNEsw8ARcJ5cnaG93tuB+uLmxrio59dK3j97hcXNhe0CIJxKvwl9LcEQttRGDtPX50xAYCxXPX1OG6f8ZGU080wbPu+jXnj+rvCWXTrGRKD6E06+qZ7mSoRb/c/P8gzOVizyhNiiaLwCgufIuxk6TVxL7JyvdkPXimIWeFOMuTyu9UeqRKIaJyVx8QNdZWODlbV19f/7GHx6Bv1YV5W9+V1K3BTZExAqsdFcH/lCI6313bvP7pKVOOH5GinPbmyJl3IBZ65sItrAoHDmTCXO2EXKdk2PCCFChp8RLBDoRDYOdIi7Z+UFVV1WKxTVqq496wTBbiBZYIrLSMjhqdYDIniuetWdieJ8sQR+K7XCBW8npOK2Kc/SfOEofKXR3lDm1O9i3zmsrNjLAztyQJxjgiW5gUQugIkCREIgBC9Gr8Z9e7XHUQR8W3+i5SXclM6EcElsOoyx05sNvHS/hhneqwaBKnDgIjsJPkouhx0UPUUSmzmvi5eTs0AOni3eITPssTKLesTSQSB0J2riX5midwD4ejX8GiQNgSJqpV5sKyV52TJuxo2yrDCJtSlHliwBd7qzRUdtHEiROt5z/B+6ZMCh8ORf/OTGMZxnQW9MFPpvyHK0NgzZgxIxcKyfvQSllRV1e3xUoDu3V9vlzr15LCzwh41lh+/ppcaO1xavfayIZ2hQ83vw4i64K4CIyFB8YNsPnTbLC7i40bYfsFyAV00vh5a1d1OZfy19JgWQWe0e9B0PkpC+skQBiCPLA64UEfU0MA1z8WMsRjqUlRubX42Ypzx+6jsoaZ0M3TE85MANZbn6XB0lMQ2/0IXnqT3Uq2N3F0Tm0ERpgGezYUmlpaX7/I8RcHtU3fUzus0E1BYuBT9zya7Df+49r6xb9JtnYy9WQulZbcto3J1O1cR3BDesc4vs105z6S/Wxid7H2GX2yDdrrpTV0yZJmDlQ2uOA34iXFhii+DNeYnOw7ukIHAqcS+nzDkkIZDlWV+YKg9y+g9z2W9N678r6Q8afBg4ZeWxqKPGQw/nT+oPwlCxYsaN27KjPwnBznY7GgyYwyeGqeilEc0d31HROGMgTWpk07DjEskvKwK20eQdxMHIb3jW7g7uWQ0jnyuNVwSMZNtm/pceXTerHY8qkEN95paFjUbLkhNcgIAuPnr1iPjmd/MOOAW3MG7zgDOaCuRgJz7RcXcec/JUx+QfEjjWucBh4RBiMh+09MiNOcli3lYUMR8sByA9gslonFr+vw+3s6INAx6flgIxb/IWy7PouHeC/TicDaCxJ7B7BSMZNx8SBa63jz2ANF/1aFPhZfiNCzsPahW72NZYLfhnmUxZlUu8C1O1q3/rk30XbOLVy6cBPCktaB69jPSnu4yFv3aLDSgYW6tpJHp3HybMEUR6pGQpFzkE/QVvgdchJdByUcJa92GiXkyrS1Ao8euf14JsO4/Dn8vngb+xEIKCdy+Y3EdOQnAPcnWzZtS0RC0RUIu/uUGWILJpFYMeQD0M84xuI5kmwBedUbXmKfffIae6uQznPYLMCyRxAegmkjsICndcKHKU1yW8YbF9SDksVysvgEmwF5RGA5CWoaZMk8WehmjpjNHl79/qipBjMuw9PGw/kSewANqQJwyV9SNL/pHz3USOUwxwLHeSIh7oCQgakI6qXtVuRj3NDLeTpFCFhGAN6YH6yaWfgACOzzLDf2QAPMCX60fOa4uzoIew9o7L6KWGCkkioC4XDkQpBXD0MOkVepgumx9nhBOsDH/E9hUlrgMdUdUVd6HWI5rdyOMExmb4VHyHY7bftqg0n0+33V6XpecGaLIOkqx4nvmAhbn8yZ7A0n+lZNhgxTE4JLEspOebOurlqGzTlfbFxjUMKfaElkNH8eyLM4yBmZU6FXNskGYJj7swNAKkwBeSW9Yo7uIMmSDTNc14MHlw1VUm9iI/8VzGZpC2mz84xA6E7aCDYrIxCNRuXug0qESCSYoSRGVvDM5rp8NjN35ckyTfMo3CcPAY+YBpjg8cIe4m1sohvkFbxk90dY90I8s+8BVm6RV3IYVmgwFmSCggjAS3821NqhoGpOqFTgZ3GZ64tKBwJEYKV4KYC8+ilumrshhrBMEUuvNsek7Zh4q/mYG7tzKY4JIocMhCPZKmviIv5XWy2TaARyzLp3DGOH2szpk4RG1qrYmDwn4jz+jrVevFF78KB9LwEpMs6Wtga/Bu2cddHYpYjPtHONMWG0h6rukpKR/6vrqxehY/m7pU4RbLU6ysB3zLCek8lIH0GEBVk20RJegm2rra1daalNmionEjYIe3d0+5zCB90BNhNSxz6y5lV4ZpyTiPnH4H65ATp8lgk9HOhzBXLETZe2FFU2OWoDFl/9pcHoZYaIvw6CbKoDuvYqAuOwvNcKdJIQsInAmPZwWqHWe41NW7ptxsVFK88utvcu3K1Abx8k0sX++MHVNnI7yKtb7IugltogwNmMdWvW/0obe5IwBC89ctfBI5KoulcVEDQ3NjQ07NjrhGMHuB1yIWfowKFOhFWlZEU4HB4AwmasNSH8Q3fxtKaNU7XbsWDiKnvy+NLa2sVP2Wvbdyu/32/nGoPDohqhqv239vsJJhOv9m1pmmpw3pimnpLrRnCrXpCt27dv/yA54anVKj+uvBgSrHlJ7Mx/5Q6Zm5o5MgpwcooiHGmO+4G8rxxBUi0h4ypXrsMOfbP7xVqLMcYX4M/WszsDVpkgle6F3pOlV5nT/ctNpxJtZj3eN36Hv3yn5XcrT1D+q25xoYOOIOAX4lYI2uyIMPWE5BjxxLXqqZUZjYjAsok7tpX9rcz9YbM5NdMQAZAyl0eQP0BD0/Yyqd1TidtNKChWbdz86f17CXXygLDnHZMwMj+REsIvc9vgvdVC4ULL8EEufJK8Gm4BiS+qCi5/6DFXcacgFG8jJH9sVTqeE0qEqj77xrPbGE/IHDHNVm1wp75Y5Y5c61KDweAQtBptrSV/VybJt9bGXu2433p+LtwK6pIzhhoeWMifoi5G9i4VatUJgeGVG7aCyLp3zIFNhwphfgU/s46TQp26S+2jYG/hJSAod1qUeqcmbM/W8LrqhznMbOHjL+EH8pg9z7r7zeDmCnd7IOnZjMCo+Ws+wTWN+bmmhbNvrzxjpPabVCQzekRgJYNSlzqRcNmNOHRZl8P0lRDAbFn8CVvEl+kOxT4Dh8gcOuNt2Ynd5JYtW9Zmq22yjXzWc2C1izZ5xskFPJSten4wYSo8OU12zLrUw+YIkri6tMvhZL/W1zZU/SfZyinUs7OSn/FrbJe9dXV1a7AzoCSxPtl1LFP/CyGaMtV31379zG/9Hkyj9452mzwI68+8rmPmxHf8fqcth5kT+pIMewi058mav+bJMfMaTzANswREkcyTFbcnzfFWMehze+vGfkeDvHrRaemR4yLheJv5CuRej79k8xM6pgae80RgOYYmCeoOgbxY669AYlleXOxOloLHfD7DJzmIrC+YK1GxggB26LgUD+CfW2lDdbMKgYDg/LFgcKrF1XvvYCQT1mMb5J/a0RgvZh/6c405dtpaaYPwLplnwbI3hArhXdgN0fLkGQ9y7TwHDOabjTEcYGXcd9UFHul5RttL5D5EpedDfX3VayCxvgTs5Hb0mSsGX525zvfs2bThEZTOexDeI9JL01IRhk/JZ0RJSUkAhmQ8dFuCaST0e45aukiysPLYh9e8InNLmYZvV56szzMIwwtCGEdCn6s7dlV0TBXcZ/3hdXWbMHg1hGbMg4P7KYTQsUElQd0iID0WMUf5ZbcnNTiI3RxObzyzcIoGpqRkAt65qCSLALZyPxdu+L9Ltj7Vy1oEhvt5vLLjxVw7EBIxIUNnbYV1Yev3G+UuaG6DsrMPGy9KCuxEiB8nywRWggeUnJzaHWfsSjYO4R3fs9de1HYkKbfX3EIrbtjaLIAZRlwZLyxpbn191Vv+hHE0Pr4gv2eicG6uykS/3fWJ3JaW70Ekq0njPWhdP84Ty7qzNdPHcnMHSPIq7Z4g3dgtfP18SmLUja50yGEExj68aq3Mk5XXr6U9TxbEW97JOAWVtsNj5OqiWFNp8fzVjl+D4XDZjLzc/HegnwzJz+S8TyBP4MoUcKKmhEBSCCQCvj+holp5NZPSPKlKXBjsxqRqalwpkw8yT8EK8up0TL7/CqW5pxQnZTOCAF5Ggv1yCm7OSOcudhqJRIbBA/Fym12878/h8222tdzM1k6Egu3XEbpmuT+nGuABY827AruL1dcv0sotX8TZrcDT1qQW4VXXOjUWfckxma3NAiBWKEVgSTurllQ1+XOMLyGM6g/4mvZk31gxXS31UKHgHrRMYAXiPC0EVsfCyIEWcVpbU1OzwWKbtFQ3bHicuqRYY0deO5fEk1gvIDDsvk+2yDxZRQc2HdKRJ6vOZb2r8bw5An3ezitZwsm+SktLB8Pr6h54dT8DuWOclG1LFmfrkSdwu6221IgQsIDAuAdWtmAedpOFJl6rOn3lzNFTvaa0k/oSgZUEmqFQdDrIKznx9iVRnaoQAu0IIBztChCfX9UJDmHy62GPrbAueBZdlw7vq114m8IeuWCYORnbEQu77o3Cj+7QXTYk+b/M25J2wiFJ3SxXw0v34cCgwnLDnQ2eq2moWWyzrY1mCTs5sBiWzzJ2jfVmJO7Plrr6mksFN8JYq3m9t7oOn9sOgiXjebg6bAIHyiZatG8TCMBmi21sVc/PyT8YDS2Ru5ggp4Vcs2OQHbLQTj9JtFEWoyR0pyoOI8BnM7N4Z56sUsGMo3GdOp0nayOeMxcgXLAcfx84rD4rDZZVMNOQv0/nOy3btjzBlttuSw0JAYsIjIk1/Q337bsWm3mmusH5rXiGwMTsLERg9THumFAeBJAeRbVAH1XpNCHQFQFMhPgDodDU/bue8OL39rAuwc6zpztfVldXXWmvrb1WhmHaCwEwzIx5xximYdnzAznX9Jp4mcYdGHFbv00gXq6zd7XYa9XS0iJfyC3nWlPRA6szAnV1VS/U1i8+ihn8K3g/Wtr5nMOfP4e8e5GDS+ZzwLtY5kv5ceXF0GKgNU3aN1FIi/5gqq0/IxQmsOyETFsbmyRrpzUENEmdqJoSCBTPW720PU+Wz3cgZou3Qym5A63tAhlPcT+bJD298NnR5wa85EeWhqP/xCrJY1BwmG0lXWgIW1e4IJZEEgLdIiA9GgU2jer2pB4Hj208q+hUPUyxboWtSYL1brzZQrrfYhv3J6H9Pt60gLRWAIF9DB7/J7Zlz1NAl5RUMOPiZgiwtPK/q0PBhSQWMPdKX8Gk2JZ3DNYzMucdY1jvGy+F2hBYHTt4nmDnKiVC5sYAAEAASURBVAEOz0jixU5bu20QDiHJq5U22h/ogWeCWVu7+EkQWccgaVcENt6LP0k4pVY4W4c52/0gLk7/fNOn+9XWV19QjxxcqQl1rnXMZ9q5/9N2D3LGrYUYAxpgnTb9rI+EaZmQs95H3y3AIihzDfatLdXIBAJjH1q1QiZYR54smfD9cvzmrLKmh1iPEO1vQsapRXOamq217bM2Lw1GzxEJvgyU2Gl91s5EBW4jL2km9KQ+tUGgaH7jI7hPX9XGoK6GJMTNYra9Bd+uorz23e81hdOlL3Za82OrWekxMiFdfVI/miIg2GQfD8jk/xd42UK/6ftZ3B+3lV+orrY27StvLS1bX8jLy7Ps/YZcPDsyNU6tsZz7cnJa/2Gl//6b+6+3Ul/luq2JnLdgv+Uxkza1xWIZCUETPFGOa6afVVxz/bk2PLes9uJIfVFbW1ULSbUVFRUXrVmz4UhmmuV4KTwGxMgE/C9/Iwt66OkznH8Pk703QWK/ibDqhtra2ldQF4fULPF4a1UgELB6DaZO7CULh9/8LRNC5uNMupiJxNqkK6e5ouHnXzJNpMDPcFEZowxDQ913QUDmycKh32Pi+IfV7406mXHjp7iAg12q7fEVxHMl94sfFM5p/nSPEw58kV7+nMXlAsNUB8S5JkII8sByDVwS3C0CuC/FKiygY2OWJ7ut4PWDnE1qeq9wFmNND3vdFKv6Z/ylwarC6aqPxIdyB4OL0tUf9aM/Akgq/p2a+poH9LeULCQECIFsQgCh9gMCbYH8eG68f4fdn4OokmE2yhJV2TQ+ZCshQAi4i8Dqs4oiwhSXYVJ1MnrqvKDxAnJJXF00v2mx0xq0L7S3mhdD7s3wHM93Wr7T8pBMvjy9OSqdtoDkeRWB1bOKsAgnwl7Vvw+9l2+JDTpkYuWytj7qaXWaCKxuhhNuuBfjx+CP3ZyiQ4RAKghsh7fGsXV1dctSEUJtCQFCgBAgBAgBQoAQIATUQuCDbx0wMEdsP9YQxiDMI95wI0G7tDgyJTKZ+fhfsUJwjFoI9KKNYRZjYWN1LzXoFCHgCgIgsKIgsBwnkV1R1o5Qzi8ZM7dROt5kTSECq8tQh0JlxxhMyHAJW7l+uoijr4RAFwT4sh2tW4+lrYS7wEJfCQFCgBAgBAgBQoAQIAR6RABeV/0SreI6hGRfiUr+Hiuqd6Jt5OgR/SsrKxPqqaauRkjKPywej29taGjIWGoLddGxptnqbxUugE/4l6218kzttTm+2IT9Hlq/zTMap6goJXHvBOC0kmmDDCHkjoNEXnXChT46iYCYmJeTf6eTEkkWIUAIEAKEACFACBAChIC+CESD0RBy874C8uqnsNJL5JUclFVEXlm7NktKSvqzBH/CMHInWmtJtbtDwODiahxP62ZS3enh0rGRrfHA/7kkW0mxRGB1GpaW3Na74fI7rtMh+kgIOI8AZ98rDZWd7bxgkkgIEAKEACFACBAChAAhoAsCkshAXt7bsNVBDWw6xIt2IdxnhRf1zpTOGPMAFrv/jhDRIHKHKbFTa6awcKrfwoebX8dmCpY2SXKq73TI4Zxd1VhROCQdfanQBxFYHaMQDkcuZIzPVGFQSIdsQEDcFQyWH5wNlpKNhAAhQAgQAoQAIUAIEALWEAiHy2bk5ea/g1ZX4c+7czbBlluzPKtr8365BffCoWLGThQEeWA5dDnwhCl3Uo87JE41MfsIP79CNaXc0se7D0MHEcEOShOxxeavHRRJogiBvhAo8HHzsWAwmNdXRTpPCBAChAAhQAgQAoQAIZAdCJSWlg6G19U98L55BhaP8bzVnJMHVpKDGAlHf4ldy8/dVR3ea7Y9sD6qGD9olxz6n7HCR5vfBw4PaosFF5euPKt4pLb2dTIs6wms6ZOn53PhqwQmu7b/7gQPfSQEXEXgMB/3E3HqKsQknBAgBAgBQoAQIAQIAW8gUBosq2Cm8S60Pd8bGiejpUkeWEnAVBqMXiwE28OLBmGEk5Jo2m2VQE7bf1fPKvyocVbhPatmja6Qu2R2WzGLDvr95o0wt1VTk/MNM3GNprbtYRaI3ewuWOH4PRC4NLtRIOszioBg36ptqJ6XUR2oc0KAECAECAFCgBAgBAiBjCCAaJABTPgewsTsqxlRwM1ODfPo2trapW524XXZIC5nMi4ehh17OZe0xQP7vvji859atXH1zMI3EYrYmQBrxfVVh0zmz/qY+O/oeTIvFPbmy7KyembRb4H15Zqa3SaYcUjxvNVak8Z73SSaDma3ZoXD5cfhxMXdnqSDhEC6EODsz3AXPzBd3VE/hAAhQAgQAoQAIUAIEALqIIBokPlakleAOJFIUAhhL5da6XHl00CoPIAq3c7Lc31tnUmoXiTteYobbNWeR1gu2KqpuM5uMxl/FZ5Z6xtnFT22albh+Y3nFI7uUlfbr36WuBk4bNHUwByDmbM1tW23Wd3eKLvPavxhxowZudw0/wYTfRqbSaZ5AgH+PNTc4AlVSUlCgBAgBAgBQoAQIAQIAccQiIaiUQg72TGBagna1NDQ8JlaKqmjDRawS5hh/hMa5fSklWDcFoEF36q3epLZcXyYYKIChNY9Is6aOsINf79q1qhpH8w4ILePtp49PWr+mk+QZ0xGYGlZQM59q+ms0YdraVyHUX6djevNti2bt82GW+WhvdWhc4SAywi04sflqtqGxXeiHzxvqBAChAAhQAgQAoQAIUAIZBMCgrNTdX0LxMut1qFMqVynodDU/ZkZfxoyBvQmBwSTfQILjS2U8RivSzkzLs0d3LJ99ayiehBcC+EYthAhaVqFgMZiub8KBNp+AGyGWsDHK1UN0+Q3QNmveUVhq3pmpQdWKFR+BH4ofmwVLKpPCDiFAH4gVmLFpQy5r+QKAJFXTgFLcggBQoAQIAQIAUKAEPAQAkjcfYiH1LWqKhFY3SAWiUSGGSwud5kc0c3pPQ4JLmwRWJyLvjyw9uinyxdsbiamgf+6jTPz5dXfKlyLkMM5Mhn8qlljBnep67mv+1cu38Q5+6XnFE9e4a82zRwdTL66t2pmHYFVXl7uR2yoDB0MeGuoSFttEBDsn4Ec40gktFyijU1kCCFACBAChAAhQAgQAoSAHQTG22nkhTYGZyu8oGc6dZQJ+0WC/wd9Jpn/lh+GutZ8qdBgx+d57+C/OP5SL4Lth9X2sznjj4HQ2oBww5dBaN0mww1fPr/Ek3PqeMAvI2CaUgdHTQkm57epqVnqWmUdgRVvM6Xn1VGpQ0cSCAHLCOzA788F8Lo6vaqqaqPl1tSAECAECAFCgBAgBAgBQkAnBCQxUayTQZ1tEYITgdUJkJKSkgAS9lfikJW56KDyKeWWk6xPWPBhK5LDf9Cpe6c+yvzRJSC0rkK44XPDt67/DGTWkzIZ/PJZIz1zLY97YGUL5mW3OAWKgnKikmBUUK+UVcqqHFihUGg4EPtZyqiRAELAMgL8PWYkzoDX1euWm1IDQoAQIAQIAUKAECAECAHtEIA3zkgkkkC4lqZFcAoh/GJoeV6//L9ivE/84lByn+JGex4sy95CXBhvIY+V2yGqBSCzTgETe4ofe6PBO2s5Pi80kT+rjef9d8LcDzcnZ2X6a31cMPyvIOCkc8v+6e/d/R5BMN6KsXke44H/9ClZRWAZ3H8jhm+gPsPnqCXywv4Q+HwItv4TfN7ABN8Ah9VdF3wejvXDThhDcWgkPkt35wn4y6prCPbaKOIhf45xUVVV7VYbjakJIUAIEAKEACFACBAChICGCBgJY5zQOB5GGLEVGg6bLZPCwbJfMyHOsdOYGwkZRijDDq0VgTxYnFVYa5RybZkM/nyEG56fK1riILRex/enkAz+yTHzVr+iEply9L1LY40zC2djI4WHUrZaTQFHN80qPI3Na5I7XWpTsoZ8QOL2SUyY39dm5FI3JIGHSZ3BxVMmM17Oawm8snDpwk1WxE6cODFnyIAhk4RhlOKBXIYH5HS0L7AiQ/O620H2XVxTX/OA5naSeYQAIUAIEAKEACFACBACFhEQnGvp+dEBgzlw4MCVFiHRsnokVPYTeEL90LZxJp9oq63B3tztimBLQMqNJNdQAtKqhDHzeoQabmhkvEp6Zxl+9nTRnKbmlHtIUUDhQU3zGt8rvALz2MNTFKVkc5OxW0Q5+zevcigfmgJWZg2BhcTtvwLeMmY328sL2O3kgbgZ+NeSJc+vTwWMZcuWtaH9Kx1/dyJBfr9EW+JEsNgXwntLusfieZWthS/jPvObNTU1b2crAmQ3IUAIEAKEACFACBAChEAvCHA2rpezXj+1ZsGCBa1eNyJV/UuD0Vkgr1JKqI25lT0CS7BUdiJM1fTu2g8DFhWYIFYIpJfvCDeEM4X5ZNvn/Wva83Z118rFY3w2M1fP4tcjyu5fLnaTMdHA+qDGUUVnMdb4QMaUcLjjrCAYSoPlX2bcXOAwdl4SZ2Kgn4Kn1B21tVW16VAcMf0HIUnhpehLuspml1eWYH/b0bbt0qVLl25PB9bUByFACBAChAAhQAgQAoSA9xCIBKMPgJz4tvc071tjRHpU19VXl/VdU98akWDkeHjZPQMLc1K0cnttffUAyIBDTfJFzGZG4/uFMgdVfvKtMlYT8yZeD4JrIcINFxbPW700nZogCX095svBdPaZrr5g16qWz/sdlAmC0A0bs4PACkWrAV7EDQDVlylqeYJdXLOk5o1M6BoMBof4eOAX6PsC/OnuAbdVep/V1VXPzQTW1CchQAgQAoQAIUAIEAKEgHcQKNV4jsIFe7Cmofpc74yGs5qGQmXHGEwsglRHFvJN5j+gvn7RR1a1hJfTS2hztNV2Ga/P2TpcQ88h3PBJTCElofW5mzqtnlUUhRfWYjf7yKRsEMqXFc9rujOTOjjVt8ZpA3dCJB8e+JSN5NXniHm+vLa+pixT5JUcgYaGhs+wYnAx8mwdjYDCup2jouG/gr0teOI4Iq80HFsyiRAgBAgBQoAQIAQIAXcQkJsiaVmwqLtCS8OSMCoYLD8A5BWIF2fIK9kl53F7YYQMidy9WATbD6TL2UgG/xhn5gYQcS8jh9Ztq2aNmvby+SUBp00aM68RDi/iOaflqiIPXkvXbvjuvtKLz/NFewILBv7E86Nk0QDc7ItMFj+4tqH692hqydXUYldJV6+vr3qttq46gofQRWjUknRDD1TE6sCf/blGSV1d3TIPqEsqEgKEACFACBAChAAhQAhkGAGZOxYqyJ29NS18uaaG9WpWJBIZaXBTEiEjeq1o8aTB+CSLTXZW54Y3Caw9jZVRPCWY417FmfHc8K3rPwOZ9STC/s5fPmtk8Z5VU/hmGj9Da3SjZRm2oyXvMh0s05rAikaj43ANnqbDQCVpg7zh7mxp3fbl+vr6j5Nsk85qoqZ+8d2GYCF0qsOP2hYkq58F9+gfVFVVaUXKpfOioL4IAUKAECAECAFCgBDINgRaW9lY2KzvXMzgK7JtTKdMmTLQTPCn4e0ix9bRgtxQ9jyw1Evk7gQuBZj0ngKc7/Ez30p4Z30EQuueVbNGV3zwrQMG2u1gzCONL6Pt43bbq99OXNF0zuih6uvZu4b6PjRht5lgP8Z/uudd2jXCbXDVPRPhepcheXhs10EV/69uqH6VGSZisflTKuqXnE58KWLRj6xtWDw/ufpUixAgBAgBQoAQIAQIAUKAENiJgGGY43XGQoiYDovVSQ/RxIkTcwK+3L+DVDky6UZWKgpuj8Ay2ZtWuvFo3fEgtM6X4Ya5ouVj5LN6rnFm4ZVNZ40+HMcxJMkXwY2fo7YSEUzJa510zUGJBL8q6dqKVrQ0oIra0K1acMstiLea63DJ5ndbQa+DrZyJ02vqa572mFkGklfeDZ3P95DeAisgfxw4qOBK2hrYQ6NGqhIChAAhQAgQAoQAIaAQAuFw5BIu+B8UUslJVVqwqN4fAsEfZEUxSsPRR2BthYvWtvpzjAJEfcSt9gEPpU/QxvOeN1bt7qi/AcRWFZLBLzT87OmiOU3NfckB+VUJx5Bv9FXPo+dbDC4mFM5tbvKo/szvVcX70jvehtDBLCGvmMEramqrvUZeySE08eN2YSQc3QxW6Iq+xlSB85vxMDuvrq7mMQV0IRUIAUKAECAECAFCgBAgBDyKAHKojvOo6smovQKVsoW8YliQ/43L5JXEPBdhpwfg/3flF4tF5umNWmyjS/VhcD6ogNdOhQD1BzLvbXx+0mTmwrbP+9dMWPBha1dDORc3C8ZPx3EdnX36YXO1a2HbhV3t9sp3fUMIuTnLK4OQgp64/nhFbe3iJ1OQkemmoqau+kooMTvTivTav2BL/KZxOHYZJPKqV6DoJCFACBAChAAhQAgQAoRAnwhwri2BhVm/JLCyooC8ugaGpiU5tp8n7IURsqwII0z2ejsUzGp7MvjcwS2fyXBDJIO/atWsMSW7BBTOa34N3NXzu75r978Q32s+a9RBXrVLSw8s7P4wTCT4NK8OigW9b/Q4ebXbVHhi3VAaisDVmKu2a6RcPfrD55s/vXLZsmVtuxWmD4QAIUAIEAKEACFACBAChIBdBARHDixNnZSEFps19TmykVDkLIzgL/qs6FAFeAXJnQj/YVkcF29h4ynLzbKgAeaeYhqQAW9gSu+sFYzzZ5Ga5784fhcihHTlE/wJ07gO4/stL46xnh5YCXYmBkNLcu6Li4w/BdInbQ/ML/p171Ntfc3VcNSc414PliVvwgPsm8D5MiKvLGNHDQgBQoAQIAQIAUKAECAEekRAaOuBJThf0aPZmpwAeXUyCKX7YU76mCHObHlgCdP3liawu23GOCbEBSCu/ok/3aNuzmg6Y/SBbgPqhnw9CSzGZ7oBlkIyt8YS/u9DH912SBCfb/z0PKxkLMo41pzVIdHfYUiM//eM60IKEAKEACFACBAChAAhQAhogwA2m9oXxgzUxqCuhgi9QwgjwcixQvBHYXZ6HSZMewRWPO5/E7piikXFAgLpHVsLijlU1Wca3tyRUDsCqz18kLHjHBpYVcX8esmS59erqlwqeklPp7zWnK9DxvupyEmhLRZT2G3+gFFeXV3dmIIcakoIEAKEACFACBAChAAhQAjshUCiNTF+r4M6HfAllutkTmdbolOiE+Bh9iTmC+nf6Z6zA2fMmJHbWZ9kPu9fuXwT6vW5+14ysqiORghwdvaKM8eO9ZpF2hFYIm6UYxDS58qZ/hH/WPDEr9Pfbfp6XLh04SZkp5c7P2xPX6/tPX2C8PBTauuqf2pni9o060rdEQKEACFACBAChAAhQAh4EQHOtCawYrGYliGE4XB4lOkTz+GSG56hy86/beM2u2Ff0guLCiHQGYGAzxeTm6l5qmhHYDFufslTI2BRWSHEn+vq6rZYbOa56vX1VW+BTDo/jYovTgj/Edhl8Jk09kldEQKEACFACBAChAAhQAhkGwLc0JnA+mTJkiWbdRvSaSXTBnHhxzyBF2fSNsGFvTxYnFEerEwOnKp9C/7d1WcWjVJVve700o/AYlxrAosZpu4J5XZfpyCT5iJa+2+7D7jzwQQpeOPI0SOOb2hYRK617mBMUgkBQoAQIAQIAUKAECAEOhAwBRunKxgIg9HO+wo5y/q15LY9iTRSh2d63JDrxBaBBd2XZVp36l9JBPoJn7hASc16UEorAgv5r0bCzoN7sFWHw2/B+yqrHj472rZdih/CD10avA1ciJPqGmqur6ysTLjUB4klBAgBQoAQIAQIAUKAECAEdiOAXa61JbCwe5tWBFZFRYUvHjPnYfAiuwcwox/4JFvdC9qJ0BZuWdCIC3bey+eXBLxiqlYElohr7n3FxLNeubCc0nPp0qXbQWBJVlg4JbNdDhcLY4nAYTUNNf91VC4JIwQIAUKAECAECAFCgBAgBHpDQGicA8tgWiVwX9O87reYhZzW23Cm95yYbKe/QEH8HbTTbQd7O1BQm70RGDli2/pT9j6s5hG9CCzGj1ATZme04sx41xlJ3pJSXV+9CGn573VIa+lpdcPIUft9WdedHB3CicQQAoQAIUAIEAKEACFACDiMAMLR/HivLXJYrDriBNfGA6s0FL2eM/5/6oDbrsk4JJMfYFWnUfeukZtjaTM2Vu2n+r0jAM/Js3qvoc5ZrQgsw2ZSO3WGow9NhPl+HzW0PR2Lt/4Exq1O0cD12PZ2Rm199WwKGUwRSWpOCBAChAAhQAgQAoQAIWAZgbY2oxiN/JYbeqWBybXwwIqEys4D5LMVhJ2jHGpLL0F5sGzhlh2NTl5x7th9vGCqVgQWmMNDvAC6XR2RYC1rWXO5mwnIpwvtYgfX3wXcJw6rq1sst76lQggQAoQAIUAIEAKEACFACKQdAcM0tc1/JcE0DcPz85XS0rJTBRN3pf3iSLJDLvhhSVbdsxo3aCfCPRGhb18gkGvEYl/94qu6n7QhsKZPnp4Pd1y5oqFtMU2zRVvjkjAM5NMCJJl7MImqnavE8eXq2obqk2tqajZ0PkGfCQFCgBAgBAgBQoAQIAQIgbQiYIjxae0vvZ0lWls3pRoxkV6Nu/QWDpcfx0zxCA4r6yUnbBJY2Dzg7S7m0ldCYDcCmGd/efcXhT9oQ2BtH7hd7j6ojT3dXTNwF1X2Qdqdvm4ca00Efgy5yRJRqw3ByhAyeDvaCDf0IZmEACFACBAChAAhQAgQAoRA0ghwjXcgZKwRGzDFksZCsYrILTWRC/NpqNVfMdX2VEfYS+TODUEeWHsiSd/2QICfKCqYb49DCn7RhhDhJj9Ed4bCiBv74hpao+B1lDaVXnzx+U/D4eiVYIgf6LVTwZ5MsNi5tQ0Nn/Vaj04SAhYQmFYybdD23HiRjyWKTcELOWf7YhVsqMHEEDx/hoBCHwKqNA8id8WQF+Bz121ppSflDtkt2mzCf5/LP6yKyWv1c8hchxON+FuNtb9GeA6uxXEqhAAhkCEEkHC5oLWVFfpZYoRp4L4XfATu3uH4G8g4z0f6gnzOxSAmuLzf8zv+OmnLt+CL9AZGMXHvc9z3YjPabsZ9vlH+of06YfqahC/WCG/r1Q0NDe3PiJ1t6F9CgBDQCgETOxBii21Ni2fzXwWDU0dzEX8G4zJE+bHh3NZOhDs+zXs3d3CL/D3ShgNQfqy8peDgVbmjDgfd8IrKamt08Rqj2qeDKqOdqm5G+5a7b6Qqxuvt6+qq54RD0XPw2z+1G1vkQ/lmhAzeiP9pq9huAKJDvSOAyeo+8Xj8oJ2kOIdnJz8ILSbg+VLUwtoGSjdPgTdPEE3tBRNPfO8ouz/sOtD7/3u+v+78hsnwziK/Ys9M7IDTCh1WMpl4k7O3BWdvCWEsa23d8p6XVzl7R4bOEgJpRcAoP658TMwnJuB2lvf6gbipD8T9Ng7/F8XbzHwf7sf2+779/ux0k+Jj+52LG7Pnsqu+rLGrXrvAnU3aP+Ifw2Rc+JiP++R9Lz2NG1F/uRDmG9iF+C2T+96or1+0Asfpt20ncvQvIeBNBHj7+7w3de9DazxD5TPKc0UuULYYbc/gQT/GI8oPiUQiI60uck5Y8GHrqlmFH+EXR77bUiEE9kLAMH1TcJAIrL2QceGA4GIwHjpaFyQxByPK/qW1kckZJ3wmu8Q02GuonrO7CX404cVyZk1DzYu7j9EHQqAXBKLRaJGIi6NMwY5CiG4Jqh6JySrIcPhU7W73xafdh9L7IRdT54Mw75UvG1/HyyE+miwvNz9WGoy+wg3WIExen2C++oaGRc3pVY16IwS8hcDEiRNzhgwYMgkO8keBLD4KXlNH4YaaHGdmnry3dhe83beXXf/vPpG2D8PQE/6EfDZ9Q9JnBpy4QGxtxcdlUOtVsF113M8XV1dXg+iiQggQAl5BAPfvuM6PG6/onZSe3HsEVjAYzGvhrU/h98CWV1NSuLhQKZFoT+S+1qpoXH/L0IYILKvAZU198xiYerfK5mrjgYUwnn1BXqiMdeq6CVEOITekLsj7EqpfqH4HL/J3wJJrpDUY+Se4z/xOTW2tDMeiQgjshYCcuA4dOPRoYYgwCJ8IJq1TzDhDGNAX3lR7NVL7QEDagEn4FExkL/ftnNyuxt3wPMju/3BuPldL94PaI0jauY5AaWnpYMZ8pUjIW4bOIvg7Ar8XObtfF/Am77FS0H7fM9z3jF8o4HMMj+SV8AitBq+9mPnMKtz3ng3h8dhYkLqEgGUEpkyZMhDPoKGWG3qlgeCeev5UVFT41jatfxjwlnoF4l16IiJA7kT47K7vyf4vPfmxYPP1ZOtTvWxDwOYOl2mESRsCiwsxBC91ehfOQ8cee/xQmQdKb0OTsy4hYjf7WOA0EBJ319XV/DG5VlQrixAwsJPMUUjGeSJsPgF/xyLuJg8rbJKz0rXA9Z1/By8m32HCSIDkXQJDF2AzgyeqG6rf1NVososQ2IVASUlJ/7ycvKmMG7jneRmIK7zgCxn5q23B42wsCLmxeK6dg/3r4aVVtkww8wn4bP2rvn7xyzAc82UqhAAhoAICuUbu/ngX0bYIg6/wkHEc5NU9eHZ6kszBu54ksCwXLNtiJ0L6WbAMXPY0GK+6qdoQWHj46Lua8cVVlJPjj5+Br3d9cSh7P8kkt/CqOXLZsmVt2YsCWd4ZAZm/KhYzT8aE7iT8Np/AhCnDcLK1yF1EQvLP5OwXCDd8mxv8UcETj8BD4/1sBYXs1g+BUGhqMTZWOAkv5KfglfxLsFBupICSrS/oYiImKPgTPwOJLcOKn8Ai3z8RXv8/fNZ57iwHnYr6CBjwjBwk1Uwkcvr7fG25ppnDDaNt1+YnKVsghNiK0Nsed8KLxXK3BQKt3b47+v3+LVVVVTKfqislYbBxIB60LUK0LfeKcXg+/gK6fs8r+nbVE+uxtggsRCG8xXW+CLsCRd+tIjBk1awxg4vnrVY2qgnzPD0KHkIyubmtG9ljCLxfW199CHSml1CPDRyp6w4CoVBouMECX8NkVa6gycnrF3nR3OnS81Lx7vwqksLPMVl8DojgzzxvEBmQdQgEg+UH+Lh5JhavKsBTeSpvSeYGS6yCV9r9JvM/gGTw+EyFEHAGASwe+RM7EofC++YILJSMhefjMPg9job04bg/R+J/hPK279Cp/O8z9lI4VKapgL6ulHAwegVCfmUKDP2KYNuwiZLcjVX5Eg5HLsSOskrn+UkCxFZ/jlFglXB9+fySwPCt67dCvvL3YxIYUBUXEEgI85Bx89e864JoR0Tq44GVPduBHghPijPxAzHPkSuAhBACHkQAL8sF8LQ6HQtIZ0P9cpBX0tuISpIIYOXiSGyjeCRCcG8tDUcfwwv7PQgxrE+yOVUjBDKCALw2xoiE8U1M/uCJbB7droTGngzOg8yLIXM2ksFfh0W/5+GhdV/BoILHFyxYgJ1OqRACySOAe3E8Jv9TmclL4AVyFDY/mYztM/tJCfB+Ak8qPyQvT6GaIsZjK93UB8+vcW7Kz6hszjzhfRUJRb6K3Mk6pB7JbW1lB2DMLRENR9+7NLZ6VuEHaDcxo9cLda4sAj7DN0BZ5aCYTgQWNpzPksLZbcjz8a+lS5duzxKLyUxCQCJglB5XPpUZiXPirebX8RKYT7CkjEA/TDLOQYjhOZjQvomwoz8UDOo/hya0KeNKAhxCAGR1P3m/YzZ8HibLZbjv5dSYSmoIyJxgJwjGT9iyadt6eCL8PhDw3Y1V/I2piaXWuiLQnuh67dojkGPtVLBTp8DDqqSdn9Lvblwr01O4Oo5cjG/PxelqJ5kRjsthRWZ6Tr7XSDBShmffI2ihxcKnj8k8j9YIrHa0OF8GtpkIrOQvnayqiTyaA1U2WCMCi4PA8uZyj40LpKh/Tv7taPd/NtpSE0LAUwhgArsPJrDfxk57uN7N/duXdvV7aVZhTA4TTNyLCe1NILPuhlv672hCq8KwZKcOCBE8GCGC58Kz43ugrPbd6dKRnVi4bPUIeNLcApxlvqz7DD/7VXV1daPLfZJ4byDAo6FoxGTi+2ub14O4MjpyVGn8rs3TQMAIrnyCZNuXp+IeWKFQ+SRMzB+Hfe3egrbtVKghN9rT51RaVYmbYpnc04gKIdAtAnBR7Pa4Igc1IrCwh3wWFVxWF8MF9j819TVPZ5HZZGoWIRAKlQUNLi7BxOp0TGBzaQKbtsEfjp6uB+6XYkJ7VweR9UnaeqeOshYB6eWxrnndaYLzy7EBQzhrgciM4TJvzaVmnF1YGorMNfz8FyCylPemyAxUeveK8MDBzPRVYFH4EiRbhXeH0vMYZwdDCLdD4KT3Y7GzSqsjDXNeZZ8Z5VPKC+PMfAZoyXxs2hRE7OIetVE4e8tGK2qSLQhw5q4naoo4akNgIZeDqfGaUHfDjPQ//GGsUh/T0FD1YXcV6Bgh4EEEsDtR2cm4nS+Fa/O07HGqVHKk5EveNSCyLgOR9adYovWWJUuWbFZSU1LK0wjInHbxNjFrbfPHP8Jk+SC67zM6nEjqy78DIuss3PdI+B7/eX19/ccZ1Yg6TwsCIK4O56bxU2Gy00BeZWVyZ5ABrhIwIFFGgUTBgpymxXAXP7uo4TdmX/zGLET7Irsy1G1n2iKwDMNcljAln0qFENgbAZFgSqcp0obAAvRZ5YHVcantgxCLf06fPD347BvPbtv78qMjhIA3EJgxY0bu5o3bzkV+mx8jt8aErFrxVX+IpGfGVQF/7rcjobIbt7du/Svy7/W4Pbn65pCGqiAQiURGIq/Vj0CSngedBqmiF+nRjkAA/55vMH9FJBy51Rfw/QEhxS2EjX4IRKZEJgs/vxZ7W38DC8FZ5G7VzVga3FUPrISR2JkGoZuudTgkRNxV/OxghJzB/fEb8wTaHmSnvfpt+BjoKO9bS34co1rXfNgYKJTPdG3CKdUfK+9oaAif0gvW2lCvgotN3rksHNX0sO35LXMgMbtfOhyFlISlCwFJXGFXzYuRd+lDkFd/Rr8gr6goiYBg+yFH1l15ufnLwuHoV5TUkZTyBAKSuIqEo78VCf4RPB6ugNJEXqk7coMRFvTLeFvi3dJg2Ux11STNrCKAZNbHwsvuKeHjr2Hqi5BBeo/0ueyBBYTHWR0nD9UX+VvyV6qkL8irQP/cfJkfKqSSXg7rEoAjQ3+rMnklS+C+f89qO6qfFQiYrZtzm1S2VBsCCzfhWpWBdlU3zr5eGir7oat9kHBCwEEEJHGFna8uAXH1EV7o5FbGhQ6KJ1HuIjAB8ctPgHj8d/lx5WPd7Yqk64QAiKthmDDfBuLqQxBXl8O2PJ3s09sWXoyNNOaVhiML6L739kiXH1O+H/KczUGuuRdgycn4owXQjiGNCf9Hro4uN8a7Kj+Twjlbr1g0CM/L7X8P3JJOyiQsaej7Y9u4c7YsDfpRF95DoHnCgg9bVVZbGwILD6jsJbDarzDxy1AoOl3li410IwSAAMcqfgWIq7ex89Uf8H00oeJRBDg7NW6Yb4OQmC0JSY9aQWqnAYFpJdMGdRBXq9DdVfizvFqcBjWpi2QQEPzLcW6+FQ5GLpdJ95NpQnXUQAB5gPxYeLgsHjDfxU/x2dCKiKs9h6aloWGRq3MJJOsdt2eX+nzDwtYKlawpDUdvwSX+HZV0ckcXIcMjbRVEL1Eid1vIad9IuVDgrohrQ2DhZ9jVH52uwCn43YfBfCgajWqYoFBBtEklywggXOF4TGJfxir+Y2is7yqkZWQ83UB60Fy/ZdP210tLy0s9bQkp7zgCMnwD3sHnt+S2yTAFSVyRx5XjKGdAIGf5nPPfrmle/xISf5dkQAPq0iIC+P0tQx6gV/Gu/Ds0pZDdbvHjkmA3uz3l0EFsOKXtuw92R1eGwJJELSJzrnZo2FQWs5EZ4ia7Chomf9VuW2qnMwJiqerWaUNgGdkcQvjFVTY8EWdPIBY6/4tD9IkQyCwCmOAcGAlFn0a4gtwB5qjMakO9u4OAOIiZ5mLkNboDq/yUENQdkD0lNRKKnC7zpSGv7D1QfISnlCdlk0IA7jtHMtNoCAejMo8ZvlJRDYH2PJMybJfzRdBtkmr6KaWPEOnwOhinlM1OKqOIBxZydJ6Bp9FvnDRNUVlxLsSZtbW1q+3q1y+vpQ5tZSJ3KoTAbgQQIVO/+4uiH7QhsAB2tntgtV9i8oWyI6m7NmOr6L1DavWBgNz5RYaXYYLzRhbkIOgDjaw4bciE3PFWc2k4XH50VlhMRu6FQHRKdALu+2cF43/HSdqUYS+EtDsQwAYcdyA31rMyt5J21nnYIOScOxTh+jLPlfR+pHfCvsbSYK4SWMFgUHqg6nuPCHfx62v45PlwuOxLCGV8EB91v96xpw67oKah5r/J4NJTnWH3fbIF88bbejpPx7MTgYTPRwRWuoYeW9OuTFdfyveDpO7hUOQXyutJCmqLALwvzoT3xfsw8Hr8UX4kbUe6G8M4O5QLswEkxvWUI6cbfDQ9JCdnkrA2fexNmHiCpmaSWT0hIPg05FZ6nXJx9gRQWo9zGbqLzRJeQq9HpLVnL3fmsgeRYbQncAdfoGnxGa4SgH2hFg1GD4NH0j9RT/d3TmwMKy6qbai+ry9MkjlfNK/pBjjQXgRv6ZXJ1Kc6miMg2OtjH16lvFOQNgx1XV3dGvwqfKr5ZZW0eZzxn+IFRibppEIIpA2BcDg8Ctfd4/C+mI9OKUF72pBXriM/NJqNHDmL5DWhnHakkKMIIGTjKz7ufwdCibB2FFnPCRuOl8pnkOD9BiKvMzN2U6ZMGYjf4H93hO7SZgkWhsHtHE6c+8dbUMdzVU3TyFgOLKSqGG8a7FmAto/ngLOoMOZ3V9fV1fzZYrNeq4+Z13h30YHN+wtulmIufTty1crfcyrZiADn//CC2doQWBJshCnRbgpfXHV4Bom/ysSdXxyiT4SAawi0r/hy4XsX193XXOuFBHsKATyEorgmXoNbP3nkeGrkklM2FAoNx2S5EiEb2AWJFyfXimppjoAPCd6vW9u8/gmQ1wM0t1Up8+QkPuDrh9APcYpSinlEGc7Nj1xVNaFvAnfgFhs9emiTq/j1IBx5N/dlpu8ZTAL1Dc/8wvbZNfWLf/nFV+c+cST8KJ67pg4eWVePmdt8qOnzjce8+gK8xz2FXtqc64kkqYwA8iUSgZXuAUJA8Bvp7lPx/nJwIf49FJq6v+J6knoeRkAmaUfoUC1emmWyZpqweHgsXVJ9GNz6F+AauQbytVo0cQkvT4gtDZZVGMyPRSPxDU8oTEqmG4GTQV7Xlx9XPjbdHWdjf5HjImGZUB/348RstN8Jm2Ox2Aon5PQog7NxPZ7z+AmQHKsqKysT6TZD5lrF7ppP4ro/KN19Z6C/39fWV9+Qrn7HPrRqRfG8pntBaJ2a44sNEcL8Csb5IfT/ebp0oH7SjsDS4rmr3057rzY61GoywZlBHlh7XwT7Giz++LSSabRt8t7Y0JEUEcBWxefgpXkpxIRSFEXN9UbAB/NuKg1H/067pHp7oEFYDy4NReYgxOAxWDLM29aQ9i4jMClumC/BAzPicj9ZLT4SKjtPGPx/AGF4VgORgvGYmH+6ZMmSzSmI6LMp+hjXZyXvVkh7/iuQVwHkWpU5r47zLmzJai7uB3n1w2RrO11vv4fWbyuev+ZJkFnnFMWahglhRHA9U6ih00BnWB686X+XYRWS7l4rAgveRuSB1f3QH9aS2/aPiRMn5nR/mo4SAtYQmDLl+BEgr/6NrYofRMsCa62pdtYiINhp2wta66LRaFHWYuBhw7E5w8kgrBEmzM/2sBmkenoR2BcemM/CY29mervNjt7g2XoVog/uhbWB7LDYNStdJ2AQjjXeNe0zLNjt/GHdmMf75+T/BcdP7OacVoeQU/bh2vqa78MoXEKZL7ySJYrnr67dFWoomLE/FLsc7wULoV0s8xqSBnYQwBh+3LKxX6WdtplooxWBNXBg3qsAcUcmgPRAn8cPHjTkAegJ0pwKIWAfgdLSMulOvAxX0qn2pVDL7EVAHG7GWT12DDoyezHwluVy8SMcLPsNXqQRqkFeHt4aPSW07QePvbnhYPQKJbTRRAm56ydMuU0TczJthusEFgwcm2kjXevf5R0cu+qNa/8OkGbf7npcv+/8X4Ec/h3YZapqW/G81csRavh7JII/wfCLkSDUv4mJpgw13KSqzqRXNwhwceuEBR+2dnNGyUNaEVgLFixoxUtSnZJIK6EUn4mH/o1KqEJKeA4B6a6N6+dXzBRPgKkf6jkDSGGVECg0Oatu9+hRSSvSZS8EZA6jwYOGLuZcyPAFWgDZCyE6kCQCyO3O7sBvCBEuSQLWSzUuCWWcv76XOnTKCgKCu0pgSa91qKOvt7rL+HUeyg4i/Medj2n6+bkBg/qfWVVVFfeKfYVzmj8tntdc2R5quKZp345Qwzuh/2qv2JCdeoqVbZ/l3e0l27UisCTwmFgv8tIAZEDXa7Fr1EUZ6Je69DACMuQrr1/+/2CCfGmgSayHx1Ih1Qvg0fNEex41hZQiVb5AAGMzCzmMZGh+FuQY+cJu+uQqAldFwtE70AP9jtiD2UAuwbs7CGV7EqjV3ghwtmLvg84d8fni452Tpp4k5GBzFb9dFstQZBDht+/6rvH/9f239jut3THDo0byKhbvCDW8bMy8pmKDCXjd8+tgzkv4w3SdiioIcMav9ZL3lcRNOwLLMNnzqlwQ6uoh7oTnw1fV1Y80UwmBSDByIkK+XsPPTVglvUgXLRDwYRp7XyQckfkdqCiCALYl97d7ynA2FyrRzqKKjIsuagjBrpAkDOzR7h3U7TEC+fdr/BZf4HY/2SZfmO4SMCActSawTLPVVQ82eT1GQ9GpiLK5Hx+1fm6A2XnVn2Oc/Owbz27T6T4snNf8GsIMfwEy69hALD4CoYbfBnFSCXu36GSn12zBStLzhfOa5nlNb+0eAvsV7id3RNvotYFIs74+mRQwHC4/Os39UnceQwAeGJdhc4SnofYQj6lO6noHAZ8Q/F4QJtkQEqD8qIRCoeHYllwmY71KeWVJQe8iABImHCr7W0VFhdyhlEoSCMjQKZB/SJZMxXEE/HF3CRhTawJrU0NDw2eOj0kngXK+YjL2BA7ldjqs48c3Y/HACQgb1HoeO7Jy3QaEGs4pmtf4TSPGQGaZJ4BIuRPkfLOOg6qwTZt9fvO7wN5zHnHaEViVlZUJDMMihS8WVVQr4MJ8OjolOkEVhUgPdRCYPnl6fiQUfQTeMb+DVjTBUGdodNVEhhP9CiQWkSYZHGGZWN9gvhehQlkG1aCuswQBzsS565rW/w3myvufSi8IhMPRM7IkdKoXFFw7Fd+xY0eja9IhGGM3zk35mZSNma+r5F8oNHV/zFeego365hDbOYAfcJ848cUXn/80k+OZ7r6LKpt2FM9bsxB5sy4rmt9UhJvlWPApN2Eu/3q6dcm6/gS/fNScNau9aLd2BJYcBGGwx7w4GBnQebjpY8/TlvYZQF7hLuX1sL2gtQ4vJWcorCappicCt1GOvswMLMLKz0Ji/XpMtYozowH1mo0IyJ3EEE54SzbanqzNCOMv44I9iPpavrMni4Nr9QRrXLp0acw1+VKw0JfAwrW5wi3sIpHIMIPFF0D+CLf6UERuo8n8J9TU1KxVRJ+MqIGVDDFmbuNLY+Y1/3zM/KYj4iwxFnORC3BcEphtGVFK2075n8fMb7zfq+Zp+WPY0rLtSQzIVq8OSpr1LkJ+o2dKS0sHp7lf6k5BBCJTIpNxPWAnT3G4guqRSlmBgPgjvA2+lxWmKmJke6gw43OgTj9FVCI1sgkBwa5GHrwrs8nkZG2VXvII48+G0KlkIXG8HkhU1wiY3cpyPn73Z80+cMMdD6xwODxAJPh/AJfukSLrBU+cUF+/aJVml0bK5oyft3ZV8byme+GddWoixz+CCT4L85NHIXhTysKzWAA8Quu3xAZe5mUItCSwsJKyHRe4JLGoJIfAJGYaz5SUlPRPrjrV0hEBmaxd+HgNbCvS0T6yyTMIIN8tuwe7DVV4RmOPKtqerD0c/XNHqDAWOakQAplBAHnwbqfNHPbEHvdnv4SPycnaoD3P0DcnEUAo60dOyusqa+LEiTk4NrrrcV2+4951nACUmBnC93dgdJQuOPVgxycgr46vq6t7r4fzdLgDgXEPrNwIj6H58M46syjWNFQII4KXFrkj5QcEUvIIwKPtvZgZ+PrEymWe9mjTksCSw4iLWv7oU0kegePycvIfkROa5JtQTV0QiITKftCRrH2gLjaRHZ5GALsTiofC4bKIp61QWPlpJdMGxWOJBQhtoR3NFB6nLFKNYyL8ZxDXp2WRzb2aGm81/4h32SN7rUQnU0bAbQ+soQVDi6GktrlEXcCPDx405K+YaE9PeXDVFrBJcGMGyKtlaqupnna8kiWK56+uhWfW1djV8ECQWZNwvVyN2T8iSPBWQ6UnBD4Qhu9L4+evWN9TBa8c15bAKhhUIN1OP/fKQCihJ2enxtrE3dCFVuKVGJD0KCETZ2M727vQm7YvWOlBknpxGIFcQ4jHg8HyAxyWm/Xiyo8p36+lX1s13PGnZT0YBIBKCEjieh68gZHEN7sLwnpn4U2MQqnTcBkYLuZwkuoLQ+sdCGGhszs4RsLR32AacnYahj6TXWzHovGpdXVVL2dSCV36Bpm1DKGGt4+Z11jqM81ivNtcDNuexZ+nvYwcHp83uZ99aezDq7TIs6YtgbVgwYJW/Gzc7/Dgay8OrtTfB6HxW+0NJQMlAhxj/Sv8fxvBQQioiACW0Yb6uPkkPEP3UVE/L+qEfIdj4gFzMdYoJ3tRf9JZewT6CYM/kc2by4RC5ZNAXv1F+5FWxUDhTg6n3eZxY/zuz/p9EIFAYJVTZoXDkZ8KwS53Sp6ictrAap5eV7dYpuyg4jACox9Z04hQw7vgmXWiv8AcLIT5FXhl3Iv3yY8d7soz4mD/87FYTqRoTlOzZ5TuQ1FtCSxpt8kCd+K/RB8Y0Om9EbgMxMY1ex+mI7og0J77JhR5EPb8WBebyA5tETg43mZSeLMDwwvyajxLGFUQdaAD4kgEIeAOAoLtl4izJ6ZPnp7vTgfqSpW/zQYTD0BDykmapmHy5fqWu9mVqfEOhMBtTVVVVYsT+GHzlm9xwW92QpbCMmLM4N+obaiSUUJUXEZg1L1rthfPX/MkQg0vGLOmabQpxPEgc36Pble43LU64rm4a33BiBn7Vy7XKvG91gSW3NEBjKvcepOKdQRuQkLVH1pvRi1URwDJ+gPxNjE/C1y0VR8K0i95BE4EiUWegsnjtVdNkFeHY7OOenh2jNvrJB0gBBRDAJOMI7fnt9wHtfAxe0qiTfwI0QMl2WNxxi3dAgLmE1e14FqHEDpC/oG8OgmbtzyAcdD5fk8gtO3btbWLaZMxV2+47oXzKhYfO795Ecisy+GdNV4wY39wBPD20zZv1ibG+Zlj5jZffPS9S2Pdo+Ldo1oTWO3DwrlkWqnYQAAJVX+NPAzftdGUmiiKQEVFhS8vt/+DeEH+hqIqklqEQE8I/CgSiny1p5N0vGcEosHokSCv/ocaI3quRWcIAcUQ4OybeAe5VDGtXFOn/LjysUKI61zrgAR3gwB3hIDpRnDnQ+M7f9HpM0inlPELhcqOgRy58ZbOm0gh1z3/QW3DYiweU1EBgeJ5q5cjb9bvZd4s5IYqwrP3Qui1AH9IQeTxItjjBheTxsxt1HZDO+0JLMQYy5f2Nz1+KWZKfTxv2T1IqPq1TClA/TqHgPS8Wtu0/jGsNsx0TipJIgTShgDecfn9cpKXth416Ajk1WEmb09mOlgDc8iEbEOAsztwDYeywey4Yd6Ld66sC5vM6NhykTIB05f+cCka11cdr55PdQdCuUkLQmZlpEyBVzFIUu8ra+oXU167JMFKdzWZG6p4fvM98Mw6qV+sdV/BRQXu24egx6fp1iXF/j7knJ00Zn7T1wvnNjelKEvp5toTWBJ9PGBvUnoU1FbOj50yHi0Nln9ZbTVJu94QkHk18nLyH8HL8dd7q0fnCAHFERgc95kPy+tZcT2VUC8cDh9kGu3k1b5KKERKEALWEQiAgJU58LS+hhFC9W1Ac4J1eKhFKggIk69MpX1fbYPB4BDU0XcTkhR2cMTv0yiDm88Bn+F94ejl85zza2rrq3/tZRuySffhlRu2Fs9t/jtCDc8pijWNwMppORNCjt8yhXH4EOGC3/u4YMShRXObpBeZ9iUrCKy6uupKxLm+qv1oumdgDuPmP0pLy0vd64Iku4iAEW9L3EfklYsIk+j0ISBYONaWuCF9HXqzJ+S8OpAL3/+w2+B+3rSAtCYEdiNQlGgz/7b7m2YfQM71wySJFlozMa6G6aoHlmHkjs+EWWnr02fYwm/KlCkD8fv0NLxcxqZN1wx0hFQsv62pW3xLBrqmLh1AgFeyRNH8psVj5jdfAe+sSX6/WQwPp/Mh+p/42+xAF6mIwIadDFFmfCaItoMRLnifjrmuegIoKwgsGC/govrznkCg40kh0J+Z5lPtuVSSqk6VVEEgHCz7FR5wZ6uiD+lBCKSKAGKbfyLzZqQqR9f2odDUYuS8eh72jdTVRrIruxDAi/pXdM3JiQ0qLsNoFmbXiKpirbs5sLgpxqliqRt6JBLGCqtyJ06cmBPw5/wD7Y6w2tZT9Tn7U13DYmzKQEUXBEbNWbMaHk5/AZl1etGapqHt3llcyJ0zq/G3PQ12CixKvg5a4xdIQn8AcnhNRQ6vRyTRloa+leoC5Hf2lHAouhgGR7PHYlcs3ZAQRrShoepdV6STUEcRKA1Hb8XD7mpHhZIwQkANBN4ZMCj/yAULFng/4aaDeB577PFDc/yxWog82EGxJIoQUAGBrSbzH4Edpj9SQRkndJhWMm1QS26b9GKRoWZU0owA3mcPcfN9tjQUvQom6bqDbgtC42TONtPCsBmloTIkltZ8IyHO5tTWVX/HIjYWYKSqqiHw8vklgRFb1x8Jr7ujmcEmIyn8ZOg4CbzDgBR0jaH9W3C1epUZ2C0xwf4z5pHGNSnI06ZpVuUR4YZxPbyI4G5HJQUEhvl44j/RaDRSXV3dmIIcauoyApFQ2Q/wACXyymWcSXzGEDhk88atP0Pv12dMA8U6Rr6VPB+P/RtqEXml2NiQOo4gUGCw2AOQVIY/K5NmRzp3Q8iO3NafwKOUyCs3wO1bpsCGY6v6rpZCDc7GYRFR17IShlm6D0Ho/VZ78kqwf/pzjO9ZxUbXiyRb7OoI33sR9sq/3WVFxdj9fDmJInhjjjENUcSFMQBJ4gcYgg3aXQkfTME2Il/aVnxs5EKsE37etKVl4PsTK5e1da5Hn3ciAGIvuwo8Uh7Dj0lFdlntirUfcJ8oq6mpWeuKdBKaEgKRUOR07NiGHQexDkCFENAXgRgzzGNqa2vhUp3dRSa2RyjSv4DCydmNBFmvPwL84tr6xXd53c4pU44fETBiH9HOgxkbyTXwIBrtZu8gbJ6FfD2T8wu2oLah+qRk8QsHIz/HBP3GZOt7sR4m1c8WDMr/CnmGe3H0SGcvIZB1k1t/m3EpBmiTlwZJUV0niAT/rwxXUVS/rFUrEowcC/JqDgDIuvs7awc9ew0PcNO4G+Zn3WJM1yGPtQm5RTeRV12Boe8aIiBuKT+m3PObEwR8sR8QeZXRyzMNoahifEYtdLNzgy1PVnwkHPm+7uQVHO0W+XKMrxJ5lexVQfUIAfsIZN0Et+qlqnUIq5ptHzJq2QmBw5BrZSF2uxrc6Rh9zCAC0SnRCYLzp6FC/wyqQV0TAmlDAC+NwdJg2Zlp61DBjpDc+mrOxLkKqkYqEQJuIDAonmN6elv6kpKSAID5vhvgkMwkEeBsRZI1bVWrqKjwYW2lyFZjLzQSyeFXGiw9BXmB5EKTzuWFAMirqqqqFp2NJNsIAVUQyDoCSwI/qnC/P2DS86oqg+BxPY6AB8TTCF8p8Lgdnlc/HA4PMH38cRiyr+dYZJ4QAABAAElEQVSNIQMIASsIcPHL6ZOny2SyWVfC4bIZ8OK4KesMJ4OzGwHBZoXD0aTDl1QDq39u/9Ohk6vha6rZrJw+SRIwdvXe0LhBklc5dtsr307wPj2wsMA9BcEAj8AWjXMu89cTInYyyCuZv4gKIUAIpAGBrCSwKisrE4YQFwLfeBow1r4L6QERjyUeB4nVT3tjFTVQrvQZwoeXBDFRURV1UguXPFuPvzcZFwu7/skcCKhQjVx7b6POBvzJ+lTcRaBwe0HLle52oZ70UKh8EpJ9YkcnhpV+KmlEYAf6+rzjrxF3+IpO3+l+T9NAYAvzX8vcb2nqztFucJFc7KhAEmYdAZF8CJx14UjKbJj6hg8CEJNz+dzrsUQikUMBwjOah8m+H0v4T2xoaPisRyDoBCFACDiOgCd/+J1Aoaah5kUkFLwFMdnXOSEv62UIPk0mEJ4xYwbFf2fgYljbvO4WuKp7djU6A5Al0aVYhVxir4GQek1w9gbn5iqEH68NBAIfY6XNCvltIFnvsFwjNgovfJPw2jeJCX4YXuok2TgmCUWoSnIIXAkvxHvr6uqyYothTNz3jbea/8Z1lMoWzckhm121NuKefwfbVr8NbFeCnFptcNYUE8Ya0/R9PmRIzsa+cpwgPKx/Xl7evqg/wsfM4QifGQuiezzjHDuS8UPBaU8ApFm5gOjwpXRwok2cB5meCk+SxDN+B0odxoLEWUXAZ/TpQWRVZOf6Cc7GgWTVtvRv9fdIYAWDU0eLROwZGK/xDpviI8HNLy1ZUi0XNKkQAoRAGhHI6sS3cuUu0WZW4/clmEbM9e5Kbh+ba5xhcYKvNyYuW4f8N7Mw0Zrrcje6i4/BwBfw9yxmlfVYOX0VO9tJDwtXSzAYHGIYgXI8iKdjonwCOtN6xdZVMCFcMPGHuvoauVGH1kV6XK5pXv8srpupWhvqvnFbgGED3gFeBEn9kmn6lzY0LGp2u1sZ7rptQNthhkgcg5yFEVy4UfQ5wu1+NZW/XvDEBBDXW7xiX2kogvxd/Ede0VdXPRPCX+jm/Y4dCGVo9zU64ofn5qc19dXdpquYVjJtUEtubDF+kQ/X0fYOm5oNP4tUV1f3SOJpbDuZRghkHAE8g7K7ID57PFxcXwUKA7MbCSetFw/V1tecC4km/qi4iIB00RZx/iIIrHwXu9FV9LsgPJ7jhvGc38//p0L+glBo6v4+lphuMnEmHs4RAJ/1z2iLF18LJiUHuDkpsaiPK9UxMfoFBF/rinC9hSZAVtXhpnrWZHxRTg5/SZXFlvZwUJ44lZv8q7jrj8EwkIdW8tfiTbX11T9Pvnpma+L+/Qga0GJFZoehBdeMfG9y7T0VROU8/ITPzKyZrvX+MvCTz6k9Chbl8nw88F8clO8vupYNhsnKql+ofkdXA8kuQkB1BGhyhBGKhCLnIlToftUHy2P63Ycft+9DZ8wXqLiBgFzF357fIskrhKRQSQ4BsQovlI9gxf5+rNi/l1ybzNSKRqNFZpzNwkP6+7iJDsiMFt7rVXcvrNJg+ZcZN+VOo0RwJHd5tuD+eZoz/kRb3P/Miy8+/2lyzTJXq3xKeWHMnzibC+Pb+Ak9KHOaeKRnwbZxvxhXU1OzQXWNI1Mik4WPv666nlmg37t4Rz3ETTvhHf8C3s+muNlHxmQL9lhtQ/UZnfuXnsFrm9Y/Bpu/3vm4Zp83cVNMrXmh5hXN7CJzCAFPIZC1ObA6j1JNfc0DkWC0HCEEeFmk4hAC342Eo5/V1FVnXWJlh/DrU8z2gh13g4wh8qpPpNhaztmjzBTzZe67vqurUQOu6Y3Q5Hb8/TISjEQFN67AZPZkfKeFh16GCETFeci/cbuOXlg7SU3zIZhP5FUv1wBOgbNiVbhVHurXGvjnwqULN/VeXa2zVUuqmqDRrfIvGopG4S32Q5j0FXynce9uqOCBLMz2kLyfdndapWMgr05TSZ9s1QU/oq7mv2rHlWvsZWfsjd+6pvW/05q8AlHOfMYpNfVVRF5l64OD7FYGAXoZ6hgKX65xIV55lygzMhoogiS4V8BVfrYGpihnAlb2vovJ2dnKKaaWQouxQ9tpI0ePKAKR+kMvkVddYBTQfXFt/eJTTWYchefUYzjvWthDl769+LWfj8e0yy+DxOABEQcRy1i3eUe8OFAu6PwJEqbfkRDGgfCumIp75n6vkVddMamur66GHacZCXYw7v2/4byVDSS6itP3u2AXy5yCHjDwax7QUX8VXd6BEDl2CwDiMG2BFHxFZ9si4bIb4QRwSedjmn3eIcmr2tqqWs3sInMIAU8iQCv5nYat/Jjy/eIB82UcGt3pMH1MHYGr/5+9L4GToyjbr+qZ3c0dIoQrkEsUAUUxkmR3djcrgWgAAcGoKF4oooCKfor4eeJ93/4RPEAQD6J48RmFEDa7OzNsMIhoEA8gEELCTUKu3Z3p+j+1OdhjZnamp6u76u23f79kp6ur3uOpvurt98BiQnuS8BYCAu0L2p/np4T+AqRfkHgbjkA/PBV+KX3xTcou3qi2d6QUqU9gQavza/B9fPg5oPeeTjd6h9uQ12y0aMFaBhcISn082Gjyo+7B4umrU6ZM/OlYFQJdR6K5ueMFnvQ/i4teh+nwtT9kQlEl9tPZfPcnhzRZ9RP37UOlShkvEmCV0nuEgUvkek+J1cJTPfgQszHlq82e7z1WaChsj0PeYrG4K5/P7zTFm3qoKIpPLMlmV9+s8cs0t58PL/fvm8LSArr9UqgzEa2jQ/d5YwQYAQsQ4JefEZOApO7zkNS9G83jRxzi3eAIYG0hL+zOrUbIG2/1IKC9MMY3TdRfgObXQ4fg2G1Sye+ItP8d5EHZRFC/kirtDi8S38XBF5XskOhGeSE8V/4fBQgymY6FUvn6ucRh/8Mn9C/wsvwcPBR/j+ZEeSXi2j8BCutn6vOHQ5LovacmbBt3+E133RSLUWQs5FubF71aSHXDWP0IHX8auvwEHpHfz+c77yGk15iqIOz/DBh5fjNmR0c7+CJ9RC636t5Mpv00ierjUCPlqCpjiV3EAuYN2WyX9nznjRFgBCxBgEMIR0xET0/PWtys3j2imXfrQwDPN/VdhL29uT4yPBrGq08ABTZePXsqDODnlekB73nd+dX/myTjlYZAhxfB00iHFV6MXafy/Gj5zW7qfaDv/DNOF2uA8eoa6MLGq2dPmL/r8GB49s6H8eq3aE6U8UrDgGt/Fa59Xab+s/jHYYUaFCGmbZ+809rQenwxPn63mMT/17mChLgUxsTDcI1enDTjlZ5d5KycS3iWi1u2PLJBf0DDy70Oa6dqvEJEujifjVeEz2RWzVkEqN506pqQDRse+NvMw2dp77SOugjx4KEIwAlLnHb4zFn/Ar7rhh7g39Uh0NKyqBkn5Y/R2/lFeXUaV+yFvMbi58Lzz+rJdl+7/uH12yr2Jnxw/fr1/oMPPdA79+A5V/tp/4WIKjqCsLq1qLb/YYfPyuF+c28tg2zre8gRM74DmZbYJldM8jwMY+1FqH51wYMPPfjPmGSwhi2u/cKDGx64ddaMmatwP1yMa38/a4SLSRB44s7F/dBKb++Zs2ZeijmibNjQMa2/Fyn/VDyX/3jvI/fqD0yJ3A4/fObZeOldQFT5vvFNE9bDuPMT6Ec1lQWMV+qCbLb7B0TnkNViBJxGgBfCZaYPX40+hUMkwk/KqBhHcwpfa65tbW49NQ7mLvNcunRpkyeUTuDLRmcxmENjXk+2643wmLzP5XkNU/bO2zs3Y9FwspTqEtBN7MJhKKZYTL1z6L5rvzOZRUthsHFah5Aw3wU6n4PH0ZEwXl2D34nzuKqEI/L9ZdONqZfAOHJjpX6JOCbF0QjfOsFCXZFGR77MQrnCEklX/rysO9d1Bp7LD4ZF1FU6MF7NdVX2KuQeD0ulNl5RNph/BMYrynm9qphm7sII2IuAZ69o8UuG6mXvxRP5d/FLQkqCBiG967EwezkprQwrs+3pHTox7VGG2dhOfosOlevJdS/K5TrvtF3YmORT3dnuryB8oQXGm//GJIM1bIHBq+bPX7y/NQLVIIiuYoUwOf0CDTUSvd0KT8sX46PSxygl5Q97RoHN08j5drquwhg2bdfoKU9eaJvMyK/6PMhEdcG/C8a5s/Z8+NWGLN6EoGzAoj6/l+Fc/hJ1JVk/RsBlBNiAVWH2li9fXtzVt/0N6HJbhW58qHYExmNhdmNra0dr7UOTN6K9uf04uDJ/KHmaP6sx3oh/rWTxaHhffAut7H3xLDQlf2WznX9p6mt8GQx+K0p2SE5jY0Nq4DUuqlvo9z8HuWe6KHtIMj8N2925WEgshkfHv0OiSZ2Mn82vvgRemOdB0SJ1Zcvqp8QpbW1t08sej+GAUh7Cu0luiCRT5/XkV5NNWB5g1vRHh9kBxvGQ+BH49h5DbPySsASMACNQFgE2YJWFZveBtWvX7pApdRr2/jNGVz5cGwIThO/DiIWqj7yVRQBeGOmiFDp0MJkJnKXYjJfjM7K5rtdks9mHywLFB0YhsHLtyi3pJg/3LnXVqIMJapCeeJNr6iIEShdqsM6LJCocYbBe5aXFsfAo0ucudnmrBQF4Yf4QVoU3YkxSQ4kbVdE7uxbMTPdF+gTtgUVug7H0w9257p+SU6wOhTKZzCEYPr4OEjw0FgTUVTBeXRwLa2bKCDACNSHABqwq4EJls8cQwqDzNj1eRXfuUj0CU4XvrWhf2J700LiyiBX6/AvxKe+4sh1oH1gtPfVSvBxzGG/AeUZYUQEhl+diOJIHJ3RTIgND+fNd0X7evHkNKL/+Q8ibxHx32uDyQRisT+rq6trgypzZKCcqZ/0SYV2vg2yJrFCIysdvtWxenLkH1YDbn3XIeg39E9FVyoa5iVCUlJLyV4fMOFh7rvIHE1LzyspQRYANWFXOrA5hQNjbKbi16fLAvIWHwHTfEzd3LOyYHR5JGpQ6ju84GNlvLqOhTU1a+EqpTyMH3WIYjzfVNJI7l0RA53NQSrwLB5MZfln0ziwJjIWN4xsn/g/EepGFopkVCd6WwvNOwLn6NTBK5nkaMsI6rEuHd4Fs4hZl+sMPwu8tuo4UNQPWTl+kE+slWvFSLfpswKoIkF0HcXP8XbpRnq3TxtglGUvDCDAC5RBgA1Y5ZEq0d+e71+C9+vU4lMgvmiUgCatpRtHzbx402IRFkQCdYoP/VagxlYAqtajwmFDeKdl89yf5ZaIW2Mbum813XYFcaslccEjxqrERir8HQk8OhdH6o/FLErkEtxX99Mt6ejp7IudMnCE8WK/WYV7E1Sypni/FWSUPxNIoqRmwvpTLrbo3FihtZyo5gbvtU7RPPqlWNjR6r9fe6vva+AcjwAhYjwAbsGqcop58D8pU21fhpkY1rOuOLyBHFBr8mxDqM8064WIQCDlwFgETXUAgSdsdSNT+kp5855+SpHSUuuqy0FLKJBpIFra0tBwYJdZBeEnlfRHjJgUZ6+4YdW1RDZyQz6/a6K4Odks+GOalBnMp2i1o2NJJ8eqwSQahd+K8E/WHKOvvPzXo1u+LwuU19E9WVynmJEthZ7XNpRtSr4bxapezGrDgjEBCEWADVoCJR2LZKzGMS6wGwG6MIS9CTqw/Ljl2ycQx+lE/7Cnp6TAaREEkZMNXsIFi38s5Ubv5+e7Orv68lEJ79yVp81IidbLNCsN4vwCX/Dk2yxiybP1SyHciR9ub8/n8zpBpM7kRCKCgw0V4oNw+opn2rhLHtrSc8Ny4lexr7DsybhnC5K+EvD6Xyz0aJk1StBQbsByYzzvTjd4pMF5tc0BWFpERYARGIMAGrBGAVLuLPB0fQVWZn1Tbn/tVjcDCHZN2/Wbp0qVNVY8g1rG1ZdEbkbIkSdUZf4yvYEt7e3u3EptKa9XpznZdAvPoNdYKaEAwpaTNYYQSxvtvQu2kGK2fQU7Jk7tzq39gYKqZZAkEtJeBTA+G1D1V4jDZJk8UzohbOd+TtCoQJuzZEeD8mRtgDA+JDoG/9xcaTsQ98enoWDInRoARCBMBNmAFR1Pt6N+uk6PeHJwEjyyDwEnPPL39Z8uWLUtcFa7m5maUXlafLYMLtWadWPhTMAa/HS8SnH8g2tlV6QbvfEzAX6NlGyM3KU7q6OhIxyhBWdaZTLsOF15YtgOtA49KX3Ugp+QttNSyXxtd2RFJ3S+wX9JQJVwaKrUgxHxSCdx3TJkyoSsIDEkYg2fMOOh5SBJ0dVFHfCH6r0ypV6xZc8sTLsrPMjMCjMBuBNiAVceZsHbt2gGEPb0GH83X1kGGh5ZCQIozNz/0yHdLHaLclhIN74N+MynruEc3OMSo98J4dVkCdLVSRe2RoUR6GYTbYqWA4Qs1ub9fHRc+2foozps3rwHeSEm5DjYKz2/rvq37jvpQ49FBEUBS919gEXdd0PEOjsvsMSrEJrqUHqUE7t0rVqzoiw1Myxn39YnZEJHXVnbO04aU753E1a3tnByWihGoBQG+ydaCVom+OuxJpnx84ZP/KnGYm+pAQEnxrtaW9qR4I4nBBPZSJKVa1IeQUDxxBso6LgcjQwerSCn5NhDX3nDkN0+odtuUHDduwtvx/Ig9T08EuDxUVF5HT0/PvyPgxSwqIFBQA+/F4ccqdKF0aJzf77fEqxApD6xk5VGr8cTxPH9ujUO4ezQIPIoiQSd13ta5Php2zIURYARMIsAGrBDQhTX/MS+tTgKpDSGQYxLDEfhoW6btQ8ObaO5JlXo/NNuPpnbDtPoYPK90knreLECgJ7/6N3CH0/mX6G9KLLJJSR0yLJX8mE0yGZJlI4xXL8/nO/9riD6TrQEBJM1/EkbTpHwsEUWhFtcAT9hd4fAmyOTAQgjqnWEDRIueYgOWfRP6OIxXJ6BIEDsa2Dc3LBEjEAgBNmAFgm30IJ1bwlPiFBzhpICj4amrBYvrL7U2t59bFxHLB8+fv3h/pZQOH6S+fRbGq89RV9I1/absN+EjkPke1+SuWV4pWjHGmudeSjbofEQzatbDrQFPYvHwCjZe2TVpqKZ8NRwve+ySyow0qHbZYYby2FQzmcwh6DV57J5u9JC+vNsNSeOREsWd5sTDmbmWQWArqnovhfFqXZnj3MwIMAIOImDNi7yD2I0SuSvf9Xd9o0QwzvZRB7mhHgTw/imuRKLj0+ohYvPYplThfyDfFJtlDEG2b8N49fEQ6DCJkBEYzGnie+8JmayN5Ka1LWh7oQ2CIS/PJMhxqQ2yGJMBz0I8E0/hxYMxhOshjDSEQj93khA+fJzONVcPWEHHStlAKf+V743z7g+KRTLGeXOToacTWu7AIvdV2WznX5yQloVkBBiBqhFgA1bVUFXXETfK24TwX4/eXFWtOsiq7ZXCy/bP25rb5lc7wJV+g95XUtE2Hiix4pAZB33AlTlJopw9t3WuRKzLdeR1T4mX2qBjoV+9E3IcYIMshmRA1KB47e5noiEOTLYuBFAJcg2sVzfURcSNweMnNEx4USyi0qpA+JAu/hELju4wZQ8sO+aqX0n5mq5cV5cd4rAUjAAjECYCbMAKE809tHryPTciAflbsesbIJ9kkhPwQPptS8sJsyiB0JgeuAj6aG8Mqts96SbvDcuXLy9SVZCKXv3FBu2R8RQVfUrpoYR8San2KNt2e4MQDxmGd0822/XHKHFlXrUjID3/fzGK/Ac3PyVi+fglpSKT/wrGTs5hN+YlxjmwxoTIfIcC1mDLstnVK8yzYg6MACMQBwJswDKEOl7cr4N/fhJyGhlCsCzZQzxV+ONgxb6yXdw5oJM4Q1qdB4fq9iTcMF6Fr7acG86BGe7tveURJOn9pAOiBhYRi7DjAg8OaeD4pknngNTMkMjZR0aKK3ryXd+yTzCWaCQCg1Uhpbh+ZDu1fXhwx2LA8hWdBO5I/H8ftfMiTH3a2tqmgx6ZfGdhYhMhLYWg6POxBvt9hDyZFSPACESMABuwDAKezXZ/F+klvmyQRTJJS3G08L3lyCGTdh2AlGx8G3Q40HU9yshfkEq9lpM3l0HH0uZJUyddCdEeslS8usVCmKT2wMKf2DbYCNUHY+NumrESvU89/cR7TbNh+uEhIAvqS6AG2y7dDYk0XxiHdrjRPDcOviZ44nl+rwm6VGiiEM9cKrq4qodS4hJ8PPmxq/Kz3IwAI1AdAmzAqg6nwL16ct2X4rXwR4EJ8MByCCwuDvhfKXfQhfZly5alsJJ9vwuyBpERHoifQI6VW4KM5THxIaATuuO8pGx4nwIPzjlxIdzW0nYazGdHx8XfMN/HvQaxbN26df2G+TD5EBHo7u2+S0j15xBJWkcK1rmjIFTUhmvcSulUpUNOu/utm1iLBEKFxtieKxbBEJ8oSvwhm+/6anwCMGdGgBGICgE2YJlHWh1y2EHn4+Xp1+ZZJYsDvrRcjMqEb3FV680bN5+K8+IIV+WvKLcU2UMPPZiyEaSi+q4fTDWmfgAdHnZdj3LyY6GhF7OxbPq+FQtj80xhs1bndHV1bTDPijmEjoCfoh7yOQn5MyMN20VI2cEwmU0Mfa5iIqgUhxBWhF5yBcKK+Jg+KMWJuMbJeDyahovpMwIuI8AGrAhmTyevbmj0zoGxoisCdoligbwWl7ctbLOiqljtwMsLah/jxIgt6aJ3Didtd2KuSgq5u9KU/FrJgwQalfBiecltX9h+lJByEQEIR6kgpfgWPC5Je/GMUppQQ0++U8/dfwipNEoVT/mRGq6VSsVynxmleEgNjY3y/pBIkSSDfGfsgRXvzI73ROF78YrA3BkBRiAKBNiAFQXK4KEXhOP7Gk/DzzsjYpkUNuPh1n69a0ndm5s7joBB80SSk6TEeztv61xPUrcEKbWzb9v3oS7R5PsqloUlKqFdCEyjDmMyf9YqcXfBH9DV7HhzFwEU+VXa85Lw5h8ZqXJFf26k/MwyewbvsY+bZeE2dcSLsgEr/il8RWvLojfFLwZLwAgwAiYRYAOWSXRH0F65duWWgWLDK9FM+ivnCLUj2JXPRVL3a8HImYVhShbfDXkJXn/yV0igeU0Ek84sDCOwdu3aHbiifmmYTVzkIzdgZTKZyciH8+a4FDbIVxdreFM+n99pkAeTjgCBVH9KP0eLEbCKh4UUh0fJGOXQIr/PmNOPwwfHwhYfJQnN91ja2nxcfae9vZ2NiTZPEcvGCNSJAMEFdJ2IGB6uy9R7abEYbB40zCpp5E9pbW53IiQP1RPHwdb2VoITtDU9IN9DUK/kqiT9q4gqH/lCQ/opbbwiWGJdfb37tu47iJ4niVKr8/bOzaiQ2U1WaRWtAUtQyokk1X1kz4sQFNNVsfEF9bAQSDGJ+hGY6hfFtbpQUv2kmAIjwAjYiAAbsGKYFZ3kVsniyXjYPREDe7ospfhqS0tHLKWyawG12F88Ff2fU8sYN/rKywYXQG4Iy1JWgUBPT08vvIburqKra13011ncgiPcpDwvQm4RsVL37uzbcVlEzJhNBAhI6V0fAZt4WMhoDQweJQ8sJdiAVeGsLRQKM3E4XaELH4oSASUymx9+9KNRsmRejAAjEB0CbMCKDuthnLLZ7Dp86TwZjduGHeCdehAYJ4V/zTHHHNNYDxHTY5FA+i2mecRA/5/ImfSdGPgyS8MISE9dbZhFHOSbkDdvv6gYty1oO1YI9eKo+EXGR6UuGgw1jYwhMzKNQFEM/Bo8qIYRRhxCSCikTIn7TZ97TtMvpOc6LT9B4ZVSH29pWdRMUDVWiRFIPAJswIrxFEDFpjWYgNMhQl+MYpBiDZeK454z5YBP2apUS0vLgVjIvsJW+QLL5XvvxUJ2IPB4HmgvAp74KYTz7RUwsGTTA4+sdWBavqnWIfb3lzeict2f7JeTJawFgVwu9yj6d9YyxqG+kV3zCCmbBFzwvKexoVgOG7AqTaWn2IBVCZ94jqU9pa5bsGDBlHjYM1dGgBEwhQAbsEwhWyXdrlzXKqEGFzdUv3hWiUR43ZRUl9j61UWq1BugaUN42sZPSQnx657bOlfGLwlLYAKB7u7uTaB7lwnacdL0it4BEfHHO7R4fUS8omJTULJwaVTMmE+0COB8XR4tx8i4jWtubh4fBbfiziIpg4bvexxCWOnEkVyBsBI8sR2TYk5DuomjA2KbAGbMCJhBgA1YZnCtiWpPfvVyJcXbMQi2AN5CQCCF3BNXzps3zzpDkRSS2kK2KGSR8wyEcNLaTEIpebPN8gWRDYbuSLwxMplFiyEfreS+UlwxGAYfBHgeYz0CvkjfaL2QAQX0PG9awKE1DVOe99yaBtjdWTU1ifV2ixizdL4gZbCMGc1w2aP6b2vzorPDJcrUGAFGIE4E2IAVJ/pDeGezXT/BgooNAUMwqfPnCyeMm3BRnTRCHd6xoOMwpI2eHyrRuIlJ8UssZP8VtxjM3zACniBnwMK1GIkBSwp1juHZiZr8TuRF+1zUTJlfdAjk86s24nvavdFxjJRTNAYsSgnchXi4s7NzV6Sz5BgzCU8fx0ROlrhSXd6xsGN2spRmbRkBugiwAcuiuc1mu78AT4evWCSS06IAy8uam0+YYYsSBc8/C7IgTReZTXm++CIZbViRsgg0NMhuHNxZtoODB5DUy7gBa9ALVInTHISnrMhYqH1vT1hp2T58gAICcjUFLUbqgNDhSIo3SEkpJ5Li/FcjT6TR++yBNRoTm1qmFrzitcuWLUvZJBTLwggwAsEQYANWMNyMjcrmV39YCflDYwySRXhyWha+Zo3KUmgDFpkN8a43dOW7/k5GIVakLAK7v76rtWU7uHjA94wbsMaNm9QBaCJZMEc0BTuEp74cES9mEyMCSGvQFSN7Y6z9lBdJlWKkC6ATQigl57+qcEZmMpnJeB/av0IXPmQFArJ108ZHOHejFXPBQjAC9SHABqz68DMxWh0648B3wVHntyaIJ40mXipe17qw48S49V6wYPFBkCETtxwh8lcpJTiMKERA7Scl77BfxuolRBic8QWHVP6rq5fIgZ5SXAXvq8cckJRFrBOBhqJH0gNLKRVVbkw6HjmKKxBWupxwStExVlZSlMaxT2UyHQtpqMJaMALJRYANWBbO/fLly4vpRqkTDt5qoXjuieQpHeYWa+hegzfwCshA6Xq7Cd5Xf3XvZGCJAyOgBC0PLCFMVyPDPUe+KjDe9g30i773TfvEYolMINB5W+d65MF6wATtOGmmhHkDlg5TwsezmXHqGSpvJdgDqwKgKDM7p8JhPmQXAml8WLpOe83ZJRZLwwgwArUgQGlBXYve1vfVITsDxb4zICgpr4d4gFfz2prbTo+H9x6uUr0yVv5hM1fyirBJMj27EfClR+tepKRRTwzcc47HjBKqPih/n893/tfus5SlCxUBJXtDpWcBMaXMhxBu2rRJ596MJFQxCkiVJ++Pgo+zPEjlO3N2FmoRfK5U3rdqGcB9GQFGwC4E2IBl13wMk6a3t3erTGnDh+Qqb8OQqX1HSfkZjIrrfAdfeVLtUls6QorNO/u3kS2zbinqsYs1Y8b0f0IIOonclWoyCqrnnWqUfsTEfaEuj5gls4sZAenJdTGLEDp75SG7l/EtPdc4iwgZ+H6KPbAq4c0VCCuhY+kx+ba2lrbXWyoci8UIMAJjIBDXgn4MsfjwXgR0vhEvrZZif9PeNv4bCIEXZjLtrwk0ss5B8MR4GUgcUCcZm4ZfvXbt2gGbBGJZzCOgQ5vBhY4x3TMcSqRU7Ln3QjsrkAMnl+taGRo9JuQEAjBa3uOEoDUIKaU0/+zySYWU7crnV/H7Z4VzTCrBIYQV8LH1EApmXd7a2kon1NdWoFkuRsAAAmzAMgBq2CS7urru94W3BHSfCpt2kujhJeMzHR0d6ah1hvcXHe8rJEVBHpwfRY0h87MDAbgu0PHIUNKYB9aCBQumIAeODiEkscFr5QdQxCehDCtRAwJFOtf7Hq1l0e+vAYBAXSUtj5z1AIGv/QpnAu71pDzuKqhK7dB+wvd+qnPWUVOM9WEEqCPABixHZjiX6/wHJkvnxNrliMg2ivn8Yn9RYxjphkV/e6QMDTLDi9qtnAfHIMC2k5bybttFrEE+YzmwGhrGLYIckRvLa9C9lq66cNvPahnAfWkg8PTTT/8HmhRoaLNbC9/zjBuwfEIeOXh/uY/S/BvQBRCJWQboMsloEGjb9NAjH4qGFXNhBBiBsBBgA1ZYSEZApyvX1SU8+VqwIvVCGQF0+1jAZfiCfTsR/NhTjWhBBKwiYeFJ9fNIGDETOxFQPiWPDGNJlqVSJ9g5gUGkUtlcbtUDQUbyGLcRWLdunTb2kErcH0UIoZR0QgiRMex+t89is9I3N59wKDiYrmhrVomkU5fiMwglJPOenvTpZP2TgQAbsByb556e1X9AQvBzITacYXgLgMDLUT73mADjAg3ZvGHzizFwaqDB9g1CJKv4P/vEYomiQqCgUnQMWNKch5RSYnFUc2Kcj5K/MM6DGViLAF406OS9A8pe0d9uHGxCHlh402QDVoUTJpXy51Q4zIfcQCAtfHkd1gaT3RCXpWQEGAE2YDl4DvTkVl+Ll4r/dVB0K0SWKvXOqARB/qu2qHgZ56PE7SgqwMlcjQNtL4PDDpuuFzM0KhH6ZvRAnr39gFFkRnLDZ4uSaXWDYR5M3mIEkM9ps8Xi1Syan/K31DyohgG4/seh+yE1DLG7q5IcQlhphor+3EqH+ZgrCMjnSuV9zRVpWU5GIOkIsAHL0TOgJ9/1RYjON9tg8/eWJccumRhsaI2jpFxY4wh7u0txo73CsWRRIKArEcIjg0hlMmXEEDcwoI7HXJB4tiK5y1/YaB3FlWUvD+WrR+yVLpBkRovh9PWJ2ZAKlw6NzZeSPbAqTSWthP0jNU1Y8n55HqqVnzkSBN5nBBgB+xAg8ZJtH6zRSNST6/oQcjr9NBpupLhM3Tmp7w0RaXRcRHyMs5FF9XvjTJiB9QhgZbbVeiGrElAaMWAh/xWZXBowVnLIcFXnEt1OUshHCWmn0un0Myb18Tw6+a80ThP60mzAqnDCoLr1nAqHHT8kUcRBXeu4EjWJj/n8IfJhzaxpEHdmBBiByBFgA1bkkIfKUO3q23YuFpR/DJVqAogpoc42rSZCCSbh4f8803yioa8e6O7tvisaXszFagSUmG61fFUKh+TEO6rsWls3JebXNsDe3jDGrbBXOpYsCgSQkJySB9b2zs5Oo0VwpK/mRjEvUfDAu+UTK9euNBpyGYUeJnngOUJmvkfhpNR94/qa3oP32AdGHaPbME343jW6ABNdFVkzRsB9BNiA5fgcrl27dmBH3/ZleNHIO65K1OK3zZ+/eH+TTIu7ijqBO5VrbJVJrJi2OwggJ85B7khbXlIplBkDliRjwNqWakrdUR5BPpIEBIh5YD1tfM5ohZRx/quxTxi6BixP3KcNmEp6bwIMxbGhINNj0eaHN3+AjDasCCNAEAEqi2uCU1O9SjBi7egrNLwKI/5Z/ajE90w3pfs1ZsY2PyXIhA8qJXuNAcWEnUFAf5VEWNk0ZwSuKGj4IYQtLSfMAksiBj6RM+2tUnF6+KAVCAwoj1IIoXkDFq2QMjZgVbgKly5d2oTDdBL2j9R1TwXKbHZ1Nw59c+Rhyvt45/1cS8sinc+SN0aAEbAQATZgWTgpQURas+aWJ9JFbwnGbggyPoljfCHPMKk3vly/0CT9KGl7vmIPvygBt5TXgw8+eQBEI/HcgCdZ6B5Ynup/kaVTV7NYMFR21TyIB5BDIJUqhH6dxAjSY6Z5I6RsjmkeUdGHLpz/qgLYW7dunY3DJJ6HpdQcOv/pRu9jqH5+d6l+RNsaPKGumTdv3gSi+rFajIDTCJC98To9KwGF7+ztfEjJ4lIMN1plJ6B41g1D2OUSo9UIlTjaOqWDCfTMwTMPXhdsKI+ihEAqVSSR/0rPiVIidG8MKVNUrnmhpFxD6dxlXYIhkO5L9wcbaeEoJYwbsPBeQcaAhZsAG7AqnsbpuRUPO35QKW+fBx68cXeJlH8uVEpSKOELJjRO/Jrj08jiMwIkEWADFrFpzWaz65B499VQaxcx1UyoM37nxJ0nmSC8h+ZRBmlHSXrN8uXLk/TSEiW2TvGiVGELyak3hg2+LwSVax4GvoG/hY0P03MPgR0yNeCe1GUk9swasFC4ZT9w1v9obL7cZ8CgoVC4WlBK2F8KmZEVKHt6enrhufyNUn2ptsEL7V1tLW2nU9WP9WIEXEWADViuzlwFubvz3auRoFgnXcR6irfKCMjFlY8HO7pgwWKdB0eHWzm/oWIj579yfhZDUsCn412gfLU5JFT2kcF9l4oH1qZcLvfoPsX4R2IRaGjYxR5YVc4+CrfQ8shJF9iAVWnuCYWLjlQTnoQlK1BOmjLxY+ibqHy7SsgfZjKZQ0dixPuMACMQHwJswIoPe6Ocu3Pdv4KHwQeNMiFAHGEybSbUaEoNHGOCbhw0cZP4exx8maeNCKjn2ihVEJmkkg8HGVdhDN75xQsqHHfnkFTsfeXObBmVdMqUKZQMWI8bBcujY+AHTsWdO3dyTtVKJwythP0jNS1pvFyxYkUf8se+XZ8fIwcQ3j9AqtTV0E8/43ljBBgBCxBgA5YFk2BKhO5st3b1/bYp+jToqhftcfsPVZ2iJOOJIXyZ+m+o4DAxhxGQZDwMUsVUqAas5uYT9BfaKQ5P7j7Rle+x0XofGsn+gQUrmRBCZTiE0FeSTP4rFHHYgArXZObeyFUsBZnn4Uh8kCOybP6zXG61LurzvZFjiO+f1JZpu5i4jqweI+AMAmzAcmaqggnak+t6PyqH3BBsdCJGecW+4rywNUUFQhqeGABGysK9YePD9BxFQCkqL+zF6bOnh5rQWcriTEdndZTYyHOyflQjNzACjiMgpReq0XokHLhuyBiwoFtJD5yROid8fzZZ/b3K87+zb/tH4I6UqI+bSskvtLR0vITsnLNijIBDCLABy6HJCiiqXxQD5+BBo7+Y8FYCAYQRhv9A8hWJEEKcN08gcSdXtSxx3iSt6ZhjjmmEA/0RRPR+NOzCBCnhzyKCDabZf4CKLqxHfQjAQ3lCfRTsGe37ntmQOFIhZZzAvdKZ29zc/Bwcp5Owf6SyY1SghHfeDuV552EYnPUSszV5yr9u3rx5ZO6JiZk5VpQcAmzAIjeloxXK5/M7U43eaTjyn9FHuQVGmuNCR0FKEtXI8GbC3lehnxxuEtx/yv7aKNvopvSjpA69AiGsPoeP4uJqQ1GYXei7iksC5S4Wi+OJqO1v2fLIJqO6SDoh1p4sH0JmFENHiHteExVv5NKIV1GBsqens1MqcUVpAkRbpTh6/LiJXyaqHavFCDiDABuwnJmq+gTt7Ox8XMniq0BlS32U6I2GkSZUY9P8+Yv3B0q6CqHzG4x7bPR0fhbDUaDoiZeGQyl+KqgqdE/YUviKjgFLNSg2YIV9gjhKr1hsoOFtIMWj69atM5mQHo9LRcYLU/lswKp8yfqkDVi+591fWf/dR8dvH6eLRSUr3FSJC1pbF+n1FG+MACMQEwJswIoJ+DjYZrPZfykp3gzefhz8Leb5vDBla2goHB0mvThpwbj3UJz8mbdFCCj1YoukqUsUeBeEXgZcCo+KB9YAhw3XdXqRGqyUT8MDS8nwvS6HzHQmkzkEu+OGNLn9M1VMllGixtmC59GcGoe41L3Y17flwWoEvumum7ZLpd6JvnhdTMyGKHv1o7a2Nn3N88YIMAIxIMAGrBhAj5NlNtv1e6XUp+KUwULek1taWg4MSy5PCTIJ3IEJ578K68RwnI6UkowHlvD9u0OfDqWovMxuCx0bJugsAmlVJOGBJYUyasDyih4pgwbu92zAqnTV0krYP0xTWKJqqkDZne++BQSuGkaE/s50UZRXQ014XvLGCDACUSPABqyoEbeAXzbf/VmuTDh8ItIqHVpyaoQSherRNVzSaPdQSvnpaDkyNxsRGEzg7ovwix3EpKxKqfANWFJMi0mdsNmyAStsRB2m56e8iQ6Lv090097ESGg9dx8z939s6+7uDrVKq/uQjNBACUrzPUK52kMCx/U1fgBEEuWxj3vKktaWRe8ZCR7vMwKMgHkE2IBlHmMbOah0k/cWCPZ3G4WLQybk9zksLL6eVEeGRSt2Oh4bsGKfAwsEeM7k5xyP74wkFrKAsy+dTpvwLtBVqShsbMCiMIsh6YCqW6F5J4ckUiAySiqji2tJySNH1m7ACDQpDg+C2w0pj7uhU4HwyPuH7lfze+XalVvg5fiuavrS6qO+3NraSia9Aq25YW0oI8AGLMqzW0E3JHXf5ov0q9Fla4VuyTnkq0PDUhZfZZ4fFq246Xi+Yg+suCfBAv7Kkx0WiBGWCP/G/a8QFrEhdKYO+e3yz+0uC8+yh42AR8KAJX2zObDgeU3GoAHP65oNGGGfdTbTW7ZsWQrveTNtlrEu2QJWoOzOdf8fCqT8tC7e7g1uEkXvZ83NzTRyBbqHP0ucUATYgJXQiddq53Kr7kVS9/MSDME+1fH1NJT8NR0dHWkQpeRabmKhvw93/uEIAlJ1OCLpmGLiy3no4YNI4DwZjBvGZO5EB9wNeWME9iDgK/9gCmCgcINZDyyhyBiwhOL8V5XO+Y0bn9Ae+42V+jh9rI75HyikL4a39man9a9VeCmOTsmGL9Y6jPszAoxAcATYgBUcOxIjkdT9+gR+MRk1d1LJg0Y1Bmjo6xOzMYzSi402yPGWYAR257+SzVQgwP1uTdi6IOExlfxXgEZRun+FPdWJo+cJScIDy/d8owYsnBhkDFie9NkDq8KVLmWR0kfK0ZrWUYFyzZpbnoB32vmjiZJveU9rc+up5LVkBRkBSxBgA5YlExGnGA2N8t3g/584ZYibt5IylPAfz/PJhA/qOVFCEfEqifsMc5f/c6Y8p41Q/ivhC5EPeza8Ao1E13twaQobH6bnLgJYjJIwYCHv3cOmZmHevHn6OTnDFP2o6aJSNRuwKoAufULediX09P36DJi62jleHq8vQZpykxTS+1HH8R0kPFYpTxTrRgMBNmDRmMe6tNidD0u+EUQG6iLk9GClQ4Dq3jxBKIE70MATmT2w6j4r3CYA4+6ZbmswTPq+qVMn3DGsJYQdP+2T8VqCwYKMLiFMLZPwRCjeyTED+aR+zzElQ2Pj5FmgnTJFP2q6Ms0hhBUxp5Swf7Si23K53KOjm2trQaGoCzGibjq1cY2994GFxuJVkILD8GOfChaAOgJswKI+w1Xql8utvh1f3T5TZXdy3fC0mRKGUkh++rww6NhCw/ckL2ZtmYx45NAvYqfHw9oAVyn+smLFir6wKft+isx1ggmfFDY+TM9dBPBMI+BZJI16FEnpUwopUzt27Fjv7hkbgeSSVJ7TkYCFcq3AYPw4qhK+byRx8vtKvrK1uf0C8nqygoxAzAiwASvmCbCJfUNT6guQ506bZIpKFrykTwyDF/LrHBkGHXtoKBLhI/bg6ZYkLS2LFkJiAgvYPbgr0WNiBjxPUgq7238w75kJoJimUwjoamswaOqE1a5voSzKy4EgCVUghI6b165du6OcrtwOBBRdA5YS4r6w5hhVCX8BrG4Ii54zdKT4atuCtmOdkZcFZQQcRIANWA5OmimRdWl5X8h3gj7SxCRskyKUawEv+6Q8sJDcnuP5E3YpDFUXC7NXD913/bdU6jYTOng+nRBC4COnT5rOhmsTJ4pjNDdt2qSN186HkeMDlVkDFqWQMhmeAcOx070WcefU0tmpvnVUICylZ7owGEr4ZKljhNvGqZT3M1QlH0dYR1aNEYgVgVAW7bFqwMxDRUCHEmLRem2oRN0gVnf+ij0PKzreKrvn7RA3po+lDBuBQe8Lqd4QNt0Y6amiLOZM8Ef4NWzXdLaBtGDDNZ3pDKyJUqlZgQdbNFBKsd6oOIRCynArM2rsMzoPERBHwv4JYEPWwB92BcrO2zs3wwvr/RFMjWUs1DEDferzlgnF4jACZBBgAxaZqQxPEZXyPw1qA+FRdIGSqvta8Hf5+qtc3XRsQgurcl7I2jQhEcqyeePmV4IdIYOsvCuM5LSlpkBKSex+6R9aSk9uSxoCaiYFjWFeNmuUUXIuBZwGdVB+aCFkZDAZokhT02Q916Q+WAxRT5ioQNmT77pGCfG7oXyS8FtKdXEm035yEnRlHRmBqBEgtdiOGjyq/Hp6evQLTMK8sOpfgPrSfy61cwKhF7Op6cT6VIcAvsSfW11PN3rBs/SPpiQtiPrvH6ZkC0KXWjXVIBjwGKzSydz/C4aNMoqMAcszbexz/MIilrB/1GwYq0Apizqx+VOjGNJugA1LXLVgwWIKlVxpzxRr5xwCbMBybsqiEbiovK+AEz6aJGODojvr19QjZ8DCd8bncxx//WeGaxRaWloOxNy/yjW5K8mLikg3VjpezzFyHli+PKYePHgsGQQoeGCphoaGB0zNyInzTpwK2tNM0Y+arhTSsLEvao3C5Sd9MSdcilZRM1aBMpvNPgxrziVWaRuNMAc2eANXgRVZr71oYGQujMBwBNiANRwP3tuDQD7feQ9+5pMCCJ4s9RuwKCVyfXbi036ff9Szu/wrCQh4Iv026NlASNfHDzrsoF5T+khZIBVCiJArNmCZOlncojvLLXFLSrsJBWp2lTwSQmNfQx+tD1dpw+GWIWAeKwma73l7ITVagbI72/0jMPrzXmaJ+SvF0kym7fzE6MuKMgIRIMAGrAhAdpeF/KG7stcouVQ7ahxRoruk9SK7R8OiJ7gccInZptq0dOnSJuj2Xlr6qRXLly8vmtIJeUOMLZBNyVyRrhLaaM3vBxVBSsRB9z2wTIfEeWIuoTOhv6urayMhfcJXRZGa7+H4mK9AqXyR1oacZ4Yzpr+Hit7faG9ufxF9TVlDRiAaBPgFNRqcneTSX0j/HoIbW/TZBAoeLk/ULY+ikwdjKBZSKTZgDQWE+O9tW3a8GSqSSuIND0tj+a/06VAojHua1GkhxcS2BW0vJKUTK1M7Ako4b8AyXlWPlkfOepwkfu0nSoJG0JrvYRNn/FoBt1xu1QOIprt0GONk7IzzpfgZp+RIxmSzluYRYAOWeYyd5bBmzS3aqGMs7MYmYBAy83id8iB1BNXcCLK9Tmx4uCMILFu2LKWE+pAj4lYrZkF5ymjYwrZtm8klp/XTgq/7as8wgv3a2tqm45k20XXVTCclR6GTOa5jtE9+qe7b95t/lENgdrkDzrdHVIGyJ7f6clSIWOk8XrUr8MLigP+Z2ofxCEaAERiJABuwRiLC+8MQkFLeMqyB6I7yVV0eWM3NJ2iPlfFE4TmutbWVTJJaonMUilqbN25+NQg9LxRithDBizIqqxo1MK1bt64f6pIKI4RFng1YtpzDMcjh+ykK+a8EDEz3m4VP0gkhNI6V2ZkwTX1PNblJpvnERd+0sXeIXspLyXdif9uQtkT8xP3oA60LO05MhLKsJCNgEAGSBqy2lrbTW1o6OPwhjBPH9+8Ig4ztNDzpba5HxgZZIJn/ag8mKVmUi+rBh8faj8Cg95WSl9kvaY0S+vLaGkcE6y4FrTBCJfQ1j+hL3pKIgKeKJAxYwpOGDVh0ciJJ0/nCHL+QUqkCHWNlibmIsgIlcq3dj9yRHy8hBvUmT3j+T+bPX7w/dUVZP0bAJAKkDFiZzKK2tpb2nBLytyiZ/j8mgUsK7aJs+GsydPUfrEdPX9BM4L4XE8Tun7D3N/+licDDDz3yDpgrjialnRLb002ezuVnflPiMfNMIuVwYNvCtuMi5cjM7EFAup//SoOZLoj1BkHV79AzDdKPlrQSHEJYAXFPKTrhoqX0jLgCZTbf/W0hVE8pUYi3HdqYLiSnSBbxyWT14kGAhAELuRqObs20X49k011KiGYNJQxYZ7e0tBwYD6x0uCLh4gZoU6CjUWlNfOmvL32k2laaCdz3ao8k96fiN3tj7AWE2N8lxy6ZiK/vnySmlj5hf9XZ2RlNmIJU5Kp3+Z44i9o5wfpUhwASOlPwwBqYfvh0/Q5jZENo/WEgrKu2ktjwnGcDVqWZlHS87Uqo2RdDBUpfSf8dkGVnCXmIN6kz2loWnUdcSVaPETCGgNMGrI6FHbNbW9quUUX5d6HEshEoNXki/bYRbbxbOwI+hjxS+zDnRjxYl8S0X2y06WpOS8uihXVhxIOtRWD7xJ0fgHCHWCtgQMGU8n4acGjNw8DroZoHWT4AISWvsVxEFs8YAiQMWBuWL19usJJyeq4x+GMg7DV5psMtY9AqVJaUPbAeAFL6fT/SLZvN/gsML4uUqSXMEEL5jebmjhdYIg6LwQg4hYCTBixdHae1pf2bBc+/ByvrNwHxcnpcMG/evAanZsRKYWW9Ffqs1GqIUA/jIfrMkP3af/qCcg6sQTyk8M+uHRgeYTsCLS0nzEKxhktslzOAfA8fcvj0WwOMCzQEXr/kPLAAxPMzmcwxgQDhQU4jgGqkFDywzBpkfFIhZU/BW5VWHr/wr0C6BqwYK1AeMuOgr0ohbg9/uiyniCqvKelfd8wxxzRaLimLxwhYh0A5w491gmqBdJgLDFcfhsfVf7D7Pvwby3V75vjGibzo1uDVseFFNvKvMnWIW/tQqe6ufdCIEdQ9sKAuvDFeqxN9j9Ccdx1HICUKV0IFcpWVEAJ1nVnvi+ETL6Ui54GlNZQqpT8S8ZYwBPByONN1lZEP1agBC2HXhAwaHD449vlOOFVEjOGj+jktffEW4E+qku/Y59Ngj5dO22//RHqgVYkPd2MESiLghAFLW6czmbaLdkzadS+0+CL+TS2pTenGD6PZCT1Lix9/K76MqPilMCcBytr+sx7qCxYsmILx0+uh4cjYgzZv3PxKR2RlMatAoLW5/c24uJdU0dW1LkWZKn4/UqF9YXSxHKkuw5m9vaOjY9zwJt6jjADmexLuC85XyfJMV9VThAwaMXrguHAt7Y7mkDrnGckN78GxPr+6buv6J0LqPk8S3LGUUuKS9pb2E8bqxscZAUbgWQRsN+x4WGC9YdrU/f+J5JLfgdgHPSt6lb9QVautue20Kntzt5IIqFoMhiUp2NwohfePeuRLpcbPrWe8S2OVFBe7JC/LWh4BXeQCHgRfL9/D3SNYfN/Y09NzX5QapPyUzuVBcTug0OefSVEx1qk0AgMDA7NKH3GrFb7jphfldJ79SpnGyq2TZ4S0jY2T9TVB1gPdk/HPf0NT6gvw+V07Avok7HoIc7lm/vzFzn80SMJksY52IGCtAat1YceJCBe8HXFL1wGqul4SlJQfsQNuR6VQ8mBHJa9KbF/INVV1LNMpJYrk81/tU13JE1F56cX79vmHqwjAdpW+UhHwsig1AdLzvlmq3WRbZ2+nzoEVTcVDk4qUoi3Vu0s1cxtVBFJ6se785kux3qQS+KBDJoQQurABq8LJ4nmk8p2N0tSGCpTIwVYQXvHtEG5glID0G2Y0pgZ0OgfeGAFGoAoErDNgwVtqPgxXq4Tn3wz5X1qFDtV0mc/umdXANLoPQgn2gxFx4ugjZFp2NjaKujywEKGaHAOWnnZf6vxzvDmMQFum7WKEBp/usAqVRP9HT0/n6kodDB1DFIbQ+RkJbhJ2645WgoqxSiUQQD4aEoaZYjFtzAsTIWUTkFyh9qiAEnjb0IScgcawskG/umXwCYWLlgDDlgqU8Jz+G4rK6FQxydukOBNRR+cmT3HWmBGoHQFrDFiodHRkpqX9V/CWug1qvLx2VSqPgHvmpZV78NFSCBQK4iWl2sm0SXHH4FefehRStL/MjYZGvqG5+YQZo9u5xQUEMpmOl2GxQvcFUYlvYB5gS4p+QyXCe6LnGg1H6fsfj4YTc4kdARqeRTt6e2951BSWTU2TdWQAvgPQ2JTy2IBVYSrhskzCqFtGxSdtqkD55NOPfxZy/r2MrNSbv42vRc+nriTrxwjUi0DsBiy9EG5tabsSlY7+gTeBs6CQ5CHRrgAAQABJREFUqReCk/TCrV7AEjfeV2F5wdkJnRI99QoG1/tkeWCh+mdKFj5dL248PnoETpx34lRP+T8HZ6plmx9LN3k/ix7Z3RyRT+/OuHib5guL4JJMZlGbaT5M3wIEFIHFuhoMHzRmyCYWUubvt9/4DRacefaKQLvStFXGy3Xr1vV7arAqYfJCCXXEi5/6mS5eZu/FwJIxAvEjEJsBCx5XkxEq+CkshBFyIc8DFGnTcEildEVC3mpCQJ1QU3fXOiuvs36RabuWl8HnLS0tHS8sc4ybLUQA4cDpXeP6foEV3REWiheWSN/Dl+RdYRGrlQ48sP5S6xiX+uMZ+kmX5GVZgyFAIreT6ZxORUrPfbVhxYoVfcHOloSMomDULTdVpq+VcnwrtHflu/6KwySLzFRQe88hNQ/Fyz4xdj/uwQgkF4HIDVjNzc3j21oWXQKPqwcAu34ZHh8d/OrM5uaOF0THz21Oeq6gwcvd1qKi9AXlDWQr9hjj4LJly1IwwM4coxvFwylP+HTD0AjOWLHP/4ZQ8pUEVdur0hbkTvz23p04/jb2NeoKSsa8PuLQaQTPxchTecaINt4lhgDc4Oe4rpISyqxXCaWQMsUJ3Ks43+dW0cfNLkqYvVYCojJ56sRP4ml6d8Dhrg/7CDyeKa+/XJ8flj9mBCIzYOmv/0gc/I6UbPg3Xiy+BL2nxaC7l/I4j0e1uKdEo17sTqi2v3P9pOjNZrPP1CP3pk2bdC6ohnpoODz2FDxgT3JY/sSI3tbS9h54VVxEWWGl1NeQAPapOHVcuXblFvD/b5wymOaNPJXfXnLsEsqFPUxDaDV95F/R72b7WS1kFcJ5pr1KVH3VsatQIboukhO4VwJbh97j+HMq9XH5GKqP3G+j/NorUHne2yFb0Ub5DMvkweP5GjgSkD3vDOPH5IkjEIkBq3Vhx4mFAX8tEgf/AHgeFiumSry+vbn9RbHK4Apzz3+nK6IGkVP54rdBxg0dI4vS+S/VQ/Wp+bdSV8I4PanmcTwgMgQymfbTlJA6sTnl7cmC3/8tKxSU4nYr5DAnxOE7Ju/6mDnyTDlOBGSBxjNN+d56ozhKSckjx0oDhtH5q4H4jqYC7fc8z14DZjbbeRvWjrF6VtdwqoTd9TBPNlwZNlGmxwhQQMCoAQtltztQEvQ2hHXcDDfQYy0BzIMnwkctkcVaMdrb2+cg3GiJtQKGIJgvvLoNWCg5QPvFZgycpRCzEZr2hTG68eGYENAfD6QSvwR7hLrS3aSUX+vt7d1qg4YwjHfZIIdRGZT4ADx1XmyUBxMPhIAOa9dG60CD9SCPxjPNl9KwUUbNCoyxZQPxTmwYK8sUrlEcKX1KxspR2vu+6WtlFMuaGnb1b9MfTJAvOXkb3rHPwjr6zcnTnDVmBCojYMSAhQTtx7Rm2q8Xvn8rFvgLKosQ/VElxLK2BW22GNSiB6AKjn5BfQTdjJwfVbA330WKu/L5zrpDfeDZMtu8sHZzwMvvBciLs8huKZMnHTxNW/Dx4DfQfBxl7fGC94QvCt+xRkev2GmNLOYEaRRF72fz5s2jG2JuDjtjlLXxavNDj/wI10RzYCZEqq1N6EsbM8p0HN9xMPAl43kMDxcrcyAFPofDHugTChcdjU1x69bHHhzdbE/L2rVrd6Aq4VshkW+PVBFKIsX32he0Py9CjsyKEbAegVANFNprp62l/adI0H4XPK6WWay9p1Le5yyWL1bRBr2vhHxrrEIYZq58Vb/3FWSEd8tsw6K6QB5ejfLHe3KnuCAveRkxFwt8KVZAUTKLrHKThg8SX6k3l1052kHaIcu/MG5jkLFOjZHi6AmNE7/mlMyEhdXGq00PP/JjfFB4C7ynAxtvkA9njuswaaP2nnx0RlTpb1DOYzQUmGIxzQasoYCM+C1Je9qrh9atW9c/QmXrdlGVMAeHiMutEywagSaplLgOH4waomHHXBgB+xEIxYCFHDgHtLa0f9EviH9iMfFGqB0KXbPwqVNbm1tPNcvDTer+gPgqJCd9o5QpdUMYs4PFwuww6BCgMVf43i93V2UkoI3DKujQbczFn6HCFIfVqFb0DTv7ttvjfbVXailW7/1J+S/uf+9CuNqZlHV0QTe9sNm88ZGf4MPhYKgJ5iWwAYtCWDw8o9ebnDcp1VyT9COmvaO395ZHI+bpFjsCRt3ygLvjfTfhmXEfRpHfe8vrQvcI1tbHj2ucwLkn6U4xa1YjAnUZmnQlIhiuPlzo9/UNBTcW0VQj/3i7S/ldDoEYPgVYjJyMF1jSCxI8CNajWtnfhmseeI/Ul9jAKOweeNLDD23+RJ00eHgdCKDa4OkI3daeV7pqEvlNCvUBHV5gm6KoHnSzbTKZkgdeqFdzSL4pdMemiypV48c3Tbphz8fDwQFKpYJ71CiPwjMtuAFvbMgRyETKgKXPFZw+vJVFgFbC/uFqKhH8XjGckvG9m+66absnpC4ulcjzFbk+P8bpOoyfZszAEQQCGbCOOeaYxtaWRe/dMWmXfkn4Iv45+qVfzhrfNPESR+bKuJjz5y/eH4uRK4wzipkBFr3XhyHCHnfeGWHQokJDP2BbWxe9ioo+LumRaW4/H54Hv4bMpHNe7ZsTpTq7c92/2rdv0Y++QuMfIE5SSn9PVin5x+bmE/heGPE5CO/3/VKyAd6Waqg3ebGvb8uDAUWRoDUr4FiLhvlGF+WkQspUHd56Fs24QVGIXBNlEKrHW7MMSZPNXbmuVbhH/dAkD4tp63Qd13K6DotniEWLDIFaDVgevvCfM23K/vfgBqJLlk+PTFJzjD7MyfEGwZVN6YFr8Oswc1BbQVl5RRnKw2/8+PGHQyPS1d0CzJgniurngwnEAwzmIYEQ8FA04wtYVH0fo5NyPhalL94XCK0IBq1Zc8sTeEbmI2BlC4sZKVm4QXsD2SIQdTmQq/LwwoC/Gnq2DdUVrgkb4JU4MLSt2t8wQh6Kvs4bwOsKoawKLDm3qm4udJLueODEAWfHgg5tmHf+miiLnYMGzIFi/wehz4ayOtE+cLhQHnlHA9pTyNqFgUDVBiwdWoZF0l/xhf9aCjkShoA3TifH015lQ9oS9xOhoB/Fi+/J5BWX6pau3q7/hKGnLEoKoRZhQDGchhQTkUD8j20L2146/ADvhY0AKr5OzrS03wCH+kvDpm01PRjrunu777JZRhgUf2+zfAZkm5+WDb+FVxDdxZ4B0IKQHCzSUBRrcN2XqqYc2PsolfJJPNM837hXEQmcBs89Bw0YQa6ZoGMG0rQS9o/EQXle4PvFSFpR7ff29m6FJ9L5UfGzjg+KpGFN/kbr5GKBGIEIERjTgIV42/kwbqxCaNn/lXlZilBcM6xguDl+vykHfNYMdfuptjYvOhtSftp+SeuXMMwQSd+Ts+uXiCyFqcqTf2pu7ngBWQ1jVkx7jqLia68U4vSYRYma/VPpBu9TUTOtlZ+S6ne1jnG9P56lSwp9/g1Lly51Kx+mQ8APPq99rxPvYweXEhvPuPtLtVfV5tNYrKuUCo7BGEDt+dipvXJobCl3knjHAzipfGejIFSq3zkDllYim129Ave6n4xSKCEN0P37eL8+IiHqspqMwCgEyhqw2he2HwWPqxtg5e7FqJePGkmsAVVl/ieTWbSUmFpjqtPa3PFKIZV+CGAdTHyTYvOOvh2hLSrxAJlNHLF61Zuekv7N8BI6pl5CPH44AljELvNT4na0HjX8SBL25KWdnZ2P264pCkX8GzLeYbucocsnxdJtW7azEStkYOHZls40L/oyntfXgXRZLzfpBTdIEMnt5E+ePPmBkOHfR27/SfvPwg6ZUG3fl8aMfftAc/gH3vPmOCx+ZdGV2J7L5R6r3Mneo039jTqNwEZ7JTQq2aSU51/Nlb+NYszELUZglAEL8d6HwePqCt8Td+EL36stlj1s0TxUjvpFkqop7a446P8GQDaEDaaV9JT4UdDcIKX0gcWP7otNKYWDtR0GL6FuGIeH5WkJRopH6RxDuD9/C4tYXYhgagIRubUnt/oH7ugttbEhcZtCOPozW7avamtro5AnM/b50+9lhf7irfjQ9iEIg0dPhU3VkcCcRnW9h1esWNFXAaG6DimPlkdOY6NYXxcg1AdLwu95u/Of4Xbt5rZy7cotQvnvclP6EKRWIrP54Uc/GgIlJsEIOIfAPgMWFkbP0V/3CilffzXWZUrTzmlTv8BTkA/r9x3Hd5R0za+fvD0UYLx6Hb4s/RYSlf2Sa4+0oUji+yId6sIXiWJnhyIZfSLTYBy+GQUgXkNfVXMaZjIdL0PFsTvB4b3muFhNeQeu4fMgoTMv3DLl/xzyJqUa4ciTp0UVZQ+HOYyEpbZ93DdPwXvZX2G3aq1mJAwsgT1qiDzTAutfDb5CenOr6udGp0fgzbrNDVFjklLRMlgORRGWcLPXylBmhn735HtuxL3xF4bIW09WKfXxlpZFzdYLygIyAiEj4M2bN29Ca3P7pVgY3bvn617CqwjJWYUG/w+6PHXIWNtCTsKD41MwXumFVTI8rzTyUvwul1v1QKiTwCGEtcDZhAIQv2hrWXTJ4GzUMjLhfXU+od3XrJ8DFM9PLhzyI7iG73VJ/+7u7k1YJNzikswhy/r8tPRva29pbw+ZLnlyCxYsmJJpWfQD3Df/AGUPqFZhKYOHEILHnGr5WNtPml2U+4RCynBvcjL/UbTnHqGKkyOBI1KBsr+QvgiqPTJSvYTspz2lrtPPi4Toy2oyAoMIeOOaJvZgcf8F7FE12ASZ6pcV+v2bUelnWpDBto5ZcuySiahYthzyfRL/8O6SmE2hKtFnwtR2T5LiQ8KkmQBaKSXUl1pbFv1ee3wmQN+6VWxvbm955untOo+SvmaTY3AegRxuVnmEDn53RLMTu0rJq50Q1JCQSoj9fRjxYIT9KOfrqA7klpb2JQ2ppr9Lod6BEbU8q5+B0TRQThsyycnrSWJfzfRIOh458Lhz3gOnmikL2mdPRVWyERl4NpGY/zVrbnkC53JSPdP1E2JOQ7rpO0HPcx7HCLiIgIcXpJtdFDwCmV8mfG/l/PmL94+Al3EWOrfXjkl9umLZWcaZ2cZAiRu78l0IwQhve+aZZ2aB2r4Q3PAoJ4GSOlWHwmnjTBK0DaKj/pqmc135UnTj5eToIDQIjemTvng79IEdxL3tqa2P/xpzuNk9yUOVWKck+Oymhzav1PmcQqVMiBhyhh3S2tJ2DR4sf4JaM2tWrQ6DxLRp02aDn/PJyU0bZfAONafmebF1gGIPrEpT09cnZuM43fc8VSTjgZfNdl2PjyW/rjSfpI8p8eY9FeVJq8nKMQJ7EYBjSsOV2MF1z1sJBF7amO7vxUulywtIhAwueqdKyTym+ZgSOpJv8qUM1ftKA+b73mzywJlV8HAYZzpR6fQLOjG5WVZOUfcQ0n0uvC/ugdT6iyLdl+eqp0X+b9dtXf+surtlHdetW9cvhQw1/55lKlYvjpQdxZR/J87xN1Q/iH5P7f2UaW7/IHKG/Quf098EjWEnCbCpOsIHi+m5AThaNwRuvqa9SkjgNDhx5rGy7vyoRSDP8+nMdQnF68mXV4Jc7E1eSr0bQgTyQI1d+DAEkOryjoUds8MgxTQYAdsR8AZziii12nZB45NPPhcvlbnW5o5XxidDMM46eS68OOBhp64AhQnBqDg+SokVudzq28PWAjnE5oRNM4H0GmA61/n3/tHW3PaKBOo/TGUkaV+I6zWLpeuPcIDDUzU6uH4ROviNYUA5uJMqSP2hqOCg6KGLjK9l++Mcvw7n+k2c4F14KKjy2mlTD7hLSvEVgD25HsBVPQYJKqFxaXMGrD2h73TSbaQ8Mh449Vw35cbC85fye57atWuXaWNvOWiNtOvwaUQVfcAIcTeITi14xWs5VN+NyWIp60Ngz9d9/jo8BoxThfRvxAv3F/fkPhqje7yHtUdLW2bRp1PS/zskWRyvNPFyV573aRMSeELOMkE3oTTnKin/1NbS/lPknas9bMZx0HR1QXik/FEqH16SYqHj6oQp/kaZVm8BQdg83N46ezsfglPNb93WInTpT9LPKDyrPqGLyYRO3W6CEoarM/FOcSc+hvwSp/iRoYjr+XUYJEjkdurv6uraGAqWJYikUilSBg14kpMyYJSYsvqakFuoPgIWj5bikbVr1+6wWMJAonXnun+a7GetbN208ZFLA4HHgxgBhxAYNGClm7wbpBBPOCR3HKLq3BAffmbr9jVYZL84DgGq4Omh5PbrPdlwty6tiv7jqhhDtgvO6Zuy2c7bTCiIPBt0X2xMAFYFTVgp3oi8c/9BWOF3M5nMoVUMcbpL28K2l8Jo9zsYrtbAI2Wp08qEL3xReN45QRNShy9O/RR9Ib5cPxVyFMbhWXXZ+KaJ/9Gh7kiarHNlkd30BzA8o98KXf8Kw5XO1/KiMJX16vLAEhTCpR4AnrjUDG3FFAWM9oIzMGPG/jCs81YWAUnimiitHuH8ZzLlXwClnyqteCJaP6U9+hOhKSuZWAQGDVidnZ27sHiE1Zq3MRFQ4lgssv+CL6dXLFiw+KAx+0fTwWttXfQqVBj8C0pu/xyGm9nRsLWai+9L76PmJFSMsRlwG+Fvc6FUqf8imfHXdFJjM2xioyqxgD0F1+otypNrcd89DZLgkuVtBAKf6enp7BzR5vSuDmXGRN/ktBLmhIfBWl1R6Ff/0B9hqBmy9H0s09x22TNbtj+IZ/RV0NXIRzDp15EDS0nnjTO4vu43d4qCMpUwS62KEA8sX768aBQv14kTuCbKTQHuQ3V4a5ajakc7PnxtwnvkB+2QJhYp0vgwep0uBhQLd2bKCESAwL6vnUoWf4BF4/si4EmBhcbtnQ2pgdch/OHLwO7ynp6eyK39J847cequpoE3CqUuFL46mlfBw06tq+F99ZdhLWHuSDHb/cCmMAEJnRYSu8sPqKJ4D7wVfucJdXlXrutWcIHNx71N505JiYY3YdVwPhQ4iq/VCnOoVOchhx382Qo93D2k1OeFlEvcVcC05OpI/RFmoN//Aj4SfX9cX+P3V65ducU0VxP0tbfVM8/sWILn85twHztDStFggs8QmmpADqwfsl/jTzWnxgH2dTftVaI9r518ApWcKrIGjJLaBmokcE2U0Rsl6O8vc4hEc0++68etmbZlQknn8heHNAFzG1KN3wStc0Oix2QYAasQGLaOwgtjFtK1WCWhG8JsQzjA1SrlfweGrH8bFhlJXxdlpD+YG+b1WBBPNMzPRfLPpAe853fe3rnZhPA6XwtCXraB9rDrxwQvpjkMgXsQbnSF8Pzrs9nsw8OOWLijE2lu2vDYy0XKfxsWPWdCxESH9FY5RY/gg8BLXZjfKvUZ1Q2ehd24dbSOOsANpRDQH4au8YV3dS7XeWepDja16WqC06ZMP0FJdRaSCb8GskWZ8PvhnlzXjCB4wENsOorVPBpkrGVjLgUGXzIlE0K+/wz7FQ0DtBRX9GS73mUKK9fpzp+/eP/G9MDjrutRXn55LgqkXFX+uPtHmptPmJGShX9Akyjvw1YBh+fQ2cgL9gurhGJhGIEQENjngaVp4UT/Ab5+sgGrdmAnISfSRQgtvAhGwDsw/Pqi8n6dz3f+t3ZSo0doN9DGVGMbXpxOxyydji+6B7LpZDROQ1o+Z8p4pXlMbJg4C0k22Hg1BPCIfr5ASvkNoVJfgxEghy9rv4Jx6DcwGj8YEf8x2egF7H77HbAI7tvLkEjz1cITBxD6Yj+m/nV26EMOnzO7cvYbJ+vRU0nvE1KpVfXQSNDYadD1fZ7w3wdPzL9J6f9EpuRvkajbGu8BvdBtaBhYjHP3NDyjT0EKpv3ieTiowB41+DCA8MF4pA7zXMZ7mOnzwvkwy31415MvbR8Ruj/S6QKduS4xTXhHCXy/KEHOyqZ8ftXGTKbtI1LJy60UMAKhsKa/vKXlhHwut+qBCNgxC0YgMgSGGbB29O24Hp4l2uVwamQS0GP0Uqj0UlRX+iKMWQ/jnTCrfJWTInWPSBXue+qpp9avW7euv5Ta2mPjsQ2PHY5a60eoVPEI3HSPQz9tUDwaL8ZeqTHcNgqB+yZPHTyHRx0Iq6GYEnPgccdbfAjgWoAHixStMBp/E9fZP5VQK6Xn3TxuZ0NXxCFH8IjMHCVVGtU+FcKFRAcMzPCKdH8xGPX0YvF5IcJEc1HzjZpfNrv6Vnhy/BG3kJOj5u02P/VipeTXVUF8Hdf8P3CJ3QhP5D8VRGFNPp/fGZVuOhzY8xoXwAi5CNf5iUIMHIfrHvar2Lf7g0qA3FlzLJA/qPj7xuH8CIzBPiJlfgx61G58ZGaZw+41K7o5kMKYDKnznVG4KMqAIRuSMf/ZbPcVeF5oD/iTykBBvXk/TxSuxf3r5ZzzjvpUJ0u/YQYsXVIVFcB+ipv2hcmCwZi2hwLLZfAaWTZYGMf3xLSp+/u4meqcHtux4O3DC/AAfuswwEnw2JgKM9WgoQrGK2NCkSas5AdXrFgBXM1tmJvZjqZiMgdKvJSRU0oehTxw79nV1K/gqfFvvHfejgXmX5Dn4e8iLf4Dj42HIGJdr6NILD2uUCgcqZR3JIxULwbPBaB5PKgiUeYe0nzZBj0Tvp3Ndv0o6GDXxqHE4ofhVfQKyK2r2/JWOwIvxCX3QiXlpcgtN9Da3H6H9ETeF+Iv8NK6J51O/wvFaXSYd+BNGyw2bnxitqf6j4J96gXIXYZrXulr/nm4/vfQ3fs3MJsQB9axIJUeFus26RIMlsZGeX+wkWOPwrlwGF7OGsfu6UiPVJG8B049MyF95Duj+zzvP+igg6xPw1DP/A0Zq9K+986C5/8dbZOGtCfpZ9umhx75EBT+YpKUZl1pIzDMgKVVlZ76f8iFoEuQ0r11xzun2kClwyLwjyEOcyqA5h+786t/EybNUrTwnj8bCXl5sxMBzIw6Ev8dicvrHCxohYBLI4zG2kPjv6gitREL38dghHocubQegzHSR76aLVJ5g12xiBuPceNgdJ4Ir67nYMyh+Hcg5nxGod+fCUdI2MT0xifAIAxh/CfVynRD6n/CIOUKjVyu8x84J38Cec91RWaL5WzA5bgA1+iCwatS4Xtzv6+v+QfRvgGhxo/hnqAXazrH0y4YnrWp5mmtj1L+BFzrTbjWp6B9Iu4Nh+CwvuYPwQclbbBowkvRnqvdcgNPHQnM4SU+l8AtbSuMlsZyFklZJOWRUywWjRn79LXl/CZhwKK7rU+SN07nbZ3r8WETVcnVt+hO6RiaSfGZ1tbWW5Fyo3eMnnyYEXACgVEGLJQfvRv5ZZDMnZPMOjGDLOReBLbKtIgkISmMV5RfbPbiSe0vqhqKF2Ex+yKtGMID8C4zuNzFelX/3bM43d2Ehe3wxeqeZj2UtzARQB6WdGPqbCw8YWZM1lZU6U8gwSy8c8XkZGkembYzcVnD6Dz8Woaxap8AMF4N/obxanfb4B83r3blyfv3KVbrDynm1jrEuv5SrDcrk84TRmbbgrDbJ8loY0KRwRBCN+8FVcAR/F5RBXEbuyBh/XczLe0oriHabZQvApnSwpfXIeXFcSiS80wE/JgFI2AUAXxgLLElOOFdCTS4yQEEYG+4BGFiG6IRVc2Ohg9zYQRII/CUTKtTTXpN2IyeTjAL+S6zWUaWzR0EfD91Xx3SPreOsXYMNZzTCd885tihaP1SwIRbz7lSvwAuUCA036PhDl7wYTQtZ1p86fnnQdrI8iXah4x8rlDpr9snF0vECNSOQEkD1lNbn/gVSFEoqVw7IjzCOQTwMtaVzXddGZXg+IJD5kU2KsyYDyMwAoFdyF90uvb4HdGeqN10o6dDGu5MlNKsrAkEdsEguikIYV05FeNmBBlr0xh8xDLrVULL85oNWBVOXp3/Dn7aMyt0cfoQHE/NXiuWooPwuX/jPvEJS8WLRCzkcXxHJtP+2kiYMRNGwCACJQ1YukoewmoSk1DXIL5M2jwCu/Z8VYEdy/wG99vJYLS/eU7MgREgi0ARL1HnoBpfN1kNq1RMh04iI9P56O5XOYS7MQKlENAL0kDn0LRp02ZjLBbsbm+e9M0uyhWBMMu9U2zYW20vG1f/6mrgkL3BVfnHlLuOfHlj0ra8Az52fx0R40iTk9wN3qTfRz4ssgba5M5ssjQvacDSEBRE6nv4058sOFhb1xBA7pJP6q8qUcmd8lOzo+LFfBgBigggaf7F3bnuX1PULYhO3fnuNcjTxB+MgoDHYwYRgFdwYOONLEoSHsXIWxgYgypPo7lV9rO+GyqRmMbKegwqCeh7Ppm5Lqmnn+j594u+9w7gsqskNslonKZ879rdnobJUJi1pIdAWQOWzs8BK+3P6anMGpFBQKnOg2cc+LUo9Sl6HD4YJd7MixYCWGR+Ipvt/i4trerXBsUw/0cJ00mo65eTKdiJAOpQBDdISI/EYl155gxYS45dMhEzf6Cds1+7VErVkfC/dnbOjYCLMAmjbjngU+PqypdXjqwz7fl85z0o4PEZZwQ2ICg+erRvfnjzBwyQZpKMQCQIlDVgae5F6X0Vf/BezRsjYB0CjynPf2PUpYARWjvbOiRYIEbABQSkuCKb7070S2O5adJVgaTnvQnHi+X6cDsjUBaBekLCdLU19ze1a9eu4Ea8MfTfNXEXBYye1TJVuO/ZHf41EgF8vKdswHoKoetPj9Q5afupBvll6PyXpOk9VF8Ysj/X1tw2f2gb/2YEXEGgogErl+v8BxS5yRVlWM7EIKCEJ9+ORd/DUWuMBJCzo+bJ/BgB5xGQ4meHHHrQhc7rYVCBnp7OHrxQftsgCyZNFAGp/MAGCeWTyO20ee3atTtMTS/CnikZsPzJkyc/YAorGnRJzfeIKZGB7xUjCDm9O5h/sqjeDiWSnCqnQUh5XUdHxySnJ5OFTyQCFQ1YGhFUioo0RCuRs8BK14QAFnnf7OlZ/YeaBoXUWXpqdkikmAwjkBAE5K/SDd5bovaWdBFcX/R/FNWv1rkoO8scHwIqVUf4nCRhwDLmfTU4qzQw2nuCblyxYkXf3h3+WwoBGnnhSmkmpGID1h5gunu778LPL5TEKSGNCLE6ojDg62gr3hgBpxAY04CFSlE3I1Y275RWLCxhBOTap7c+fmlsCtJ2LY8NVmZMFAElbkg3yrP1106iGoaqVj6f3ym84pkg+kyohJkYaQQGBgbqMeAQ8C5S95qcYJ/Qcx8L1nrOFZMw20SbwDVRBk7zxQ7KMLazOd3ofRaS3WGndBFJpcT5rc2LlkXEjdkwAqEgMKYBS3PxpfxkKNyYCCNQBwIwpD6Bxd1r161bF6fL7+w6VOChjEByEJDiNzv7t7+ejVe1TbmuqiqFemdto7h3ghF4rLe3d2sQ/RE6cgDGTQky1q4xZsOipPDm2KVvPdKYxaoeyWwYSy1h/0hM6yr4MJIYgX39fuILT4cSDhBQJ7gKUv2/TCZzaHACPJIRiBaBqgxY2gsLYq2OVjTmxggMQ2BAed5rsLiLzf35xHknToVE+w2TincYAUZgNAJKrJg8ZeLZyEuT7JfC0chU1dKd6/4FAvh/UFVn7pRsBJQI/EwsFArPpQCe8UW5opMTyaunYiWFk2UMHcgl7B+hL1JwBL5fjCBFZjeX67wTBZqSHkZ3gFSpqzGpVdkFyEw+K+IsAtWfqJ73MWe1ZMGdR0AKeSGSHHfGqciOpgKhr7BxIsm8SSOgxB+e2vrEGZxnpb5ZTjem3gsKyQ5tqA/CZIyWMnBImPSp5PoxuijH64eYTeZkqiPhPxkMKihS9EhXIBRKeWzAKjH/k/abcBnnnxQntbYsurgEPNzECFiHQNUGLF0hCRf3r6zTgAUij4AS6jvdudWxeyN4SrEBi/zZxgrWh4D8BcIGz4o5zLc+FSwZjdCGXUoWXwVxHrJEJBbDQgSUqKMCoZAkPLB8P2VsUd7W1nYwpn2ChVMfTCSfc2BVBM6n421XQk9/v/3GbyjRnvimwQ9uXlGHEhaTDYb6fEtLx0uSjQFr7wICVRuwBpXxih/GX65e4sLM0pHxlobG1AdsUEd6/mwb5GAZGAE7EVCX9+RWv5HDBsObnWw2+7D01emguCM8qkyJEgJ1hYTRSE6+K59ftcnUnMoCFS+13Qj5KT+wx54pjG2iKyWt+R6OrdrAntHDERm6hxQlvdj/5tC2BP5u8oT/s3nz5tEx2idwEpOgck0GrN35h9S3kgAM6xg/AkqIv47razzLmiTQvpwbPyosASNgJQJf6sl1XwDJfCulc1io7tu670BS9zdDBdwSeWMEhiOA3C3BvY+koPBM0wYZY/cdFDEi4aW256zZBaO4MWPf8DPT1T3C73mKve/GOisnT534UfT551j9iB8/avy4iV8mriOr5zgCNRmwtK47+3Zchtdo/oLj+MTbLr4U4r8NA97JK9eu3GKLrEgUyyGEtkwGy2ELAj6eBxf35LoutUUginIgqfuvodcnKOrGOtWJQLqe9zES4VLBDXhVQC9pPff1uzsbwivPO933PFmHsbsyZmSOag81X0gdSmjMKO4EWEpckMm0n+aErCxkIhGo2YCF8JAdypMXJhItVjoqBDamfO+kzts7N0fFsEo+FL5WV6kqd2MExkQAOZrEG3ryXeyVOyZU9XeAkfCzWHt+vX5KTIEQAgXP8wLltEGISAPymh7mOhbIkWnUgOXTCLMcnGZ8GOSPz5VPeEBEOtcpz3/l+R88msutzuO+8r0qulLuIqUSP0QOwEMoK8m6uYtAOojo2ezqFahUgITu6jVBxvMYRqACAo/LlFrSmetcX6FPHIfwYiNmx8GYeTICtiGAi+EJ5XlnZAeLe9gmHV15EKb5wdaWtmkwPLyNrpasWfUIqAeChthPTE+cDReDVPW87OxZVw6wqlQi4aU2qCk+OLABo8KcdxzfcVBB+GRz//D8V5j8EYd29e24dELTxKVwVzxixKEk7U4XRXk1FH4l/gGKaLbW1taZQnlfDZObLKpvIR1DdijN9pb2dl+Ki4a27f2N3KPf6853r967X8vf1uZFZwtPvbrUmKKffj9yNm4sdYzbakMgkAFLsxgopi9qSA0sws/ptbHk3oxAWQSehuvuybnurrvL9ojpQCaTOQS37/ExsWe2jIBNCNyjPP+Unp4uo54PNilskSwKYfznj2+aeCBkOsUiuViUWBAIHhKkPG2YgSna9U0Jo/chIETH85rTf1Q82/20T2euS2iq6smXV4Ie5SYdbdTa2nGe8P1V0JPAjTLYbMFqtaS1uf29UXrae0VvKgxLy4JJXHqUkt5vcGSYAQvrzVlCqZJ8lJDj0D+QAUtI9XGsF48qLYn/idLt3ForAl6tA/b27+295REklj1v7z7/ZQTqROApqdQr4Lp7e510jAyXsoH0i40R0JgoPQSUWJFu9Jp3F/Sgp54LGukqj0g0exbeqW90QV6W0SgC9wemLj0Sz7SiSN0bGIMxBi5durQJXQ4do5szh9kDp/JUFT3aeU6LxbRRY29ldN072tPT2QnT1ZXuSR6yxFJ8CV5RLw6Zqt3kpDi5vb398FqFbFvYlsGYMsarWqlx/0oIBDZgaaJILPs7/PlxJQZ8jBGoAoFHPCUWwV1zTRV94+lSpP1lLh5QmatDCGj38S/hK9ypCFl62iG5SYqqE80+teXxs/BZ+PckFWSlqkOgHo8aSSM0rrFRrK8OrNp7bd26dTZG1fWeXDtXcyNSPocQVkTXp3FNlNFxBxwPHi1zjJvLIDBQ6LsEhx4sczgpzU2i6P2subk5kiiUAeHtxAe6teX/iTtHAy//Vb6/XCuF/+ToMRVbUn5BvKVijxIHkSP83BLN3GQAgcAhhHtlwdf49xX6/Rbsv2BvG/9lBGpA4EGvKE7s6u36Tw1jou9KqxJR9PgxR5cR2AZv27fuqYTnsh6kZF+3bl3/Mcccs2za1AN+ifQUZ5BSjpWpCgHlBQ+fUz5C41wPjJFiMwzq26oCK0An6TfMEdIPMNLOIX7KX2+nZHZIRazi5EhQtfeV/hDFWw0I9Pb2bm1rbjtXSXkzhrl+x6xB8xFdpTg6JRq+iNb3jTgS+m4+3/lfEH1ZOcILFiyY0pBq2jL0uKfUuV35rtzQtgC/d2FMAf8mDY5VQhujPo9/VT0EkGpmMq6w1w6O3f3f4/hzwJB9/hkiAnV/WdIvD0i6jXAGYewlIkR9mZRVCKh7fZFut954BcxQjWOOVdCxMIxANAj80xdeMxuvogG7Vi7aiAVPrNfhrRpGLN6ShgBy2gQOIUQ4mfPPNDyXA+tfzbmCMlzOYzREzy0I/X5qyD7/HIkA5fc8w9fKSCgp7SM65BbY/q6mpFNAXd7T2tx6asCxLgx7BgaoZ9+l8IzMZBYtrlZwT3ivQ9/dxi89SIofVjuW+9WOQN0GLM2yu7v7brwMvaN29jwiwQjcNlBszORyqx5wAQOc33NdkJNlZATCQ0Bdu7Nv+8tyuc5/hEeTKYWNgDZidee6zsYL9pfDps307EZAqf7A+Z9g9HT+mYYkvIH1r2ZmlfBnV9PPkT5GsXIEg8piSun8NVFWQRncW7MszQQdGNfX9H6o+1CCVC6lqhTS+zGqdR5c6iCFNl/KHw3VA9UIq7Zt4IPS2/eNVWI7vHd/sW+ff4SOQCgGLC1VNtulrZZfC11CJkgPASl+htDTl+tCAA4pR+lLrEOws6gxIPAMDLbn9OS636wr8cTAn1nWjoDCfH0YXw8vxtCq3N1rZ8EjLENgaz6frzWvx6AKHR0dOqxhqmX61C6O8nVYlLlNydnmiEdLWQmz3mrRahM+t3nz5jWA6ozwKVtCkT2w6pqIlWtXbkEqhXfVRYTG4OmFxuJVUAXfQOhtudzqPFT72z7NpDijpaVFV32uuDU3d+g0Sgv3dZLqes/ztu7b5x+hIxCaAUtL1pPrugSn9G9Cl5IJUkEA71BIBJ3tOgehpzrW2IkNL/vjICiZSkROgM5CxoXAbchJNw8fJK6LSwDmGxwBXeoaL9lvBAUkQeWNOAKBjTf9/TRC4zxp1ihDKSeSaaxcv9YmpifOhg4p1/UoK39KBr5flKWZsANIpfB/sNrwu5GSr2xtbr+A6vQr5V89RLdGT6TfNGS/5M+ULJ439ICnJIcPDgXEwO9QDViQzy/6A/rl+TYDsjJJtxHow8LqzTByXgo1tCHLma2vT8yGsGFfK87oz4ImAoEBaHnZITMOanUhJ10iZiSgknjJ/gXylrXgJrs+IAke5gICKnhIUEr4z3VBxbFkRDyL0UU5rqHZY8ngyvF68qW5omM9chZS7ueEq6S/78v7Kx3nY9Uh0FdoeB8cNTZX15twLym+2rag7ViKGiK9zbXQa4iThdTGqbIeZyim04jD5wzB4h4klIcnF28mEQh9UQ6X9p1I6n4aTBR3mxScabuDwOBCyvMXYWH1U3ekflZSz6PxtfpZjfgXIzAUAfk3WVQvg3H5U8uXLy8OPcK/3UQgl+u8s1BsgDu76nFTA5Z6TATq8D6CMWP2mPQd6OAVPWMGrCXHLpkICKY7AENVIiIsnA0YFZCSlBO440EwaVsjz3+F+a/20Jo1tzwhlbqo2v6E+41TaXnt0qVLm6jpqOcYl8yQaDJ1ZGtrR6acns+Z+pxX4di+MEMU/7gS+1j68mYSgdANWFpYJHV/rCjSSzB9fMM0OXsu0FbihoZG7zhUv+l1QdxSMlJ5sUE4xDehH+c0KjXJyWzbqaT63519247v7u2+K5kQ0NVa5xh8asuTi6Hht/CPX6bITXVw7yN8Sp5FAI6+zt7Oh03psW1S/xxTtOOgyx44lVH3hKRwTZRT8tGb7rppe7mD3F4bAoNVmaVYXtsogr2VOHbr0zu+QFAzhNwMDwGURb9CMnd57hAM+jHYSWeNITo48dOIAUtrns+v2ihS/on4+ZATSLCQYSOwC4vjdyMny1nId/V02MSjpafmRsvPCLfik08/8WEvLV4I6n82woGJOoMArBldReW9NJvt/gIStevwQd4IIqArFMKz7mLhydNhtMBXRd7IIKCCG7Bw/VNYrN+PufRNzaenCrNN0Y6BLqa874EY+DrDUnmKwjVREm/c+415KpZkmIDGdIOnc0A9mgBVK6oIb6OLM5n2kyt2cvBgV67rVlw3/90rOjxYX9va2jpt7/7ev83NJ8zAzfUVe/cRSniDduJ5dp9/mULAmAFLCwyvm/uwYG7Hx997TSnAdK1E4B7h+QuxOP6+ldLVKhQB13LcYDfoxWxXV9f9WNC+EvnI3sQL2lpPBBL9H8Xcvy2b6+rI5zvvIaERKzEmAj09q/+QKnovwX2ga8zO3MEJBJQ3cH9gQaWcGXisLQMNe/hLKefYomoIcmzW6T1CoEOZxCzCyrEBK+TJxYf5x4WSuupv0jfYsMRVCxYsPogYEMqX6sdDdBov/NTZQ/YHf6Zk4a34sa/4g1Q+J28fCZKhfaMGLC2zXjCnB1KtSH/GISqGJtEisgXI8u0J28a9DMbLZ8uQWiRgIFGkpJDwdtgLjM5HVhSFo7Gg/XUgTHiQawhoL6tvj+trfD7m/mr8xtTzliQEEG71EAyXL8cXwvMx+xxO4vbk+1OmTFkfXAXlvAELH2CMfhjFDXJ2cHwtGynZA2fMGVEkvBJLqolz+f6SB7ixLgR68qt/jmfpDXURoTH4wAZv4Cqogtsyna2hP6V1ejZCQarzR2iHzCzirfva8FGlO9996759/mEUAeMGLC195+2dm/sHGk7AmqnHqDZMPEYE5N+01xW8e95HL9be/STu8LoZ9bKfy+UexYL2NfiK9FqcOOzyGuPVY5S1VCuVLB6nr82Va1duMcqLiduOgN+TW32lL9MvhqCrbReW5SuLwMYV/7+9ew2Oq7zvOP48Z1eyFWwuNcQxBlt2QgrDJQUXXEuWUW0nbZhJhyQkJWFyaVImM70lTae39E06nV7yprRNO8y0kzQkaVrqdJIMJG6AgCx5pZggIBS3JQXsQBIMhIuDLVmWznn6e2SvI8RK7Gr3nD3P2e/OaLR79uxz+Txnd8/+z3PZvXtqwWcXeeKqq3as0tMrF9kliKecten+KC9QDyxWIFz8kN60aVOX9liz+F4BP5tyb8WAZZouenkm+k0l8nzTCYWegDVv7e8fmB/gCbpWPnbhjPnGqUpozi8NI9xUfdzff/Wgnn9D9bHCd5/R/eTUY+6kKpBJAMvXwM/q7yeUVVfDW1KtEYlnLeCj05964fCPr1Kvq/GsM087v5Mn+6ennU/a6S+2ApGuIu1KzMwlztgvqhz6POZWEIH79CPvLXsrI2+uVCr7C1InqtECgdHRux9bs3b1DvX9/7iSe6kFSZJEhgL6kD6w1OyWRcfXL/W1eXqdhmq8rFdxq8vmnOltdZrtSi+ySz9e2lXmLPNd2bVyrfI7NQwoy7wzyauU3mqdmZQ/x5nMBjms8d+jHX+zzt60bcu2S4sEMX9IoI2jX6/WL3Luw9X7+j8Tu/Ln5jzmbsoCmQWwfD38HDwjY8Mf1OTen9DDOOW6kXzaAs7s1kTQl6lnxx/5tk07u3akXy7PbGxHvq3Pc/EJf0/0xtrzvsTYzcr73tbnT4rZCdhHfK86vS+vqlT23JldvuQUksCuXbvikcrITTrpukg9//8tpLJ3ellr9ait18TZqBABLF3nTjWAZY3ZUK9p3vdTMG7JAc+8160V5YttXIz3xIIYM6m+VxbMtkOeqFSGb3HGfK1DqrtYNZcn1nxpcHBw+WI7hfTcmvPW7FZ5n6yWWZ0BblD9VuzctPMMtfnbq9v1ffGN2cXrqhv4n7pApgGsam38ylcminbq8VPVbfwPSuB7xiVv0wqD1xR9Imj1UCjESayGENR1AjM6uuc76pnRp35Yv6Uj8oWgjsoOL6y+QB9Vu3243G0v8b3qxKHvV24ILC7gT7o0rPA9OhnYoUAWPfUW58rHs87etdSCOJMU4sd6qadU13faUpz8jxO97sylvDaXr4nsgVyWKyeFUu/zQrwnFuCcXrNmzQ8XeI7NrRKwsV+VMPAV11uCcUk8nfxZS1LKQSL+Qp+KccucoqycOe7edWzZ9A3a9prqdhdZJm+vYmT0vy0BLF+3vXuHhsrT0RW6e09GdSWb5gWe15Xf35mcOqofyHtvbz65/KdgE1OIHlgzM+W6T/b9B7aCk/9Q7o7eqBjIX6uVjuW/pTq4hH6BDGff+7q1qy9Uu31Wq+P4xRS4IdCQgJaNvnvN2te+SVcYfRd5fvA0pJfpzveXl0X/vvQco3VLf21uXvmMPueOpFWaiWUzhbhwVfVJkogAVhWj1n9rivCeqFUzv+3gyR/hCz3P9hYIaJqGH1lj/6AFSQWfhHp8fnzrLwz6TiqFuJWTaN7cVk7nSHOGD1pzqFy2vqcWtwwF2hbA8nX0Y4c1zGXnyXk4JjOsN1k1JuDnSPlU7KYv0Apmnx4fH/fzXnXGzboiBLAO+znoGm0wv0zw3tGR3yvH0QW6QumvLhAYaRQx3f1HTGR/ZW9l+Of8ajicpKaL3Qmp+2NIwyE+4z/r1X/vj1VnemHmp+E1abv7guYrfGszQWpdhCpCb5O6L8gspfk0t0mRAljTa9eu+sFSHDrlNUXugaWe2QQvMzqQR0b3+PPkb2aUXZ6zibSo1y0aand2ngtZb9mGvj10UO+ju+bs36f7vgPO7M05x4XjKkaG/9sawDpZz8TPw6GD/RLj3FCGdSerVxfwVzj/bjruusDPczU2NtZ5K23Y8OfBcKa5uUKG9g39oDK650a9Ry/WKhtf0jFBIOvV3ztp7aHecO6fI2eu0Hty2969e25TRmpibgi0TkCf9ZPqzfdX6oW5TkfXx5Qyw/1bx9toSt5eF5DKr9cFhff7+QobTeBl+1vT+7LHIT6wzX2nvVqVbZSEb3Sqku4JLm6cwqh5pyBB3Zp10+d3qsHe2pl27FaXmLJfiY+FUYw5V0Pt/qkoR4Lm9vK9sGrd1OGs67O1nmBbugJ5CGDN1lAr2D2+d2xkuz5sP6ANzZ2gpWvWCalXe1yt14/kj+7b962nO6HSNevobBF6YLXkBEbv0e+pt88NUdm80Trz9/KaqGnGxjQEHrfW/oktuXX6Efuh4bHhB9LIhDQRmCvgh2kpkPW3Gjb+Bl1l/F09d2oy07n7cT8VgXv0w/o6H0Q8cQHp7lYN61yXSmmzTDTlH+WJC//C1anmYAXCUxQL37HhvycWqpy1BxZ6iu2tF9AKv9/X71jfe5mbcdcO9F19YxEgXnzxua+qHq+MTVj3Lb+qcxHqGFodchPAOgnndLL8efX0uPDkD2R6emR7RP2fPng/Nh1PnXfihLkDe1zN8Vb317Ienj9nU5h365zAvd7KDQ8PH9Bqor+tH1br9Zo/1d8rP9TrTYz9FhOY1NCGLzprt+v9+IaRyp6/GBkZeXaxF/AcAmkIaNj4RGVs5G/0nt+ooMq7lMdIGvmQpvmJOlTe7Gx8id7z2zVk/z+aGS443/Mtl73lNG0LfliHjsFUfzBoOfje+XbBPmYFwldrOo0OcoUNYLEC5as1f+uf1+/Ym5UqK0ALQRe+burv77+49crZprh///7jyvEL83M9Ob3K/M08zkAgbwGs2Sqrp8cL/gey7+mhDf+ovzgDi07NIjHW3aVJoN+t1ecu8lfb9+3bp5NobkmS+OBVV/ASUdKSHljzHU7MkTX8yRcOP3e+Jn6+3hlzt/bRP25NCMQnHO1Hlk91r9HQzfdVKnvuUXq4NoHKS1sj4IMpCqp8WcGVbYmJLleq/vv5cGtS79hUJvQL+lZ9B79DAcLV6mH5G5oQOJXVICfPmFxfBOXYRKn4nLIpwNQB1brou/lA9T7/XynQ19d3jrb2vPKZgmwpxamc/xVEJ61qJMdnut6jxLG35jTrSru3bdsWfGcAXVjyQyJPnYvre/u5008/zffM4tYGAd/DJLc339NDhftIX9/gp61JPqmD5e16nMugW24RFy6YhgW6f4ld6eax0aFHF96tg5+ZKcYwAtfiHljzj4iTVyZu1fZbt27dquGF0Y266vdePT53/r48rimQaGtFX4u3TiddX+7oIbs1ediYR4HR0aEHVa6PqKfqR2em3Ns0P9779Z3yVm0r5bG8OSvTlDH2Tl2e3uWi+Ct7K5VM5kzRanTr1XspZxQNFydZcWTZfzf8qsZesL6x3fO7t+ZL9OfR3BYU6FJbB/+eWLB2cRzT/gvqpPeEXzhJwdEtkSt/Tt+N/nuxk2/nxzNmWEGs7Sd/1wdpoQtLj2zt3zaqj4t+X4HE2c/v3r1b3+Xc2iGQ6wBWFWR0dOhh3b9OP443miT6qA6eD+sDwXeF59aYwKTcbjfWfmFy8sh/dtRqgo05ze6trqGvL8aJTTnV4RZzaf08WXr8+/r7w61bB/tMkrxL939Vf6v1x60q4MxRvQ/v0cPbFET++thYy+a3qebAfwQyEVCvLC0sYHb5vy1btq8t2fidzrh36oLTVm3jgtNPW+Elmeg9775S6i59VW4v/vSpbO4lyfF9pVLp57PJLZ1ckqQc3/HQHUfTSX021Ujnme9IMf1Mk56xU/dnmmFgmXVP2ydnyubdgRW7ruJamyQdufhSXTrp73RywY1rZi/sJqUd+l7058HL08+59TlYa0q6MH36UlPWd5+JY3ue/jUdUO3p6ZmYOWbePLcs3dPl/XMf13PflpK73HTpVDpRlBx/tdclrvyBKEk2+P2irvi7i+0/PT19qOSWnUrf77tyovvJxV7Dc/UL+GMquNuWLVt+pmS7P6iCf0gng8GPrU25AfTjwmqIoPnS5PEjX/NzmaScX2GS7+8b+HNr7CcCr1CsCZh72hms9HOJxVPxDhfZt+k49FeiNgZuupTiz6ju4wogD+kX/R1Hp46OtLNNllIBXoNAIwKDVw6+bro7vlZD435ZJxo79NoVjby+APv6OTzv1Rwgd9lS6c5y2XzbD8EsQL2oAgIIIIAAAggg0DaBIANYc7UU2d5sXPRrmvT9OmfMqrnPdex9aw6ZxHxdQwVu7znac2fKVysLy7y17+p/VYD0+pArqPfEwcro8OzVgrzUQxM6/mxkoms0tPGXVCbfFbeIP2yP6cP1AQWsNDTQDSU2GVb340yGCeWlnSkHAlWBiy++uHvVGau2JsbpPW+3afsm/XVVny/Ifz8U+BG95++2zt15PD5+D/NJFqRlqQYCCCCAAAII5EYg+ABWVdL38lCXwkETxer6ba/V9jXV5zrgv+/2eJ+/0mui0m2VytC4Hit2wa0Zga192/bp9Vc1k0a7X6uD4G4FsHzvh1zeZt+3MzNvMnG0VUPqNOTI9amg5+aysAsXyo+B/x+V/QFrou9oTpt7JycnH6KH1cJgPNPZAn41vGMrjm1WxGdAJyFXaaLpK/SN9bqAVGKV9xGtEHq/ccl4Sf+n4qkHCVgF1IIUFQEEEEAAAQSCFChMAGu+/on5sko7tcLeTp1o+jGoZ87fJ+DHE7rK+4DqtddEtjI9fWwPJ86tb00FsJ5Rque0PuXsUvRLvGoluxuzy7H5nAYGBs4xM+YyZ6M3KQB3qT6kLlVwSPORtf09/Kzec48r0HZA5flf9XDcr55V/9XV1fUYQ4Oab3dS6GwB9cw81yb2Cg01vlQ9qi/S8O0L9f73KxGf0UYZxdic5qywj+o791HNYfJwKbH3Lz+6/Lv0bG5jq5A1AggggAACCHSsQGEDWHNbdHYOnmPxZp0Y/6IqfKVOiq/Q834yuRBufs6qh33ASifPD0aJub+0rHQ/P5jTbTr9mFqppV9/km4u6afurPtEpTLyl+nnlH4Os3PflUobTFzaqPfCemud72V5jubYOVtBpdfqh6YPNq7UX4/+6pkoc1r7HVFQ6kW9vzQpsHtRaT2jz4gfKTDsg1VPucgcimJ3MFoWHdB77oj254YAAhkK+DNfWmsAAAu3SURBVLm04nK8LonseTYx5ysor/d+crYCXKs0qewqTS67St/pfvoAPySxnuHIvsek/171Q3qf12ufVxrP6f4zes8fUm+wJ20c/TC25gdnntlzgFWGJMMNAQQQQAABBBDIiUBHBLBqWWt509da27VJc1VcoRPYy3UCe4FOXv3k0vWcANdKstlth5XAY/oh7VeMe8wk9qHIuQdXn7/6e7t27YqbTZzXNyYwsHngMleyi64w0ViK7dlbP8a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"}))),I.createElement("image",{x:342,y:60,width:51,height:83,xlinkHref:"data:image/png;base64,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diff --git a/content/assets/js/6151.12da4352.js.LICENSE.txt b/content/assets/js/6151.12da4352.js.LICENSE.txt
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t[e]=[],this.setQueryParameters({hierarchicalFacetsRefinements:i({},t,this.hierarchicalFacetsRefinements)})},toggleTagRefinement:function(e){return this.isTagRefined(e)?this.removeTagRefinement(e):this.addTagRefinement(e)},isDisjunctiveFacet:function(e){return this.disjunctiveFacets.indexOf(e)>-1},isHierarchicalFacet:function(e){return void 0!==this.getHierarchicalFacetByName(e)},isConjunctiveFacet:function(e){return this.facets.indexOf(e)>-1},isFacetRefined:function(e,t){return!!this.isConjunctiveFacet(e)&&f.isRefined(this.facetsRefinements,e,t)},isExcludeRefined:function(e,t){return!!this.isConjunctiveFacet(e)&&f.isRefined(this.facetsExcludes,e,t)},isDisjunctiveFacetRefined:function(e,t){return!!this.isDisjunctiveFacet(e)&&f.isRefined(this.disjunctiveFacetsRefinements,e,t)},isHierarchicalFacetRefined:function(e,t){if(!this.isHierarchicalFacet(e))return!1;var r=this.getHierarchicalRefinement(e);return t?-1!==r.indexOf(t):r.length>0},isNumericRefined:function(e,t,r){if(void 0===r&&void 0===t)return!!this.numericRefinements[e];var n=this.numericRefinements[e]&&void 0!==this.numericRefinements[e][t];if(void 0===r||!n)return n;var i,a,u=c(r),o=void 0!==(i=this.numericRefinements[e][t],a=u,s(i,(function(e){return l(e,a)})));return n&&o},isTagRefined:function(e){return-1!==this.tagRefinements.indexOf(e)},getRefinedDisjunctiveFacets:function(){var e=this,t=a(Object.keys(this.numericRefinements).filter((function(t){return Object.keys(e.numericRefinements[t]).length>0})),this.disjunctiveFacets);return Object.keys(this.disjunctiveFacetsRefinements).filter((function(t){return e.disjunctiveFacetsRefinements[t].length>0})).concat(t).concat(this.getRefinedHierarchicalFacets())},getRefinedHierarchicalFacets:function(){var e=this;return a(this.hierarchicalFacets.map((function(e){return e.name})),Object.keys(this.hierarchicalFacetsRefinements).filter((function(t){return e.hierarchicalFacetsRefinements[t].length>0})))},getUnrefinedDisjunctiveFacets:function(){var e=this.getRefinedDisjunctiveFacets();return this.disjunctiveFacets.filter((function(t){return-1===e.indexOf(t)}))},managedParameters:["index","facets","disjunctiveFacets","facetsRefinements","facetsExcludes","disjunctiveFacetsRefinements","numericRefinements","tagRefinements","hierarchicalFacets","hierarchicalFacetsRefinements"],getQueryParams:function(){var e=this.managedParameters,t={},r=this;return Object.keys(this).forEach((function(n){var i=r[n];-1===e.indexOf(n)&&void 0!==i&&(t[n]=i)})),t},setQueryParameter:function(e,t){if(this[e]===t)return this;var r={};return r[e]=t,this.setQueryParameters(r)},setQueryParameters:function(e){if(!e)return this;var t=m.validate(this,e);if(t)throw t;var r=this,n=m._parseNumbers(e),i=Object.keys(this).reduce((function(e,t){return e[t]=r[t],e}),{}),a=Object.keys(n).reduce((function(e,t){var r=void 0!==e[t],i=void 0!==n[t];return r&&!i?u(e,[t]):(i&&(e[t]=n[t]),e)}),i);return new this.constructor(a)},resetPage:function(){return void 0===this.page?this:this.setPage(0)},_getHierarchicalFacetSortBy:function(e){return e.sortBy||["isRefined:desc","name:asc"]},_getHierarchicalFacetSeparator:function(e){return e.separator||" > "},_getHierarchicalRootPath:function(e){return e.rootPath||null},_getHierarchicalShowParentLevel:function(e){return"boolean"!=typeof e.showParentLevel||e.showParentLevel},getHierarchicalFacetByName:function(e){return s(this.hierarchicalFacets,(function(t){return t.name===e}))},getHierarchicalFacetBreadcrumb:function(e){if(!this.isHierarchicalFacet(e))return[];var t=this.getHierarchicalRefinement(e)[0];if(!t)return[];var r=this._getHierarchicalFacetSeparator(this.getHierarchicalFacetByName(e));return t.split(r).map((function(e){return e.trim()}))},toString:function(){return JSON.stringify(this,null,2)}},e.exports=m},210:function(e,t,r){"use strict";e.exports=function(e){return function(t,r){var s=e.hierarchicalFacets[r],c=e.hierarchicalFacetsRefinements[s.name]&&e.hierarchicalFacetsRefinements[s.name][0]||"",u=e._getHierarchicalFacetSeparator(s),o=e._getHierarchicalRootPath(s),h=e._getHierarchicalShowParentLevel(s),f=a(e._getHierarchicalFacetSortBy(s)),l=t.every((function(e){return e.exhaustive})),m=function(e,t,r,a,s){return function(c,u,o){var h=c;if(o>0){var f=0;for(h=c;f<o;){var l=h&&Array.isArray(h.data)?h.data:[];h=i(l,(function(e){return e.isRefined})),f++}}if(h){var m=Object.keys(u.data).map((function(e){return[e,u.data[e]]})).filter((function(e){return function(e,t,r,n,i,a){if(i&&(0!==e.indexOf(i)||i===e))return!1;return!i&&-1===e.indexOf(n)||i&&e.split(n).length-i.split(n).length==1||-1===e.indexOf(n)&&-1===r.indexOf(n)||0===r.indexOf(e)||0===e.indexOf(t+n)&&(a||0===e.indexOf(r))}(e[0],h.path||r,s,t,r,a)}));h.data=n(m.map((function(e){var r=e[0];return function(e,t,r,n,i){var a=t.split(r);return{name:a[a.length-1].trim(),path:t,count:e,isRefined:n===t||0===n.indexOf(t+r),exhaustive:i,data:null}}(e[1],r,t,s,u.exhaustive)})),e[0],e[1])}return c}}(f,u,o,h,c),d=t;return o&&(d=t.slice(o.split(u).length)),d.reduce(m,{name:e.hierarchicalFacets[r].name,count:null,isRefined:!0,path:null,exhaustive:l,data:null})}};var n=r(2148),i=r(7888),a=r(2293)},3076:function(e,t,r){"use strict";var n=r(185),i=r(2344),a=r(2148),s=r(4587),c=r(7888),u=r(9725),o=r(2293),h=r(210);function f(e){var t={};return e.forEach((function(e,r){t[e]=r})),t}function l(e,t,r){t&&t[r]&&(e.stats=t[r])}function m(e,t){var r=t[0];this._rawResults=t;var a=this;Object.keys(r).forEach((function(e){a[e]=r[e]})),this.processingTimeMS=t.reduce((function(e,t){return void 0===t.processingTimeMS?e:e+t.processingTimeMS}),0),this.disjunctiveFacets=[],this.hierarchicalFacets=e.hierarchicalFacets.map((function(){return[]})),this.facets=[];var o=e.getRefinedDisjunctiveFacets(),m=f(e.facets),d=f(e.disjunctiveFacets),v=1,p=r.facets||{};Object.keys(p).forEach((function(t){var n,i,s=p[t],o=(n=e.hierarchicalFacets,i=t,c(n,(function(e){return(e.attributes||[]).indexOf(i)>-1})));if(o){var h=o.attributes.indexOf(t),f=u(e.hierarchicalFacets,(function(e){return e.name===o.name}));a.hierarchicalFacets[f][h]={attribute:t,data:s,exhaustive:r.exhaustiveFacetsCount}}else{var v,g=-1!==e.disjunctiveFacets.indexOf(t),y=-1!==e.facets.indexOf(t);g&&(v=d[t],a.disjunctiveFacets[v]={name:t,data:s,exhaustive:r.exhaustiveFacetsCount},l(a.disjunctiveFacets[v],r.facets_stats,t)),y&&(v=m[t],a.facets[v]={name:t,data:s,exhaustive:r.exhaustiveFacetsCount},l(a.facets[v],r.facets_stats,t))}})),this.hierarchicalFacets=s(this.hierarchicalFacets),o.forEach((function(s){var c=t[v],o=c&&c.facets?c.facets:{},h=e.getHierarchicalFacetByName(s);Object.keys(o).forEach((function(t){var s,f=o[t];if(h){s=u(e.hierarchicalFacets,(function(e){return e.name===h.name}));var m=u(a.hierarchicalFacets[s],(function(e){return e.attribute===t}));if(-1===m)return;a.hierarchicalFacets[s][m].data=n({},a.hierarchicalFacets[s][m].data,f)}else{s=d[t];var v=r.facets&&r.facets[t]||{};a.disjunctiveFacets[s]={name:t,data:i({},f,v),exhaustive:c.exhaustiveFacetsCount},l(a.disjunctiveFacets[s],c.facets_stats,t),e.disjunctiveFacetsRefinements[t]&&e.disjunctiveFacetsRefinements[t].forEach((function(r){!a.disjunctiveFacets[s].data[r]&&e.disjunctiveFacetsRefinements[t].indexOf(r)>-1&&(a.disjunctiveFacets[s].data[r]=0)}))}})),v++})),e.getRefinedHierarchicalFacets().forEach((function(r){var n=e.getHierarchicalFacetByName(r),s=e._getHierarchicalFacetSeparator(n),c=e.getHierarchicalRefinement(r);if(!(0===c.length||c[0].split(s).length<2)){var o=t[v],h=o&&o.facets?o.facets:{};Object.keys(h).forEach((function(t){var r=h[t],o=u(e.hierarchicalFacets,(function(e){return e.name===n.name})),f=u(a.hierarchicalFacets[o],(function(e){return e.attribute===t}));if(-1!==f){var l={};if(c.length>0){var m=c[0].split(s)[0];l[m]=a.hierarchicalFacets[o][f].data[m]}a.hierarchicalFacets[o][f].data=i(l,r,a.hierarchicalFacets[o][f].data)}})),v++}})),Object.keys(e.facetsExcludes).forEach((function(t){var n=e.facetsExcludes[t],i=m[t];a.facets[i]={name:t,data:r.facets[t],exhaustive:r.exhaustiveFacetsCount},n.forEach((function(e){a.facets[i]=a.facets[i]||{name:t},a.facets[i].data=a.facets[i].data||{},a.facets[i].data[e]=0}))})),this.hierarchicalFacets=this.hierarchicalFacets.map(h(e)),this.facets=s(this.facets),this.disjunctiveFacets=s(this.disjunctiveFacets),this._state=e}function d(e,t,r,n){if(n=n||0,Array.isArray(t))return e(t,r[n]);if(!t.data||0===t.data.length)return t;var a=t.data.map((function(t){return d(e,t,r,n+1)})),s=e(a,r[n]);return i({data:s},t)}function v(e,t){var r=c(e,(function(e){return e.name===t}));return r&&r.stats}function p(e,t,r,n,i){var a=c(i,(function(e){return e.name===r})),s=a&&a.data&&a.data[n]?a.data[n]:0,u=a&&a.exhaustive||!1;return{type:t,attributeName:r,name:n,count:s,exhaustive:u}}m.prototype.getFacetByName=function(e){function t(t){return t.name===e}return c(this.facets,t)||c(this.disjunctiveFacets,t)||c(this.hierarchicalFacets,t)},m.DEFAULT_SORT=["isRefined:desc","count:desc","name:asc"],m.prototype.getFacetValues=function(e,t){var r=function(e,t){function r(e){return e.name===t}if(e._state.isConjunctiveFacet(t)){var n=c(e.facets,r);return n?Object.keys(n.data).map((function(r){return{name:r,count:n.data[r],isRefined:e._state.isFacetRefined(t,r),isExcluded:e._state.isExcludeRefined(t,r)}})):[]}if(e._state.isDisjunctiveFacet(t)){var i=c(e.disjunctiveFacets,r);return i?Object.keys(i.data).map((function(r){return{name:r,count:i.data[r],isRefined:e._state.isDisjunctiveFacetRefined(t,r)}})):[]}if(e._state.isHierarchicalFacet(t))return c(e.hierarchicalFacets,r)}(this,e);if(r){var n,s=i({},t,{sortBy:m.DEFAULT_SORT,facetOrdering:!(t&&t.sortBy)}),u=this;if(Array.isArray(r))n=[e];else n=u._state.getHierarchicalFacetByName(r.name).attributes;return d((function(e,t){if(s.facetOrdering){var r=function(e,t){return e.renderingContent&&e.renderingContent.facetOrdering&&e.renderingContent.facetOrdering.values&&e.renderingContent.facetOrdering.values[t]}(u,t);if(Boolean(r))return function(e,t){var r=[],n=[],i=(t.order||[]).reduce((function(e,t,r){return e[t]=r,e}),{});e.forEach((function(e){var t=e.path||e.name;void 0!==i[t]?r[i[t]]=e:n.push(e)}));var s,c=t.sortRemainingBy;return"hidden"===c?r:(s="alpha"===c?[["path","name"],["asc","asc"]]:[["count"],["desc"]],r.concat(a(n,s[0],s[1])))}(e,r)}if(Array.isArray(s.sortBy)){var n=o(s.sortBy,m.DEFAULT_SORT);return a(e,n[0],n[1])}if("function"==typeof s.sortBy)return function(e,t){return t.sort(e)}(s.sortBy,e);throw new Error("options.sortBy is optional but if defined it must be either an array of string (predicates) or a sorting 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e.name===t})),o=s.reduce((function(e,t){var r=e&&c(e.data,(function(e){return e.name===t}));return void 0!==r?r:e}),u),h=o&&o.count||0,f=o&&o.exhaustive||!1,l=o&&o.path||"";return{type:"hierarchical",attributeName:t,name:l,count:h,exhaustive:f}}(e,n,i,t.hierarchicalFacets))}))})),Object.keys(e.numericRefinements).forEach((function(t){var n=e.numericRefinements[t];Object.keys(n).forEach((function(e){n[e].forEach((function(n){r.push({type:"numeric",attributeName:t,name:n,numericValue:n,operator:e})}))}))})),e.tagRefinements.forEach((function(e){r.push({type:"tag",attributeName:"_tags",name:e})})),r},e.exports=m},9374:function(e,t,r){"use strict";var n=r(7775),i=r(3076),a=r(8078),s=r(6394),c=r(696),u=r(4853),o=r(116),h=r(9803),f=r(185),l=r(4336);function m(e,t,r){"function"==typeof e.addAlgoliaAgent&&e.addAlgoliaAgent("JS Helper ("+l+")"),this.setClient(e);var i=r||{};i.index=t,this.state=n.make(i),this.lastResults=null,this._queryId=0,this._lastQueryIdReceived=-1,this.derivedHelpers=[],this._currentNbQueries=0}function d(e){if(e<0)throw new Error("Page requested below 0.");return this._change({state:this.state.setPage(e),isPageReset:!1}),this}function v(){return this.state.page}u(m,c.EventEmitter),m.prototype.search=function(){return this._search({onlyWithDerivedHelpers:!1}),this},m.prototype.searchOnlyWithDerivedHelpers=function(){return this._search({onlyWithDerivedHelpers:!0}),this},m.prototype.getQuery=function(){var e=this.state;return s._getHitsSearchParams(e)},m.prototype.searchOnce=function(e,t){var r=e?this.state.setQueryParameters(e):this.state,n=s._getQueries(r.index,r),a=this;if(this._currentNbQueries++,this.emit("searchOnce",{state:r}),!t)return this.client.search(n).then((function(e){return a._currentNbQueries--,0===a._currentNbQueries&&a.emit("searchQueueEmpty"),{content:new i(r,e.results),state:r,_originalResponse:e}}),(function(e){throw a._currentNbQueries--,0===a._currentNbQueries&&a.emit("searchQueueEmpty"),e}));this.client.search(n).then((function(e){a._currentNbQueries--,0===a._currentNbQueries&&a.emit("searchQueueEmpty"),t(null,new i(r,e.results),r)})).catch((function(e){a._currentNbQueries--,0===a._currentNbQueries&&a.emit("searchQueueEmpty"),t(e,null,r)}))},m.prototype.findAnswers=function(e){var t=this.state,r=this.derivedHelpers[0];if(!r)return Promise.resolve([]);var n=r.getModifiedState(t),i=f({attributesForPrediction:e.attributesForPrediction,nbHits:e.nbHits},{params:h(s._getHitsSearchParams(n),["attributesToSnippet","hitsPerPage","restrictSearchableAttributes","snippetEllipsisText"])}),a="search for answers was called, but this client does not have a function client.initIndex(index).findAnswers";if("function"!=typeof this.client.initIndex)throw new Error(a);var c=this.client.initIndex(n.index);if("function"!=typeof c.findAnswers)throw new Error(a);return c.findAnswers(n.query,e.queryLanguages,i)},m.prototype.searchForFacetValues=function(e,t,r,n){var i="function"==typeof this.client.searchForFacetValues;if(!i&&"function"!=typeof this.client.initIndex)throw new Error("search for facet values (searchable) was called, but this client does not have a function client.searchForFacetValues or client.initIndex(index).searchForFacetValues");var a=this.state.setQueryParameters(n||{}),c=a.isDisjunctiveFacet(e),u=s.getSearchForFacetQuery(e,t,r,a);this._currentNbQueries++;var o=this;return this.emit("searchForFacetValues",{state:a,facet:e,query:t}),(i?this.client.searchForFacetValues([{indexName:a.index,params:u}]):this.client.initIndex(a.index).searchForFacetValues(u)).then((function(t){return o._currentNbQueries--,0===o._currentNbQueries&&o.emit("searchQueueEmpty"),(t=Array.isArray(t)?t[0]:t).facetHits.forEach((function(t){t.isRefined=c?a.isDisjunctiveFacetRefined(e,t.value):a.isFacetRefined(e,t.value)})),t}),(function(e){throw o._currentNbQueries--,0===o._currentNbQueries&&o.emit("searchQueueEmpty"),e}))},m.prototype.setQuery=function(e){return this._change({state:this.state.resetPage().setQuery(e),isPageReset:!0}),this},m.prototype.clearRefinements=function(e){return this._change({state:this.state.resetPage().clearRefinements(e),isPageReset:!0}),this},m.prototype.clearTags=function(){return this._change({state:this.state.resetPage().clearTags(),isPageReset:!0}),this},m.prototype.addDisjunctiveFacetRefinement=function(e,t){return this._change({state:this.state.resetPage().addDisjunctiveFacetRefinement(e,t),isPageReset:!0}),this},m.prototype.addDisjunctiveRefine=function(){return this.addDisjunctiveFacetRefinement.apply(this,arguments)},m.prototype.addHierarchicalFacetRefinement=function(e,t){return this._change({state:this.state.resetPage().addHierarchicalFacetRefinement(e,t),isPageReset:!0}),this},m.prototype.addNumericRefinement=function(e,t,r){return this._change({state:this.state.resetPage().addNumericRefinement(e,t,r),isPageReset:!0}),this},m.prototype.addFacetRefinement=function(e,t){return this._change({state:this.state.resetPage().addFacetRefinement(e,t),isPageReset:!0}),this},m.prototype.addRefine=function(){return this.addFacetRefinement.apply(this,arguments)},m.prototype.addFacetExclusion=function(e,t){return this._change({state:this.state.resetPage().addExcludeRefinement(e,t),isPageReset:!0}),this},m.prototype.addExclude=function(){return this.addFacetExclusion.apply(this,arguments)},m.prototype.addTag=function(e){return this._change({state:this.state.resetPage().addTagRefinement(e),isPageReset:!0}),this},m.prototype.removeNumericRefinement=function(e,t,r){return this._change({state:this.state.resetPage().removeNumericRefinement(e,t,r),isPageReset:!0}),this},m.prototype.removeDisjunctiveFacetRefinement=function(e,t){return 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t[e]=[],this.setQueryParameters({hierarchicalFacetsRefinements:i({},t,this.hierarchicalFacetsRefinements)})},toggleTagRefinement:function(e){return this.isTagRefined(e)?this.removeTagRefinement(e):this.addTagRefinement(e)},isDisjunctiveFacet:function(e){return this.disjunctiveFacets.indexOf(e)>-1},isHierarchicalFacet:function(e){return void 0!==this.getHierarchicalFacetByName(e)},isConjunctiveFacet:function(e){return this.facets.indexOf(e)>-1},isFacetRefined:function(e,t){return!!this.isConjunctiveFacet(e)&&f.isRefined(this.facetsRefinements,e,t)},isExcludeRefined:function(e,t){return!!this.isConjunctiveFacet(e)&&f.isRefined(this.facetsExcludes,e,t)},isDisjunctiveFacetRefined:function(e,t){return!!this.isDisjunctiveFacet(e)&&f.isRefined(this.disjunctiveFacetsRefinements,e,t)},isHierarchicalFacetRefined:function(e,t){if(!this.isHierarchicalFacet(e))return!1;var r=this.getHierarchicalRefinement(e);return t?-1!==r.indexOf(t):r.length>0},isNumericRefined:function(e,t,r){if(void 0===r&&void 0===t)return!!this.numericRefinements[e];var n=this.numericRefinements[e]&&void 0!==this.numericRefinements[e][t];if(void 0===r||!n)return n;var i,a,u=c(r),o=void 0!==(i=this.numericRefinements[e][t],a=u,s(i,(function(e){return l(e,a)})));return n&&o},isTagRefined:function(e){return-1!==this.tagRefinements.indexOf(e)},getRefinedDisjunctiveFacets:function(){var e=this,t=a(Object.keys(this.numericRefinements).filter((function(t){return Object.keys(e.numericRefinements[t]).length>0})),this.disjunctiveFacets);return Object.keys(this.disjunctiveFacetsRefinements).filter((function(t){return e.disjunctiveFacetsRefinements[t].length>0})).concat(t).concat(this.getRefinedHierarchicalFacets())},getRefinedHierarchicalFacets:function(){var e=this;return a(this.hierarchicalFacets.map((function(e){return e.name})),Object.keys(this.hierarchicalFacetsRefinements).filter((function(t){return e.hierarchicalFacetsRefinements[t].length>0})))},getUnrefinedDisjunctiveFacets:function(){var e=this.getRefinedDisjunctiveFacets();return this.disjunctiveFacets.filter((function(t){return-1===e.indexOf(t)}))},managedParameters:["index","facets","disjunctiveFacets","facetsRefinements","facetsExcludes","disjunctiveFacetsRefinements","numericRefinements","tagRefinements","hierarchicalFacets","hierarchicalFacetsRefinements"],getQueryParams:function(){var e=this.managedParameters,t={},r=this;return Object.keys(this).forEach((function(n){var i=r[n];-1===e.indexOf(n)&&void 0!==i&&(t[n]=i)})),t},setQueryParameter:function(e,t){if(this[e]===t)return this;var r={};return r[e]=t,this.setQueryParameters(r)},setQueryParameters:function(e){if(!e)return this;var t=m.validate(this,e);if(t)throw t;var r=this,n=m._parseNumbers(e),i=Object.keys(this).reduce((function(e,t){return e[t]=r[t],e}),{}),a=Object.keys(n).reduce((function(e,t){var r=void 0!==e[t],i=void 0!==n[t];return r&&!i?u(e,[t]):(i&&(e[t]=n[t]),e)}),i);return new this.constructor(a)},resetPage:function(){return void 0===this.page?this:this.setPage(0)},_getHierarchicalFacetSortBy:function(e){return e.sortBy||["isRefined:desc","name:asc"]},_getHierarchicalFacetSeparator:function(e){return e.separator||" > "},_getHierarchicalRootPath:function(e){return e.rootPath||null},_getHierarchicalShowParentLevel:function(e){return"boolean"!=typeof e.showParentLevel||e.showParentLevel},getHierarchicalFacetByName:function(e){return s(this.hierarchicalFacets,(function(t){return t.name===e}))},getHierarchicalFacetBreadcrumb:function(e){if(!this.isHierarchicalFacet(e))return[];var t=this.getHierarchicalRefinement(e)[0];if(!t)return[];var r=this._getHierarchicalFacetSeparator(this.getHierarchicalFacetByName(e));return t.split(r).map((function(e){return e.trim()}))},toString:function(){return JSON.stringify(this,null,2)}},e.exports=m},210:function(e,t,r){"use strict";e.exports=function(e){return function(t,r){var s=e.hierarchicalFacets[r],c=e.hierarchicalFacetsRefinements[s.name]&&e.hierarchicalFacetsRefinements[s.name][0]||"",u=e._getHierarchicalFacetSeparator(s),o=e._getHierarchicalRootPath(s),h=e._getHierarchicalShowParentLevel(s),f=a(e._getHierarchicalFacetSortBy(s)),l=t.every((function(e){return e.exhaustive})),m=function(e,t,r,a,s){return function(c,u,o){var h=c;if(o>0){var f=0;for(h=c;f<o;){var l=h&&Array.isArray(h.data)?h.data:[];h=i(l,(function(e){return e.isRefined})),f++}}if(h){var m=Object.keys(u.data).map((function(e){return[e,u.data[e]]})).filter((function(e){return function(e,t,r,n,i,a){if(i&&(0!==e.indexOf(i)||i===e))return!1;return!i&&-1===e.indexOf(n)||i&&e.split(n).length-i.split(n).length==1||-1===e.indexOf(n)&&-1===r.indexOf(n)||0===r.indexOf(e)||0===e.indexOf(t+n)&&(a||0===e.indexOf(r))}(e[0],h.path||r,s,t,r,a)}));h.data=n(m.map((function(e){var r=e[0];return function(e,t,r,n,i){var a=t.split(r);return{name:a[a.length-1].trim(),path:t,count:e,isRefined:n===t||0===n.indexOf(t+r),exhaustive:i,data:null}}(e[1],r,t,s,u.exhaustive)})),e[0],e[1])}return c}}(f,u,o,h,c),d=t;return o&&(d=t.slice(o.split(u).length)),d.reduce(m,{name:e.hierarchicalFacets[r].name,count:null,isRefined:!0,path:null,exhaustive:l,data:null})}};var n=r(2148),i=r(7888),a=r(2293)},3076:function(e,t,r){"use strict";var n=r(185),i=r(2344),a=r(2148),s=r(4587),c=r(7888),u=r(9725),o=r(2293),h=r(210);function f(e){var t={};return e.forEach((function(e,r){t[e]=r})),t}function l(e,t,r){t&&t[r]&&(e.stats=t[r])}function m(e,t){var r=t[0];this._rawResults=t;var a=this;Object.keys(r).forEach((function(e){a[e]=r[e]})),this.processingTimeMS=t.reduce((function(e,t){return void 0===t.processingTimeMS?e:e+t.processingTimeMS}),0),this.disjunctiveFacets=[],this.hierarchicalFacets=e.hierarchicalFacets.map((function(){return[]})),this.facets=[];var o=e.getRefinedDisjunctiveFacets(),m=f(e.facets),d=f(e.disjunctiveFacets),v=1,p=r.facets||{};Object.keys(p).forEach((function(t){var n,i,s=p[t],o=(n=e.hierarchicalFacets,i=t,c(n,(function(e){return(e.attributes||[]).indexOf(i)>-1})));if(o){var h=o.attributes.indexOf(t),f=u(e.hierarchicalFacets,(function(e){return e.name===o.name}));a.hierarchicalFacets[f][h]={attribute:t,data:s,exhaustive:r.exhaustiveFacetsCount}}else{var v,g=-1!==e.disjunctiveFacets.indexOf(t),y=-1!==e.facets.indexOf(t);g&&(v=d[t],a.disjunctiveFacets[v]={name:t,data:s,exhaustive:r.exhaustiveFacetsCount},l(a.disjunctiveFacets[v],r.facets_stats,t)),y&&(v=m[t],a.facets[v]={name:t,data:s,exhaustive:r.exhaustiveFacetsCount},l(a.facets[v],r.facets_stats,t))}})),this.hierarchicalFacets=s(this.hierarchicalFacets),o.forEach((function(s){var c=t[v],o=c&&c.facets?c.facets:{},h=e.getHierarchicalFacetByName(s);Object.keys(o).forEach((function(t){var s,f=o[t];if(h){s=u(e.hierarchicalFacets,(function(e){return e.name===h.name}));var m=u(a.hierarchicalFacets[s],(function(e){return e.attribute===t}));if(-1===m)return;a.hierarchicalFacets[s][m].data=n({},a.hierarchicalFacets[s][m].data,f)}else{s=d[t];var v=r.facets&&r.facets[t]||{};a.disjunctiveFacets[s]={name:t,data:i({},f,v),exhaustive:c.exhaustiveFacetsCount},l(a.disjunctiveFacets[s],c.facets_stats,t),e.disjunctiveFacetsRefinements[t]&&e.disjunctiveFacetsRefinements[t].forEach((function(r){!a.disjunctiveFacets[s].data[r]&&e.disjunctiveFacetsRefinements[t].indexOf(r)>-1&&(a.disjunctiveFacets[s].data[r]=0)}))}})),v++})),e.getRefinedHierarchicalFacets().forEach((function(r){var n=e.getHierarchicalFacetByName(r),s=e._getHierarchicalFacetSeparator(n),c=e.getHierarchicalRefinement(r);if(!(0===c.length||c[0].split(s).length<2)){var o=t[v],h=o&&o.facets?o.facets:{};Object.keys(h).forEach((function(t){var r=h[t],o=u(e.hierarchicalFacets,(function(e){return e.name===n.name})),f=u(a.hierarchicalFacets[o],(function(e){return e.attribute===t}));if(-1!==f){var l={};if(c.length>0){var m=c[0].split(s)[0];l[m]=a.hierarchicalFacets[o][f].data[m]}a.hierarchicalFacets[o][f].data=i(l,r,a.hierarchicalFacets[o][f].data)}})),v++}})),Object.keys(e.facetsExcludes).forEach((function(t){var n=e.facetsExcludes[t],i=m[t];a.facets[i]={name:t,data:r.facets[t],exhaustive:r.exhaustiveFacetsCount},n.forEach((function(e){a.facets[i]=a.facets[i]||{name:t},a.facets[i].data=a.facets[i].data||{},a.facets[i].data[e]=0}))})),this.hierarchicalFacets=this.hierarchicalFacets.map(h(e)),this.facets=s(this.facets),this.disjunctiveFacets=s(this.disjunctiveFacets),this._state=e}function d(e,t,r,n){if(n=n||0,Array.isArray(t))return e(t,r[n]);if(!t.data||0===t.data.length)return t;var a=t.data.map((function(t){return d(e,t,r,n+1)})),s=e(a,r[n]);return i({data:s},t)}function v(e,t){var r=c(e,(function(e){return e.name===t}));return r&&r.stats}function p(e,t,r,n,i){var a=c(i,(function(e){return e.name===r})),s=a&&a.data&&a.data[n]?a.data[n]:0,u=a&&a.exhaustive||!1;return{type:t,attributeName:r,name:n,count:s,exhaustive:u}}m.prototype.getFacetByName=function(e){function t(t){return t.name===e}return c(this.facets,t)||c(this.disjunctiveFacets,t)||c(this.hierarchicalFacets,t)},m.DEFAULT_SORT=["isRefined:desc","count:desc","name:asc"],m.prototype.getFacetValues=function(e,t){var r=function(e,t){function r(e){return e.name===t}if(e._state.isConjunctiveFacet(t)){var n=c(e.facets,r);return n?Object.keys(n.data).map((function(r){return{name:r,count:n.data[r],isRefined:e._state.isFacetRefined(t,r),isExcluded:e._state.isExcludeRefined(t,r)}})):[]}if(e._state.isDisjunctiveFacet(t)){var i=c(e.disjunctiveFacets,r);return i?Object.keys(i.data).map((function(r){return{name:r,count:i.data[r],isRefined:e._state.isDisjunctiveFacetRefined(t,r)}})):[]}if(e._state.isHierarchicalFacet(t))return c(e.hierarchicalFacets,r)}(this,e);if(r){var n,s=i({},t,{sortBy:m.DEFAULT_SORT,facetOrdering:!(t&&t.sortBy)}),u=this;if(Array.isArray(r))n=[e];else n=u._state.getHierarchicalFacetByName(r.name).attributes;return d((function(e,t){if(s.facetOrdering){var r=function(e,t){return e.renderingContent&&e.renderingContent.facetOrdering&&e.renderingContent.facetOrdering.values&&e.renderingContent.facetOrdering.values[t]}(u,t);if(Boolean(r))return function(e,t){var r=[],n=[],i=(t.order||[]).reduce((function(e,t,r){return e[t]=r,e}),{});e.forEach((function(e){var t=e.path||e.name;void 0!==i[t]?r[i[t]]=e:n.push(e)}));var s,c=t.sortRemainingBy;return"hidden"===c?r:(s="alpha"===c?[["path","name"],["asc","asc"]]:[["count"],["desc"]],r.concat(a(n,s[0],s[1])))}(e,r)}if(Array.isArray(s.sortBy)){var n=o(s.sortBy,m.DEFAULT_SORT);return a(e,n[0],n[1])}if("function"==typeof s.sortBy)return function(e,t){return t.sort(e)}(s.sortBy,e);throw new Error("options.sortBy is optional but if defined it must be either an array of string (predicates) or a sorting 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e.name===t})),o=s.reduce((function(e,t){var r=e&&c(e.data,(function(e){return e.name===t}));return void 0!==r?r:e}),u),h=o&&o.count||0,f=o&&o.exhaustive||!1,l=o&&o.path||"";return{type:"hierarchical",attributeName:t,name:l,count:h,exhaustive:f}}(e,n,i,t.hierarchicalFacets))}))})),Object.keys(e.numericRefinements).forEach((function(t){var n=e.numericRefinements[t];Object.keys(n).forEach((function(e){n[e].forEach((function(n){r.push({type:"numeric",attributeName:t,name:n,numericValue:n,operator:e})}))}))})),e.tagRefinements.forEach((function(e){r.push({type:"tag",attributeName:"_tags",name:e})})),r},e.exports=m},9374:function(e,t,r){"use strict";var n=r(7775),i=r(3076),a=r(8078),s=r(6394),c=r(696),u=r(4853),o=r(116),h=r(9803),f=r(185),l=r(4336);function m(e,t,r){"function"==typeof e.addAlgoliaAgent&&e.addAlgoliaAgent("JS Helper ("+l+")"),this.setClient(e);var i=r||{};i.index=t,this.state=n.make(i),this.lastResults=null,this._queryId=0,this._lastQueryIdReceived=-1,this.derivedHelpers=[],this._currentNbQueries=0}function d(e){if(e<0)throw new Error("Page requested below 0.");return this._change({state:this.state.setPage(e),isPageReset:!1}),this}function v(){return this.state.page}u(m,c.EventEmitter),m.prototype.search=function(){return this._search({onlyWithDerivedHelpers:!1}),this},m.prototype.searchOnlyWithDerivedHelpers=function(){return this._search({onlyWithDerivedHelpers:!0}),this},m.prototype.getQuery=function(){var e=this.state;return s._getHitsSearchParams(e)},m.prototype.searchOnce=function(e,t){var r=e?this.state.setQueryParameters(e):this.state,n=s._getQueries(r.index,r),a=this;if(this._currentNbQueries++,this.emit("searchOnce",{state:r}),!t)return this.client.search(n).then((function(e){return a._currentNbQueries--,0===a._currentNbQueries&&a.emit("searchQueueEmpty"),{content:new 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all-in-one distribution image"),(0,o.kt)("li",{parentName:"ul"},"Pinot-Presto: Presto image with Presto-Pinot Connector built-in."),(0,o.kt)("li",{parentName:"ul"},"Pinot-Superset: Superset image with Pinot connector built-in.")),(0,o.kt)("h2",{id:"pinot"},"Pinot"),(0,o.kt)("p",null,"This is a docker image of ",(0,o.kt)("a",{parentName:"p",href:"https://github.com/apache/pinot"},"Apache Pinot")),(0,o.kt)("h3",{id:"how-to-build-a-docker-image"},"How to build a docker image"),(0,o.kt)("p",null,"There is a docker build script which will build a given Git repo/branch and tag the image."),(0,o.kt)("p",null,"Usage:"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build.sh [Docker Tag] [Git Branch] [Pinot Git URL]\n")),(0,o.kt)("p",null,"This script will check out Pinot Repo ",(0,o.kt)("inlineCode",{parentName:"p"},"[Pinot Git URL]")," on branch ",(0,o.kt)("inlineCode",{parentName:"p"},"[Git Branch]")," and build the docker image for that. ",(0,o.kt)("br",null),"\nThe docker image is tagged as ",(0,o.kt)("inlineCode",{parentName:"p"},"[Docker Tag]"),". ",(0,o.kt)("br",null),"\nDocker Tag: Name and tag your docker image. Default is ",(0,o.kt)("inlineCode",{parentName:"p"},"pinot:latest"),". ",(0,o.kt)("br",null),"\nGit Branch: The Pinot branch to build. Default is master. ",(0,o.kt)("br",null),"\nPinot Git URL: The Pinot Git Repo to build, users can set it to their own fork. ",(0,o.kt)("br",null),"\nPlease note that, the URL is ",(0,o.kt)("inlineCode",{parentName:"p"},"https://")," based, not ",(0,o.kt)("inlineCode",{parentName:"p"},"git://"),". ",(0,o.kt)("br",null),"\nDefault is the ",(0,o.kt)("a",{parentName:"p",href:"https://github.com/apache/pinot.git"},"Apache Repo: https://github.com/apache/pinot.git"),". ",(0,o.kt)("br",null)),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"Example of building and tagging a snapshot on your own fork:")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build.sh pinot_fork:snapshot-5.2 snapshot-5.2 https://github.com/your_own_fork/pinot.git\n")),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"Example of building a release version:")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build.sh pinot:release-0.1.0 release-0.1.0 https://github.com/apache/pinot.git\n")),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"Example of building current master branch as a snapshot:")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build.sh apachepinot/pinot:0.3.0-SNAPSHOT master\n")),(0,o.kt)("h2",{id:"how-to-publish-a-docker-image"},"How to publish a docker image"),(0,o.kt)("p",null,"Script ",(0,o.kt)("inlineCode",{parentName:"p"},"docker-push.sh")," publishes a given docker image to your docker registry.\nIn order to push to your own repo, the image needs to be explicitly tagged with the repo name."),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"Example of publishing an image to ",(0,o.kt)("inlineCode",{parentName:"li"},"[apachepinot/pinot](https://hub.docker.com/u/apachepinot/repository/docker/apachepinot/pinot)")," dockerHub repo.")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-push.sh apachepinot/pinot:latest\n")),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"You can also tag a built image, then push it.")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"docker tag pinot:release-0.1.0 apachepinot/pinot:release-0.1.0\ndocker push apachepinot/pinot:release-0.1.0\n")),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("p",{parentName:"li"},"Script docker-build-and-push.sh builds and publishes this docker image to your docker registry after build.")),(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("p",{parentName:"li"},"Example of building and publishing an image to ",(0,o.kt)("inlineCode",{parentName:"p"},"[apachepinot/pinot](https://hub.docker.com/u/apachepinot/repository/docker/apachepinot/pinot)")," dockerHub repo."))),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build-and-push.sh apachepinot/pinot:latest master https://github.com/apache/pinot.git\n")),(0,o.kt)("h2",{id:"kubernetes-examples"},"Kubernetes Examples"),(0,o.kt)("p",null,"Please refer to ",(0,o.kt)("a",{parentName:"p",href:"/docs/administration/installation/cloud/on-premise"},"Kubernetes Quickstart")," for deployment examples."),(0,o.kt)("p",null,(0,o.kt)("a",{parentName:"p",href:"/docs/administration/installation/cloud/on-premise"},"Kubernetes Quickstart")),(0,o.kt)("h2",{id:"pinot-presto"},"Pinot Presto"),(0,o.kt)("p",null,"Docker image for Presto with Pinot integration.\nThis docker build project is specialized for Pinot."),(0,o.kt)("h3",{id:"how-to-build"},"How to build"),(0,o.kt)("p",null,"Usage:"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build.sh [Docker Tag] [Git Branch] [Presto Git URL]\n")),(0,o.kt)("p",null,"This script will check out Pinot Repo ",(0,o.kt)("inlineCode",{parentName:"p"},"[Pinot Git URL]")," on branch ",(0,o.kt)("inlineCode",{parentName:"p"},"[Git Branch]")," and build the docker image for that. ",(0,o.kt)("br",null),"\nThe docker image is tagged as ",(0,o.kt)("inlineCode",{parentName:"p"},"[Docker Tag]"),". ",(0,o.kt)("br",null),"\nDocker Tag: Name and tag your docker image. Default is ",(0,o.kt)("inlineCode",{parentName:"p"},"pinot:latest"),". ",(0,o.kt)("br",null),"\nGit Branch: The Pinot branch to build. Default is master. ",(0,o.kt)("br",null),"\nPinot Git URL: The Pinot Git Repo to build, users can set it to their own fork. ",(0,o.kt)("br",null),"\nPlease note that, the URL is ",(0,o.kt)("inlineCode",{parentName:"p"},"https://")," based, not ",(0,o.kt)("inlineCode",{parentName:"p"},"git://"),". ",(0,o.kt)("br",null),"\nDefault is the ",(0,o.kt)("a",{parentName:"p",href:"https://github.com/apache/pinot.git"},"Apache Repo: https://github.com/apache/pinot.git"),". ",(0,o.kt)("br",null)),(0,o.kt)("h3",{id:"how-to-push"},"How to push"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"docker push apachepinot/pinot-presto:latest\n")),(0,o.kt)("h3",{id:"configuration"},"Configuration"),(0,o.kt)("p",null,"Follow the instructions provided by Presto for writing your own configuration files under etc directory."),(0,o.kt)("h3",{id:"volumes"},"Volumes"),(0,o.kt)("p",null,"The image defines two data volumes: one for mounting configuration into the container, and one for data.\nThe configuration volume is located alternatively at ",(0,o.kt)("inlineCode",{parentName:"p"},"/home/presto/etc"),", which contains all the configuration and plugins.\nThe data volume is located at ",(0,o.kt)("inlineCode",{parentName:"p"},"/home/presto/data"),"."),(0,o.kt)("h3",{id:"kubernetes-examples-1"},"Kubernetes Examples"),(0,o.kt)("p",null,"Please refer to presto-coordinator.yaml as k8s deployment example."),(0,o.kt)("h2",{id:"pinot-superset"},"Pinot Superset"),(0,o.kt)("p",null,"Docker image for Superset with Pinot integration.\nThis docker build project is based on Project docker-superset and specialized for Pinot."),(0,o.kt)("h3",{id:"how-to-build-1"},"How to build"),(0,o.kt)("p",null,"Please modify file ",(0,o.kt)("inlineCode",{parentName:"p"},"Makefile")," to change image and ",(0,o.kt)("inlineCode",{parentName:"p"},"superset_version")," accordingly.\nBelow command will build docker image and tag it as ",(0,o.kt)("inlineCode",{parentName:"p"},"superset_version")," and ",(0,o.kt)("inlineCode",{parentName:"p"},"latest"),"."),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"make latest\n")),(0,o.kt)("p",null,"You can also build directly with ",(0,o.kt)("inlineCode",{parentName:"p"},"docker build")," command by setting arguments:"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"docker build \\\n --build-arg NODE_VERSION=latest \\\n --build-arg PYTHON_VERSION=3.6 \\\n --build-arg SUPERSET_VERSION=0.34.1 \\\n --tag apachepinot/pinot-superset:0.34.1 \\\n --target build .\n")),(0,o.kt)("p",null,"How to push"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"make push\n")),(0,o.kt)("h3",{id:"configuration-1"},"Configuration"),(0,o.kt)("p",null,"Follow the ",(0,o.kt)("a",{parentName:"p",href:"https://superset.apache.org/installation.html#configuration"},"instructions")," provided by Apache Superset for writing your own superset_config.py."),(0,o.kt)("p",null,"Place this file in a local directory and mount this directory to /etc/superset inside the container. This location\nis included in the image's ",(0,o.kt)("inlineCode",{parentName:"p"},"PYTHONPATH"),". Mounting this file to a different location is possible, but it will need to be in the PYTHONPATH."),(0,o.kt)("h3",{id:"volumes-1"},"Volumes"),(0,o.kt)("p",null,"The image defines two data volumes: one for mounting configuration into the container, and one for data (logs, SQLite DBs, &c)."),(0,o.kt)("p",null,"The configuration volume is located alternatively at ",(0,o.kt)("inlineCode",{parentName:"p"},"/etc/superset")," or ",(0,o.kt)("inlineCode",{parentName:"p"},"/home/superset"),"; either is acceptable. Both of these directories are included in the PYTHONPATH of the image. Mount any configuration (specifically the superset_config.py file) here to have it read by the app on startup."),(0,o.kt)("p",null,"The data volume is located at ",(0,o.kt)("inlineCode",{parentName:"p"},"/var/lib/superset")," and it is where you would mount your SQLite file (if you are using that as your backend), or a volume to collect any logs that are routed there. This location is used as the value of the ",(0,o.kt)("inlineCode",{parentName:"p"},"SUPERSET_HOME")," environmental variable."),(0,o.kt)("h3",{id:"kubernetes-examples-2"},"Kubernetes Examples"),(0,o.kt)("p",null,"Please refer to superset.yaml as k8s deployment example."))}d.isMDXComponent=!0}}]);
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-"use strict";(self.webpackChunkwebsite=self.webpackChunkwebsite||[]).push([[1770],{4137:function(e,t,n){n.d(t,{Zo:function(){return s},kt:function(){return h}});var a=n(7294);function i(e,t,n){return t in e?Object.defineProperty(e,t,{value:n,enumerable:!0,configurable:!0,writable:!0}):e[t]=n,e}function o(e,t){var n=Object.keys(e);if(Object.getOwnPropertySymbols){var a=Object.getOwnPropertySymbols(e);t&&(a=a.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),n.push.apply(n,a)}return n}function r(e){for(var t=1;t<arguments.length;t++){var n=null!=arguments[t]?arguments[t]:{};t%2?o(Object(n),!0).forEach((function(t){i(e,t,n[t])})):Object.getOwnPropertyDescriptors?Object.defineProperties(e,Object.getOwnPropertyDescriptors(n)):o(Object(n)).forEach((function(t){Object.defineProperty(e,t,Object.getOwnPropertyDescriptor(n,t))}))}return e}function l(e,t){if(null==e)return{};var n,a,i=function(e,t){if(null==e)return{};var n,a,i={},o=Object.keys(e);for(a=0;a<o.length;a++)n=o[a],t.indexOf(n)>=0||(i[n]=e[n]);return i}(e,t);if(Object.getOwnPropertySymbols){var o=Object.getOwnPropertySymbols(e);for(a=0;a<o.length;a++)n=o[a],t.indexOf(n)>=0||Object.prototype.propertyIsEnumerable.call(e,n)&&(i[n]=e[n])}return i}var p=a.createContext({}),u=function(e){var t=a.useContext(p),n=t;return e&&(n="function"==typeof e?e(t):r(r({},t),e)),n},s=function(e){var t=u(e.components);return a.createElement(p.Provider,{value:t},e.children)},c={inlineCode:"code",wrapper:function(e){var t=e.children;return a.createElement(a.Fragment,{},t)}},d=a.forwardRef((function(e,t){var n=e.components,i=e.mdxType,o=e.originalType,p=e.parentName,s=l(e,["components","mdxType","originalType","parentName"]),d=u(n),h=i,m=d["".concat(p,".").concat(h)]||d[h]||c[h]||o;return n?a.createElement(m,r(r({ref:t},s),{},{components:n})):a.createElement(m,r({ref:t},s))}));function h(e,t){var n=arguments,i=t&&t.mdxType;if("string"==typeof e||i){var o=n.length,r=new Array(o);r[0]=d;var l={};for(var p in t)hasOwnProperty.call(t,p)&&(l[p]=t[p]);l.originalType=e,l.mdxType="string"==typeof e?e:i,r[1]=l;for(var u=2;u<o;u++)r[u]=n[u];return a.createElement.apply(null,r)}return a.createElement.apply(null,n)}d.displayName="MDXCreateElement"},4963:function(e,t,n){n.r(t),n.d(t,{frontMatter:function(){return l},contentTitle:function(){return p},metadata:function(){return u},toc:function(){return s},default:function(){return d}});var a=n(7462),i=n(3366),o=(n(7294),n(4137)),r=["components"],l={title:"Build Docker Images",sidebar_label:"build-docker",description:"Build Docker Images",draft:!0},p=void 0,u={unversionedId:"misc/build-docker",id:"misc/build-docker",isDocsHomePage:!1,title:"Build Docker Images",description:"Build Docker Images",source:"@site/docs/misc/build-docker.md",sourceDirName:"misc",slug:"/misc/build-docker",permalink:"/docs/misc/build-docker",editUrl:"https://github.com/apache/pinot/edit/master/website/docs/misc/build-docker.md",version:"current",frontMatter:{title:"Build Docker Images",sidebar_label:"build-docker",description:"Build Docker Images",draft:!0}},s=[{value:"Pinot",id:"pinot",children:[{value:"How to build a docker image",id:"how-to-build-a-docker-image",children:[]}]},{value:"How to publish a docker image",id:"how-to-publish-a-docker-image",children:[]},{value:"Kubernetes Examples",id:"kubernetes-examples",children:[]},{value:"Pinot Presto",id:"pinot-presto",children:[{value:"How to build",id:"how-to-build",children:[]},{value:"How to push",id:"how-to-push",children:[]},{value:"Configuration",id:"configuration",children:[]},{value:"Volumes",id:"volumes",children:[]},{value:"Kubernetes Examples",id:"kubernetes-examples-1",children:[]}]},{value:"Pinot Superset",id:"pinot-superset",children:[{value:"How to build",id:"how-to-build-1",children:[]},{value:"Configuration",id:"configuration-1",children:[]},{value:"Volumes",id:"volumes-1",children:[]},{value:"Kubernetes Examples",id:"kubernetes-examples-2",children:[]}]}],c={toc:s};function d(e){var t=e.components,n=(0,i.Z)(e,r);return(0,o.kt)("wrapper",(0,a.Z)({},c,n,{components:t,mdxType:"MDXLayout"}),(0,o.kt)("p",null,"The scripts to build Pinot related docker images is located at ",(0,o.kt)("a",{parentName:"p",href:"https://github.com/apache/pinot/tree/master/docker/images"},"here")),(0,o.kt)("p",null,"You can access those scripts by running below command to checkout Pinot repo:"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"git clone git@github.com:apache/pinot.git pinot\ncd pinot/docker/images\n")),(0,o.kt)("p",null,"You can find current supported 3 images in this directory:"),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"Pinot: Pinot all-in-one distribution image"),(0,o.kt)("li",{parentName:"ul"},"Pinot-Presto: Presto image with Presto-Pinot Connector built-in."),(0,o.kt)("li",{parentName:"ul"},"Pinot-Superset: Superset image with Pinot connector built-in.")),(0,o.kt)("h2",{id:"pinot"},"Pinot"),(0,o.kt)("p",null,"This is a docker image of ",(0,o.kt)("a",{parentName:"p",href:"https://github.com/apache/pinot"},"Apache Pinot")),(0,o.kt)("h3",{id:"how-to-build-a-docker-image"},"How to build a docker image"),(0,o.kt)("p",null,"There is a docker build script which will build a given Git repo/branch and tag the image."),(0,o.kt)("p",null,"Usage:"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build.sh [Docker Tag] [Git Branch] [Pinot Git URL]\n")),(0,o.kt)("p",null,"This script will check out Pinot Repo ",(0,o.kt)("inlineCode",{parentName:"p"},"[Pinot Git URL]")," on branch ",(0,o.kt)("inlineCode",{parentName:"p"},"[Git Branch]")," and build the docker image for that. ",(0,o.kt)("br",null),"\nThe docker image is tagged as ",(0,o.kt)("inlineCode",{parentName:"p"},"[Docker Tag]"),". ",(0,o.kt)("br",null),"\nDocker Tag: Name and tag your docker image. Default is ",(0,o.kt)("inlineCode",{parentName:"p"},"pinot:latest"),". ",(0,o.kt)("br",null),"\nGit Branch: The Pinot branch to build. Default is master. ",(0,o.kt)("br",null),"\nPinot Git URL: The Pinot Git Repo to build, users can set it to their own fork. ",(0,o.kt)("br",null),"\nPlease note that, the URL is ",(0,o.kt)("inlineCode",{parentName:"p"},"https://")," based, not ",(0,o.kt)("inlineCode",{parentName:"p"},"git://"),". ",(0,o.kt)("br",null),"\nDefault is the ",(0,o.kt)("a",{parentName:"p",href:"https://github.com/apache/pinot.git"},"Apache Repo: https://github.com/apache/pinot.git"),". ",(0,o.kt)("br",null)),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"Example of building and tagging a snapshot on your own fork:")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build.sh pinot_fork:snapshot-5.2 snapshot-5.2 https://github.com/your_own_fork/pinot.git\n")),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"Example of building a release version:")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build.sh pinot:release-0.1.0 release-0.1.0 https://github.com/apache/pinot.git\n")),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"Example of building current master branch as a snapshot:")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build.sh apachepinot/pinot:0.3.0-SNAPSHOT master\n")),(0,o.kt)("h2",{id:"how-to-publish-a-docker-image"},"How to publish a docker image"),(0,o.kt)("p",null,"Script ",(0,o.kt)("inlineCode",{parentName:"p"},"docker-push.sh")," publishes a given docker image to your docker registry.\nIn order to push to your own repo, the image needs to be explicitly tagged with the repo name."),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"Example of publishing an image to ",(0,o.kt)("inlineCode",{parentName:"li"},"[apachepinot/pinot](https://hub.docker.com/u/apachepinot/repository/docker/apachepinot/pinot)")," dockerHub repo.")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-push.sh apachepinot/pinot:latest\n")),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"You can also tag a built image, then push it.")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"docker tag pinot:release-0.1.0 apachepinot/pinot:release-0.1.0\ndocker push apachepinot/pinot:release-0.1.0\n")),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("p",{parentName:"li"},"Script docker-build-and-push.sh builds and publishes this docker image to your docker registry after build.")),(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("p",{parentName:"li"},"Example of building and publishing an image to ",(0,o.kt)("inlineCode",{parentName:"p"},"[apachepinot/pinot](https://hub.docker.com/u/apachepinot/repository/docker/apachepinot/pinot)")," dockerHub repo."))),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build-and-push.sh apachepinot/pinot:latest master https://github.com/apache/pinot.git\n")),(0,o.kt)("h2",{id:"kubernetes-examples"},"Kubernetes Examples"),(0,o.kt)("p",null,"Please refer to ",(0,o.kt)("a",{parentName:"p",href:"/docs/administration/installation/cloud/on-premise"},"Kubernetes Quickstart")," for deployment examples."),(0,o.kt)("p",null,(0,o.kt)("a",{parentName:"p",href:"/docs/administration/installation/cloud/on-premise"},"Kubernetes Quickstart")),(0,o.kt)("h2",{id:"pinot-presto"},"Pinot Presto"),(0,o.kt)("p",null,"Docker image for Presto with Pinot integration.\nThis docker build project is specialized for Pinot."),(0,o.kt)("h3",{id:"how-to-build"},"How to build"),(0,o.kt)("p",null,"Usage:"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-bash"},"./docker-build.sh [Docker Tag] [Git Branch] [Presto Git URL]\n")),(0,o.kt)("p",null,"This script will check out Pinot Repo ",(0,o.kt)("inlineCode",{parentName:"p"},"[Pinot Git URL]")," on branch ",(0,o.kt)("inlineCode",{parentName:"p"},"[Git Branch]")," and build the docker image for that. 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rename from content/assets/js/89bc24d5.6103135f.js
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"})),I.createElement("image",{x:370,y:82,width:51,height:83,xlinkHref:"data:image/png;base64,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"}))),I.createElement("image",{x:342,y:60,width:51,height:83,xlinkHref:"data:image/png;base64,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Pinot."))),B.createElement("div",{className:"slide-img",style:{borderRadius:5},"data-src":"https://miro.medium.com/max/3200/0*2Vorw0A5VEy_U2uz"},B.createElement("div",{className:"slide-caption"},B.createElement("h1",null,B.createElement("a",{href:"https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7"},"Change Data Analysis with Debezium and Apache Pinot")),B.createElement("p",null,"In this blog post, we\u2019re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot."))),B.createElement("div",{className:"slide-img",style:{borderRadius:5},"data-src":"https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png"},B.createElement("div",{className:"slide-caption"},B.createElement("h1",null,B.createElement("a",{href:"https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38"},"Deploying Apache Pinot at a Large Retail Chain")),B.createElement("p",null,"Our real-time analytics journey to production"))))))}function w(){return B.createElement("section",{className:"topologies"},B.createElement("div",{className:"container"},B.createElement(s,{id:"uber"},B.createElement("a",{href:"https://eng.uber.com/?s=pinot"},"Uber Engineering 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merchants."))),B.createElement("div",{className:"slide-img",style:{borderRadius:5},"data-src":"https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png"},B.createElement("div",{className:"slide-caption"},B.createElement("h1",null,B.createElement("a",{href:"https://eng.uber.com/operating-apache-pinot/"},"Operating Apache Pinot @ Uber Scale")),B.createElement("p",null,"Present details of this platform and how it fits in Uber\u2019s ecosystem. 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logic."))),B.createElement("div",{className:"slide-img",style:{borderRadius:5},"data-src":"https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png"},B.createElement("div",{className:"slide-caption"},B.createElement("h1",null,B.createElement("a",{href:"https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights"},"Building LinkedIn Talent Insights to democratize data-driven decision making")),B.createElement("p",null,"LinkedIn is a mission-driven organization, and we take our mission of \u201cconnecting the world's professionals to make them more productive and successful\u201d very seriously."))),B.createElement("div",{className:"slide-img",style:{borderRadius:5},"data-src":"https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png"},B.createElement("div",{className:"slide-caption"},B.createElement("h1",null,B.createElement("a",{href:"https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts"},"Monitoring business performance data with ThirdEye smart alerts")),B.createElement("p",null,"Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics\u2014such as new free trial signups\u2014for the timely detection of outliers in business performance data."))),B.createElement("div",{className:"slide-img",style:{borderRadius:5},"data-src":"https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png"},B.createElement("div",{className:"slide-caption"},B.createElement("h1",null,B.createElement("a",{href:"https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye"},"Analyzing anomalies with ThirdEye")),B.createElement("p",null,"Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data and help our engineers understand why these anomalies happened through a dimension 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efficiently."))),B.createElement("div",{className:"slide-img",style:{borderRadius:5},"data-src":"https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/smartalerts2.png"},B.createElement("div",{className:"slide-caption"},B.createElement("h1",null,B.createElement("a",{href:"https://engineering.linkedin.com/blog/2019/06/smart-alerts-in-thirdeye--linkedins-real-time-monitoring-platfor"},"Smart alerts in ThirdEye, LinkedIn\u2019s real-time monitoring platform")),B.createElement("p",null,"Focus on smart alerts with LinkedIn\u2019s comprehensive platform for real-time monitoring and root cause 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"})),I.createElement("image",{x:370,y:82,width:51,height:83,xlinkHref:"data:image/png;base64,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NiK7xLqTLO2y47Fm+w0Sc10hT2kBUWwYqEjJDGmxb0mf5Ju3oHebRJWkrihvLbWnDTWyGcP2cVMbaMlBShdx9rxVaRBIHJJPt9gWSeUfT/kTtvyTVwljGDVaHvEnkGCgJmRrfR9AiScfUxtoW4pCWQ1s2/FJ0Sxs8HQNJoV5Rutj8sOyQIrTp337nnUSplFS+7dL9/NChHr/o7Z4r+lu7s0jHQEVRtfQ9RPySZz8HLDRT/9sHH3SdF5yFiLaXZLHqGMhSRihaLBpbitA2sDWiOGFu0PKWIAQyhMKJI8dAcajU+B4xSqUIp5kffvSRVcu3oK4sKyUlcgMScHUMFLRAQz67lDa7FB1RumE2E8s4ZkkJwmYpjhwDxaHi7sUisGfvXjnujM0x302ieEtJ45LOHWvLQNicOHIIhBGQmn3CeUS/15aBohVx17IISB5W6ir5P1S07mtKP88kOQYyibaBvKRUeKoY3fPC9Y06TJVawiWVxTFQEjI1vZ+0Vq9pdawpdtLZmmMga5pIT0GkZgrTI3sRNKrYFzsGUi3F1N8UkupEkupBurDHyFJqCZs0gNSWgXR2+na6Troat+7pVOFeKi9mg5Tpv6QmRlx5astA+AzTRSNGjvSwtdeVnkunGgSkZp92tZHT+2iXa8Hf8NTDKDNUqZfrHBFxVjJx0iQPJxzsIbBQ5RPRbdNMvQtC33oNX21FfLyVyTPPuywzpZgoaWlsNQPh6BungHithGmSJCF5QG73LOkP4O87hUzyJqIBZwt41cR3gu1+4XzBA+bpM2bgJLEdhJX+NmrUKLE+guOZOLKSgZhp6Lw2bFxhphZDKbdao1QgJqK7obRoq/eem0IayXSesePGeTg6lPD7Ftc589z7wbJlfpLGdJ504p5FgJDkN8MaBlr+yCM+HXSEcqZoM+Fkgr/nn3/exxLSNt9x0uYGIy1tH+ygpJZvLOdxURxHlSsHYkE5YeJEo25b44Aocw/n6TbtlWBuqc6E08m/7dljlVkDe7O77r7bk/JE1M7BYqUz0KpVq0TNj8swRZ53WdqsWbPGt4WRrqrRUioeELMv9bWJ2JtJLvevXbuWWN1KGIh4NVRYWiiQWGuhH8aoMC1I8k4pf2V/eOONymb3/koQIkk4rF/Y3e3bYFy39IEHfI4hJPtSOwaSRTrSikjVkGox1UpWOJKtsUvqxN/tKr4Ms6uxjEMZIYBJcwYYerzQVwa/O2bOLPSu7pfmzJ0r6jMdAUK7faWxUZIOhX+tJjJOUqdA9HlOhUQxIbHDbzhLK50+w5PqxX021keVhWqVYv2fPP54Kzhbu3KW/Y09X7vwneIMFESg62R1mXab0LINzPsE0WLWMT04MUB8prz07HjrLfF+FMUJb6HTpk2L3tZ+nRbuUbTixECV2sxqR0o4QTrbqZMnU+PN5CkGIzBi/+DgN8+7up7FwfznBw96f92xQ7QvhcvLkcfUqVONDBj4nGs3y4pVuurAtmHAbfquQ1LHrD5m7FjRtX8ezBgcjqnI6+06Wp702j3LHg9hjYnZlgPztHCeIgyEoKDKUbFdA9jwGwGKN2/enBt7Rl4YR1pIUBSj44qJTqgodbv37Mldt7Q871+yxEdcbTJCHQ7003yAa6+oqahoaYDb/juKqhs2bMiMv8lwjWWwY793WvmPY7kajcZdJF0OScdNmOBNUoftJgdllqbr1q1LbZ/UB/JU2jFPHrQ8j6XPr15+uW0bsFxDU7xuxPKH2ehL5ejjvZ0729YxWjf07Zhl0W1DXC6lVRHNN3ydZfbh+VwVC2cQ/m46GnQ47yZ8f/HFF/u0Q5MwZd/HjBScp+C/LWwegB8HPH/2U2doRISbqqRrKBNXRVkGtqBsWjQRpk+fHqTnPgsggBpQmIkkddkKFK/0K5xPhdV/WtrNiokCBygml2ZZKnNCMXtW6jPyZX2R51AEnTl7dp5X3LMOAasRyLs3LaXKY4s6h9Ut4gpXGwSYGfMIdqhYYQbCsMyELL426LuC1h6BKwk2P+0qVoiBEKnaehbRrrLuN4dAEgKIrYuczeUWInCYVxf1HKZkxKj4M0ADvJP18ZI6jrvvtdwBZznzicMqNwNNnjLFiBpFXGGT7nF4d1ydOXCAl8den9Pt29UBHeYHbjmahG7z719QcV+LUi4p3MqVK1vKi0Uz0/neyRMnvMOff+59pU709+3fn6seceVYuGBBa1k6d948a1Vl4srt7pVDoKymfOYZiIO94QlxIstVIfvbVBbt2EuXLmlREwnnHFhXXrx0yR+iDMbGjx/vORF9GKHmfcfS9JWNG0sNvpkZiNPhqpY5KF8eP3q0ZZwWdHSp5gzPZvedOdMyUps1a1ZldZeq50Flx/OXbdu6muKXIi9OZWeeIL9M3FeVIiNCgAMHDrTUQKQZJwAk7nPxokX+NKVtMUHtlepOcQZizz77rN9JApY0K9M8bZyJgapQEg30p955991MZcxT6aLPPvzQQy3FzjqK8C+qjfJvXn01EctOYSKW/1u2bEnEIW/fSE3ItFWpDbb27UC871//1Z83f37LS2m752z5Da1omGfrm2+mtjWH43UcHLJircOYMZpXKqgoOkZfkrqGeQ4p8+Bt27enlkuqDFnTrWpZm7V8bJBhnLwOTZC0Iiyqar+btX55nqNfnVFHHBKuxtp2VJOdBBXyg2q/Y9K2Pk8jxD1r0rw4Lv+4e+CIY8V2y7W498L38PAzTkkhiVpRd8qrHJq3vm0ZyNTswwjx6f793ltvv922PHkrZ+L5Hz/2mI/Iu+oRG4HLdcU869ev14Yh+yJTbrJ0txV96oqS3pYZSLKUKRFsU5aQNPzfP/20VjNPFFhmatSbqmAi8IOOKn8Eb2bY50TLnnZNPxin7HmwCq2ifmnli/4OHhjrmfJZl8hAphyDfPb3v9dizxNtqOi1yeVuOG8cefxx69bEdgw/W+a7CSeGZcoXvGsKjyC/WOBNGcqhjiOxsQsqZ/ITO/5/WbjQWHiWop59ymLCvi9sXVo2PV3vH1FeUiVm4LTyxWoiEKdHmoKlm3Q+ptJHiVX5KzMiwUJQUET1XgcWQRgX/JxPnDy5EocfQT2QNDIIm/BHF+QZ/YxloNEGGGj/vn3eRx9/HDsDRgtZl2tc3Kq9kN8J2t3hcyUEKcxKJrznwDSc55hYtmbpd30YCJ/D0pvF88rheh0lblkAPajOsYYrjzKSXmVMdNQsdQ2eCc6aWPoPUKLvW5VLKl0uhzF0IxIgHn2qnGmCukY/+zAQwXwlieXHJ0pk3VRiKTdu7Fh/1pw5YiOy9ABXtG1QTg2/C0NxltRfuazKQ98oSRpL/PAsl+d9k8/2qZnkyAkoRLr+2wcf9ALaZIVN5IVbJMJWSlruEpEhzW+zibq2yyPKUO2eretvvXwisDEkho8UcSqM2Lrp9PG+fV1sbpltpUhyoJMqcxPT7cVAAxXzSC0PmH1QI9fhL7kODUGYxy+UAaCjZiPQm4EGDhSr7Q3lifLs2bNi6duWMLPQFaU6z8DhqLkI9GIgKeVBOtFl1ZmqiGRWZdPh5IRlqxSh9CmVtks3GwK9GWjw4GxvFXgKDeFOo127d3ehMSBFxApyVC0CPQzEaDYwp7gxa9HRjJUcibOWo4rniEQgRUTLdlQtAj0MhE28lAAB5sGUthPpiw6ceTupnXsYiPgsEsT+54oyK96zd2+jz36SsCPMPWbVjpqJgDgDYZuBC6FOJQ6NGUAcNROBHgaSrJ7kPkCy3LrSvim4D9JVRpdOMQTEGYglHEKETiZ3EtTc1hdnoOZC52rmECgRYCsreOyBbgjqhGUth3vOISCBQM8MJCXChnkwgupkut7h9W9y2/cwUJMr6ermEJBCoIeBpJQeByoF1U5yXB7XUFI6hnF5uXtmEehhIKls+3V1eTBRR5PCwFEzERBnoGbC5mrlEPgWAXEGQjhhmxMM040vDrLpCrn8ehAw0rZSenY9tbD8S16nGpZXxxUvhEAPA0mp27AHIsR8p9K999zj4+bKUTMREGcglnB0oEX33deR1pPKW6moj7hmdsv61KqHgTjslBJlY/gl6eLJZriHVRzZ3GZsmlC2HgbCVSqOPyQIIUKnWk9K7v861cpXoo8WTbOHgUhAUuXk1g4ciZcsXuzj4laKznWQlyMpDMum25uBlB9iCWIfNEIFoFr24IMdtQ+aMGGC6Mxri4N1iT5TlzR7MZCk1jQOS8Z2kBeZu+bP94dXFLWuLp2vCeXszUBqBpISJDALEUKdMPFNAC6tDoQ4GdbB4vs0fJryey8Gwhv+NaFlHIAhSJitohY0nZh9Jk6a5A0Q1AF0jkrs6EV9XPHQMFISM2ahUaNGeRwuNjlCwyQVmUFaaGJ7ZAa6dxDehHbvp/6yEuFNbqq/KkI2Zi1j8FwfBvpSBTKSJEblO+fNI8SJZDaVpU2s1EnCoQ+lltllQdMdYGvNmjW+7QG2YvXsf/HCC+JR6vb97/82MkodYeGlQzwSNuVXL78c23ZlmaDI+y7EYwS1CxcueLcpFRRJmjd/vtfd3e03KU4qYnpp5pFskzxpVxVkGOPMyVOmeMxONgQZjh3FmIpnzp6dB89Cz7ow94Vg63np+LFjxoPtujD3PfC3vsQyEL/8/LnnfEkpUlAMItZt2749sRzBc7Z/PrFihT/KQHTzOBw+P3RIPADvTx5/3JdelcTVLe8904NKYsclWgNTpTSxIf77p596f92xI7Es0mUomz7Mg7Is0qYqCAw5ftiwYYN2DNnTjfsuhH1V9cuDKVjgSu3okSPigwrlags468w8hS/6LJ5LP1WRu996++225SmavuR7bKDHjx9fGfOE6waOl1QQ59++9poWHJ999ll/kJKa1oFxwjjwHSyuqNhMv3n1VS1YRNMPrtsmbnLaRrJ08MCBWs1E7Aew97Gtg7XCyShG+v3rr7dt36ATRD9ZfYxTg0ITvAmBhcTMHGCWCrCpWYgCMWocOniwFnuiKvc8QeOlfRLUufvMmVxLmZUrV/rDlea8bYNCWl3b/U6/OnXypIjAJZWBnnzyydb6vl0Bdf5GZU2tX4uUG10+RPBVCQyKlPm8ilGUZVn39NNP++grNpXOdnd7//2736X2+Tz1z5SYiYPVaKGpLKPGO+++m6mM0fclrh9+6KGWjlsdOxmb61OnTnl/eOONWDxXrVrlS6lwSbRF0TSJlLhly5ZYDIqkmSkhk3uhcCVo9ANqXwQjffjRR5nKGn5f1/fFixb506ZP9yYoDeu6E3vNI4cPe3/Ztq0HT4QFneQ9lqXtpk2beupfpk0zJ/L888/7Vfl3I9L18aNHPcIlmmQklmtjlQh31qxZjdoT0GHYXDMwISyo44xaptPzLlETX9m4MXP/T8ovcwL/9sMf+tPVKFzl5pJKc2jINLz3/fczlz2p8nH358+b5w9RZheIpk1oY8SVwd0zgwCqQOvXry/Vj3K9bFqg0A5G1IAOf/6595UaSfft35+rHnHpLlywoLWBnqs0xTtxRI7DpBPulZ2Jcne8KpdySQ0KCMePH/dOnz7tffDhh5nrdP+SJf7tynanUxRAk/Dr9PtZpZRxOGXubMHLyx95xJ86dWqlS7mgLGmfCCGwb8LrKgZuVe3h0srpfq8WAfrJL196KTcvUOpCL1UllasWZpd7kxHAcG/dunW5+aGQ9iOHcogCHTkEmoIAaktoYeStTyEGIhPk6Ex9jhwCTUEAFaa8VJiByAi9NUf6EGAziyqTo2oQ4IgGjYw8uede88UlXoWqT1w56nzvxRdf7GkLTCSaoPWQ1B6sXPDDTugbyIThZlJZ4u4fUbZEWT0C9fHKE5dg2r3DSjVkxh13pD3mfk9AIMw8PBKYITRFWINe4wl1zMCZHcyDy6qbMNB3BoiM/Djhh6GGKmVWDuxvrTCmEm7JslLPqJf1hXbPuZmoHTp9f8vqXaeOWtL4FzymfDZwRrdz165c/Sw41B6uHPPfMXNmJccPWc3kc1Wsbxfoe8cxUV9M4u7kNfRClWrqtGmVdKa48ifdg2HQEjmpNL/zHGonpYciL8vZScKeXqP5ZxVra2cgCmLKIUm00nW5Rjl28+bNhbDHnRS+KqrUSUzCGYcezDp79u4tVLekdLlPqBhmI5OOTbLMQtorGoDws2ee8Ts5NmqAQ/TztBqZgz1O9Lc81zb5YmApCuP8z5//LNafwAaf4wsWLPBMmdGzDE1zoSxaYZuUT/N0Toln6WSYD+DAX1f6+O8br2IQVbnhZqmDL4sdb72lrV5p+JhUJ0ubhcQrjYMKbGo6yWAr2gHKavxG04teg/EYFXvJtEUpgwIuyarwprRcLWWnqT2hNKWtGMQZKKggB1SDlbqEjWv3oIy6P+lgGAHqWLJlKRtegogESDAzaZw58D2sbLPClq1ZyqjzGRNi/jTrVWMMBHBsgDEfsO3gTGejkhZnHVKODrOU1YTY+5g6bNS5HM1Sr+gzGD9+73vf8yT32rQl55xJ+7tSqjzRCqVdAzhRBVjSULCmEXXiD+cdkr7I0nCTDr5F+x20QI0LQ8pPPvnEYx8mRczk7bYfWjQR8hY+sEVvmicYlmu63SblxZbnJUdk0mdjbUtUjfd27uyaMmWKqINL6xiIRoAYpZEkTVDLujqbUadtNL+trbn/klgyu51WzhptIkz7qbPUwDFkyJDE6lYyA4VLE2xCEU3irHCEUt+oA7GJRsfLlIAgKybsMyUtbz/77DPv4337jO6d0+q+a/fuLrW39icpZzASwpOBbWLdVs5AAThv/ulPPY2CNImzDdNi2aAs7T4Zga+ovyQHhe3eNfHbLW1GSx35X1YekWwk2oRBbcB3Cqo6y8iARJSKuDa3hoHCFQ72EYymMNJAJf4eqjqGxOgSzjfuO6Jo9NbYqGZxjxuXhsl7aDVLETOuLXufaB0R3OAcRsLlcjtBghza0RoWuI6KSZmZYKZhQ4eKiMKRoGGngqr9dRhHOSSxbYmWBqPkIGOzASXLyhkzZojFaUo6erGagaKdJZiZuK9TYZXZ5YwawaIMG82/069379nTs8y2EQvE61LLuMD4L1pvo+dA0czLXH+t0fSZdb1jnjKtYce7MA/R6UxSbRkosGbUARa+4xy1R0DysLJ9ztl/xVUvy2+TVFsG0glSfwHJjc7y5UlLqi7XVee0nWBy9rAmyTGQSbQN5CV1BiQpnNAFSz8lbk7aq+jKI5qOY6AoIjW/Zh/gSD8CSQOIYyD9WFeaIh5vJMj0yF6kDpQxqaMXSS/8TpLys2OgMErueyICUnpmiRkW+AGdNWzOTJJjIJNou7xEEZDa/7UrtGOgdui433ohcM/ChWYPWXrlnn4BA0kt4ZLOlxwDpbdLrZ5IWqvrqIRSldGRjFgauLySmoW+SRDOOAYSa85qEv5GSIhAbTDHx7VUNTVrn+v3ly5t+YNo/1TxXzmkjSPHQHGo1PjeV4JaFYzuKPLaSC2tfSFNdI4GknB1DGRjbyhRpj9u3Soat2nO3LklSifzKnuzscqtl9T+54bSzLfCqYgMfC7VKAKSun3Y2yx94AGrlnEzlctfSTP2pOUbuLsZKNr7GnCNWr8kTVPhR2yhRffd54++7Tax2Yd6YheWRI6BkpCp8X2WHJLELES0CMk8sqZ99913i5r+I9Vs5Azka7T7kBT9Zu0IOp/Ddl9aJ46AassefLBSJsJPgbRfcMz5w/46ou3kZiCFSH8h6U0UbJPXV69eFc9u5qxZ3v1LllTCRD9YtsyfqGIGSROhaNpRrUy6cSiOcxFGnUFtXA21q3Dcb+OU83v8LTBVI8WKe6Zu9/AeNFL5yZYkQsPPV0soJf3ycXAomVc4bZjHhDSQlUmS+Dooj7FKBxnm/STyAEqCw1QI8nYeIvOmm/Q8Sx9G7zo6FInWyVS0QDwXEeLkrzt2iPcn+gPR6qRE1mEMEcYEXnTD98PfrZ2BWN8iXTHtG47DQkZu/p5//nn/0sWLHtN40jlAGEzbvl+4cMFIRDc81syaM8e7ZehQH0aScLx47z33+HfOm2ekPkE7njt7Nvia+Ck+YiTmnPADjIN/L8jEKJNQjF63mcovKccjv3n1Vevw6lXQyAVuk2fOnh25K3cZ4HTm9Glts9GCu+7yle9rz7T7Z+ryy5deSm3v1Afk4O6dMiELCcQlaRTVO8d8VwCKRi7Luy1btliDW1otVq5c6Zt0lxzgdOH8ee+0YiTwKhIzlfOdEWqvO3nqVG+4Wr6bHkyJ95plP1x5R0AwMH78+JYhlGmQ0jpf0u+s+S+qpV3YT13SszbcX7NmjXFJGYzEfhILWRipW/3h9IN7H370Ua9+R5wfBBI4RME18USltDpy1ChvgFpOJzk0lMb1xRdf7FXGpPwyPZT0ctn7T6xYIeZJsmzZsryPpCstCG2WdKSfMRFwq10dYCYCjgWz09fKc84NdR24JuMYIZCq4hiE71UOpnmibVTCQKzNkeHXwUy4XcfgN0ZVNptxjsfT3jX5exWzkMn66cqLGXLt2rWZ+cL4QSpxLaerU+wmMA+NxtKDweCnTz1lfJmUp9NcVBI5R+kInDx+PP2h0BNGGYglm6TVYKhexr9yuPuzZ56xlomQINbBu6jxhgtlSEDhvC6eM09VoXwKfa16HV6o0AVeyrsEKJBFqVdMHa6WKmQFLyMYIn5v3qyNzECdwjyAz0EsnTRvQ5h6njg6jnojgHDjiIrEXYTEGaiTmCdoACRItm7aEXYgPXT0TwQIDh2EGv3n3WzfRBmIPYGkpWC2Klb3lK1MhOgdNX1Hnse+p8x5nhgDITBoiqStTEdDn67M+1LvEiGddX8nE4PIpk2bcu97wpiJMBCmARKxKsMFr8t39kSrVq2ykonYNCP06ESCeRhEytZdhIHGKAd3jv6JABrl6Pr984493zg0ZBPdSaSLecBMOwOx76lSDcPWjoC+n62URevY1rLnLZdO5iFvrQyEloFp+528AFb1PIOKrUs5MMmqPFkVfjry1c08lEkbA+GlZbTy1uJmn+SmZnBhf5j8RLW/NJmJEN3r2PNEW0gbA0l6howWus7Xo5Savs0EEzVNb+7YkSNiWvOlpRB0BpN26lk6H+JZ1OcxzsMIDkmYTUtLrFvrYJRn6zlWlj7AM+j+rVu3TksfT8pTS+Ks7avsoIyYx44e9a6oaRqGwbFg2C4fg62ByuYERkJ7etLkyS0N6iRQpO8j9TqsVEfq4GeBfS0KwHWjrBalZetVmoEeVRalk5XNuum9DxtCmAanH7t2785dj8BkeILyv1BFB6nLLBR0MMw1pJ0YBnmV+Tzb3V1KsyBv3rk7XjSD1atXt8xxo/elrpmWUYg8oWzW977/funyU04M/MYofwzSftTCmDALMUrmVZ8Pp1HFdzRMbDwkz2NFqhO3Uh0Qydt05Wjc1OzD6HJUbQh37tpVqtxxAOL9BS//U6ZNi/tZ5F5dTMLjKo80kQNzU20fV4bAGhj/bUWVQePSzXOvlF+4cepw0ASAjNb4OCuj9JcGykcff9yl/lpO04nEZmJPZyKPtHoX/T1oCzQscARyq/Kcwx5TmmAaBh48hmbxmiNdnlIjuQnjLHS1WOq0c/CtG6QH7r/fv/POO42Yndd5Forizqw0QAlrBipBDeHmy3rUYeCk/Yl3hGSV8JUB40bzruq68AyE6Fq60ME+wSTzUKfv/Dz78++6S9ydMJ2tKRTt3MxOmLMUWaXQ9khVbXfWUpiBbhMOagSASKpMM0/QmWEi5djPv0Pti4p0gCCdtE9G7KbS719/vdQKpw64FNZEkF6/X1EeLat2pcvGVNoEmn0Dkq06dBZXxr4IFGIgpG+SozJnPDgpt4E++eQT77wy+ZUkZ3goia5s2oUYCImLJH2pzGxNxptpVxc0Gs4rP8+SFHjllMzDpS2DQCEGkvRzgEz/0MGDMrUtmOq27du7OINy5BCIIlCIgST3P4z2RVRzohXTfX3q5EndSfakx3LYZjOHnoK6L30QyM1Ayx95RHT/g+jSRiJ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"}))),I.createElement("image",{x:342,y:60,width:51,height:83,xlinkHref:"data:image/png;base64,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Pinot."))),B.createElement("div",{className:"slide-img",style:{borderRadius:5},"data-src":"https://miro.medium.com/max/3200/0*2Vorw0A5VEy_U2uz"},B.createElement("div",{className:"slide-caption"},B.createElement("h1",null,B.createElement("a",{href:"https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7"},"Change Data Analysis with Debezium and Apache Pinot")),B.createElement("p",null,"In this blog post, we\u2019re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot."))),B.createElement("div",{className:"slide-img",style:{borderRadius:5},"data-src":"https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png"},B.createElement("div",{className:"slide-caption"},B.createElement("h1",null,B.createElement("a",{href:"https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38"},"Deploying Apache Pinot at a Large Retail Chain")),B.createElement("p",null,"Our real-time analytics journey to production"))))))}function w(){return B.createElement("section",{className:"topologies"},B.createElement("div",{className:"container"},B.createElement(s,{id:"uber"},B.createElement("a",{href:"https://eng.uber.com/?s=pinot"},"Uber Engineering 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merchants."))),B.createElement("div",{className:"slide-img",style:{borderRadius:5},"data-src":"https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png"},B.createElement("div",{className:"slide-caption"},B.createElement("h1",null,B.createElement("a",{href:"https://eng.uber.com/operating-apache-pinot/"},"Operating Apache Pinot @ Uber Scale")),B.createElement("p",null,"Present details of this platform and how it fits in Uber\u2019s ecosystem. 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pLP3qbrJYWFladxkfhxgFSrb1s52MwxulSj2tkzFiIQaiVPcCYhmE2Y0E3u6Mf9Sy/drDJX8r/9bVRutd+k0e8nTYrqB+FizsaIZe8jxLKJGTqZVk0cEzEEMGRIpg+fot/2F+4svEx4sdCA6eFWYaBA1rEjkXKNTZ1QeIMwCaN1Ee5p4aV/772J+shkBybj/9S9o4VZv73YcNhqTRnHH49jJ5mf+CBh8YqbtI/6VCpPqXQ6SUJXML6UylNNujXwjBlbSt/u4S+7zPlaucrYsdnvx3Cz5pqFBI3NHw9kNd+UzGPfJ1nF+u81hMBlhbDzS4X9hQa/VWQEApQ8XkH6vDgmD3zrSNoqUHJpBhDrj+eK+VqbK5Wna+ZmNgLjgK4obG42WTGNxLBOvm/f1ZwIIOdetED2oby06FKjyyGEaQFEkP6LZiqTyCJMsVbq49TgeesByjyYd0sGqOC/P/bYie7EE52TmTYIbnnZSl4i7WsZWAak/jnZNEKZmURF5NxxMujUDLQTgIYRw7IQAOy/t3CW8GUh0E04mgiSKKoHageSKMCCxRhMi2in6wlCwiAArbceM0o+vKaE0cLn828EQezSS6Pk0047VMIKoocBgt8ZdlEQsihDlO5WQ2+pAxCyAFbmskI3KUBGd6r/pZG33945mWVr6nzewOKPZMci6VNWEmRHCIJcr17J1OriRgCmSeippWDzdOsqwiAQKAREd64jOqPs6qHz2cFC48TwShxKdg6wr35/QEzr8dy++0oZLoB7lbKHsLDzyXryyZEU3r//2tIAhpKUgEsUL65A0/GMXCRs68jEg1VF4RzAG2/k1DFKrPEXaX/jjcVW4as1AuphEpD8Te+3dLl7pV3YVW2haTkQWgxtGcFqwnB8yXRLVagxH+nUyY7X/GogvuB2E8I1RCZO3Rex/nHjjiGaBzCHLNvIu+lYG69dswFg/RiMsjBb0VIKh6RWia3ox8svn32i1hjTGYCOzjLtpoKV19RyWLqe0xQqELVQewrrAiMAprwYFsABgPnC5NAUI4tYIQRgoFWqBuSFSzwhnCjsJnTaXy/rW3eiCThX8YsS14VRphk+at11+8iYMjgvA7T2dV5adMno5/vqZf1WqDSAADSuWRPtXq2htn4XdFqtZZCf9tAyrgKgD7baqiC5qgT2HgDsP4hhnhGARKhg2LEb04hMmaKmj9teOm6Yp5Ushhs6HiZ3vBAO4HSGjjvqqD2IJuBvil+ZuC6MMn/b6Of53NHPtPFk4UNxCsYQ2CassinA/jwATgRRIRDWC/kjtt5ymErMmpksg3kcY1c9YASQ4OQfW9M9pwKZCgxgyC88+KDMgbdEEjbWqxhOVPhrIaM/dD7pOmRB815WvIxEigu5VRbkuAlS7VJLLenYupUFBI6zs5dFYkizWLeaClKrgq8Aa2Byymtquc3xPJpFPQBHscFMPWN42whAYykHvtLVSFJuuCGaX2NBianhZOH5wmVlUAgd0KHDkjJdhuxKBv4tHCNM0hTphaBFDQHWXHP1hLmXpMuFMKbSwFLuRoGNKi2mTAq7jSq+YeXgIKoHkg4qBMkYZhsBWEIyfF4XL8mFGBwc2KYF5O8Gy9SqWKcTsAJVjRo1XPblWJQO4sQflQ0aqgymksydiwXH8n+pyI12UTSUyZTt1A0D9H9gzpxIDsh+S0he5H9sWsNfkvAjzCpHAFT6VlgHbFrLqpxs7e7WW53TWrtwzW5WQLtxokj4ZfaQNFUlDB0aZXznnQ+0dfux+CnCrM4ZJ2YCKoGRpKlzf6ZARUwQpGzqjLFlcQLTbtgYk4CnKhHABGWeL5NmUD+wCyB0MZewl122dzVcD7fJJtJXAqBDXRrHqwsgrP79o7yHH36GJFQ4h9hOCYCVYYiqVxcuUWyoF/fefz/KYSOmVP5FKR1OaTYc+iwGdIIZdlEuZM4PK1A52Ijlx8kVL0ccsZts0maz/03N9mmx2uBFY8cO7znwwJ1VxiZFy9HI9LvtFq1w5blGIt463s9ybxwmMgo1tPxGfmutZbEWkjrhLEvsLppKp1fiAOQ5QXisqOgz1CStVs1Z8bL55huRRyAyczeFWK0/nI6BxREYP/5G7dlDwSiEP0q0gFXnrWopzFhHilnuTEdOCk11FNeqHsFPAmi1cNLQdTtp1RAAI+N0YXehGHZYyw9XCDBggCmlM3X9nzi1toC5nIUSrJAB9t//K7M5RAn6ZSMnssfvf59JamjE1Enmf2BxkQEgaBP60OhioJbXE6+GAOJn3OeKPCiUZSBsypTxp4uMFcvF96fFYe0BRg/s+FrkEIwfCCza4BiEMUpj5+2+++rEg1Oj5V21v6HyE6YjGyFgNjXTaeWnW28OhFqA9YqaBgzuUeQtLmohAHuYUKYTBMIVCWLIlm4ptYTY8rE1jB4dmVK1l8397W/RdDNqVLQgEtdoc4FZxzRHZgDP26IMGLWsXlq1lIQz7aK9RWoMw7DPHrWGQInxp37Al44EjnS/7bZO6wAjWwOUCwfAKtkoM2uxr8QVDCTNrxBAwnceZajjFy8j6hdlYTxrpAGr1OfA0czgw3oOLegxeECRKXZRLwdYigKyPnvV0MWTp5VcY8gUYI1/4IGRhRGrHJQ7fLhzQ4fWWGCN2SEyIOlYsmkhulP779tvRwdRwcGYTlqq81H7aDu+H7PvGWdkvl1f4Y7IXClSLwG0oRD0pAjejcOmBazhZ3TgTk3avJENmhuwawBmESTeVAJgCtMePi1pj/YLtMTIh9DwamLHQAA86qisEKgqnSJ8hroZ1EsAoi3mZzOXyaXXAKCBbCMHqiHA6G+00ScqOfvLOgBWO/F+8wlwt6mmZsrVEfGuV69oOsOx1pyAsefFFyOjD52vtY7hOn7ngwoz2pt9R70EMI8CPv1UZBbAwviyCQHTgFbCOh2JEuCgg5pQWJWPMlJhZvjfeXejgJ08nE2I7MLaSp1Z4LRFLOwQMtdsI95FWXPmRO5s5BbY/v77y8w3I1O6JKmw8JcpIAdE83WB5EudpvvBx/HDBeXWVSgP0Vh0AkITjiI4QHMAo0XLuMNyNw55Apijk2AqIWlMB8nrZL5icewIrOcztm+bU9i9BCL0srCD3USbbqrTGqR9UO9qBV3sFajLLNBF2oeA4VhaQu60zyFp8Jmp79ObXFE2XS8BBNsSHrwFCxZqFW0QCYq1Q11peCCpkE74KLoHr65CaQE1gU7PcGzR0pLrHD0fY5R29OZAkhtMnRrZKtjRUw1AvIx+g3zfAhqPjnEJyCJU1hFqz4X8KtGUgVAMwfFdEAXtwfzOaIe4YPGkARCz9hIEWQNOkIDrFd9XqBzFoV4CeJfivv56vnv77fe1IFO1bSBgbgaSHRCl1PfLimbc11gSaTiARu3TJ5rzcXAh/TMqDbiftAmsu64Wsl/s3BVX6E8Exzqn83bKQv5INi2j2EOMYKY8m/b4Do605fv4Lt6FqRqiYuTT4SyExSPKYNF29HyBVZOAO1J4TbH3JdPqJYBXrZBZs2aLAJaxy4aENlpg0Xj+fv3r+opF/x49Wv8aeVV2tNORsOahQ8svJGVUYqE0YK0fz3GOL3M7lsnDD88KrZavVMgILQd8D9MERAB3AOE6NcJrys+EdqGwcYJZkY/ooTQYkB87Fg/geQ31nGmUhmNdKF+dEP5nR+yu6newG+d3v3Ne26HDN4qNeskSnjOD8IpVgxplBe+TWTU8y//+SF0MZ/XYeQRizQX57ZvxLFp7lQovvzw6wiXhadUYDx62cs9+ojyQyRjhQKH4Vm1QLweQ2BLBI49If4oOp7SkJofsY0eYYZfMP/8Z+QUQdippBMyPHLfOHgM8YLBhNmiwmgkvYjlgzjWBDYm9mAUQ+wQrkfr2jaYTLGzqOKeNofKLRJwmubPH3seC2nIAa2eVFfliL6RqG/ZqLBGHKyjsKJREEP6+lo5/R6iv+WbgDr02UGanTh21MZL/3ik9Auq9Jyk3jFx71zbbOC+CCP+5kyxTU4bXrqJwLJzl5SwcRlWp0c4BS+wnlKesoLxk2flxqVg5ZWq7dmaEioC8VMqCtpAlLpPHvi8ZsuGW79xpp0y+K3W/RaAeDoCohFoR4LPPPtfZu69oiZgmsLC5OL7RgIANH/gEdEJmUG0YcSBOIww2CEZwBhaWmvuWtQKM+HyVjs9BqsbpBDLK64F84xD7+QyQ0pEN8Cuwz9EASb4UMO/rr2bD96MexiD+1zKQEHOqfuEhyjmc3Jg5sXd37txR7BrjINNWYwFBDH0ZXRn7Nu5NJHkaHumeaxoetozVjUOSk+yeaYBGRtJn+xjCXS36fH5tkL6TXkKMSEwLAomHYW9l3ylTonYRxwpqnLhIIGTWPJh6x/fg9Bo9Wrx+lcjnERtuVKPw5xALFDY7qHlqglHK/Xdhe1QVDCgjRyIJr6AOGSip+faaCqs1M4YP1CnMtnQ8ox5uwPyZdOJQLnO4jXab22t9X7H8qF0QHMD7kTFin8HnSuojVKuERTNBhmEhC5xKQqnTAVLBsIVaBxGikaDq4iv461/1VAS7KrjWLpo7bF/DC3ZRXuam9owq7MyMNIwdL700V+rL+w6Kb05AL8cvwGjHqIPARGfwPYws2Dp5GOVcNxrgPNb5lI2amnAYieTCnwwxSK4Q7sqR9Kzjh0tgh4BbmnmWAYT+P2ZMVv/XM+cIW6zz9a6qYTflhO515InzkrTDwQcILvxVOuk77JB7YGO+8LQ4XIv95wiAqIDUXZ0ZQsXFHwIw658rtPSw2FTaSRASOWmccwTFBez+QuUdKxQptz7YU5+U6Xyx/SDlskKXAxE5jFmjLZzNO2dOoQTcWjpewluBdF7rt0nmyBCARnLoeGwNHDGjNjLcMNGFv1Jc4zxzz/Ikw1m6v3nimRaNlpFPw3cw8i8TtoPNniMGFe8QCsKNLePCwwVrxAnRaLBFmk0pF8kd+aEpIGLJKQNZAGsdC1lZu4AuH8P+FlF4qVATlhstfEL4q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"})),I.createElement("image",{x:370,y:82,width:51,height:83,xlinkHref:"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAewAAAMYCAYAAAAJttRGAAAABGdBTUEAALGOfPtRkwAAAERlWElmTU0AKgAAAAgAAYdpAAQAAAABAAAAGgAAAAAAA6ABAAMAAAABAAEAAKACAAQAAAABAAAB7KADAAQAAAABAAADGAAAAAAmw5O2AABAAElEQVR4Aey9CZgcV3nuXz3aRvto3zdrtSRL8iIZ4xUbYzAJtlkdMNsFshBCbsgN/8sSCCEk/EPuJZAAIQm5cBPAQBwciFkMNhiEF9mSbO37Lsu2bLzJtiRL7vv+jqfk1ng0M93T1VXV9Z7nqeme7uqzvOfUec+3nO+UIicjYASMQA4RKJfLJaXyAw888N+ffvrpIYcPH37vM888M2HPnj3RI488Eh06dCh6/PHHo+PHj0e6N+rXr180fPjwaOzYsfF106BBg24aqDRhwoSvKK/H4zxzCIerXAAESgVoo5toBIxAkyKwZcuWzz/xxBN/8OCDD0Z6Hz366KPRww8/HD355JPRkSNHoqeeeip67rnnThC2uDlqa2sL14wZMwJxjx8/Pho9evTPROa36/1HmxQqN6sJEOjbBG1wE4yAESgoAiLna++9995o48aN0YoVKwJZQ9RI1RB1TNbAIwk6amlpCZK2JOtozJgx0bhx46Kzzz47uuCCC17Wt2/fcbrNhF3QsZSHZpuw89BLrqMRMAInEJCqe7wk6a9KDX7F8uXLo9WrVwfpGgkbFTgk3VWCuPv37x/U5g899FAgcv6XOn3+9u3bnxgxYsSbRo4c+cOu8vB3RiANBEzYaaDuMo2AEagZAdmoX3LgwIErRK5Bql6zZk2k/yHcbsmaQrFnHzt27IS6fO3atZHIP/z/7LPPDp09e/YP9u3bd+nkyZN/VnMl/UMjkAACJuwEQHWWRsAI1B+BgwcPvlq26pb777//8lWrVkWowtetWxft2rUr2Kwh4p4mVOZcclSLHnvssQhJm9/zmUg7Wrx48TeU14Se5uf7jEAjEDBhNwJll2EEjECvEZAj2X+JrKMdO3ZEv/rVr8qbNm0qicSDdFwNWXesCL/FoxxJ+9e//nUgfzmmjd+/f/9fT5o06YP6Xlr0Us9XAx0L8P9GoE4ItNQpH2djBIyAEUgUAdmtj2/bti0SUUe7d+8u7d27N0jHqLd7m8hD28OC8xplSOIuyxb+J/Iyv9Jk3Vt0/ft6IWDCrheSzscIGIHEEJCUO10Sbwl7NRcqbLzBu3Mwq6ZCsYoc4paqvYTKfefOnV8gD6TsavLyvUYgCQSsEk8CVedpBIxAXRHQ9q2fiqRb8ATfunVrkKzrSdZxZVGPs5d7w4YNEXu2hw4dOlU27i9Jyv69+B6/GoG0ELCEnRbyLtcIGIEeISBHs9fJi3sUW7YIioKdGekacq13Ik88xvE6l6c428Ra5IQ2r97lOD8jUAsClrBrQc2/MQJGoCEIiDDPlaPZ34uo24hmRuSyo0eP1lUVXtkQpHa8xpHkCWV61llnUd7xynv83gikhYAJOy3kXa4RMALdIqBtVxdof/X42HsbyRoHsSSkaypDvmz1Yk83dnJCnErCfrbbivoGI9AABKwSbwDILsIIGIHaEBB5PotNme1cvMKdSZF1XMM4f0ibbWNSj1+g8m9V+Yvje/xqBNJAwISdBuou0wgYgR4hgIoa4sR+jTocT+5GJcpGwhZRD5Fd+2W6pjaqbJdjBDpDwITdGSr+zAgYgUwgAEFDnPEr0q88thtSN8qiXKT69oVCYwpuSOtcSB4RMGHnsddcZyNQMAQaRdIFg9XNzRkCJuycdZirawSMgBEwAsVEwIRdzH53q42AEagCgdgRrYqf+FYjUHcETNh1h9QZGgEjUG8EYts1qvFGkmdLS0sUX/Vuk/MzAtUiYMKuFjHfbwSMQMMQ6NOnT8RFEBNeG2nLhqhbW1sJTxrClKoORxvWcBdkBDpBwIFTOgHFHxkBI5ANBCDN/v37B8LktZGEzSJBx2xGo0ePXj958uTLVPaD2UDFtSgqAibsova8220EcoCAJNx+w4YNi8aMGRMk3VjKTlIt3rdv3yDNDxkyJBo0aBDS/f0m6xwMlgJU0SrxAnSym2gE8oqAyPNHI0eOXD9r1qxo3Lhx0YABAxJtChI8ZYwYMSIsElgsiLQ9TyaKujPvKQIeiD1FyvcZASPQcARGjRq1XqS5XWrpQKKDBw8OdmVU5UmkmLC1SEAVHqR6qeIdMCUJsJ1n1QgkM+qrroZ/YASMgBHoHAFJ1leJqA+gFp86dWo0adKkCOKGXOudyHP48OHRzJkzo7lz5wYpWypxH/5Rb6CdX00ImLBrgs0/MgJGoFEIyF5dEllPnDBhwvHZs2dHp512WoSqGnt2PRNkjaOZpPro9NNPjxYtWoSU/ZCk7VfWsxznZQRqRcBOZ7Ui598ZASPQEAREpGUKkl25DxI2x1/u378/4shN4oxz9TahYh84cGCQrrGVT5w4MRo/fnwkx7OHe5u3f28E6oWACbteSDofI2AEEkVAUvYXL7jggveOHTs2EPbDDz8cTvE6evRor0kbyZp8p0yZEi1cuDBavHgx7/9Fi4T/m2ijnLkRqAIBE3YVYPlWI2AE0kEAtbjS7+tc6vdycpb2RZclZfNZ9Nhjj0W1kja/ZxsXW7gg7OnTp2MnLyv/kl7flU5rXaoR6BwBE3bnuPhTI2AEMoSAiDWoxaW6XqRtVy+7/PLLPzdt2rTozjvvjNauXRs99NBD4dzsatXj2MGxWc+YMSM699xzo6VLl0bz588vicTf3L5ICOVmCApXpcAImLAL3PluuhHIGwKyK6994oknjsgZbI0cwxZhd4Z0d+7cGR08eDCQNtI2UvixY8fCRZAVJGku7iViGq/stybsKFL1kiVLogsvvBDP8H8RYb/LZJ23kVGM+pqwi9HPbqURaBoE5CG+RfbrL4twP37mmWeORZ29d+/eaNu2bUE9/sADDwTb9qFDh6JHHnkkkDdq75ig2WMNUeNYFqvBFyxYAHE/JZv1rwEqluibBjQ3pCkQqP9GxqaAxY0wAkYgqwhUSr8HDhz45qOPPjpGUvdlq1atKks1XoK49Xkg6927dwcpG6mavdsEQ8HTHKJm65b2dJe1Tayk15skvf+xiHpzZf5ZxcD1KiYClrCL2e9utRHILQKx9NtOrL9FQ/bs2fN1/f9mkXfYjoV6XCQePfjggyck7MptW9itsYHL87wkqfqb2uP95hiQOP/4f78agawgYAk7Kz3hehgBI1AzAvfcc08/qblf/cwzz7SImD8q8j7z2WefjY4cORLOz2afNRfbtyRtl+WcdoO+/6aimj2n7Vs/Ekkfrrlw/9AINAgBE3aDgHYxRsAINAaBxx9/fKQczgZRmgg8FIp0HSedAHZcB3o8KZI+FH/mVyNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAg0FgFv62os3i6twQgoxnSr9twO2Lx5c5nzk7lI8WvH6hC2svLS2chHdTCE9+h2BMr/GwEj0HAEHOms4ZC7wEYhQCQshaq8XtdVnOL01FNPRcSX5jhGAmpwOER8uhOHQWh/bkSwDf0uxJ0m9rS+/4X+f6X27D6/obdRlXc5RsAIGIEOCJiwOwDif/ONACStFI5EVGjKt4igrySe9H333Rdt2LAhHBKhM5UDeUPOnOpEgrAV9SpSQI1IsaU5tSlSBCxiT18kgv+0bvnDcKP/GAEjYARSQsCEnRLwLjYZBCBrndb0Lc5HXrly5Vlbt27tt2nTpmjHjh3Em450ylNQhx8+fPgEWcc1efrpp4NkDZEjiXMCFJK4iPu6FStWzJk1a9ZfSl3+y8pFQfxbvxoBI2AEkkbAhJ00ws6/4QgoNOUbIWfZraObb745QsLmIAhU4pyVzBWrwisrBzlD1lwcy0g4S6RxneQ08tWvfvUrJW0vle37Bi0Kfqfyd35vBIyAEWgEAibsRqDsMhqGwP79+/ciUaP+5nXjxo3hxCbs1bH6+1SV4XuuWMLmDGV+h4OazkrmZKdROoLxzYpP/Q2R+W2nysefGwEjYASSQMBe4kmg6jwbjoDszDN13SJpetpPf/rT6KabbgrOZZyLjPobR7JqkyRpTnYKl9Th0Zw5c8J17bXX3r1gwYJl1ebn+42AETACvUHAEnZv0PNvM4OA7M9v11nI0yBoSdnB/gxRx8cr1lJRSB71OVK27OLBMQ2p+8knn5wjqfsjOkf5syL1p2vJ278xAkbACFSLgAm7WsR8f+YQkGQ9Y9++fVfIMSyowbdt2xacxiDaWiTrygbye9TksouH85Sxa2/fvn24JO+/wDFN339GpH208jd+bwSMgBFIAgETdhKoOs+GIiCb8nxdy9i6hc069u6GbHtL2HFD4nOVH3zwwYgFAZL24MGDPylJ+2u6Z198n1+NgBEwAkkhYMJOClnn2zAEJOkekjo8qK3ZzoXk25kXeG8qBPHjjIanOV7n2La1X7s0bNgwP0O9Ada/NQJGoMcIeLLpMVS+MYsISOL9hOzLH2OfNZLvrl27gpNZEnVFNc7C4Pbbb4+kgg8OaEOGDEmiKOdpBIyAEXgRAibsF0HiD/KEgBzLPibSJk54icAnOJnVW7qO8UDKxi4um3kEUePUxuVkBIyAEWgEAi2NKMRlGIEkEFAwlNHskZYTWAnPcOzMkHW97NYd6xyrxQnCAmmzOHAyAkbACDQKARN2o5B2OXVHQNLuy7FX4wiGqhrpN+kEaSNVszhoRHlJt8f5GwEjkB8ETNj56SvXtAMCIs/BldJ05fsOt/pfI2AEjEDuETBh574LC92A6sOXFRouN94IGIE8I2DCznPvue5GwAgYASNQGARM2IXpajfUCBgBI2AE8oyACTvPvee6GwEjYASMQGEQMGEXpqubt6F2NmvevnXLjIAReAEBB055AQu/yxkCOnSjf0tLS9SvX79wkhbHYTYiUU6jykqyPVroqBmlXDvuVbZB76fokJaPaLvdRXrfqusEfLzXWOmjGPCr2traXq92Hz/xpd8YgZwgYMLOSUe5mi9GYOTIkf+wcuXKL+mYy2jo0KHhQI4X31XfTyBqFgjEEu/Tp099M08oN5FVX4Vv/SMFevlriqANOnVslV7PTqjIhmWrNpQVP/4+HXm6aPny5SHWO3vzO4t4x4Etiv0+dfTo0cfWrVsXibi/OmnSpPcpj6caVmEXZAR6gYAJuxfg+afpIzBo0KBo1KhRTMQNIVAkesg6y4R9//33D9JiYoKCuzxHD23YsKFNZPXXBw8eFHeXSyw0hg8ffpaiw+1VDPZFY8aMadOip6R7jgrLfen3avc1kCQ9UgexYNL7kQh7EYe+cFobke/iA2AIbMPihISE3draGo0fPz6aNWtWGDM6vOUd+vwdipS3VONnv3A4EG72HyOQUQRM2BntGFerZwgopvemyZMnz9NhHGWRdwnp9+jRo4mEJ2XyJ39J9pEmd6TUQAI9q2lj7nrkkUfOE2n9N2HwbmKrS/IMUqfIuSySC+xFO9BISMKcLKL+NTUjcptI6xkR+JskgW7R+82NqXH1pegI1VHSGNykNp67Z8+eiLC0+j/asmVLiHgnDCLaXhlTHsIeMGBAuI+oeGhl+I3aWp4yZcrdWsTcr7ZfIxJfUX2N/Asj0BgETNiNwdmlJISAzqS+QgT6KZH2dUjbECqnaiURNhSiY9KfMGFCpPIC6SXUrKqyRWpW4gCUv5A6+H06sWz4vffeW1bI1hIkRihVEViJhQxtIMVqfTQTLD4mTpwYnX766QMXLFjwPWG6XHm+VvcerKoiCd4ct5EipAn43Jo1a86lbVu3bg3nnyNZE+MdVTgX/Q9JVyY0C9IyRJA8iy1IW4Rdmj9/frR06dKJM2fOvE0Ll8v13fLK3/m9EcgKAibsrPSE61ETAiLrPZKuvypV53WoO5GemLwlTdaU36l+BNFhA+WUrhkzZkSa3MOEjyr5VL9p1OeQtaTFb4mI3gghya4f3XPPPSWOAMVWG2scKgmM9nCJnKNx48ZFkjKDJM5iR+17qYj/buF4nfDNBHnRRrXtVrVzoNr1krvvvjuSpB2kapkAwhno4F3Zxsr3fEd7SZg1IG9U5NIyhHazgNHnrVqQ/VDEf4UWMreHm/3HCGQIARN2hjrDVakNAU2yrUhLixYtCrblzZs3B2mr44RdW+7P/4pJHuk6LmfevHnYQbeL8FJ1WBKpvkrS89+KtObccsstQT0sm2wkKTssXlB1Q8JdJUgeiRTJ9MCBA9Hs2bNbzjjjjGmSuH8pcpwrbcKWrn7fqO+k+r5k1apVJdonDUKQlB9++OGg/u6ujdQxHg+oyuNT3fgMKZ3+JQ8tboZILf6rTZs2naY+3tmotrkcI9ATBEzYPUHJ92QaAak1V0iy/sFZZ511JapOvIRRl8aTcj0qjwQWO7gtXrw4kuoYCe39sgU/VI/8a81DmoRLZKeeA4ndfPPN0c6dO4OGARsuBNQdkT377LPhqFBs3ZC1VM2oxgN5g+XChQs/LZvwO7Q4eaLWOvb2dyLUAVpEHFHbnrv11lv7bNu2LZA12hS0B5W26p6WxW/4LQsVFjdoZPgMPMDs7LPP3qFyWym3p3n6PiOQNAIm7KQRdv6JIyBV50GRzXckFZ4nAm2TVFlCamRCx7GIibnWhDc4kjXSu8grqMKlMn5CquI3SD1+c6359vZ3kgxbJFX/ibQJH/z5z39elsNUSVJhhMSJzTqWJrsrh/tiYo9xQuJEfax8ylqUXDNnzpxr5Hk9Z+zYsVu7y6/e32vxNV6q/h/fcccdi37wgx/g8R5s1rG9urflQdJoFnBUw3zAwgXSxkwwbdo0tr1ZNd5bkP37uiFgwq4blM4oLQREOuKX0lf1ukbkepecrfqKwCJsuNizYyKqtn6QFoSNnRfCvvzyyyPt22Xr059D1u3lnuzZVG0hNd4vMp0i6fDTkojLP/nJT0p4SrNIoa2QcG/SY489FiRtqYmDQxaOaVKLb1Ce/RrdZhHp29SPi7BXsyBhAUb9kIzrmcgPDFkIYPaQtqY8ffr0X6m9ozUOHqlnWc7LCNSKgAm7VuT8u8wgoAlV82og7VWSBH9X+2z/mQlXxBo8o5mIUZOjJtZ93apQIWnUwVx4g0uyjORJXJajWUmSdV95Vf8vGk+5jQahvZ1lkdfXkKalzi2hyuY9ZF2LerhjGyAv8GI/M6p2nLNkEjgmovxttfkfO96f5P/SlhxG+qUPecUmjwRc78S4IF/aTTlaJJT27t1Lef+qsq6Mca93uc7PCFSDgAm7GrR8b2YRiMlT5PqV9evXr3rNa16zSmRTlhdwCbssNm28iSEjJmYm6M6S8glBWCBptjudd955kVTC5SVLlpQkVS8ViafqZEY7RSiflL36YrUzeEpjf0WtWw+yrsQESXb16tWBwKRlaBUmv6XvG0rYtAstCdoSiDQJsq5sMxhiSkGiZ0eA/BUuEWlfJtxvqbzP741AGgiYsNNA3WUmioAcwlZLOjxTUuHq2JbNZB8TGx7BTMyVpA1RxxdBRSBr9lvL6QjbdUlk9Tmpw1frnq5drhNt2fOZi7Q+iPQn6TqowbFZd+dcVku1kGZZ5JB3u2khRE6rJa9afwNB0z5U1bzWe1HSsV6MCdrNuEH9Lq3KQJX7e7rPhN0RLP/fcARM2A2H3AU2AgER7L0itFcrIMZNqLXPP//8MAlDPEiOcQQwCID91XiBQ9SowZGuCSSCLVOOR0+KvJ/VPX+fBbIGO6m+W3bv3h20BpBKve25cf8g3ZI/pgQkXGG2TIuetyqsKWrihiVItPJKsmDKYWGAiQGTAG0XviOSLNN5G4GeImDC7ilSvi93CMhp6AeKN32lPH7fJ5LrJ8LpJ0ntEtl8USuXUH0iwWGjxRMcqRoHKzyEpQ79sbZxHRZp/41IfHmWGg9BQyjYrtEaJCFd016wYXEDcYOV7LtDhOHlIrXrtXipvyE5IyDTbmzZFVJ95/aTjNTX1SgOAibs4vR14VoqYhGvlH6ohnOFJOel/5CEeA1EF5MdZI2jGVGv2Gste+0XRdq/H/+mPZ/MTNpoBZD8tBhJxHZd0e5A2pgQIG6kbWkh3qLv/4+un8X3Ndsr+LIo4uI9UreTEcgCAibsLPSC65AIAiLrF820+uw6SdFXSAV+RAFXxmsy7isJdZ9U3i0Qt66SJO3vV1aos3wqv0/jPVIgkm9S0nVlmyAsJGyCsmgx0yKNxCJ9dptwabhNu7JeSb5X25LM3nkbgZoQMGHXBJt/lFcEZJt+WnX/LvUX6TAra27OF/FAoBA1F++TTpSBRA9pI2lL4n6T1MXYscNJX0mX7/yNgBF4HgHOk3UyAoVEQESNzrxppcR6dioSPd7TELcI/DypiwfXM3/nZQSMQPcImLC7x8h3GIHCI4AtN5bqCw+GATACKSFgwk4JeBdrBPKGQCPU73nDxPU1Ao1EwITdSLRdlhEwAkbACBiBGhEwYdcInH9mBIqEAFu7+vTpE86Npt146hWp/W6rEcgCAibsLPSC62AEMowAqnCiwREFjktcvUH/423vZASMQAMRMGE3EGwXZQTqgQDCbXzVI7/u8qAsQrfGAWZ0/3Z5jdd+yHh3Bfp7I2AEOkXAhN0pLP7QCGQbASKzQaCoqZNOEDYnV40fPz6EbZXE/e86uvSJpMt1/kbACJyMgAn7ZDz8nxHIPAIQKPHPFXUshFTl/yQS+bIgQLoWQUdTpkwJpK1yTdZJAO48jUA3CDjSWTcA+WsjkDUEsCePHDkyHFZCvGuCmvBa70Q5nGDGxclllKmFws90/aLeZTk/I2AEukfAhN09Rr7DCGQKAanD++rYzxAmlIAmnCqVBGGjcufkMo4bnTp1KoejrNAZ4a+Q5F3/1UGmEHZljEA2EbBKPJv94loZgVMiIMn32yLOoKJGVZ2ULRu1O4SNKhzpWh7iT5msT9kt/sIIJI6AJezEIXYBRqB+CMjhS5xZetPdd999pSTeIRyxuW3btnBy1+HDh+t6GIiOIY0WLVoUnX766dFpp532rFTjt9WvJc7JCBiBahEwYVeLmO83AikiILIOx3Odc84543QM6FM68rIsKbiESvyRRx45cYZzb6qIoxle6Mo/mj9/fnT22WdHkyZNOiwC/0T7giH5I8J60wD/1gg0KQJWiTdpx7pZzY3AwYMHW+S9/b05c+aUzj333PJZZ50VHMPw6Bap96rxOJnNmjUrWrBgAUQdPMSlhv8QmcYLhl4V4B8bASNQEwKWsGuCzT8yAukiIEewQ5J236Azqr/x2te+9nVbt24NTmh79+4NrxyFGZ+w1V1NCTvKhVc40vX06dOj8847Lzr//PODOlwE/hpJ29+3dN0dkv7eCCSLgAk7WXyduxFIDAFJu0claf+7CPWaQYMGtdx///3R/v37I6nJI4j7ySefjPR9OBbzVJVAImc/N/ZqvMFxZps9e3a0ZMmSsuzXJX3/CpH1T/i9petToejPjUBjEDBhNwZnl2IEEkFAZHq9Mr7+gQce2HXFFVdMg6BXr14drVy5MpC3JPDgiCbpuNPy8TDHA3zy5MnRGWecES1evBgHMzzDS3Jqe5vs44GsO/2xPzQCRqChCJiwGwq3CzMC9UegXVU9/eGHH75z4sSJZ0m93Q87NtIyh3XgPX706NEgaUPcfIf6G+l62LBhQbKOCRuvcOWxTST+OpH5mvrX1jkaASNQKwIm7FqR8++MQEYQQFXdTtovefDBB/+HHMbeJPX2OY899liwQ7P1i/e8krBXExsc5zJJ0SdeRd679f9PpV7/rsk6I53rahiBCgRM2BVg+K0RyCsCsX1ZKuy/efrpp7916NChqyVVH5WX9zFJ2X8q1fi0xx9/PDQPwsZmLXJ+UmFNf0/fD9HVVyS+UmR9Jze1LwA616PnFSTX2wjkHAETds470NU3Ah0REOnu1Wd/F3/+61//+i599iNFRZvEZ6jERdD3a6/1eVJ974nvq3yNFwCVn/m9ETAC6SJgwk4Xf5duBBJHQKS8Tp7jsxRq9ETcBW37ek7HZR5OvHAXYASMQN0QMGHXDUpnlAcEpOrts2vXrqEir9lSDX9WxHU+25/0eTiyEkcsonxpP/Lnjx8//kVplXfPmDEj98TWDG3Iw/hyHY1AkgiYsJNE13lnDgF5Un9ApPzX2HNxwpKTVrRv377gQc0RknhN44yl1/dLbfx+Sac3qBGvr2yI7buVaPi9ETACjULAhN0opF1OKgiIlCc89NBDV4uoh8iWO2j79u1/pr3KZX1eIhoY+5YJOCJp+oTHNB7UBBOR3TcaPXr0ZTfffPPfyUFrl7ZJtYjEn5Z99wupNMaFGgEjUGgETNiF7v7mbrwk4aEi409Iin7Pli1boh07dkS7d+8u6/9A1hyYwR5leVWHMJ4EEUElHl/tB2C0yVnrfTpsIzhrSQp/Vvn+p0h7X3Oj59YZASOQNQRM2FnrEdenbghoK9NFIuT3IEGvW7cuWrNmDYRdInznkSNHAgETbxv7NQnv6fiV98TV5rxpVOWSrMOrPu+nU7H+VvedpCYPP/QfI2AEjECCCJiwEwTXWaeDgAi4n0j56IYNG6Jf/epX0caNG4N0ja06DiCCCry7FBM4Evjtt98e1OecXnXRRRe9bv369WVJ5K9VkJLvdpePvzcCRsAI1AMBE3Y9UHQemUJAcbWPSqoui1RLP/rRjyLZrSMFEgmqb9TgSNU9SUje2LmRxtul83DcJEFHIPGFCxd+S9L2aZLCrR7vCaC+xwgYgV4hYMLuFXz+cdYQ0ClVl4iwo02bNpWwW3Ny1YEDB4JTWU+JurJN/IbriSeeCF7lEP7mzZuDGl0HZPSTg1q/yvv93ggYASOQFAIm7KSQdb4NR0AS8TSR9E9QX3/ve9+L5B0eSQKumaw7NgDiRqV+2223hYUAp1rJk9zhOzsC5f+NgBFIBAETdiKwOtM0EBBB/5W2bhEYJbrvvvuCOjv2AK9HfVCR41Uux7VIMbgDefO/kxEwAkagEQiYsBuBsstIHIFt27b9D6mqf0uq8AjCJjBKNfbqnlYQ0iZfCLsWFXtPy/F9RsAIGIGOCJyILdzxC/9vBPKCgIKgTJTX96vwAudCDc75zxArBOtkBIyAEWgGBEzYzdCLBW+DyHmWCPtinM248AhH+jVZF3xguPlGoMkQMGE3WYcWsTlSTw+RrboPkczYwqUwpEWEwW02AkagyREwYTd5BxeheZKuy0jU7JnmQhXuZASMgBFoNgRM2M3WowVsDyFEY/U3r/H7AkLhJhsBI9DECJiwm7hzi9S0OIxokdrsthoBI1AsBEzYxepvt9YIGAEjYARyioAJO6cd52obASNgBIxAsRAwYRerv91aI2AEjIARyCkCJuycdpyrbQSMgBEwAsVCwIRdrP52a42AETACRiCnCJiwc9pxrrYRMAJGwAgUCwEf/lGs/nZrC4iA9qX31WEoUxUR7qSzu7V//YGRI0c+XkBI3GQjkEsETNi57DZX2gh0j4BCtL78ySefHL1z586ZigT3ScVcL/Er9qz369cvamlp+c7WrVu/09bWtnPMmDH3xDmK4HVLyaemxID41QhkBAETdkY6wtUwAr1BICZZpOlHH330z5944om+Ohv8vXo/mMNQDhw4EOn/EAWOyHDDhg2LRowY8YZRo0a9QZL3rj179vyotbX12JAhQ34psv42dYnz7E29/FsjYATqh4AJu35YOicjkAoCMbGuX79+xV133dXvscceW/LQQw9FIu1wEIoORgmv/E+SZB2JmMMFcUstPl3E/bt6jYYOHXrd6tWrPyCp+1si7s+m0iAXagSMQKcImLA7hcUfGoH8IID6+sEHH9x05513zkWSXrt2bbR58+ZwEArSNWeDHzly5MT54Lo/6tu3b1CLoxrv379/IO8pU6ZEM2bMaJs3b965S5YsOVfnit8vIv9WfpBwTY1AcyNgwm7u/nXrmhwBnf/9KZ1Q9uFt27ZF9957byTVdrRmzZpo06ZNJ4i6JxBA2vv374+QzJHIIXJd199///0HJk6c+Iue5OF7jIARSBYBE3ay+Dp3I5AYApKq/1hngH9YavBIxBoIW1JxJBIPZK1jR3tcNvfK3h1xprhs2hGSuf4vX3LJJbfJw3z28OHDt/U4M99oBIxAIgiYsBOB1ZkagWQRkOr7z+UB/lGk6VtuuSVIx7t37w5qcFTgELBs2z2uBPeLmANRx7ZvvMqnTp2KpP11Sd5fGjt27Fdje3mPM/aNRsAI1A0BE3bdoHRGRiB5BGLCPHjw4J9C0NiqtW0rqLIhWqTjWhOkHRM3ZI+a/Z577oHEl82fP3+ZFghPxx7ktZbh3xkBI1A7Aibs2rHzL41AwxHAwUzbs34XqXrjxo2R9lEHskY6hmzrkY4dOxY8zHft2hXdfvvtwS7OVrDRo0e/W/mHLV/1KMd5GAEjUB0CJuzq8PLdRiB1BKSq/vyWLVsibeMKZCrJN3iB16tiCrISbODYtLdv3x5pm1i0cOFCXvvUqwznYwSMQPUIOJZ49Zj5F0YgVQS0RauEGhwJm21cvVGDd9UQbOE4sVEGjmxaGFy6b9++f+nqN/7OCBiB5BAwYSeHrXM2AokgAEGzBQuPbtmyw/7qJAqiHKRryoCwRdZl2cnfKY/0a5Ioz3kaASPQNQIm7K7x8bdGIHMI4BAGmXLxPsmEepxyIG2px0vYtbXv+yKV25pkuc7bCBiBFyNgwn4xJv7ECGQeAaKVcTUqPfXUU5H2fQcVuRzQ3idV+ahGle1yjIAReB4BE7ZHghEwAt0iEG/5QtqW1N1Xi4XCzB2NXBh12xG+odAIFOahK3QvN3nj4zjZqG9JSauJmxzOwjeP8RNfLFTY5uZkBLKAgLd1ZaEXGlQH7dmdqZOYBsnrt4wHMFfekybUsqJ9TaMtxMCGvJlkTdp579n06h9va8MMoDPFIwWoGfKud71r2mmnnTY0vVq9UDJx37kGDx4cXl/4pj7vyJsUlzF+/PhIh8D0mTx58n31KcG51IqACbtW5HL4OzkL/ae8ixdwQASTEZJD3okNdSXBQ+S5XJbXdIk9yRC3kxGoBQHImmcDr/jDhw8HZ7tf/OIX5+oY0l1EfstC4qQ1jkeFsAcMGBBOXqun2p7jVzn8hbx1zGo0cODAUJ6erYU6fnV9FjAoah1M2AXpeRHzWZp4Rvzyl78Mxy8qWlaQsPNO2HH3aaItIWXTnmZpU9w2vzYWAez0LGZjRzvitWcpIfmOGDECqTcaNGhQkITrRdjkA2FD1iwIJkyYEOYJFglatHxLz9ZS3fNMlvAoUl1M2AXobR21eKnOSL5RkuhQ7aUNoSyRRGObbwEgcBONQI8RiBd9PB9ZtF9DqJh+CEcLeRM2tl6ETdvJnzwhbSR5AvToiNVo0qRJC/T/qhtuuOEpnZteGjdu3DBJ4mfqUJhDPQbXN/YKARN2r+DL/o/1AA6RKu86EfXQOMwkD7vJOvt95xoagc4Q4NmN/TX4vl5kXVkWecYXB8xIFR7piNVo5syZ884555xA6qjNReD2yKsELuH3JuyEAU47eznNTBJpvxObHJfs2HU7JCLttrl8I1BUBJCEGyX9s8DHTIBNH5KGuJG+JYmXFyxY8IwOiBn00pe+1GryBgxGE3YDQE6zCBH0McJL3nfffdGqVatCqEm8qJ2MgBEwAj1BgMUBpM0CAS0dseW12yRatmxZSeekl5cuXfq0yHxma2vrjp7k53tqR8CEXTt2mf6lHjJptEpl2biuhbA5xKHZHM0y3QGunBFoIgRQw8c2fZzxIHDZrnFKK02ZMiXS1q+b1dxZTdTkTDbFhJ3Jbul9pSBrbXO6UVu4fhOnEW17Ck4qrJJZMTsZASNgBKpFIJ47sKFzxKsOgwnbyuS1Pl5zzX/Ipv3xkSNHrq02X9/fMwQc6axnOOXyLq2Er1LQh5a9e/cG6dr261x2oyttBDKHAAt/YsuvW7cuELdU44NF4tdoa+XCzFW2iSpkCbuJOrNjUx599FGORAw2J9RY9gzviJD/NwJGoBYEkLQhbS5MbTi0sjdc28EsBNYCaA9/Y3B7CFTebpN3+D4k65UrV54IlBKrs/LWFtfXCBiB7CKAf8yGDRui9evXY2v7N/2/ILu1zXfNTNj57r9T1l6BUfoRWIHVL3YmtmWYsE8Jl78wAkagRgQwtUHa0uiVcEbTPONtKDVi2d3PrBLvDqGcfS/V9wSR9cflANKmuOERccOxNZmwc9aRrq4RyAkCCAZycA1hUg8dOtQUhwplFXoTdlZ7psZ6iazfJIn6d+QEEk4aYksXK2AnI2AEjEASCOAxfvDgwTDfMNcgZTslg4AJOxlcU8tVq93hbOFiywWStR+e1LrCBRuBQiDAHINgwAV56/VwIRqeQiNtw04B9CSLFEmXOW4SZzOczggn6GQEjIARSAoBpGp8ZTg7nNcxY8bcKTu2hcEEADdhJwBqmllqtdsfmxJOINiTHIY0zd5w2Uag+RHAmZV5Bj8ZHFzlfDZO27yubv6WN76FJuzGY55YiXpwJumw+atwNNMJXcGuxBnRTkbACBiBJBGAtNHm4eiq43zLEhq+o8/6JVlmEfM2YTdRr+th+a6czhYSxAAnEEvYTdS5booRyDgC2LKZe3bu3FlCPS5b9scyXuXcVc+Enbsu67zCIus9IumlCkUanD94eBw3vHOs/KkRMAL1RwBtHqY4TvNqj/3wlvqXUuwc7RjQJP2v/ddTUEfxsEjKDmTtUKRN0rluhhHIOAKoxLFhQ9iclQ1hS2Don/Fq5656JuzcdVnnFWY7BWooLrw2eYCcjIARMAKNQgCtHvEf0OxxjgEE7lRfBEzY9cUztdw43IOHBdu1CTu1bnDBRqCwCKASR2BAeICw9X+QGiQ86LTfkiWIOowM27DrAGIWskANjjqcYCk8ME5GwAgYgUYiwNYu5h7U4Vxyem3T62+YrOvXCybs+mGZak48IByliR0badsq8VS7w4UbgcIhwJyDOhxJmx0q2to1RNf/ksZveuHASKjBJuyEgG1ktnpQhiFhow7H6cMq8Uai77KMgBGIEUDKhrQRIFCPi7Dn6Lo2/t6vvUPANuze4ZeJXyt2uCIC/jp4h6OScnSzTHSLK2EECokAkjYSNj41o0aNihTMaUAhgUig0ZawEwC1kVmKqK+ErAm8z6o23n/dyDq4LCNgBIxAjACELak6mOg4iEgCxHki8HHx936tHQETdu3YZeKXUoH/k86i7cNq1gd9ZKJLXAkjUFgEIGsuIp4pRGm0YcMGbNpXyEy3tLCg1LHhJuw6gtnorETQl2vlOoBVLBI2tiMnI2AEjECaCEDYzEecaYAjLGY6BXHypuw6dIoJuw4gppWFyPoarVxHsZpFBeVABWn1hMs1AkagEgFs2DjAckHYmOqceo+Anc56j2FqOcg2NCTezuXIQql1gws2AkagAwLx1lI8xSFvXcc73OJ/a0DAEnYNoGXlJ3iDY7dG/WTv8Kz0iuthBIwA5jm2l0LcXK2trW+TJnCwkekdAibs3uGX6q8JUIBkvXXr1rCFwmqnVLvDhRsBI1CBAIcPIVDoBMGy/GzeqvnqHRVf+20NCJiwawAtKz+RhP0s6iZCkiJl24adlZ5xPYyAEQABhArZsUuKwChftPLfG5XeIWAbdu/wS+XXihd+mqTpz8gD88x4O5c9xFPpChdqBIzAKRDAWxzCZo4SYZdQjTv1DgETdu/wS+XXeghGS6J+Ldsm8BD3udepdIMLNQJGoAsEYsLmQKIRI0YE57MubvdXPUDAKvEegJS1W/C4JHY49mscOyBsnYiTtWq6PkbACBQcATR/mO0w2SFtO/UOAUvYvcOv4b/eu3fvQBH019esWRMpwlk48IOVLJeTETACRiArCDAnIVDs3LkzBHWCtPXZQAkXz2SljnmrhyXsnPXYgAED+mjQz2XwE5QAu5BV4jnrRFfXCBQEASRstIHMV7xqX/Y3abrmMKsEaxgDJuwaQEv7J2zfwi6EDZvABBA2q1knI2AEjECWEGBeYr4iTgSkresqbfF6j6RsT1g1dJQJuwbQ0v4JextxNoOwOanLEnbaPeLyjYAR6AwBCJvtpqjGIWwEDM1fH+zsXn/WPQIm7O4xyswdqJHGjh17CMJGFY6KKXY6y0wlXREjYASMQAUCkDaqcQibLV5ylh2oz+ZX3OK3PUTATmc9BCoLt6FGIgDBqlWrgv3a8cOz0CuugxEwAl0hAGHjIU5ExoEDByJxT1L6sH5zXVe/83cvRsAS9osxyewnBw8e/BKOZhA1NiFUTcQTdzICRsAIZBkBzHbMW5jy2gWN57Jc36zWzRJ2Vnumk3pJBf4OtnJxxizqcNuuOwHJHxkBI5ApBGKVuASOaMiQIdHUqVMRNkzYNfSSJewaQEvjJxr0gxSA4ChkTexwbNdORsAIGIGsIwBhowl8/PHHYxs2hD006/XOYv1M2FnslU7qJLJ+q0i6lVUqKiWfzNUJSP7ICBiBTCKANhBHWRzP2lXiV2su+81MVjbDlTJhZ7hzKqsmz/A3Sw3en61c2scYBj8rVycjYASMQNYRgLBjL3E8xbUdtUVz2vdE2mdlve5Zqp9t2FnqjS7qInJuQarG6QzVkiXsLsDyV0bACGQOAUib7V1sS33iiSdiocNCYxU9ZcKuAqw0b8UjnEFOXF5WqATUdzICRsAI5AkBbNnscMEPBwe0MWPGjM5T/dOuq1c3afdAN+VLsg4xdyVRH4Ow2RZBtCBL2N0A56+NgBHIHAKY8XCYReggvHJra+sf6bMBmatoRitkws5ox8TVIljKtm3brhFRn4U6HJUSg97JCBgBI5A3BGLnM/xwFASK+ewVIm5renvYkQaqh0CldZucM16lrVz/sX379jDAUSmZsNPqDZdrBIxAbxCAsNEUbtmyJcSRwHN8xIgRPrmrh6CasHsIVFq3aQU6JFaF42XJgJfUbdJOq0NcrhEwAjUjgMCB/83evXtDmFLs2WxVdeoZAlaJ9wyn1O5igEPY2HvYvwhhW8JOrTtcsBEwAr1AIFaJow5HLQ5hjxw5cmovsizUT03YGe9uHDQgagY3R2lC4E5GwAgYgbwiwByGKpztqUjXOhhkvQSSV+S1PY2stwm7kWjXUJYG81GIGhUSg5vBbgm7BiD9EyNgBDKDAGY9HGjRHO7atQvP8R9mpnIZrogJO8OdI2Ie3L9//99gGxcDO7ZhZ7jKrpoRMAJGoFsEEDo4cpNtqpyPIGHk8W5/5BsiO51leBBoEA9VwJR3oxLHjo163NJ1hjvMVTMCRqDHCBAMCkEE7aE8xXv8uyLfaAk7o70vYi5pQB+QOryMZI3Nh5B+JuyMdpirlTgCHvuJQ9ywAuhLJGwinu3evTsEUmlY4TkuyBJ2RjtPavAJeFLKvlNqP93G519ntK9creQQwKsYSYzIfvbfSA7nNHKOCbtv377RjBkz0qhC7so0YWe3y74GYaMu0ildlqyz20+uWYIIQNI4J0HavDo1BwJI2PQn0Rvlp4PHeB99NkDOaEeao4XJtMIq8WRw7XWuWn2+HGczLtThSBpORqBoCDDuka5ZtOLDAYE7NQcC9CX7sPHPkblvsDSJ/ykCP685WpdMK0zYyeDa61yZpLDv4EHJgLb9rteQOoNeIpDGGOQ5iPfr8hxYyu5lJ2bo53EQFXx05KvTR062V4jAv6B+npehamaqKibsTHXHC5Vh9ckEhf0aZzNL2C9g43eNR4Dxx8W4hLhblBpRC2majjP+0TJB3mksGhrRziKWQV9i6oj7l/lOfXym+vqMIuLRkzbbht0TlFK4B/Xfnj17QlABJAwnI5AWAhA1wXs4i72trS2ophmfSSapRoepjMc3bNiApqmsid0HRCQJeIp5ozVBMOFAkKlTp3JGdoq1yXbRDVklZxuC7NROK84wKem1Hx6U7FHE8YyVpyXs7PRT0WrC2GPRyFhkTELWffr0OZwkDprEFxBUg0WCxn/J4z9JtNPNG0mbA0Ew/+GzYwHl1P1hwj41Ng3/hrOv5RV+zdatW68nDGnsaOPJquFd4QIrEGBCRSXNZAqJtl8fFpEmZmuULfNGyHrTpk2OoV/RF834lvkNoYT92Mx7JuxT97JV4qfGJpVvtNL8bR308UrOv05a7ZhKA11oLhFAAkLrg5lm/fr1ZW3Feb9OWbpMjVlYrwahYWLRqnLOWr169Vhd0e233x4OvqFsp+ZEAL8Itndh/hg1alTU2trqrQCn6GpL2KcAJq2P5TH5DPYcVpzYdpBunIxA2ggwqeL0BXFLCiqhvpQGaEFcL8g2fl/raztZL5Uk/1/YzJHoubxwrRXRfPyOOY4FGZI1WsXRo0efno+aN76WJuzGY37KEjVw52lCnMvpNQRMwXvShH1KuPxFgxFAdYkN+2c/+1l0/fXXR6tWrYo2b95clkboBsi2t9XRWO+/du3ar9x6660Tbr75ZiT5QNhM5jYL9Rbd7P6evmUhiI8EGpxBgwb9hcbZXo2HXi8Cs9vq2mpmwq4Nt0R+JbvdhZKq5yJVoCJiojJhJwK1M60RAWzZ2JbXrVsX7dixI0yykoyu1pj9kMbslFqy1RgfKq3SNEnt31A+Z2zcuJGFQFgcEFgD6d6puRFgexdaRSRsJG2Ns8kaCxOau9XVt8427OoxS+wXGrRjNUH1IWDKQw89FAg7scKcsRGoAQGkIVTUTLCShkMOU6ZMaZk7d+5fDh8+/C9F5r8zffr0b0jiPoSE1J3kLU3SW2S7fKXG/XVIV+SJZI2GiYnbZF1DJ+XwJwgm8djCHILAMmDAgJ+qKfNz2JzEqmzCTgza6jPWgD3KQEVywUZolXj1GPoXySLApIrmB8Jevnx5hDQ8bdq0aOnSpdHkyZOjZcuWfRmnSUnMPxdZf76r2kiC+qiuT2pXRHT33XeX16xZU4Ko8UKHrCmD8pyKgQCkjUYFgYX9/kOGDLEtu0PXm7A7AJLWvxqsg+TMsxCVI/YcLjudpdUbLrcrBGISJaQkpErQM3mMh8l26NCh0YQJE64ZPHjwq6U2f71Iu18neeEJ3ke+GstYmLJ1S7siSvExi+TLYtWpWAhA2CwGcbrl8hh4cf+bsF+MSSqfaFX5KpH129iHiEoICQPCdjICWUUAr3HGKJMsY1bbcSI5jOE0BIH3nzRp0oX9+p3M10zKsbc5i1NJ2GHvbWy/jKX3rLbZ9UoOAcYG42Dbtm1hEYjGxulkBEzYJ+ORyn9SAY7VavLfNXmVNWBLrCyRXBjATkYgqwggaTNGIV7s2pKmgxMa5xsjcaPa7oywGd9okHhlguY9ecX5edxntceTrRf9zjhi3AwbNiw4oCVbYv5yN2FnoM9k8yNWMo42JVRBSBmetDLQMa5CtwgwTnEMq3QOg7j5H0laIUwDkVeOZ6RyvmPMx1J6twX5hqZHgDHC4g8/hoEDBwYtY9M3usoGmrCrBCyJ2+URfpyJC2cznM4qJ78kynOeRiBJBJh4cR5Cgu6YKom78n3H+/x/8RCIxw1SNoSN8KJ58Y3yFv+2vtM6sPd7/fOOqvdhZ6AHZ8yYMQvVIGTNCjN26slA1VwFI1AzArGau/KVSTm+as7YP2xqBBgfaF/w45H28VuSuN8DWSsVPpCKCTsDQ1+ryf9NlB+8ZFlV2tksA53iKhgBI5AaApgFiapHAB359vyjiPvdlrCjyISd2pB8oWCtHM+PgwWgSrSE/QI2fmcEjEDxEEBowRmRXTNEP5Nq3IdkaxjYhp2BZwH1D56RxBC3DTsDHeIqGAEjkCoCEDZb/pgT2S7IKV5OlrBTGwOxPUZBIs6JtzLgHelwjKl1iQs2AkYgIwigEoewiVtPmGbmRScTdmpjAHuMpOl3yWb9E2w1eNSKxFOrjws2AkbACGQFAXbKoBKHtHHIhcCdTNipjgHZZv5EK8g2YiljpzFhp9odLtwIGIGMIIBKHPNgHK5WPj5PZaRqqVbDTmcpwi+SPoztmmD37MM2YafYGS7aCBiBzCCAhI2pkF0zqMTHjRv3OZkPz8pMBVOqiAk7JeAplj3XrCLxhOwsyESKVXPRRsAIGIHUEEB4QYhB88hhMOyi0Q6aldreNTq1SmWgYBN2ip2AjQb7tSXsFDvBRRsBI5A5BCBs1OIIMpA2UjbELcm7LXOVbWCFTNgNBLtjUXg+QtYETWH/tVXiHRHy/0bACBQZAWJSoImUZB2EGx0s0+UZ682OlQk7xR7WQOyPhI0d2yrxFDvCRRsBI5BJBBBiIGwEG0nZHJL0qkxWtEGVMmE3COiOxUi98/9rMM5lywIX6h9L2B1R8v9GwAgUGYFYwoaw5esTjh4uMh6OdJZC70uqfotU4B/Eho19hhWkT+hKoSNcpBEwAplGACEGc2E7YQdHtExXOOHKmbATBrhj9lolniWi/jcNwLJU4SXIGunayQgYASNgBE5GAAkbwo63v+L3IxIfrMBThdyXbcI+eXwk/p/2FT7HFgUFSynhSGHbdeKQuwAjYARyigASNnMkcyZRz9gCK1s2cUoLyV22YTd4IHPQB6pw9l+jDrd03eAOcHFGwAjkCgFIm9CkSNrtPj8lSdwfyVUj6lRZE3adgOxpNqjAid6zZ8+esFokOICTETACRsAInBqB2PkM1bi2wbZI2HnLqe9u3m9M2A3uWwiblSKkjaRtZ7MGd4CLMwJGIJcIIGVjwyaAisKWPpfLRvSy0ibsXgJY7c8hawbcvn37gk3Gp9BUi6DvNwJGoGgIIGGjDmfe5EAQzaMLJPR8rmg4mLAb3OMaeC2sElHtIGVj03YyAkbACBiBUyMQb+8iKuTevXuDpK25c8ipf9Gc35iwG9CvGmwlitFWrjeMHj36TRA26nC8H60Sb0AHuAgjYARyjUDsLY52Eo9xTvKSw245142qofKFdI2vAade/UR7Bssi6Su0JeHbDDRJ12WpdEpI16h6nIyAETACRuDUCEDY+P8QQGXUqFFBPV5EYccS9qnHSF2/kTT9hXgfoQZeCdu1ybquEDszI2AEmhQBCJsdNWgnMSUi+GgOLdwWGxN2gwa4Btrw7du3R1u2bAnOZo4d3iDgXYwRMAJNgQASNWZEnM8IOqVYFr8jbeVyCUKTmqKBPWiECbsHINXjFrzD2/cQhoAplq7rgarzMAJGoCgIMGdC2kjXSNmKeNZH+7HPl+Q9tigYmLAb1NOoc3CY4GKVaMJuEPAuxggYgaZCAO0kUjYmRl5F2sebqoFdNMaE3QU49fwKr/B4DyF2mCI6TNQTT+dlBIxAMRFA+EElvnnzZqKeIfycFu/EaXZETNgN6GENphYNshZImxUhAw4nCicjYASMgBGoDgGEHc5h4DwGNJaDBg36Y+XQr7pc8nm3t3Ul3G8i6SWytXxeA6sNG7behz3YVoknDLyzNwJGoCkRQOBhLm1tbY2mT59O8KkLpL3s05SN7dAoE3YHQOr9rzb5v1ED7ELU4FxI2Y5uVm+UnZ8RMAJFQQAbNpL1gw8+GIKoQOCQdxGSVeIJ97IG1jDOcCU6DwOLweZkBIyAETACtSEQe4ojAGFiRAjq06fPmNpyy9evTNgJ9pdsLG+Srfr3dZRmGVU4hG3bdYKAO2sjYASaHgHMiey0wY7N9i4EIs2ru0Xeo5u98SbsBHtYBH2EFaC2H5RYDVq6ThBsZ20EjEChEIglbbSXXIog+W/NDoBt2An2MBI1q7+tW7eGE2bY8G8JO0HAnbURMAKFQQBJG1v2jh07ohEjRkT9+vU7t9kbbwk7wR5mBUjAetThDCyczUzYCQLurI2AESgMAhA2QhDbu5CwFU2y6R2ETNgJDm8O+MDOAmEzoEzYCYLtrI2AESgUAgg/hHxGi8mF81mzJxN2gj2s1d9xJGui8TCgIHBL2AkC7qyNgBEoDAJI2JA08yuRzyQc9dH8OqyZATBhJ9i7AwYMeCUDCqJGPW6yThBsZ20Eyk+55QAAQABJREFUjEChEGA+xU8o3t4lDSY+WfOaGQQTdkK9q1Xft0TU75U6vIwdm4HFitDJCBgBI2AEeo8A8ykmR85oQMqWcDRYu3Le2fucs5uDvcQT6huR9Bu1/xpns5JV4QmB7GyNgBEoLAJI2MytbJdlP7bm2ha9ntHMgFjCTqh3cTJj1YcNG3W4kxEwAkbACNQXAaRsnHlxPmv3Fj//wIEDn6hvKdnJzRJ2An2hQCl/d9ddd51E2LZfJwC0s2w4AqVSiTCQUUtLS8R7Lt5rD2x4X0uFeDaYeCtfWeTGVy15+jfFQCCeV+PtXezIGTx48JBmbb0JO4Ge1YrvfVrtlWVbCRHOLGEnALKzTAWBvn37RkOHDo3kUBn1798/4v8hQ4bEgStqIm1Umvh4VF44a8ZxolNpqAvNFQKoxiUoBXv21KlT36Oxc+OwYcN+matG9KCyJuwegFTtLSLsslTiJbYa4MFowq4WQd+fBgJIy6RKybmjJK2zh6PRo0cjxUQDBw4MpyQRZWrSpEnhfZxHT+uPhARhQ9A4Z8YXNklOYyK/OKRvLIGTd+zAyWv8vqdl+r7mQ4DFXmyGlLQ9VATelIeBmLATGLsMnvYY4sG2YsJOAGRnWVcEIEZU3ai2IWKk5uHDh0eSUgIRxwQNYbe1tYV7kLC5kLjHjBkT3ldL2DQCQkalGV+VBzvgAwKJI0HxPe95vuLPeM54H5N6XUFxZrlBgPHBIg+VePvYaMotOSbsOg5JSQCar0plJhwmEgYQzhCWAOoIsrNKBAGkVwibc4VHjRoVTZ48OZo+fXo0Y8aMoO6eMGFCNH78+PA9pM69McmjFoe4JY0/qHyO1FDBqSxqeU545YKAcSaCpJmEeZ54feCBB4LWSo5FwaGTnRg8Y07FRoCxwuKOMcJ4aNYFnAm7juMcstZEsnnTpk3Bds1Kz2RdR4CdVa8RgGQhWIgZSRqJGWkaSZoLqRppGXKeMmVKJHtgIGypwX8tEh8lQu7TRSXKXXzX1VfP6+I7uUP1PS5S/pYm5Ddio4zJG+JmDy6EHZueIHUWy5ihmLSZxLmcmh8BJGwIGzMK40JamFrHYqbBMmHXsXvkZPYDTSRz2vdf23ZdR2ydVe8RiMka9TYSM3bnadOmRbNnzw6SNEQtdfcxkfn9ciprEaG36vXrkrj/O6W3a5Aaukexvcw3qfg3aQF8ta5/kvQkXj7M8/WciHm8iLo/oX/Xr18fCP3ee+8NRM7EDYk3q7TV+xHRPDmwMGOhxoIOW7a0QP9TGs7b5F/xWPO0MopM2HXsTU0eTzForAqvI6jOqlcIQNKor/Hq5kKqxkkMlTcSNCrvuXPnRqeddhq26FtGjhy5QqT94c4KVV4Nl1oqy9RC40bVi+tEklT1ERHz+ar3KzVpl7CnQ9K0mecQIsfmjWqdST1Wu5/IwG+aAgEt7IKfAws5jQfMki+RmeZaNe4fmqKB7Y0wYdexN0XWbOUK57MyWWCLczICaSEAaWFbRtUNOUPSSNZI1Ki88fYW0aEW/4VI+raJEyd+jLq2S7UNJ+dqcWqv56f4nVShf7Jo0aLf0+Jjxumnnx7IWtqu8s6dO0sE1Iil71jqrrYs3599BCBtFmcaC6WtW7eW582b9yXV2oSd/a5Lp4ZaxQ/AzhbbUUzY6fSDS41CMJPYGQzCxha9cOHCaNasWeVzzjkHSfS/pCr+G0mtA2XDXifS3hfjVinVxp9l8bWynuPGjfuMyPgmabmmSIOAqvzokiVLfr527dqyIg6WIGrsnDyTbCGzb0kWe7T3dcL8gS1bi7WSxgRq8lnyy9jW+5yzkYMl7Dr1g1Z3i2+77ba52FDwYGVSMGHXCVxn02MEkKrjQCbYpFF5I0nPmTMnqL0laZckdZ8v9fgavW+qA4S1CNkgoLhC2r1794L58+evBwf2k4MBDmo7duwIanPex8+pCTxGLb+vSNjMudiw6Vs0SpK4f6wWzcxvq06uuQn7ZDxq/k8P/oUaMIGwYw9WTwI1w+kf1oCAJM6gAh87dmxQe0NQF198cVB7i7SOS/3dImecK+VEdnsN2efuJ3Ko26Bnsk0q8a/o/eskeR3ftWtXH0ndkcg8uuOOO0L4YOyeSN9M+E75RgA/BQgb06S0SfTraflu0cm1N2GfjEfN/2klN7Td4SGs3nlvwq4ZTv+wCgSQHlF/43CFBzje39O1h5oJS3Y8Plsjsv6AJO9bqsi2KW7VIuZxNeT1NEZq8d+XduHvsXOiieBwHp5RVKg4i6JO5TJx57fr6U+20+JDxKsk7qZahZmwezk29XCXNDgWalV3DZI1Di54qcYeqb3M3j83Ap0igDTNBVGzlxq190UXXRTIGqLG61uOZE9Jmv6mJO73kAljVampJrBOwenkw/a2f0H+JeecccYZpwujc9FA7N27NzikrV69OpiyeH6Rtp3yiQALLvyISLw2W1+asHs5LrVtZLBWcd+RSnwuK3VsYmwh8Sq9l8D656dEICZrpESka5zK8P5etmxZNHPmzEje3mvlcPNZkfnDkqy/H2dUVLKm/bS9nbTfqdep8jV5tcwEkPbb2eqGGpXJXc5qJ7Z++RmOR05+XiFsHAxJCE4xYbf3fe4XqybsXo5Fqdf66yGfy0od73AeeD/ovQTVP+8SAaRqHKmQotmupe1MSNbl8847ryQP6SdFQFdLqt7RZSYF/DJesOh1j5r/JT2n/yLtxJ0veclLvoSWgq1fW7ZsiWTnDjZu1KpO+UIgVonHkrak7JLs2d9Rn7+hGUjbhN3L8cgqDpJGHY4KBtu1kxFIEgEIG4kaTc7SpUujSy+9tKx91WxdGiCpu4+k62eSLL9Z8tYkfkST+D9q8fMPsmeDYVnYlfCyB1ueayZ+7/bIT48jLMVOhGg8mZPVv6+XJvRf1d9vzU9LOq+pCbtzXKr6FCcWiLvdyaGq3/pmI1AtAiJs4nqPRR1OaFGRd0nbtIZqr7WNr1WCqUn8uXbJq7RmzZoy6tR4ooesec+zDWnbibRKcFO6nX6KiZv+xEwps1FrStWpa7Em7F7CiXcp9i/UaHidQtpORiApBNrJZZxUt/dIAnxaNupDut4lT/Cm2lOdFH6d5SvSDrZNmRgWKcjGV7R3ffq55547ZuPGjdHy5cujFStWhGfc0nZn6GX3M+ZmTJX4KBAgKLs17XnNTNg9x6rTO2OVOKTNe7zDnYxAUgjE5CJnqXOSKqOo+UoVvlZtXyY16u/Jw/6LaDDYz8tinOcaSS2W3oqKUZ7ajeYTDQmXFrqna327TL4KK/LUho51ben4gf+vDoGPfOQjT+KcEkvY2L2cjIARyC8C2gr3r5LKLiTm+oUXXli+6qqrogsuuCDEX+cscC2a8tu4gtQclTjqcKJOsuiSXfs0XWfmvfmWsHvZgzfeeOOXvvrVr4aBgYODH+ZeAuqfG4GUEdAzjHlhuZ7nyYpHvk8mh7ICrpQIO4y0htnLmrSUO6kHxeM4yJxMQCGkbfXZ0B78LNO3WMLuZfdIon4XqnA8E1nV2TGll4D650YgIwgoGM1+qcY/pC1zJbbQLViwIMRmhwAsaWekk7qoBoSN9hNzJYSt5H3YXeDV9F9JDV7Gs1RbBko4pDgZASPQXAiItD+tBfmNUo2vVLjXQbqi7373u5GO7QwqVyRtFupO2UMApzNixuPhj3pcpJ37jrKEXeM400PaTw/y05C1t3PVCKJ/ZgRygIC2BG3StrnXa5/2UU4/05nb4XAVqcpDpLkcNKGQVUSIQvOJpM0crahnMzRv988zGCbsGntPqpbPyj7Sum3bthNbPmrMyj8zAkYg4wgoctwPtTXoNTpT/Nnf+I3fiK6++upA2rJtZ7zmxa0eknUcbhZbtoj7fdrmNSfPiJiwa+w9qcLOl8qlhXNXsWE7GlKNQPpnRiAnCCgK2o8VsObP5IgWnX322SfOGmefL3HdnbKFAKYKTBbYr1GPY8+WQ+H/p89zG0TFhF3jGJO65Th2ETxH2Z9pwq4RSP/MCOQIAanB/1Lx2o/pgJXo9NNPL59zzjnhwBVikTtlDwFIG9U4QhVnPYi8r9uzZ09ug6iYsGscY6zc8D7EqYGVm53OagTSPzMCOUNAtux+qvK0iy++uMQebU5Jw57tlE0EEKYQrIiVwbY8BcTJ7UZ678OucYzJNvIczgys3FC5sJJzMgJGoBgIKCpaX2IuaMsXx5lGUpeHw0JQvcZHOhYDiey3kq22OJ3RNzihMWfnNZmwa+g5kfO8tWvXjkOylpd4IGurxGsA0j8xAjlFQCrwg/Ic/4j2Y0/USX2v0zUeW/a6deuC5s0L+Gx0bKwSZ56W02Aga5k0slG5Gmphwq4SNK3O5uqQj+/Ifj0V9QrStZMRMALFQkBHNj6pFv8lrb799tvPUACl8ajFsZOieWNe8CI+/TFRSdg4BiJly1H4ePo1q60GJuwqcZOD2TIR9ULOv8bZzMkIGIFiI6BjTdvY3oVa/J577jkhYcfRD4uNTvqtZ+GEvxGqcdTh8vAfpVo9nn7Nqq+BCbtKzPAMZ08fhM17JyNgBF5AQJLmeZIu58mxZ4gcMV+pSXKupJyJusK+J9l9j+u7tTrT+zuSeFbql8dlD96ozw++kEu+3smOfabU4ZMkYe8ReQcHJ8gBW7al7PT7kj6AqHEMxoyp8fafqtUZ6des+hqYsKvATBL1eBH1H3DuNSfAoF5xMgJFRYDQvCxakSTRNkFQP/jBD4I6GJUwqmE+4wQ7VJNcHFkp++8y2RGXIZWKuKPW1tbo1ltvZSINF7G6RYDvV1jQv8sDtlpsPKd67tW88InFixd/nDrfd999wdEJDJzSRYBxB1kzFpmzRdoLJXRdpfEFcecqmbCr6C51+Bh1/FIImyvP3oZVNNu3GoGAgIh5prxtTxNJH5N0vHDHjh1B08QkiFMPnrhxXAIInOcDwuJ7JkwShI3TD57VOAFB2gr9GSmSWLhkGw6qZU2mn9eieLgI/Q4R+Ebde3/IIMN/JGn/+c033/xxFiGoYIk3brV4NjqM8cciknGpvilrQXijapa77V0m7CrGkwi7TKczOXHOqlXiVYDnW3OHgCQTCY+lsgh3lsb7OzZv3vxqPQNLHnnkkUDO+j88CzwHfAY584pEzcXkCGF1fE6QoFFN4lXNqVdI1jqD+qQLBy6R9ychcEngt+qQnZ/zfsKECZ/MKpCbNm0aLLxC9cCGNsVbiqwaT7fX6IdYNa75u6QxdUTj8lKNxVvTrVl1pZuwq8MrrNIg7FiSqPLnvt0I5AaBdrL+hEj3tfJ+XihCihSLOdq6dWvw40CChpDj8I9MiPyPNMPF53wGiaGWJPE+XvTitcuFRKroU0E1rq1S4RXpG8kbRy5FE7t02rRpl6I6V8osYetQkKe1sPmQjuL8qylTprC4CO1GFQthxBjQCKfGIhCPQRaPzN0yywzQOGQsmbAb2xWNK02qlCdR++F0xsV7JyPQbAhoXE/UxLZa0vKR1atXj9f7fthkN27cGAh7y5YtQZKGhEiVRHSq9zFGfA+BQeaViQmVFL8ieRPuE1U50vr06dPDRPurX/1qv6TvFqnVV4jM3677H6vMJ833qgvbhT6tBf3A2bNnf2zevHkRCxC0CbS5Eps061nEssGei624mDPR7mhxOSBvWFjC7mGPrV+/vr/UJ7ukmgv2KWxUPIRORqCZENAe1UGa0PYrMFBwnLr33nuDnRrSiVXcLFQ7Em61GHQkr47/sxhASkdiR5KHvBUSNNLhGxOJLnbRRRe9RqT4qKSlPxWp/0W15Sd5v+zvf6u6XvCyl73sUqTs7du3B7NAvMBJsmznfWoEGGOYbPAtYCGVR4dAE/ap+/ekb2SPmsPqjNV+rAa0XeokiPxPjhHQRDZZaum+WoRej38Gqm+OjsUWyxZGxjyEE19JN5XJNVaxY4LCWS22i7NgYPuUpKSy1Omf1CL6GyLJ43Jk2510vXqSvyTtR7XgOQBZx7Z6nOtoT8eFSU/y8z31Q4BxjFqcMZTH+duE3cOxoIlsrbxWy1KFl+LJq4c/9W1GILMIiIxxlFqkxSjR+yYR+AOVN2SNrRryTms3BOTGFUumsVYLSZ/PRdSlRYsWlXVG9Xa14ZAWHedqYb0hC2BLbf8z2dzfLCmuJK1AWPBgRovrnoU6Fq0OjBnwpx8YS9IS5e4ACBN2N6NWnay5oFSmo+V4U4onjW5+5q+NQC4QEKnM1di+HUcc2asJsxnImhCbjHUcxLKSqAtqcp5FVJvYuSXBlvhcpD1EZP0h1fWtade3fc74iur2iBY7/y5Juw9SHSpYtAR5lOzSxrRe5dMHaEpZhIqwn3ecqFfmDcjHx2t2AzJkrc69mg7GWYHVmR1IugHNX+cCARHLABH1D+WfEa1YsSLYrJGsZccOqlwmtyyRCxJSbNdm0uVZZC84fiVoBvR6hV5XS51/JaSZVicwZ1C2HONu1Ja157C5I2UPHz48qPbTqpfLjYKmgwUfCyiN7UVa+H0gT7hYwu5Bb2ni+hwrelSF2PZQiTsZgTwjIOn5zSK7r0nt3fenP/1pIDzU34xzpECIEYLMaqJuXDgQQd44dul1jGzbYy655JKbVO9BulIPM6btaSVt9wpb1/AFYP7IOrZZ7fN61AttDOOFS0JYP4319yvOwHItplbUI/+k87CE3QOENTH0h6SZzIjaZO/wHoDmWzKNgCaqr4u0+6I1QkrFXo1kjSaJSS1LknVXQFJfFhq7du0KbYC4eU5V/yXSHAzp6reN+E7OZrsI+MJFgBic55zSQ4BxzfzNfI7jmcb6ND0L89OrUXUlW8LuAV5sYYGoCe4Q2/WyLH30oEm+pcAIiOAeR4V81113BXUynuDxQjQvRB13H88hEzD137BhQ1CTy2O8rAn5dsKfajKerC1h++P7G/mquuH/MlsBZzbJo30uW+QgbeYTFkVO6SDAmIGwWehhptB4GZpOTaov1cu9LjDjgeNrvAnbnc6CKoUHzskI5BEBLTg/LAl0IEFQli9fHt15553BNyNPUnVH3JmAsbejLcAGry1VpZUrV4b3em5TO+AhtmUrgMo82bE3EgSG/eRs8XJKDwF2HbDIwweifcvgWzROxqdXo56XbAm7C6x44OSU84eaCEaygkeFwsosb1JIF030VwVCQER9uWyoH5CDWYhctnv37qAxgvDirVN5hYM2sOjgFY0B77kUJnSK1OXfVqCMv5G3dmp2StmtP6byv4PzGYm5JO+Y53msIHRhOoGw9f5czesj1J4Hst4mE3YXPaRV1xnq0D/USmwAARAga1ZmTApORiBvCGjROVdOWqN+9KMfnVAf4wDVLInnkucTKbt9Io503OVYff4GqT6/o3amRtiyXT+JHXvmzJlh/sC8Rn09lzR+9MXjBMJua2sL87qeg3Bee+NrU12JJuwu8JKa7fVapc9od04IK2I/YF0A5q8yi4C2sSzUwvOTEBl7rPGShdyaLfF8oh4nxRIUdkppxVJdmWjPeAl1OHXhYBNp75oN+ly1B+2G/BvClScTp23YXQwzEXVJ0c0iVIfYO+hkE3YXgPmrTCIgNfgZ69atW/vjH/+4DZs1HtUQdp4mqmqBpW1Isd/97nejG264AZXYf8i8dUG1+dTrfsiaUKULFiwIUjanlDmlg0BM1owPtgWy0yAvi1cTdhdjRirwFjoTz3CczkzWXYDlrzKLgKS5NVp0lokjwAIUfwzsu81sQ8XPhOAYqMd1ldiyJrXnL9X2WWl0lGzoz3EOOI5nqGHZ3mUpO42eeP50OUxBLForTZ3p1Ka6Uk3Yp8BLarWpeqAuQYVI2EaIG8I2aZ8CMH+cOQQ0VoPeFYKWVF3CMxxPaqSJZiZrOoLnFCmbSZnnl/3ZLFgUvOTbaXSUPMNXa2vXrUjZijNusk6jE9rLjMcGZM34aHckTtVk0lM4bMM+BVJsplfHno+9j/16dCwd7WQE8oCAxqrWm6WytENfI/QohCW1eNAUNbMqvLJvkKLQjGHLZo82RypKsj2z8p5GvZd0fVBzyHtU3ve173c+KnGk7GZfODUK32rLYdHKnI72FFu2/Apm6ZnZzDNTbV6NvN8S9inQVsf14YFHskZCiR1ZTnG7PzYCmUKgnaw/I7K6Di0R0gTjmMmpKCTBAhvVOBIUUjahQZmk00pShe/QomE/9mwuFhC2ZafVG1EIEQtxt8cV/z7PDAvd9GrUfcmWsE+BEQ86JI1jAqEbmfCKMtGdAhJ/nCMENBEtVYCt37rjjjtasONKJR72/kJiRUq0l0UK2gU0C+PHpxsfQ6R9kzzFL9R+7FakOxYSaAGcGo8AYwPCRoNKaF6ZTIJaqvE16XmJlrA7wYpVlsh6LA8Sqy9ecdJxMgJ5QUBj9m0aw5NYcGK3RlPEIrSIi07ajXaBnR7tJPmUNA/D0uhLSdafkyr8MbZ3Eaa0b1/LTGn0Q1wmzwPbdtG8MNdnPZmwO+khrbhGabL7HCq0mKxRjzsZgbwgoAVmX0iKqF9I1xB2UROTMlI2kzLPtDzmB4m8N2u726I0MMFjXHbssCcbtbhTeggwNpjjWcjl4RkxYXcyVqQmmaMHeigOZ3QmahNW6U5GIC8IaMwehqDYZ8pWrjxID0lhy6SMhowJGXs+mOj5Hq/PXpNUmV3lC0njKY6U7bjiXSGV/HfM65WELe3q0uRLrb0EE3Yn2Ckq0V/hWcqEB1nzwDsZgbwgIGnyXI3ba5CwIWpUfkXxDO+qj5icwQLVONjIGS2VUG+owYl21traapV4Vx3WgO9i7QuLOYhbr+9rQLE1F2EDSifQ6UG+CNsfwRZwPHMyAnlCQBL1TC04p6H+ZeHJZGSTTjh1L6g+cSLVnugg4abRrxA2wVOGDRtmCTuNDqgok0VcbCrBIVEL25dXfJ25t5awO+kSpJF4xcV7vAmdjEAeEJCUME6E8H4k6/aAEEFD5DH8fDAVNGZIUti003IkZSsX0jXqcEc8S/epQsLmOUHzwqv+zzQnZrpyaXUlHYd0wpYLHmpPdmn1hMutFgGR0ViN2XOx1bLoRILw+H0exVglDjbtKvFq4a3L/RA10jVqcXuJ1wXSmjLhuYCwWcChiWJM8H+Wk1XinfQOanC2wrA/j/ee8DoByR9lEgGR9XNMQNhpIWyP3Re6CcJG88CzPX369NQc8eQjE9TxVom/0DdpvcNUhEocjQee4oyRLCdL2J30DlI10jUrcUvYnQDkjzKNABoiSJtXE/YLXcXkHBM2EhVq0DQShM1BIEQ7s4SdRg+8UGalhB1rpF74NnvvTNgd+kQT3RlI1UgoRDfD5uVkBPKCAOM1ttNaO3RyrzE5Q9IsxpGq0iJsSBp1OI5vJuyT+6jR/zEm4j36LObksxQclrTQzWSIUhN2hxEiqXo1DzOrcUsnHcDxv7lAAK0QEjavWbfJNRpQnun4ShMbxa32iV2N7vwuymMssMCV5mWCAuv8mLjiXdye2lcm7ArotY3rfpF1H1QjJuwKYPw2NwggXceEjUqc5IVnbrrPFU0JAZ4Rnhu0L5K0XyH/pc+kVJUuizVhV8AjFfjjqMKRsLPufFBRbb81AicQYBsipI26F4khTSnyRKX8xghkHAEImwUufkvt5pJMBuAwYbcPJHVYmzpqIOFIcUhh4nMyAnlEgIkHe1wsYeexDa6zEWgkAhA2cz5+S2hYs/rsmLDbR4WkkbdJKhmLSgT3fqvEG/m4uKx6IYB0jXaI8csrE5GTETACXSPAc8KzE4fzxREti8mE3d4rsl8sVScNjE9tsUo8i8PVdeoOAYJyxGE32TaEc5OTETAC3SOAhI2zJmQNeWcxmbDbe0W2vj50FoTNKsvSSRaHq+vUHQLs8WXLEKdBsdeX0JdORsAIdI0AEjZaKUxJELZV4l3jlfq3OOdA1KjEsWHTeU5GIG8IIGFzfOOQIUNC9Cbqbyn75F60meBkPPzfC3HmmfuxY6e1R7+7vvDyux0hJOpYws5DxJvuOtbfFxcBDpeAuHk1Wb94HMSYpK198MLhxX2T5ids64Kwmf+zasN2LPH2EYKETSfRWRC3VeJpPjouuzcIED0LKRvSTpuUetOOev8Woo7DgqYZZSyea1C72lem3r1cW36x01nWvcRN2O39y4MDWaMSp9P8INU28P2rdBHo6HSWbm2yVToLmeHDh0eTJk2Kxo4dG2z8adSQ/fHxbpSs2krTwCXNMuNFlM6Sj9jaq3gcmTy2yyrx9lEign4OlQhStgNOpPnouOzeIABhI0UiQfI+Vv/2Js9m+S1YgAsOedj4eZ9Gwj8GG2ksYVs1nkYvvLhMvMRxOkPDOmLEiNnql8EvvivdT0zYwl+rqk+qk95CZ1myTndAuvTeISAp8lgsRUJMqMRN2s9jioSNBz3SdVtbW3jfO7Rr+zVzDEIBAoLnm9owTOpX9AeLKY2RN0vT+oci7UxpoQtP2AoffqEenI9qO1fZD1BSj4HzbRQCY8aM2SyCfsOECRMCKeF45vQ8AixekKpHjRoV1OFoINJIqF+Za9jry3unbCEAacs8WhZxf0oxxSdlqXaFJ2w9OM+iApF0XeIBsnoqS8PTdakFAUnYG1pbW9chRQ4bNsznLreDGNuwp0yZEqRsNBFppDhAB5Ic752yhUC7BqRE/2iR96ks1a7whI2jGapwAr7bASRLQ9N1qRUBSZAbFDTlZ6h+Ywcrop4VPeE5P3HixOjss8+OZs2aBWmnMv+hDpdmD8cmzzkZG5QIbCyi4IV2retbslTFVAZslgDAAQTJmoeI95aws9Q7rkutCEjd2xf1L9HOcLBCuix6im3YsUpci5iH08AktpPGc04adXCZp0YgNllIgCtlTQNSeMKWY0GJlS6u/HiI26Z06oHsb/KDgAi7PHr06OjMM8+MTj/99GC3zU/t61tT7PgsWnDCQ+sg+/7j8gJ+rYj7n+tbUve5SSAYKKLuK9toOMrRWr3uMWv0HSyk9u/fH+3evTuEqm50+V2VV2jC1sNTkgQyI1aJ4whiwu5quPi7vCAg6fHfdN0/ffr0aPLkySfiihfRYxxnMzQNIungiDd+/Pgr9P67PP8p9OfF0uQNxASH70xWD5lIAZdMFImGNVaJE/UMO3aWUqEJWx3RV5PaMuwVxBGHsJ2MQDMgoHF9h6TKJ6dOnRrstjhYoRKGvIqW8AbHls/iRV70bHO7C7JWavjZo5prXiFCGAQRoNHDDOeULQQQ2lhIcWG+yFIq3tNbgf7BgwcHKMjE2/Ua1FNWiVeA47e5R0Be4n+8cOHCaO7cuWVJlWHfMeRVJCk7lq4xDZx33nnRzJkzQ7+mQdYULKI+R/NMHwQESNuEnb3HrMKGnTkv/kITdlhil8ttSNZx1CGrxLP3ALlGtSEgm+1NUgUv0WsJdTCXJO/CEDYLExYotJkFCx7i2LHTSgpH+nbZR1+KYID0ZifXtHqi63JjtTi8kLUFVaFdR7X6LtE5OBlwZc0jsOth5W+NQPcIiKTv27lzZ7Rs2bKg3tu0aVN09913B3Vs97/O7x1I1tqLHo0bNy6aMWNGdM4550RLly7lOW9Lo1VybL1MhP3V7du3Rzt27Ah9wdzjlD0EEN7QurL1Dv+mLKVCEzYdgY2CDoKwee+HKEvD03WpBwKSMD8j++2foIZFuoO0kRxYoDbreEe6JgwpQVLUdjzDj+maqM8frwem1eYhibofkz/e4TgzNSvu1eKSxft5NvBrwjGQ5yVLqdAqcTqisnMgbj9IWRqerks9ENiwYcOHJWnu0vauZ7HhInXiNd3Me7PZyoUJ4KyzzgraBUm1rxZZH6wHnrXkgTAACcSnAWJ681xTC5LJ/oY+YSEb7xxCkMtSKryETedwnCarXjrHD1GWhqfrUg8EXvaylx3TuJ4pkv62JqLXrV279oSEHdvommncQ9ZI12xnu/DCC0NUM7U9FVV43H9yMDvCPMPxjahb7SsTI5O9VzgB6drburLXN4Gg6aB4D3YzTVwZhNtVSgkBSZfPyaa7gu1N8+fPD3ZdHLCw8zbTASFoDXAumz17diBqnM20pe2wCHxfStAzxwwUzm+GBCol7LTq43K7RoDFFJyQxW1dhZawRdJIHoGsUYfH0kbX3elvjUA+EdBE9EXtyz5w1VVXfR6Jk0UqExOqWoJ4NMNilQUIDmZs45o3b16k9t6n/eiXaItbahEwkKo1+b+byFlbtmyJHnjggSBhNwPe+XwSuq41hA1ZV3qJq6+05m38vv2ONS00YWsP9sshajubdRwW/r8ZEVBYzkNq17+KQP5MzlhtOGNB1pqIwgQFeedVVatnOUQxI044XuGnnXYakvazOq3sBknYj6XZn5L6n0a6xukPvG16S7M3el42Ahy2bIWtPqJnZEDPf5ncnYV1Otu7d+9IPTz/yYksdIxXu8kNMuecLQQkbf4ppMZWLy6ioeGExmlWeYyEhkqfo0Q5hQubNa9Sie+XV/gmkfUnkY7S6gFN+GPxDEfKjv1kkN6cso8AghyaJ2lE+u/Zs+ehNMdRjFZhJWxNTI/I+aPM4R9IFk5GoAgItKv2viFb6rWyYf8mB4SQmJxQ1cZHPiJpZ3kRi1aAxCKDxQYLkMsuuyzYrs8444wj8oafzPft7U1tw7Mm/Ac3b94c9l6DL9uEPN/QM9lPsWc/Cy6NozEyt3xPtf7NNGteWMLWQ/OEVrrDYjVglienNAeIy24uBLDDtZPYa3Qi0Re01eu9RANDyl69enV07733BuKGWLDhZTFB1jiXIVmzTQ0HM64lS5aEdmjf+R+pjS267znam2Yb5B1+THbrvtiucTizn0yavVF92Yw1EvygRWzqUVQKS9isnlBNQdh0hpMRKAoCMYnJY/z3Fc3pe7L1PqFDMb4oO/ASmYgCUfNMxIvZLOHCBIraHsmaC8JGrb9gwQLe/1zS9idU7xW677m06i3sVPzzCwURdnnbtm3B2QztBfOOU34QaCfqmLBTr3hhCZuOqLxS7wlXwAikgIDI+scUK2n7sFTJgazZv7xr165IdruwZxgnqXhhyzOTVho4cGCIC44KHKKOz/uGrOVEd0iLji/ru5+nVb+4XMhaqvDLZLP+O0nW/VCFs/carUVenfrithXplb7igBZ8Dxh7BOJJOxWWsNMG3uUbgSwhIGn7PDlG7ZMn+RhFBet/3333BfX4unXrgioXooa000oiwUDWRGljn/Ull1wS1OBS5R/VXuuyiPoGXdenVb+O5Ur9/U5pK07H/glZEzSFhY8JuyNS2f0fbQhOZ/Qh2wUZe2mnwhI2kw9burDTpSk1pD0AXL4RAAE9A6hxg6OWpO2DUjePhiQhGDywUZWzxYXnheeG5ydJ8kHtzVat+LQtXgn6QmzwadOmBTU4+6z1/xDVM6wk2tuQngqgfSipHgPuuuuuEdqJEjQVkDUTv9Xh+XrWGN+MdbbiIWlnwaejsIRNJ7BywhHE2yzy9SC5tvVHQKR3guikup0pr+s1CjgybdasWUE6xGkKFTnqXdTl7CtmMktqsQtBs6caqQaHMqm7A1njDY4qXFL2Vi0q/qeQOFHvyjbUH6Ge5yiCfo/mlys5FY3TuZjsnfKLAAtXriykwhI2K16cQFj9pqnqy8IgcB2MQCUCIsgnJE1fqXCel0rN/LTI83LZta/duHHjiaMh8dLmGYo1VEgjkHd8kV93ZB5PhEjT8Xte+V/7pwNBx05leLEjWasub1cwlKGq289F6Osr652F92rzYAXauI5FzZo1a8Iix7brLPRMbXVgDDO24/FdWy71+1VhCRv1FFsseK2cZOoHrXMyAvlFQES9QbXn4vm4XiR6LXY8BSMp6yqhIkc7hZoc2yyvaKqQJlkA81x1pwKG9CXFh4M6YvU3h3ao7Ig45+326rJU3yXZ1pG479br/80qqvK4HyQtxFYJAhMIQ8p5yggFDsyU1R7rul6QNAtStEksTrMg2BWWsDt2FSt7iNvJCBiBkxHQs/G0zEdjFy9e/G/at/0KtlFBzjt37jzhUIV5iUkNEkeiZHLjHia9zhLPW+zIAzFr73Qgb95rQRDU4ZC5rpKk6o+I3D+v0J7peb111ogOn0lb16I6TmAbV4wN4Ui997oDUDn5l7HLWGZxignVNuycdJyraQSKjoBIlLOkr6jEQU7lvxZJlTWZDZEk2T+e3LBtQ9aQdleLYPZRY4/m4j3StaToQyLtNfrs/Mqy8vBeE/ooji4l+MzWrVtD7PAsTPJ5wC6LdWTsMo7RHsWL0LTraQk77R5w+UYghwhoMpOQXBpJ1UXaHxBJv1Eq8MNIk0gmXLzHHt1Z4nsilUHUqMN1X4uk6CekCn+r8n20Pf/Mq7ziekptepaulcuXLy/fc889JdmxMyGRdYa9P+s5AoxhFl3xArTnv0zmThN2Mrg6VyPQ1AiIVE+QqQJK/G81lqtuqTL/umWaQEbUU+rvq0TQN8qDvqzXEnZrJDIWJU75RQAJmwtfjKz0pQk7v+PJNTcCRiADCMh+/1ECzch2XcI7PHbAY7J3MgL1RKBzfVU9S8hJXn64ctJRrqYRyBACmjf6y9Gu/4YNG4Ltmm2iXTnbZajqrkoPEIAXKq8e/CTRWworYaPmwCkGGwUdItVWlw4yifaCMzcCRiBXCIikZ8tuv4UTzpCqOUITz3C2tWVFfZorQDNYWfox3vnAQgxnyrRTYQkboqYDcCigYyBtJyNgBIxATxCQvfo4+3MJJoNXuOKvh33XSNdOzYEAQh3mDYXqDdsXsxCxrrCEjXQNYXN5RdwcD5hbYQSSRkAT+ELZrOfIsSwER9m0aVOIZsZ+6yxIYEm3v0j5I8Qh2BEYCMEOAk87FZawecDiY++8Kk57GLp8I5APBDRvfFmnb72UKGY333xzeeXKlSWCxRBYw6k5EciS9rWwhM2Kia0XPvKuOR8yt8oIJIGAbJqTIWvs1jqNq8SJXNg5szSpJ9HuIueJf1NWUmEJmw6wKjwrw9D1MALZRkCEPFy2zG9q+9bUX/ziF8FmDWmjBjdZZ7vvmql2hSbsZupIt8UIGIHkEFAY1g9IHf4q4oTjZMaxmXgOY+N0MgKNQsCE3SikXY4RMAK5Q0D26SFyUH2TyPqjkDVS9SOPPBLU4Pi+WLrOXZfmusIm7Fx3nytvBIxAkgjIM/iftH3r2jvuuAMnsyBdczIZvi9Z8BpOsu3O+2QEtDhL3U3ckc5O7hP/ZwSMQIER0KR8wsNIccH/QUcrXivHsjLnW7PXGrLGWdWq8GINEvyddNTrDI2P4Wm23BJ2mui7bCNQBwQgGQ6hqENWhc8CHGWv/rDU3u/QqVuziWSmIzNL2KwhbUvWxRwimD90oNx5Ghf/rj3479Dxr/vTQMKEnQbqLtMI9BIBeSyX2ZoogvmQrk/3Mjv/vB0BSdBv14T8KezV69ati+66665o1apVEVHNkKotWRdvqGhBHPpdmpUWRTt7uYh7slAwYRdvKLjFRqB6BBSkY/SKFSsiEUs0adKkv5JE+HGdLX3OhAkT1lefm38BAlu3bh3Q2tp6GClaccHLOsyjRBQz4oPjDc7iyKmYCEDY+CugXSE86bBhwxbrs7u1UG74+amFlbAFNiqOcOgH752MQF4QUHjMgz/84Q/LsqmWFi9eHF188cWtEydOXCfp8GXjx49fpfHssFs96MzYlKDXkZKozycuOBL1mjVrSlKDExglnLxlqboHYDb5LYwByJoImSLsL8u34Xo1ueHPWWEJe8CAAdHQoUOjwYMHB+Ju8vHm5jURAtpmdEwTRl9J1mH8jho1KtL/5fnz5/9MgTy+LaL52pQpU37QRE1OpCla2JS1bev1Iuu3yMHsapF0WZJ2iF7G1i2cy5CunIwA4wDHs/hKC5HCEvaIESMiTWpB1aGHNC38Xa4RqBoBVvsQyp49e4JanL3BkrBLl1xySTR16tQ3Ssp+RpmasLtBVmT9Di10vnz33Xf3v/XWWwmGUmIRhL0aacpk3Q2A/rrhCBSWsGWvwk3/hISNWtwPaMPHnwusEQFCYhLDGhUdRwBiZ5Xnanjft2/fN0jKvmLgwIF36LPXUoTGtoa4PcnBQoudb0h6vkwYDVVc8P5SgZ/YXw2ODogCSk5ZRKCwhA1BV15Z7BzXyQh0hgALSy4cYSAXpEGdIMX2o3ACnQh8kCTHQePGjbtGUnh50KBB/0dj/b91lleRPhNmo+RE9vD69esDXlu2bImQqHEuk0o8LIA4dhdsnYxAFhEoLGFnsTNcJyNQLQLY1PBe5cJrHN8MiHv27NnRwoULI3mPR7Jxv1MOaYv69et3ld4/KvJ+utpy8ny/FjMTtYg5LpX3JkgaxzKCoCxfvjwQNgsfcGQBb7LOc083f91N2M3fx25hQRCAdCAfVOWc0QwpyT4LYWPbPltbwPZJHfyP+u7rY8eO/YXISRzVXGryyjZJy/AqtXe61Nx/JNKerb3rARN8Vh544IGgmQCvmKTj14IMFzczhwiYsHPYaa6yETgVAqh0cUiDtNlTTNAPbNtz586N5syZU543b95vn3nmmW+UNP6vIuv3nyqfvH7OAkTpUpH1lXIee78c8vpxfvVtt90W9lSDDWQdmxJY5DgZgbwgYMLOS0+5nkagBwggJUJGXDijYduO7bMi6RKxsEVmbfIk/4Pvf//7Z2q3RN/hw4dHI0eOHNrW1vYKbXO8vwfFZOIWtTVoCNTOhVqgfF2aA/mSPX1ch3TMlIlgPCYCIpahbVCY0QjiZqsWl5MRyCMCJuw89prrbASqQADyjlXA8oyOCBAiwua6QGryaPr06fEWR8It5iaKENK0vOSvlNT8H1qEDFCEsqBdwE5Ne/GgR6KOnfJ4RQPhZATyikBhCVsP+wkv8bx2nuttBHqCACQlQgsX9zP2x4wZE0h7xowZwVkNFTqSp+zeZTmuvVvbxtZIOt0g6bsPNnCSJPCy1OvP6PfHwgcN+iPJeJDINsxVELC0BscWLVp0ppzo/kxe8C9Hg8CF+h8NAk53eH/THocUbVAnuZiGIFBYwtbDHjxqeSVEqZMRKBICkBnqcpyuFJs8OGNBzFwi838mCiDviVWAZMorkrp+82Hh9FeNwkoLiXFSbd8i9fcC6kldUPvfcsstIcAJbWAxgjSNyhszAKpwiJq2sTjhficj0AwIFJaw2e7Sv3//cPFQOxmBoiAAgbENDAImqhdqcp4FBVoJl+zZkfZw41kezZo1C/t2kMiJDiiJ++OSXsco8NBOLXZ5cDAkH9bVousZ2cB/otcDPcVSdZktUj5bv+kjgm3T7/rwW7QCIt1jkpyvFCkvQLJGeubiPR7wMVlD0hA07cGJjNfY+9tk3dOe8H1dIaDxGRZ/8fkTXd2b5HeFJWwineFsg+QAeTsZgSIhAKFxkSBvEs+BoqQFiZWIX5A5rzrsAHV4eNXzMkCS9x9B7kjhED2pfUJ7Tr+/84477tilia27VbC4tDz49ttvn6afz9f7Fl19qROhVyFdorkhVSM584rkzMV7FhnUD1V+XP9QEf8xAgkggCZW472sxSvj+kN6fSqBYrrNsrCEzaEfSA5MRHSGkxEoOgJIp5AlJAhhombGFszzATFD5pXvicXPojeWOmT7blFM85fq2Xppd4tgkXMoA9LlolykalT1EDCv1INXLuqDFM3FfbEDGe9ZLJCfkxFIAgHGFwGJdHxtST4cf6sFa2rnzxeWsJmAFLIxqABtw05imDvPvCEA6cWSdyzdnqoNTGIdCZtnSoQdtFbdPVOUBdkiwSMxx1J1TNbxKwTtvdKn6gV/3ggEYsKWKeZ6tEuNKPNUZRSWsE8FiD83AkagewQgXPY3Q7hxgqQVqCRI4vFnXb3GpA1x854rXjBA0rw3WXeFoL9rJAIan6mrcQpL2FLvDUS9h5ovVuk1svNdlhHIOwKoqbmQQOKEqrry//jzU73GRM338XzY8fVUv/XnRqBoCBSWsKW++6DUG5/F89U27KINe7e3HghY+q0His7DCPQcgUJuQNYKviRb29/icCav13J3DjI9h9N3GgEjYASMgBFIBoFCErZUdsEWISn7G9qeUrJKPJnB5VyNgBEwAkagfggUkrBj+CRp/zb7sbG5xXaz+Du/GgEjYASMgBGoxicjabQKTdiyXUsb/nywCJzPstQxSXe88zcCRsAIGIGuEUD7io8TF+/TTunXIGUEIOo4khOb452MgBEwAkbACEDQRMJUwJQQV59gW2mnwhM2EjZhFgmiEm/xSrtTXL4RMAJGwAikiwCEjcmUELyQNYGB0k4mbBE2nRHHRbZaPO0h6fKNgBEwAukjABcg0KF5RSWeBW4wYZuw038yXAMjYASMQMYQgKDRuiJlI11D3mmnwhN2rPZALU7nOBkBI2AEjIARAAH4ofJKG5VCE7ZO6zqq7Vw/HD9+fMTlozbTHo4u3wgYASOQDQRiCRv/JtTilrDT75djOnjgboiaCzuFkxEwAkbACBiBmLBRh8MNJuyUx4Q65JjO/L0LsmZrFx2D+sPJCBgBI2AEio0AXIB0rTMnwrnv2LLTToVnJx3h9wge4hC292GnPRxdvhEwAkYgGwhA2Pg2yXQaCDsL/FB4wpZUXWJblyXsbDwkroURMAJGIAsIxCrxLHmJF94tmtUT3uGHDh0K6g+rxLPwqLgORsAIGIF0EYgJGykbc2kWdhEVnrAlXfehYzgXm5UU752MgBEwAkag2AjABRA1Gli4wU5nGRgP6ohtUodfr/OxD+N8Zgk7A53iKhgBI2AEUkago9OZbdgpdwjFjxs37sFJkyb9lkj7Z/HWLpN2BjrGVTACRsAIpIgAEjWSdVtbWwhdrfep+3ylXoEU++OkotU5j8bOZ7jyZ0H9cVIF/Y8RMAJGwAg0FIEKlfhz2ou9p6GFd1KYCbsdFNkrSniKS+IO++4gbNuzOxkx/sgIGAEjUAAE0LTicIaELe3rFu3H/mDazTZht/dA3DlI2Zaw0x6WLt8IGAEjkC4CCGwIbpD2/2vvTMCtOutzvzYzIQkZmQLhBAghEAiEABnIZEbNja213mv0sbfWaG/V3lZtvR201evQ2kFb2+tQo9bWeKPG9vo4xDjHmJhAEiBhnmcOMxwOwwEO+76/L2eRAznAGdbea3rX8yzWPpu91/q+37f3ftd/+P6frOvl6bbmpatbsNtGgdJzWNhDhgwJGeNZSOHPwgfEbTABEzCBMhJAsDHeJNif0VoTv5YFBqWf1hUPggYnuMQvuuiiSOVKHcOOwfhoAiZgAiUigFUdG3C4w5WU/K6sdN+C3TYSGqTDuMOZj02p0jiGrdW8sjJWbocJmIAJmECNCTB9i4JarOCIFmRps0u8bTSUsv8d7XsZKFzjCLY3EzABEzCB8hDADY51jQ4QHrVgZ3TsdVf1iDIBtzBIrM7iGHZGB8rNMgETMIEaEmAq1+DBg4O3lYSzLG12ibcbDQl135aWlmjjxo3hLou7LW8mYAImYALlIYCxhpcVK5uksyxtdom3Gw3dVc3DumaguMuyW7wdHD80ARMwgRIQiBPOyGeyYGd4wOUOfzuCTWZg29w7F0/J8Hi5aSZgAiaQJIE4ho2FHetAkufv6blsYbcjqMHaI6t6GAPFgFFb3LHsdoD80ARMwAQKTgDvKl5Wql466Szjg81iIAj16NGjmX8XllZzLDvjg+bmmYAJmEBCBPCujhw5MrrsssuCcCd02kROYwu7A4zEMMgSxMrmsQW7A0h+ygRMwAQKRiB2iVOTAw2Qh/WeLHXRgt3BaJBoMGrUqGBhs7yaBbsDSH7KBEzABApEgPUkcIdjYZNwJtFeoN/+J7PURU/r6mA0GDDc4Tt37gyDZ8HuAJKfMgETMIECEYgFG4Pt6NGjz1188cX36re/OUtdtIXdwWho4D4WLwJCmToLdgeQ/JQJmIAJFIQAv/GEP0k4Zt+6deujem5r1rpnwe5gRA4fPvwFLOzhw4dHdol3AMhPmYAJmECBCCDYWNYkm5Edrvh1JheRsEu8gw+dUvmP8DSJB1jYTO06cuRI5IVAOoDlp0zABEwg5wTaW9hM5cJQy+JmC7uDUVHsYrME+mbc4iy3STEVpnp5MwETMAETKB4BBJvfeKZy4V0l6SyLmwX7FKMil8hgpnUh2Eyix9r2ZgImYAImUDwCJJzFs4NYVpPf/CxudomfYlSU3r9X2eKHNL1rwLZt26Jjx45F8fEUb/HTJmACJmACOSSAhc3soBEjRkTysBLD7pvFbtjCPsWo6A7rCf3X58ePHx9deeWVYSC5C2NgvZmACZiACRSHAL/teFFxh8urukOC/VQWe2fBPs2oyMpu0sAF9wjuEov1aWD5v0zABEwghwQQa6Z0kWDM77wez5PB9p0sdsUu8dOMisR6T0NDQ3To0KFo3bp1FuzTsPJ/mYAJmEDeCLCEMkYZbvC22PVBJRk/nNV+2MI+xchoCldFg/hJTaL/cdu8vDC9y2tknwKYnzYBEzCBnBGIk80QbXZZ2HuUbPwlfv+z2BUL9ilGRe7vMHFebvH/o9jGfgaTCjjEOSzap4Dmp03ABEwgRwSoscFsICxsft/lDg9e5/j3P2tdsWCfZkS4y1ICwv/TQDYxoCQkcCTW4c0E6k0gvutvbW0Nl9bf9W6Cr2cChSFAThKCTb0NQp9UttTf67LcQQv2aUYnvsuSld2XuzAGlPl5+tvx7NNw83/VhgCfR00tfFw5FX20OIE/g7XB7LOWiADeUoqk8NuOMaYKZ5/Ncvct2J0YHc3P+xoJCVOnTo0uv/xyF1HpBLOyvEQi2q9efd21a9e7d+/ePYN6AKp3H2oD1Ovavo4JFJEA3tLRo0dHU6ZMicaOHctv+5ey3E8LdidGRy7xP8LCpjB87BLHneKtvARwR+/du7equ/Nle/bsGVMPEgcPHrxp//79A3XdUNu+Htf0NUygqARwh1MznNh1vDpj1vtqwe7ECEmcj0iwd3InRsZ4VgvDd6IrfklCBHBJy+KtrF+/PpJgz03otKc9zYEDB442NTVxPQv2aUn5P03g9AQQa+Zcs9AHa0XoxnuLPKkfPv270v9fz8Pu5BhIsN+kwvCPbdmypSq3SYWJ9qzgRclSb+UigHVN4teOHTvC/Hx9+etSeFiCHe3cuTPavn171NLS4tXjyvWxc28TIoB3FMFm5g85SXhNtfDHe3V8mMRObZnN5rSF3ckPge7CfijL+hsaYDLHw10Zd2jeykkAwcY1rYXug4jWgwLWNTcJumm0YNcDuK9RSAIINgYXljU7q3TJ+FpAZ7Ms1rTPgg2FTm6aZP9xsglJPKPGOMLtrZwE8K5s3rw5Wr58ebRhw4Zo3759X6s1CQl167Jly6KFCxeGmwV7d2pN3OcvIoG4WMqYMWPCbzkxbBljvfPQVwt2F0ZJbpRW4tfclSHWFFHxVk4CWNjEkhsbG8MuV/WNuNPWrFkzIEkinFMu8PGy5H+sjNa3cD3c4mSJ45r3ZgIm0DUCWNhkhzPzBwOM33FZ3LmIbTqG3YWxlljv175TS25eiHsSC8tb+QgglFjYuKYRTr78EupL9fgYsTAR+VRPqSDUuOfWrl3bXwluy7DiFyxYUNV1Kps2bQr17Xt6Db/fBMpIAAsbN/jEiROjCRMmkHz2VYU6N+SBhQW7C6Mk14l+L9d84Iorrvgs7kj9mIbiFdyx2T3ZBZAFeCkWNpYuVjbxsDlz5oR5nA0NDbfLCh6ou/ePd7ebsVhLmH9frvbBixcvjl544YXo+eefr6xevbpuMfPutt/vM4GsEqBQCrlHeElZNlmhzXWysP9Ov+H7strm9u2yYLen0YnHsqYekRvlrbJ6Zs6fPz+4U/jxJmvXot0JgAV8iaZ3RU8++WSwuPWDcK+mh9y7cePG2zRv/87udBfLWtb7h3RD8JfcFOtx1lwAAEAASURBVOhmoDpv3rwKK8aRKe7NBEygewSop4ErnOm5PNbv+Y81pSsknHXvjPV9lwW7i7xHjBixQxbQDRLp+RLuq5jHx48orlFv5SPATRqi+vTTT4fpVuQ2YHHL0r6jszRii7r965ubm++UNycktOnGsIIFTxjGN4XtKfmxCXSeAJ7QWLCJXUusF+r7+o7OnyH9V1qwuzEGGvhWFcxoYf4emYbxNBssbW/lIiCxDXOyJbAh+Wzu3LkUVEGwo5/85CfM2Q+VlDTn82eKm/033eBtP5kQFrXKjX5L5/gN5lir/Gj085//PFq6dGk4J8VZuCn05+tkcv7bBDpPAMHGFa56GpHykHCNt+i5XCSbxb20YMckuniUFdULwR43blywrqnv7K2cBLB6CYnwGUCwiTNzI4f4UpgB8dbft0l0Z6i06Hwo6Yeil7wy/STSezX74HuaXz2LJMZFixaF98ulHo6INzcAJLl5MwET6D4BBBsPGN9NBFsJxLmbJWXB7ub4y53yfcVBpigBrTc/zCtWrOjmmfy2vBOIrWyJccSOcCtZLIg4go3LXKJb1Z399+TW3qn+kgI+SEI/ECHmtRRgIfub5LJVq1YFyxrPjVbmyjset98EUidAZjjVzWKv6KWXXhop1+T7qTesiw2wYHcRGC9vizl+QFnifz5p0qSqimeEUqXdOJXfUkACCDjZ49zEMW+f2QRyiVeIn8lFfiFdjkUe6xzRxuWNWx2x5712gRfwg+EupUYAsWZZZBlZVWWGV+Qa/7pupj/Q9luem4IGFuxufIRkHYUBVkxylubxPaOsw6pikxXcl/wAs3srLwFizSSIIcC44bi7Z+cx+8kb4h3vvJfPD3/7c3QyKf9tAl0nwFQuckmYey3LuqKs8Hc2NDQ8zJni3/KunzWdd1iwe8Bd8ZA5KmjxdrnFv3D11VeHAhq4MbGQvJWbgG/cyj3+7n02CHCDrPBlmHONG5z4tXJHvqHnd2ejhV1rRe6C7l3rXu1fvXLlykeIU8ZrZSsuUvuL+gomYAImYAJnJIBgM82Sedcsj0zdcN1M58YFfnIHbWGfTKSLf2vh8164WiZPnhzijtR6xsr2ZgImYAImkB4BwlDEralsJhd4+I2WcbVVzx1Nr1U9u7IFu2f8yDo8rKShZYqTXEHc8sUXX+zhGf12EzABEzCBnhJAsHGHk+yp6bfVadOmEb9+jYpfNfX03Gm93y7xHpKXYO+XG/wNygKei9uFeX4sjE52MO4YbyZgAiZgAvUngGVNuFJeUAyrin6T/1PJZ2vr35LkrmgLu4csJcrEQ17UXOzvajL+DFZ/IVucObW4x12ytIeA/XYTMAET6CIBjCWEWtNuQ2UzcoxkWD0hY2pXF0+VqZfbwk5oOGRZf0PJDQuxsikuT1wbl4w3EzABEzCB+hPgN5jf4ksuuST8Hkuwcxu7julZUWISPTzqjm6p7t6WXnXVVZFiJZHiJCE7sYen9dtNwARMwAS6QQB3+OWXXx6mdCmW/XXFr/+pG6fJ1Fss2AkOh1wwz+ISR7BxwRDH9mYCJmACJlA/Ang2mcqFYI8dOzas96DHS+rXgtpdyTHshNi2lbj7hGLZe+SG+RyuGNzjlJg8ePCgq1YlxNmnMQETMIFTEaAEKStysewxC3wQx5bn85NKOvvwqd6Tp+dtYSc0WiSfIdr6YHyeDwmreOEeR7iZC+jNBEzABEygdgRINCMzHC/nzTffHFF9ktCk1r5+X+2uWt8zW7AT5I1oczolN6xSvCTc3VHD1slnCUL2qUzABEygAwIIdmxhx5Un9fu7qoOX5vYpu8RrMHSysMepgEqVVZjWrVsXqd54cIuzoIM3EzABEzCBZAnEcWtKj2pth2jWrFkh4Yzf4mSvlO7ZLNg14i9X+M9Vs/ZWuWOwuMPKTQi4NxMwARMwgWQJINhxVTNi14i2Es3OS/Yq6Z/NLvEajYHmZd8toZ7PHECKziu27Vh2jVj7tCZgAuUmQFY4YUhyhqg2qb+/or9zP+/65FG1YJ9MJKG/FU85rP1/kfhwyy23RFOnTg0rxTienRBgn8YETMAE2giQFc6c62uvvZY1r8kbYgnN/UUDZMGu4YjqQ3Q+d3tKgKiSOc68bBZT92YCJmACJtBzAiSasRN25LeWrHAqnGnBj9aenz17Z7Bg13BM5J75ulzhn5k9e3aFYiq4xZl2YNGuIXSf2gRMoBQEEGri1ljXWNUzZsxgOleT8oZ+R3OvHysiBCed1XhU5aZ5186dOxv0gXoNCWh79+4NRVSam5sjZ43XGL5PbwImUFgChBeZNkuhFAT7sssuo274LxS7/nJRO23BrsPIKlvxD7XPVubiudwVtra2RocOHYqcNV4H+L6ECZhAIQkg2HgtJ06cGIpUSbh3SqzvK2Rn2zplwa7D6EqkV2g7ev3114dypVjXsrqDcGvqVx1a4EuYgAmYQHEIxO5wLOtbb701rN+gxwOL08OOe2LB7phL4s8qCWK75gdecPTo0SDaTPBHrKkzjsXtzQRMwARM4MwEyAEigVdey1BNUqHGqvKFKnKPf/TM7873KyzYdRo/fchuVyLEhUo+W7B06dKosbExlCzdunVrEO06NcOXMQETMIFcE2BtBhZWImY9fvx49oqyxKfKJb441x3rROOdJd4JSEm8RFMONqko/Qvbtm27lg8aOx86piN4bnYShH0OEzCBIhPADc6Gdc1v55gxY8KKXDKEtijZbKn+v/ClJG1h1/kTrrvAFrLDSTrjuGPHjmj//v3R4cOHnTVe57Hw5UzABPJDAMHGHa7w4vF64azMtXv37hsaGhpa8tOT7rfUgt19dt1655VXXrlYIv0XSpD435yAxUFIQtOHLoh2t07qN5mACZhAgQkg1sy5po4FiWbMuVay2ZaxY8e+Rv+3tsBdP6FrdomfgKP2f+jDRVr4NzTZ/0ty4zRPnjw5YicJjQ+lNxMwARMwgRMJEDakkhmlnhFrWdSszfBD/WbOP/GVxf7Lgp3C+Gru4DK5xt+mzMb18RxC3DwW7BQGw5c0ARPIPIFYsDFupk+fziIfm5Ql/g+Zb3jCDbRLPGGgXTmd7hj7sQwccZn58+dHTU1NwT3OVC9XQesKSb/WBEygiAQwYnCFy8AJibr8Xo4bNw5r+5BqhpfKumZ8Ldgpfsrl1rl87dq1e+XaOUePK3v27Im2bNkSYtnM1/ZmAiZgAmUmgGVN+VGWKSYrnGlc+q1sUpb4uDJysWCnOOqyonUDWRm8cePG7+mD+Jp9+/aFcqUcKaZiKzvFwfGlTcAEUifQp0+fSNO2glizfCaiLbEe3PbbWU29gXVugAW7zsDbX05iHT5wDz744OtVtvSg7iSrqn5W2b59e4SFTa1xi3Z7Yn5sAiZQBgK4wrGuqVPBkpmscz1lyhSyxB+i//FvZxlYtO+jF2duTyOlxw8//HB/ifWNWjO7QZXPqhs2bKgwLxvBdq3xlAbFlzUBE0iNAHk9TOEiM/yqq66KXvva1+IK/xeJ9++k1qgMXNgWdgYGQRmP+7UYyGsl2p+cNWvW25iXzfzsp59+Otq1a5dFOwNj5CaYgAnUjwBrXDOFS7+HYTUuTXv9jOLY765fC7J5JQt2RsZFWZBNcn//g443aurCBFxBixcvDpnjWNveTMAETKAMBOJEMxVFiWbOnBmNHDky0rKZm8rqBm8/5hbs9jRSfqwP5EJt85VcMQGXkFb3CrFsluKkfKk3EzABEygqAeLWuMGZwjV69OgwfYspXKpRMU/P/aCo/e5KvyzYXaFVh9dOmjTpgyoI0F+Zka+TeIcPMJY2tce9DGcdBsCXMAETSIUAlrWKSoXCKEzfwiWuuPXDcoffn0qDMnhRC3bGBkV3mSvVpN9QDLuqmrlVCXWFpThZJKSlpSVY3BlrsptjAiZgAj0iwPQt5luzxrVEmiIpYY1ri/WJWC3YJ/LIzF+KYb9h9uzZ31SiRfXAgQOVvXv3RhRWYXfmeGaGyQ0xARPoIQEs63iutUo1V2+66aaKwoIVFZR6Qw9PXbi3u5Z4RodUU7wekYX9mFb3qhDLVtJFuAMlzuPNBEzABIpCAOuarPC2amaV4cOHf0fTt6ZKtB8pSh+T6oct7KRI1uA8srLvV7LF1xXLuRMLe8WKFRFH4tkuqlID4D6lCZhA3QjEhVFUEzwkmN1www2h9Kga8O8yUBbUrSE5upAFO8ODpfjNbs3D/sg111xzkz7UA5iXvXz58rB2Nm5x1xvP8OC5aSZgAqcl0Ldv3xCzljcxVDF79atfjaV9TJnizad9Y4n/0y7xjA++kjCeUDLGmzTN4QhTHFithqQMXEjeTMAETCCPBHCDU2uCOdb8rinJ7Khc4T/TFK5fl4A/msc+1aPNtrDrQbkH12grcv+fWiDkdaqn+23Nz+69ZMmS6NFHHw3ucSeg9QCu32oCJlB3AtSYQKyxrG+++eZIU1kjxav3qwzpq2hMWRf26MxAWLA7QynF1yjJTJ/fsKrX97QoyM9UV/cO5mPPnTs3GjBgQIhlE8/2ZgImYAJZJ0DcGlc4cWumcMmyxsKuKuFscNx2fvPixz6eSMCCfSKPTP4Vf4B1B/pqWdQ/OXjw4M0kaGjaQ6g5jsXt5TgzOXRulAmYQBsB3OBUMmPWi1YnpJpZVWWYmQVTUSLtAIM6MwEL9pkZZeYVEu6jsrZvl0W97LrrrhtDoQEs7bVr10YScYt2ZkbKDTEBE2hPQL9dwSOoRNqIGuF33XUX1nVFVvZ9Euzvtn+tH5+agJPOTs0mk/+DaKuQyp2U8NM87ZC0oWQN6u1G3MF6MwETMIGsESBujVgPHTo04veKXWLdrLDeiqy1Ncvt8XrYWR6dU7Tt05/+9EHFgpboA3+9hPocXOMknzFHG0vbmwmYgAlkhQBijTdQFcyiG2+8MZoxYwZrXG9SdbPbJeCLs9LOPLTDJlkeRumkNsrKPqSnvtbU1LRPq3j9h1xMfZRFHq1evTrM0eblzh4/CZr/NAETqDsBXOH9+/cPSWZUMiPJTMdjMjQeVHGUF+reoJxf0IKd4wHUh/47mzZter3uWr+thUGqWje7QlLHtm3bgnAr3p3j3rnpJmACeSaAWOMGx6Imbn3LLbdUKbUsy3q1nv9wnvuWVtst2GmRT+i6qrlL3d3eWjO7VRZ3OCtflLh8KdXQLNwJwfZpTMAEOkUAq5q51vptCstlTpkyJZo6dWpFwk0Ytrd+o2xNdIrkiS+yYJ/II3d/tX3wqy+88MJBrXQzkOldzMuWtR2sbETcJUxzN6xusAnkmgBJsYh1g6oyqigKCbJHNPf6W/q9OqaOsXvrBgELdjegZfEtuoM9S4VV5ij7cpi+GKO4w125cmW0Zs2aKLa8s9hut8kETKA4BEgwY7aKjIdo1qxZoZTytGnTmhS3fkBu8G8Wp6fp9MSCnQ73mlxVd7UzZWl/QvXG30/GOJZ2c3NzcInHLvKaXNgnNQETKD0BZqtodcGQYDZmzJhgWVMnXLk2/2axTubjYcFOhmNmzqKyf5/Vl+SAqqJ9QNO++vAlWrZsWaTkNCeiZWaU3BATKB4BCXOk9Q5CJjiVzFQj/JBc4K+Wt29j8XqbTo8s2Olwr9lVlYW5Vif/sJLQJsjKfmMcwyamjZWtbPJQEa1mDfCJTcAESkUgTjCjGIp+f4I7fPz48RR1eo+Mhp+XCkaNO2vBrjHgtE4v19T9CxcufKNEulVFVnozL5uEtM2bNwfh9jzttEbG1zWBYhGQNy/CBc4cawRbHr5Whed6S6w/V6yept8bC3b6Y1CTFrSt8MVSXyP0RdrE+tkkg1AJbceOHSG+bdGuCXqf1AQKT0Cu7oiVtziSBX733XdHWNVKfm2RYI/U8zvafoM8fSvBT4MFO0GYWTqVvjDhiyKX+CFZ2z/WYiF3kMGJW3zDhg1RY2NjiGl7yleWRs1tMYF8EGCJTKZtUb2MlQOVCR7WNVBt8LsRa3oR/wblo0f5aKUFOx/j1O1WqqrQLrnBH9BSdvfqC/T+LVu2jKagARnkcXy72yf3G03ABEpJgJt/xagjGQIslXlMM1OeVCz7U/ptWVBKIHXqtAW7TqDTvIzuhNfp+p9RvfF3q9pQKBeIOxzreteuXWHqF0lp3kzABEygIwK62Q8ucEofywgIlvXVV19N9TLi11UVSLlHrznQ0Xv9XHIELNjJscz8mXRHPHHJkiVHVHWojwS7qr3CWtrr1q0LFrdLmGZ+CN1AE0iFABY1bnAqmE2ePJkpW+xVxawrWnHr7yzW9RkWC3Z9OGfiKm1JIH0XLVrUb+bMmS1a6Svii7hv374g2PGULwt3JobLjTCBTBAguUyx6VAQZdSoUcGq1u8HyWYV7f0l1nbP1WmkLNh1Ap2Fy+iLFWds9pObfLvWp7142LBhERnkTPdavnx5pBh3qEOehfa6DSZgAukSQKxxg5MJTrlRdixs5cTsVqGUVVu3bu2rFlqw6zRMFuw6gc7SZeTKatYSnDfoi/geifUdShYZj1v8wIED0Z49e+wez9JguS0mkBIBxJqpoFQwQ7C1PGYQa7nFN+q53x0yZMj3U2paaS9rwS7p0OvLtlJdf5cS0b6t43gVOQgJaBRXYdqXFhKxpV3Sz4a7XW4CCDUljbGsKYpCMZRrrrkmWNeq6dCiuuC3yUXO74e3OhOwYNcZeNYupy/n/crwXKTEkQYVVakqA7Qyf/78aM6cORELiJBN7ph21kbN7TGB2hBQ2Cwkl0mUI93UB4v6jjvuiCZMmMASmaxxPUJivas2V/dZz0TAgn0mQgX/f8WyD0iQx6qbVc3NPnb++eeHBBMqoik+FWLaJKdheVu4C/5hcPdKSyAWaqxqXOCUGWWlLSxr5bpE8sCN1m/DJr2utbSQMtBxC3YGBiHtJuhLGBaUlyCfoy/rVt1ZV/VlHcQKX4888khYVxvRptiKRTvt0fL1TSB5ArjBuVmXty0iE3z27NnR9OnTwzQu5bncIMFen/xVfcauErBgd5VYgV8v4W5W9wZpbvYnlWzyHgok4AZj2pdW/zpeGQ1r25sJmED+CSDUzK/GsmYta6qXtVnXx3R8Uf//IYXLfpX/nhajB5VidMO9SJLA7t27b1HZ0lmyqD/61FNP9V29enW0ePHiaN68eaH+uP7fS3QmCdznMoGUCDClU1O0gvtbx6qs6gr1wWVlr1Vm+CTdxBMy0+H4lNCUWurLQsAWtj8HryAg19jjevLx5ubmx2699db5ZInqi11VTJvVv4LF7WS0V2DzEyaQOwKDBg0KFvWMGTMQ7YoE+2lN8/zw2Wef3YhY0yGLdXaG1YKdnbHIXEv0pV2g6V2XKDHtQypB+HbN3a5qyleFuZnM18ZVTmzbmwmYQD4ISHzD3GqEWt/rYF1TD/yqq66qysLmu/0+WddP5aM35WulBbt8Y96lHqtIwma94R2Ka/9cX/CH1q9fH7LI16xZE+EqJ5scq9vJaF3C6hebQCoEiFezWh+JZffdd19whWulraoW8ECs36zvu8U6lZHp3EUt2J3jVPpXKXv0a6qEdlhf+K/IdXYWiWdY1yzRyUpfFu7Sf0QMIMMEEGo8Y1jWcXKZhDoaO3ZspPLEPxo+fPjdGW6+m9ZGwEln/ih0ikCceKJs8Q8+99xzo/X32xYuXFjVQiIVrO4FCxaE0qYsIMKynd5MwATSJ4ALHLFmzQCEWq7vaNasWVXN/iC57GFZ1PtVzexBZYk/nX5r3YIzEbCFfSZC/v9AgMSTNtH+CE9okZC9SkR7L3fs7Ig2G8loLrISUPgfE0iVQByvxgVO1TLc4IpXV++6666Kpmx+QdO13pFqA33xLhOwYHcZWXnfgGjHvdcd+ccU036vRDwINkdW+lq1alVYXxsXOdY2z3szAROoPwHWB1BsOljW06ZNC4ItC7uiZNIvSsB/t/4t8hV7SsCC3VOCJX2/KqLt1sIh/TVXc6LcbQ8pw3SiEtOixx9/PMS0WTwES5sdq9ubCZhAbQlgUbNRDIV4NRY1K2xR/OjGG2+MFKfeopvsEbqJ7tP+5ru2rfLZkyRgwU6SZonO1faFZx3c+Tt27HhaRVbGa+/Dj0PsHse6ji1tx7VL9OFwV+tOALEmVo1Yy4IOXi8KoFC5jF0W9c42sdZLK04yqfsIJXNBJ50lw7G0Z5Eo8wNQ1bzst2le9lvkFj9LBVZmkIRGdbQVK1YEN/muXbsowGAXeWk/Ke54rQjwvSJOjQucfJLrr78+rK41fvx45lkv1cpb+5UNfm38Xa1VO3ze2hOwhV17xoW+AmLd9kPwRXX0izxet27dT3v37n0r7nBNBYtUcCUUWdH/Bfe4XeSF/ki4c3UkgEWt71oQbJbERLQnTZoUUblMFvZKTcG8Q9/RTTSJ72odm+ZL1YCABbsGUMt2yvY/BDxeuXLlb2nhgB/rbn+8po2EGJqei4hxb968+bibvGyc3F8TSJKAvmuIcqhYRihKQl1V3LpCKWHllWxWfYRb9BoKH3krCAG7xAsykFnqBlZ2Y2PjRXKDt/br12+dRPrspUuXRk8++WSYr83KX3v37g3C7SlgWRo5tyXLBBDo2KKOi6CwXvXkyZODWF933XUV5YxM0nzrQ3KRH1DcujHL/XHbuk7AFnbXmfkdZyCAla2XbOdlEuevScDfcejQoVB/nB8d1tlWnDvsxLadkHYGoP5vExABRHrAgAEhqUzFTkIxFMR6woQJTN9iutb/1OOl+o55WkZBPzG2sAs6sFnoFpZ2m3gTx/6lluUco4zyC+Ue76cqadHcuXODxU150ziuTZzbmwmYwMsEuMll11TKUABF4aZIq2pRsYyVtloVu94qi/ovFX568OV3+VERCdjCLuKoZqRPsVjTHLnnZiPg+tH5iaaf3IYrHKHWEp6RRDxY39Qk19SwYHFbuDMyiG5GagQQaaxqMsCZqqXvUJiipdoHVQqgEKvWc38twf5Aao30hetKwBZ2XXH7YnKR36X49gQJ9j+y2pdi22HJzvnz5wdXOS5yRDy2uE3MBMpIALEm+xuhplqZRJqFOqo6VvhblQa/qUIoT2mO9T+092SVkVWZ+mwLu0yjnYG+KiHmh2rGD5V09rSmoHxc80RvR7ixqInPKUktWNxMB8PaRrhtbWdg4NyEuhAgqYwCKP379w+WNVY107RwgU+cOJEFOx5RBvi/6LszV6K+x2Jdl2HJzEUs2JkZinI1RIsPzFGRlQf0g7QGQeYHiUQaCq2o5GkQbZLTSFZDuC3a5fp8lLG3WNUINSKthTnCTpUyCqCQWEapUYWUFuum90cxH73HSR8xjBIc7RIvwSDnoYtylT+oGPb9L7744lkkpC1btizUJSebnHW3EW02C3ceRtNt7AoBhJqNeDV1C1iog4QypmzJDX6QZDPdzF4rMV/clfP6tcUjYMEu3pjmrkcSYf1mvWQpyMLeJMt7BNY1cW0WEVmzZk2olkaSGgJOcpo3E8g7AVzflBLVMrXBmlZ4KAi2XN/BotbfeyXUl8qibsp7X93+ZAjYJZ4MR5+lBwRiseYUWqDgtYpjv1s/Yvv1+DrN0Z7+y1/+MlqyZEm0YcMG5nVbsHvA2m/NDgGSyignSrUyrVMd3XbbbaG0qL4P/yj39wUKG33MYp2d8cpCSyzYWRgFt+E4AVkcz+mPt/KELO+hyhqfr+pNw7BEiHEzHYxMcs3pDpXSsLZtcR/H5wcZJSARDslkWNUkVyLUuLqxqtkl2FXV/6b4yecl0n+Y0W64WSkTsGCnPAC+/KkJ6Eduq0R74hVXXLGL2B6uQqa2yE1eoeiKFhkJFjcC7tj2qTn6f9InQPY3An3++eezLnWIT7NQR0NDQ5hbrSSziizuGzQrYmH6rXULskrAgp3VkXG7AgGJ9u5Fixb1Zz6q3IQzVTDiCeLbWNWINDvztrG84ylgFm9/eLJAAKuaDbHGqkag46zve+65J3iM5DV6WKJ9v3I3+uv/WrLQbrchuwScdJbdsXHLOiCgoitvlIv8ISWk9SIZjSlgrAKGi5zHWpM7CDgi7s0E0iAQu78RaaxqpmTJzR1WrSNerXnU0ZQpU1pU/GSL/v/PJeRfS6Odvmb+CFiw8zdmpW+xBPsWWdnvlUgP0JSvu1SbPFRLmzNnTqQM85BRLmE/7ia3xV36j0zdACDWWNTkXMQJZffee28Qawn1aonzCiVU9tNc6+/JPf73NEyfT73N86nrNkg5vpBd4jkevDI2ve3H7XH1nZ1pXt/Uj+BvUmgClzjrbWNp82MpYQ81yjkyjxu3uTcTSJoAAs0cao5Y0rKcw/QsPpMUO7n22mvDUZ/Jf5eF/aGTr2+xPpmI/z4VAQv2qcj4+UwSOPnHTSVM36Ifwmdk0XxMVku/PXv2ROvXrw9zt7GyKcKCiOMyp9wpmy3uTA5trhqlz+Hx9lJOlxwLhBpx1nREVtGqKkGyQtwa0VZC2Tsl6pTl9WYC3Sbw8qeu26fwG00gXQIS4N7KHL9Y9cn7KJ69b9y4cXsQbbLIf/WrX0WrVq0KrnKyySl1Gpc7ZR1urHJvJtBZAsydZmoWR9zelBKNs7/x6tx+++1M06oqbl3R/92pz9dSPX9MyWWNEnl/2DoL2q/rkIAFu0MsfjLvBLT+9s+VeHaLhLwqC7uClY2IU6s8rpxGERbE25sJdJYA4kytb8RZMxZCbBqLmkQyFTrh2Cpru7dE/U16/H87e16/zgQ6Q8Au8c5Q8mtyR0A/qrfSaFnVf6y44kf0d39+UNniuuTEtGWVH19cJJ4WFl7kf0xABLCk2YlPc2QeNeKMaKs+QNhxeatOwCqJ+Xq5wF9lcCZQKwIW7FqR9XlTJ9CWoPa3il9vU/zwdlk+90u8+yi+GKxtMspxm1PylGlgiDcJao5xpz50mWgAsWksaUSaPY5Ha950SCpjjWq5ujfqNYuUTHYPjW77zHkFrUyMYPEaYZd48cbUPWpHoP0PqKztN0uQz2tpafkvSk67hwIsL7zwQvTUU09FJKjhMic5Lc4mt3C3A1nChyzKwc1dvCs3ItJe1d8VzbH+V8Won1ei2XxZ1k+UEI+7nAIBW9gpQPcl60egfVa5LKSHuLKE+Euyrn+hH9trqZiGdc0UHKwp4tr8zZKe8f/FVdXq12pfqd4EcHlT6GTgwIEh25uEMqZojRkzJsKiJpEModaRet/X6fOyWJ+tffVup69XbgK2sMs9/qXtvdzgAxV7PCgru0r2OCLNY1nYldWrV4fkNCWuHT/GVndpgRW847i/L7300jAFS9OxQnUy/mbBGerYY23rNZ+SSP+VaoFvLzgOdy+jBGxhZ3Rg3KzaEkCs29zl4aZVLvFXyQL/CfO4+fFmyhdHXORyoYdscp7DTR4fa9tCn72WBCS8x4udkEyGIJNIhkgTmyYDXJZ1s57fofj0ZbVsi89tAp0lYAu7s6T8usIT2LFjx28pg/wPNQXskFzmZ2nK12hZ3ecR31b505CcRmIaiWpOTsvvxwGxZnoW07GwoMnyxqpuy/ZuUmhksYT7bLnDb9Zrd+e3p2550QjYwi7aiLo/3SLQZm3/m97MjiXdT4J9v+Zxf0IiPZTEtOeffx63eSh3ioscS7vttS7AEkhk9x9Emjh1bFmT9Y1IE6O+5pprolmzZpEJvk9C/lblNvxHdnvilpWZgAW7zKPvvh8noB/yE6bi6O/D+s+vyLpeph/yL6ty1QRc5Ag21hlxb2LcuNBJUJOwW7SP08zWA1zezMFn3JiaxXrUsqxDNTKsakRbVvWXNL5fklg/ma3WuzUm8DIBu8RfZuFHJtAhAQnzMAn1OfrPS/TD/zOqppFNPm/evGjp0qXBVc5jYt1xqVNi3d7SI4AlzcaRjG/i0kzPIjZ9ww03hBkBEvDHlGz4pzoeHD9+/Ea91muypjdkvnInCNjC7gQkv6TcBJSM1CgC7Cu0Otgw/fA3YrEh2qy/zbQvXKxY2pQ6xV3OHot3uenVv/eINFY1O2KNZc20PWLWcbxaU7h+qmSy+/TaI/Vvoa9oAt0jYAu7e9z8rpITUILaX0u836pjH+0XzJ8/P6wKFq8OhpCToGZLu74fFOLUcmuH1bNGjhwZzZw5M4j1lVdeiRu8UVO0jqr4yZs039rFTuo7NL5aAgRsYScA0acoHwH9+P+Jev0nEuQr5SL/lizsK1kVLLawse7IJI+tbQt37T8jrEnNzhQtsr9xgc+ePTtY1Xq8UBb1NbFFrfHQwxPzFmrfQl/BBHpGwILdM35+d8kJ6Ed/iazp18vVupikNIRZwhBpmc9o2bJlUVNTUyRL/Pha3CXHVZPuawxClTK4E6ogiYzHxK0Vm+a5rcoveL1ed9z9bbGuyVD4pDUmYJd4jQH79OUgoHj2ncoYryqJqY/E4Muatz2MtbhZWOTZZ58NR6aBeUWwZD4PiDQbFjUlRSl6ElvT1113XVViXVHm/k2aTz1IpUQ3yQNCKVGvR50Mfp8lJQK2sFMC78sWi4DqTv8o7pGs7GslzOsk4L1Jeopj2UwFw+K2aMekundErBFq4tVM00KssaiJU8vTUdWylxUlmo3VcXX3ruB3mUA2CViwszkublWOCUhQNkm0L5ZVt0sJaUclHH2eeeaZCIt70aJFIaucNblxn3vrOgGEWlZzWKgDq5qiJ6ykpUIoRzWfWlreZ4qywi3WXUfrd2ScgAU74wPk5uWTgESbkpa4ZW9jChEJaBRawdpmx9Jm3jZJaRbuzo0xVjV5AqyoRfETptJNnDgxmjp1KglmTZq29ZtifdzT0bmz+lUmkB8CFuz8jJVbmkMCsgZXyj37XSVCzbzxxhuHsITnihUrIjLKmceNkDOP29uZCRBeIPub1bOmTZsWFurgOGzYsGck4t9HrHXzo3slZ3+fmaZfkUcCFuw8jprbnBsCim1vUGPvU4nTBxVrfRsZzNQlx63L1C9KmsZFVmxpdzyscREUhDquWHb33XdjXR/TnOs/k2X9sER6ncW6Y35+tjgELNjFGUv3JMMEFFN9l5p3nxLOhkh0qrKsK7h4JTRBsHGPO679ygFErJmqhXXNzc6kSZPCoh0NDQ3EsX9frvHPxO+yZR2T8LGoBDytq6gj635ljsCaNWsGyA3eKpE5jGX93HPPRY899lhYBYwMcmLbWNveXibAlC2yv6ladvPNN0e33norLvCfKBv8DlnUvSTSnqr1Mi4/KjgBW9gFH2B3LzsElBh1qK01ldWrV98kS/sXxLJZ8QtLm3g2u7cohAtIMCOxDGuapTDZdbOzVOKNWAuZxdqflXIRsGCXa7zd24wQUPnMg4ppz9XKUUM0l/jSJ554orJ79+4TVvzKSFNTaUb//v1DDXBEGstaVvVcFUE5JGbvoUESa8+JS2VkfNE0CViw06Tva5eWgBKonlXnZ8pSnCTL+xeKX1+gxLTgEmfKV1ld48T1iVtTDIUpWzNmzKi+6lWvqkyZMuV1EulNfGCcXFbar03pO27BLv1HwADSJCARWqS1tvuzTjNCrb+jF198MSzVmWa70rg2mfMs3IEbnBrgrLSlqXAVJZd9Ue3ZFbfJ1nVMwseyEbBgl23E3d/MEVAG9ChZkLuUYFWVeFeWL19eWsGmghlFUVQdLrr++usj3ch8Q+7wBzI3aG6QCaRAoFcK1/QlTcAE2hFQMZXdEqp7JFQV5hlPnjw5LA3Jus5Y3GXYsK7JCCcb/Nprr42mT59OnfD5mg735jL03300gc4QsIXdGUp+jQnUmIAKrDy2cePGv5dl+T7VHw8lOLXyV1hfWzHbGl893dMj1sSuuUHRdK1QG1yW9WoJ9irdsBxNt3W+uglkh4AFOztj4ZaUnIBKlP6TsqLft3///qqW4qywpjZxbUqXFlm0STIjdk2i2ejRo6MJEyZEChGM5ePgBLOSfync/RMI2CV+Ag7/YQLpEZBrfI8Srr4rd3CFDGm5gyPVIY+Y4lRk1ziWNVXMrrnmGuZaV+lzvDnBLCbhowlEkQXbnwITyAgBuYD3SrDfItGaqfWdF2FtkoBFWU7cxkXcYuua5TGJW6uqWUWx7P9RxL66TybQUwLF/BXoKRW/3wRSIiDB3iOBnqtYbpOKqkR33HFHSEDDyi7aRtya1cu4Mbn66qurmsLF4h5L9fxXi9ZX98cEkiDgGHYSFH0OE0iYgIQ7uIn79u0bLVmyJCShUba0SLHs2LpmFS5VMavopuT3tPLW5xJG6dOZQGEIWLALM5TuSJEIaJrXYlnZ0yRiA+QeD+tAU/0M0VZCWiG6yjQuCTVzrSMJNdO4+haiY+6ECdSIgAW7RmB9WhPoLoG2zOgHtILXfLnHX6f47qu00lekpTmjrVu3FkKwSaKjSApzzmfPnk2t8I3KFJ/fXWZ+nwmUgYBj2GUYZfcxVwTIjEa0ZXH+s0T6rVifFBS56KKLgms8V53poLG4wgcOHBgy4CXUwcpWpvg8ZYc/0cHL/ZQJmEAbAVvY/iiYQAYJxNOZDh06tIsM6paWllBcZNu2bRGreuV1I9udrHemrJFspulcrVr8ZJzWCS+Gnz+vA+N254KABTsXw+RGlpWA1oTuJUs7atCa0BRSwTJF9HCP53Uj452kOjwGOlbVp7V57YvbbQL1JGCXeD1p+1om0EUCsq4PaOrTByTYh2SJtuIaxzolYSuPG+5wlWENiWYkm1HdzJsJmEDnCNjC7hwnv8oEUiEg1ziu4o8ppv3ZhQsX/kAu5Bl79+4NNcYpWZo3S5u510zj0rzrsISmHvs3KJVPli+aRwK2sPM4am5z6QhIuHdJtJfgRsYqzVshFbU/xOBx6cd1w+mHXP7/VLrBdIdNoJsEfHfbTXB+mwnUm4DmY/fZt29fxHxs1sxmVa+8WNi4wqkZjjuceeWqaNYq6/oBZYl/pd4cfT0TyCsBW9h5HTm3u3QEyK4mAQ2XMjFsRDAvG4lyeAWwrvESNDY2/raKpvxrnA2fl364nSaQJgFb2GnS97VNoAsElGx2DJEmDsz8ZYleWH6TKV9yl3fhTPV/aVzVbNq0aaHkqqztXfVvha9oAvkmYMHO9/i59SUhQCEVbW/R8X0S7M2K//YePHhwdOTIkbDjJs/yhnVNhjuVzVRyNVjZWW6v22YCWSRgl3gWR8VtMoGTCMSuYx23yVrtxSpXuMeJC+dh6U0WMeEGg6ptxLFVltTGwklj7D9N4EwE/KU5EyH/vwlkjIAyq7dpetfQ5ubmkIBG5TMs7SxvxN9Z6GPq1KkUf3lGFvezWW6v22YCWSRgwc7iqLhNJnAaAhLsP1MM+4taHCTatGlTZpPP5A0IbVN7Q7IZHgFZ10tV3ex2/d/+03TR/2UCJtABAbvEO4Dip0wgywQkeF+aOHFiNH369FCPm/gw4pi1jTaRFT527Niwy42/U22fbbHO2ki5PXkhYAs7LyPldppAOwKUJyUznCleFCMhczxrbnFi67SNuDW7BPuwxHpnu274oQmYQBcI2MLuAiy/1ASyQkDu8P5K3DpKIhdWLGtLZ21eNhY2gs3NBVXN1M7suQGyMqBuhwl0goAFuxOQ/BITyBoBucRblS3+R4ghc7IpRkImNiKZlQ0Lm5sJlgfVwiXBG5CVtrkdJpBHAhbsPI6a21x6AhLmVrnElyKITJNimheCnaWNmwfi67jtuaFQpvj5WWqf22ICeSNgwc7biLm9JtBGQBZ2bzKvSepqaGgI5UqzNCcbweaGQu2r0ka57Ed78EzABLpPwEln3Wfnd5pAqgRINCN2jUu8qamJla8y4xLnxoGiLm0egIpi7X8gK3trqsB8cRPIOQFb2DkfQDe/vAQkiKtkZS+k5Ofw4cMzI9gkvyHUZIYTY1c7D0msP13ekXLPTSAZAhbsZDj6LCZQdwIS62WyXL91xRVXBLc4Fm0WMsVpA6562jVhwoTo61//+ti6w/EFTaCABCzYBRxUd6k8BJTI9X2J9k4EkilUuMXTjmNzfUqRMpWLZLjrrrvOyWbl+Ui6pzUkYMGuIVyf2gRqTUCu5jkSxplyQe9GsMkUz4JgY+3jDldlsxBnrzUHn98EykDAgl2GUXYfC01ArvHV2g+11eoO1m2aHT7ZwiYxzpsJmEDPCViwe87QZzCB1AnIsq4w3xmrFnd0mgVUuHbsEsfC5rE3EzCBnhOwYPecoc9gAqkTIHZNcRLixmkLNklntIEbiHPPPZfyqYdTB+QGmEABCHgedgEG0V0wAQQbgdy7d2+IGadhYXNNxFru+dAGKrCp0tkH1K6VHiETMIGeE7Bg95yhz2ACqROQYAeX+L59+1JL8kKwuXFAsGVZY2X/Stb1Q3q+mjogN8AECkDAgl2AQXQXTEBCeYT49YEDB0LRknpb2FyPymskvtEOjrK2n1O2+EaPjgmYQDIEHMNOhqPPYgKpEpDr+U+xaknywsKtt2DTebLDqXDG3Ou2Ii69U4Xii5tAwQhYsAs2oO5OOQnI9fxVifV+LFvEMo0NC5ubBtrAVK40bhrS6LevaQL1ImCXeL1I+zomUGMCKgV6iURyD6KJWLJrCc4aX/Wl03MtirZQ03zUqFHH1+euy8V9ERMoCQFb2CUZaHezFASaFMt+CuuW5C8ytuu54RLHusctTtU1/V3fBtSzs76WCaRAwIKdAnRf0gRqRUBJZ39DHJs52Qgnlm89Nq7DDUIcw1ZM/bBuGpbX49q+hgmUhYAFuywj7X4WnoBEs6ppXWuwbnGLY+1i9dZjw/XOtSTUIelN4r1D07qeqse1fQ0TKAuB+nyby0LT/TSBlAlINFuJJZMpzrFeGxY2gs1NAi55XXuXrv1sva7v65hAGQhYsMswyu5jqQgg1PFSm/XsOIJNSVJlrHM8KBE/Us/r+1omUHQCFuyij7D7VyoCJJvhlkY42xK/6hbHJoYdW9g6DiwVeHfWBOpAwNO66gDZlzCBehHAumYe9OjRo6OWlpaQCHb06NGaXx6XOPOwqR+u2uFH5Bb/dM0v6guYQMkI2MIu2YC7u8UmgIWNZd3mlj4+H7sevcYlzrVl3R8ZMWLEF+pxTV/DBMpEwIJdptF2X0tBACs7TjrD8q3XxrW4YdC1D9Trmr6OCZSJgAW7TKPtvhaeAIKJa7rego11zd4WP3914UG7gyaQAgELdgrQfUkTqCWB2MJGvOuxcYOAK5yEM64tl7inc9UDvK9ROgJOOivdkLvDRSaASFM0hSUuWTWr1uVJsaqZd33JJZdEI0eODKJdZL7umwmkScAWdpr0fW0TSJiArN0jiDbTunCLE1euZRwbwcaqpiQpNwpY295MwARqQ8CCXRuuPqsJpEJAMeSdEuhHY/c0jajHil3xTUF8TKXzvqgJFJyABbvgA+zulYuArNydra2t30CwSQCrh4DGVjaWdj2uV64RdW9N4GUCFuyXWfiRCRSCgNzhzQh27BKvdadilzhu8VrHzGvdF5/fBLJMwIKd5dFx20ygGwSGDx/+iLK2P8kymwgoFnCtNs5P0hkJZ046qxVln9cEXiJQu2+yCZuACaRGQO7wgSSfIda1dlMj2ljz7LawUxtyX7gEBCzYJRhkd7GcBBBr4tjstRLS9glt7R+Xk7h7bQK1JWDBri1fn90EUiPAFKs4+axWgs1NAecmjh1b9Kl12Bc2gYITsGAXfIDdvXISQKwRUBLBiDEjqLXasOCJl1OopZbXqVX7fV4TyAsBVznIy0i5nSbQBQJYvVjXSkAL87APHDgQ7d+/vwtn6NxLuQ43BKNGjYoaGhqIY/9O597pV5mACXSVgC3srhLz600gYwSampouVPz4FSY0yWa4rGudeBa7xRFvrcHtOuIZ+3y4OcUhYMEuzli6JyUk0NjY+Gv79u37ro4/OLn7JIEdO3YsWNi1SgjjvPF12q7V/+R2+G8TMIFkCNglngxHn8UEUiGgWPVyWdIrdPFftW8AVi/xZOp7S9BrFlvGiuc6ipVXBw8eXJFob2rfDj82ARNIjoAFOzmWPpMJ1J3ARRddtEQW7gO68NH2F5d7usICIMSwDx8+HG3YsKH9fyf2mBsDltbUdSoS7I/ouD2xk/tEJmACJxCwYJ+Aw3+YQP4IyMo9fHKrJdgrlb19eMiQIf2am5tDUZOTX5PE31jYZKLLyv68xPpj+vuEG4ckruFzmIAJvETAMWx/EkyggAQknHy3K3GMudZdlKXNzb8NgFqD9vlLTcCCXerhd+eLSkCCfURifazW/cPCZtO1/FtSa9g+f+kJ+EtW+o+AARSRgJLNvquEtM0UNFFsOZQnTbqfFEwhTk4MW9te7a9wzSd9TZ/PBMpMwIJd5tF33wtLQJbvSgnprgsvvPC4YMfWcFKdRqiJX3PUuVt03takzu3zmIAJvJKABfuVTPyMCRSCgBLPqlQ7Q1ApVZrkhvhjYcfrbh89enS7nqu5Cz7JPvhcJpA3AhbsvI2Y22sCnSRA5TGWvERYeZzkRjIbYo27naNuCKpJnt/nMgETeCWBZG+7X3l+P2MCJpASAUSaoiZY18yXTmqLXeucmwVGOCZ5/qTa6fOYQNEIJPctLhoZ98cEck4Awca6TlpQsa4RbXaE2mKd8w+Km58bAhbs3AyVG2oCXSMgIT07toBr4RKPLW0E3JsJmEDtCViwa8/YVzCBVAgotvw2lr7U1KsqVnaSG2JN7JoscY5Jnz/JtvpcJlAUAhbsooyk+2ECJxHQXOynxo4dW7n44osrJJ/FbuyTXtblP+PzqI55NHr06EjnD7HsLp/IbzABE+gSAQt2l3D5xSaQPwKIdS1c4u2ndSV9/vxRdotNoPYELNi1Z+wrmECqBEgKwypOOtaMSLNzbieepTrEvnhJCFiwSzLQ7qYJ1EK0k74J8CiZgAmcmoAF+9Rs/D8mUAgCCDVzsUkMS7LimcW6EB8PdyJHBCzYORosN9UEukMAwWZ6FyVKEW3+TmLjPLEr/NgxVyVNgqnPYQKnI+BKZ6ej4/8zgQIQQFQRapLEWluTW5+Dc3IjwB4LdwFwuQsmkFkCtrAzOzRumAkkQwBhPe+886IhQ4ZEmuqVSMY41nX7aV2y3l09JZnh8llM4JQELNinROP/MIFiECCTm+ImiDVu8Z5aw4g1O0VTWG9b5z4kK7uxGLTcCxPILgELdnbHxi0zgcQIxCKbxAnjZDPOifjr2KTndiZxbp/DBEzg1AQs2Kdm4/8xgcIQaC+yNeiUNFvq7c0ETKCmBCzYNcXrk5uACZiACZhAMgQs2Mlw9FlMINMEamwAH5MF73ldmf4EuHFFIGDBLsIoug8mcBoCiDWJZxRN6WnCWfvLcN628+1VJvqO9v/nxyZgAskTsGAnz9RnNIFMEUBUyQ4nq5u52ElZ23H1NJ1vmzLF12eq026MCRSQgAW7gIPqLplAewJY16zYxdrYCHdSgk3BFKaL6bhN53SWeHvofmwCNSBgwa4BVJ/SBLJEAAsbyxqxTqIqGYLPzvkGDRrE3i9L/XVbTKCoBFyatKgj636ZQBsBLGyElWpnSVrYnE/Vzpargtp9hm0CJlB7Arawa8/YVzCBVAlgDSPa7EkmnbW52uek2jlf3ARKRMCCXaLBdlfLTQDhTnLjfLoBcEnSJKH6XCZwGgIW7NPA8X+ZgAmckYB/Q86IyC8wgWQI+MuWDEefxQRMwARMwARqSsCCXVO8PrkJmIAJmIAJJEPAgp0MR5/FBEzABEzABGpKwIJdU7w+uQmYgAmYgAkkQ8CCnQxHn8UEMkugLZs7TOliWhd/J50xntnOu2EmUCACFuwCDaa7YgIdEZA4b9HiHKHaGfW/kxDr+Bxapat3R9f0cyZgAskTsGAnz9RnNIFMEZC4/pRa4tT97uniHwg14s8ua72q4ikbMtVZN8YECkzAgl3gwXXXTAACW7ZsefcFF1wQDR06NDr33HNDxbPukkGozz///GjYsGHxwh/Lu3suv88ETKBrBCzYXePlV5tA7ghIrCvxal09tbBxqWOps1Qnj2Vh/yx3QNxgE8gpAQt2TgfOzTaBrhCg7jcC29Na4rwf0Ue0OZ+2lq60w681ARPoPgELdvfZ+Z0mUDoCCDZucZbp5CZAMe0jpYPgDptASgQs2CmB92VNII8ESDpDtNl57M0ETKB+BCzY9WPtK5lAYQgg1prSVZj+uCMmkAcCFuw8jJLbaAImYAImUHoCFuzSfwQMwARMwARMIA8ELNh5GCW30QRMwARMoPQELNil/wgYgAmYgAmYQB4IWLDzMEpuowmYgAmYQOkJWLBL/xEwABMwARMwgTwQsGDnYZTcRhMwARMwgdITsGCX/iNgACZgAiZgAnkgYMHOwyi5jSZgAiZgAqUnYMEu/UfAAEzABEzABPJAwIKdh1FyG03ABEzABEpPwIJd+o+AAZiACZiACeSBgAU7D6PkNpqACZiACZSegAW79B8BAzABEzABE8gDAQt2HkbJbTQBEzABEyg9AQt26T8CBmACJmACJpAHAhbsPIyS22gCJmACJlB6Ahbs0n8EDMAEOk+gWq1GR48ejY4cORLx2JsJmED9CFiw68faVzKB3BM4duxYEOzDhw9HPPZmAiZQPwIW7Pqx9pVMIBUCsoilrcei1tbWHoss5zh06FB04MCBINyysi9NpVO+qAmUkIAFu4SD7i6Xi0C/fv2GILLNzc1RS0tLj0Qbd/i+ffuiXbt2hXOJ5Nhy0XRvTSA9Ahbs9Nj7yiZQEwKyeivtT3zOOec0INRYxbiyexJ7Jna9d+/eaMeOHZyrIgG/uf21/NgETKB2BPrU7tQ+swmYQBoEKpVKdfv27X988ODBj+7evbvfs88+Gy1dujTsmzdvjl3Z3W4abnG2ZcuWRb/4xS8+NG/evA+dffbZ0cCBA3G7XzB69Ojd3T6532gCJnBKAhbsU6Lxf5hAPgls3Ljxz+Sy/tiWLVui5cuXR9u2bQvHNWvWRI2NjSHDu6c9w0pfuHBhsNaHDRsWSaSjwYMHV8eOHbtr//79I84666xtunF4Sdl7ejG/3wRMIBA4wXVmJiZgAvkgsHPnzutlQY+Um7uVmDKubmLU/fv3v1Ri+akNGzZEmzZtihYsWBDc12vXro2wrvWe8LqeZnhLjKMJEyZEw4cPjxDs8ePHRxdeeCHPVS+++OLKnj173qu4+WpZ3r15HutbbTuo1z+aD8JupQlkj4AFO3tj4haZwBkJrF69WvrcPIjkL4l3iE8TVyZOjWXNcwj51q1bI1m8kVzj4W9i0D2NY8eNGzJkSKT4eIQ7PBbliy66KBo0aFB0wQUXRDw+77zzoksuuSS87vzzz+f48QEDBvxS/39cuIm548aPz+ujCZhAxwQs2B1z8bMmkBqBkwVMInubhPgPiA9LbI9hSUuwb0GMsaTXrVsXsrY58n+xOMdTuXBfE3fmGO9JdK53795Rr169IqxtHsdHHp977rnRiBEjggV+1VVXRUOHDo1GjRoVNTQ0YGlv0/8v7du3by+J93yJ+O8n0R6fwwSKTsCCXfQRdv9ySUCi+17Fnt/f1NTUV8LcX9byIKxm4tF6Lri7saB5LPdzmGKFUGM9kxGOJZ3mJlEOVjXWtlzk4TEijpWNRY513ibqrXKT75Y1PkDW+DflXn+nhP9Qmm33tU0gqwQs2FkdGberFASwppUkNkBW6fHvoizTA6tWrZoj63kGLu+VK1eGZDFi0rE1HcetmRfNjgXNEQsay5pjmhuWN5Y2uyzpcOzTp0+kOeFBqLG4caNfccUV0cSJE4PbHItciWu75CWYIKHfH7dfgt4iEXcCWwzEx9ISOP4jUVoC7rgJpEBAgtpbgtwgS/hqidqXlaB1LvFnXNoUOcGSxt2N9cxR07TCcySOIda8Jq+bkuKCpS1xjsaMGRN2BBxLnJg3O5Y5r+Mosf5z9fVRPd+o12zJa7/dbhPoKQELdk/sjYCiAAALiElEQVQJ+v0m0A0CKj7yJlnPn9M0q3NkYYcMboSZqVdxohgZ3bi2EefY1Y27O7aou3HZTLwFqxtLmyOizI4LXfHs4C7HZU7CGhY3cW9i4GSiK1HtSQn7bRLwdP39maDoRpSRgAW7jKPuPtecAK5ubcEvLSv5DRLdX5fQHkZ8ZUX31f/fqZj0EEQaqxl3N1OvcH+T5Y1Ax1OvcG+fvNe8AzW+gNiEK8RJa/zN49iqRrDJLmd+9+TJk0PyGla4LO7vy7XeqGlivXC1S+j76PFDEvkf1LjJPr0JpE7Agp36ELgBRSMQi7Us5WUS5yOypC/RlKvzcGuzY0FTwIQkMaZc4QZnx9WNC5znYrEuGpsz9Yc4N0IcW9skpiHeuMZxlfOY55j/jUsdy1ux8J0S7Ccuv/zy153p/P5/E8gzAQt2nkfPbc8sAcWgN8vtPZy627H1vH79+gj3N1Y1R0Q6nnrFEVd33t3dPR0QLO3Y2sZlHrvPsb6Z8x3HuFVRLcS8iYFfeumlYdqYLPIvyAp/R0/b4PebQFYJWLCzOjJuV+YJyHIeLEGuyCX7N3r8dgRYx2Apc6SQCdZyPB2LI89x5P/TnnqVecAnNZC4NxXTcJtjYWNpt09Ww4XOc4g6cXBex2NZ6+tltd8ra3zhSaf0nyaQKwIW7FwNlxubBQJyeZ8tIR4jF/ZXlRg2GRf3Cy+8UFUsukJ9baznWKSZboX1zE4cOn7M0VvXCcQWOJb3yZY4Io3rfNy4cdHIkSODqFM+Fbe5xPzjSmL7kV6zRO/b2vUr+x0mkD4BC3b6Y+AWZJiARHagYs1vUYGSoZp2VdVeUab2eFl7b1S8uQ8xZ6xlFtkgPq3502H6Fa5wRBuRjrf4cXyMn/ex6wQQa7b4iMsc65vYd+wiJ97d0NBAdnlV870rzPtWMt8PdBP1uF7bB4HX6yuyyo/qtX+lcdHpXCK166Phd9SLgAW7XqR9ndwRkFCfJ0v6ce0TZUX3QZBJFFuyZEkQZSxrhJnMbxLG2q85TZa3Xd71HXKs7jjTnGliuNCxuDlS2xz3ONb2ZZddFuLhPOZ5jqq89lEJ+gfr22JfzQS6RsDLa3aNl19dAgKytMZLiP9RAjxDAn0hIk2iGMljxKBZAQvxprgJgo0wYzWfvJcAVaa6SPiBnXKtWN7xjpATzyZpjbnd5BVQIpVCNdxoEZ6QwP+JMvf/u173kCzuP23fMVve7Wn4cZoEbGGnSd/XzgQBCe9XFIv+LSzm2MWNO5skMgQaAcDtzZEfe+ZNx9OwsK4Ram/ZJYBwM10Mq5ukNCqq4T5nWhhuccSb56hvjts8tsaxyPWanSreclF2e+eWlYmABbtMo+2+Hicgkb1AYnuOhPdtEuoPSqCrixcvrmBJayWsULM7Fm8ssfbJY+0TyCzWx5Fm/gHu8ninsfFjjgg4RVqIf7NTYY2dx0pY2yLX+n+Vpb5Vgr9ZNwDH65xnvtNuYKEIWLALNZzuTEcEJLgjZSnfKAu5l1zYVc11vlCuz9fqB/gu3N2ymKs6VhBqCprg+maPrWhi04g0lpoFuiPC+X+OODdTxYhns7d/zN/xKmP67Dwob8xPiY3LIu8tC321rPKn8k/APcgDAQt2HkbJbTwjAQmp9PSVGb5K/pquUp9/Kwv6NmLOCDTx51iYOeLupm43ljTizGNc3XEhE0/BOiP+3L+AmzEyzHGbs7d/jPWNm5w53ySsYXXjLscC15EyqY/J8v6W9u/kHoQ7kGkCFuxMD48b1xkCsVhLcG+Q0L5fIj0UwVUyWKsej5Z1PRJXNzW642Qx4tDsceIY4oz1HFvQ8bEz1/drikMA4Y43XOVsHLGwEWzc5g0NDSHWjXgT90bMldC2Qx6bFbK4K7LWBylm/k49/8v4XD6aQBIEXv50JnE2n8MEUiKgOPT7JMx/Jwu6KlGuIMbEoBFqEsfI5iYjGOuZneQxdh4zBcsCndLA5eCyiDguczLNSVIjWS1OYMP6RsyZ883zrO/NYwn5QQk8C5O8Xf//lRx0003MAQELdg4GyU18iYBEtSIxHiRLphdubCWCVeWSvE/H35ZQ30nxEizmOHGMxytWrAjCjSjHVjRnQ6Dj3XxNoDMEEO7YAo8fY30j1GSZc5w5c2aYOoYlTrU1stKxwFUa9TP6nP6zPqcb5G7vrRroTTqHpxd0Brxfc5yABfs4Cj/IOgFZzW+S8H5WceZzsZ6JOWMlYz1jWUuoKzoGi5rYNK8heYzXtRfrrPfT7csXASxvhJkjFnYc78bSJjmNI/9H3BsLnV2W9+sl4ms0L3yxhLslXz12a9MiYMFOi7yve0YCsoDPktjeIuEdJ2EeKNH9BFY0c6TjdaOxonF/E7PG5R1b0hQzYSoWf8dJY1jU3kwgaQJY2fL6BOsbFzmPWSIUNzqu87YYdzxFDAu8Kku8gphL6D+t9yzT6+bq77lJt83nKxYBC3axxjP3vZGoNkiEPyUB3i+xHiLrY7qmY12AGCsWXdXUqwru8DVr1oRM7zjjG2GOp1/lHoI7UAgCuM0RbqxvrGpc5FRaY586dWqovEYiG650ifwqvfZZJatVZY2v0PN/UQgI7kSiBCzYieL0yXpCQGI9UjHnZyTCIxBi5kXj1ubI37i2qTaGOMcJY1jW7FjRWNTeTCBLBBBtLG0qreEWZ8cKx+pm6hhHktbINme6GI+VfX5UxVo2KC7+Zon4r7LUH7clXQIW7HT5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"}))),I.createElement("image",{x:342,y:60,width:51,height:83,xlinkHref:"data:image/png;base64,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6krkd0Y8y9l94Q/Lwu6v1taGpV/a55tYbjKmDtlNtW765fG1/eN8umG44+KhFPnOGtYOQkr26iTffmu6TsoHntSwArp+0hgefLQEBQCCCCAAAIIIIAAAgggUFYBSWD5cDPqcUmglOz6tIlt7Vs7mmuv1Eb/wIdabkI+Xmv77x1N0XvlcsBNRuvjlDGTleo5WRoJOQ2VDN1N1JQNhoA2T8SWdG4igRWMw8koEEAAAQQQQAABBBBAAIGCCEgiQieUdu4I579NF38B9/4odZ2d18iC7pcFfEF3Z9hhSQ6+ozdRZUhX9X8f8Lx4AsbWdzutS/KUDQEEEEAAAQQQQAABBBBAAIG9AlsurYnJo6P96GFMada/6mvjLOhulHW57COr0xeGxwgUSMAY+xanKRJYBQKlGQQQQAABBBBAAAEEEEAgCAKZtOXP2VeCL9eyPVaOYyBrQ62W2UlLytE3fSIQcIHHJtzS9TdnjCSwAn6kGR4CCCCAAAIIIIAAAggg4EbAVsqf61/JDKjd1vCDFhl3M+58y6ZT4f8nbezItx3qI4BAHwGjf7n/GQms/RJ8RQABBBBAAAEEEEAAAQQQcAT8msBqn9Sy6aVyHUJnQXe5hvDKcvVPvwgEUODfw9LdN+0fFwms/RJ8RQABBBBAAAEEEEAAAQQQkLXIfZvAKsvlg33fMnWp5DWSxPp73308RgCB3ASMVteMbdu+a39tElj7JfiKAAIIIIAAAggggAACCFS4wCOLpkSE4CRfMmjzz3LHrdtURhnrExIHC7qX+2DQv98FXq7qSV/TdxAksPpq8BgBBBBAAAEEEEAAAQQQqGCBMTu3nyjDr/YjgbHLs4B7fytnQXel9M399/McAQSyF5DZV98b37Z1e98aJLD6avAYAQQQQAABBBBAAAEEEKhgAa2NX9e/Usa2H/fKoUub3gXdX/RKPMSBgM8EnutRw77XP2YSWP1FeI4AAggggAACCCCAAAIIVKqAtk/16dC765/dstErsR+/dPOz2qiveiUe4kDAVwLafGWgGzKQwPLVUSRYBBBAAAEEEEAAAQQQQKCIAsY6vYitF7Fp/S+9QqWL2IHrpqPp5M9Y0N01GxUQeDTW03ndQAwksAZSYR8CCCCAAAIIIIAAAgggUJECxq8zsMq+gHv/t0vvgu7avlz2s6B7fxyeIzCwQFpp/dHe750BXieBNQAKuxBAAAEEEEAAAQQQQACBShPY1jBmhIx5gi/Hrb2xgHt/u/qWrjWSv/p1//08RwCBQwUk0/vNupbEXw59Ze8eEliDybAfAQQQQAABBBBAAAEEEKgggZ6qKmf2lfbjkI2tH/Nq3D2h9BUS2wtejY+4EPCIwKPbR4z75uFiIYF1OB1eQwABBBBAAAEEEEAAAQQqRMAo7ds7ENppyzN3IOz/djnh5me3SVaQBd37w/AcgQMCL1sZ03TmtY+mDuw69BEJrENN2IMAAggggAACCCCAAAIIVJyArZRfE1jPTWxr3+rlAxZNJX8uSay/eTlGYkOgXAJaq89Eb+3cMFT/JLCGEuJ1BBBAAAEEEEAAAQQQQKASBIzy5QLukhjy7OWD+982zqLU2piPy3MWdN+PwlcE9gr8LtaSHPCug/2BSGD1F+E5AggggAACCCCAAAIIIFCBApII8mUCyxjvrn/V920UXdq5TvJXN/bdx2MEKllAPnOe3KOHfSBbAxJY2UpRDgEEEEAAAQQQQAABBBAIqED7gvrxMrQxvhyepTy7/lV/TyusPi/7nu+/n+cIVKDAC8pS509q2fRStmMngZWtFOUQQAABBBBAAAEEEEAAgYAKWMb26/pXzhHxTQIrelPn80rrKwP6NmJYCGQrYMvsqwWxJclN2VZwypHAcqNFWQQQQAABBBBAAAEEEEAgmAJ+TWDZVVbPv/x0SGKTEj+XeB/2U8zEikBhBfQVsdbkH9y2SQLLrRjlEUAAAQQQQAABBBBAAIGgCRh7sk+H9PRxNz/7sp9i14uVbWnzKYlZbvzIhkClCeib6loT381l1CSwclGjDgIIIIAAAggggAACCCAQKAF9uh+HI7f08/wdCAdyjbZ0/ln2/+9Ar7EPgeAKmNV7XqhelOv4SGDlKkc9BBBAAAEEEEAAAQQQQCAAAqZBhWQYp/hxKHJC65v1r/r7WmFzhex7rv9+niMQUIFnIqnMRZOWbdqT6/hIYOUqRz0EEEAAAQQQQAABBBBAIAACnVbta2UYR/hyKEb905dxS9B7F3Q3X/Fr/MSds8AumTn4B1nM/3PaqIU5t+Kviv+2Mmbe+Lat2/MJmwRWPnrURQABBBBAAAEEEEAAAQR8LmAs7dcF3JXS/ryEcP9bJtbTeZ08fnT/c74GUqBHRrVS7rq32Bhr1rYR40bXtybfWdeS+J68f53kcdC3Hm2p90Zv7dyQ70DD+TZAfQQQQAABBBBAAAEEEEAAAf8KyP3sT5OTaz9ur0RPTD7tx8D3x6zbVCYxX33cWGqt7GOCyX4Yf3+Vxfn135Uy98sMq/si4dSqg280EO8d3eaGCccZlb7c30PNInqjPxJbkliRRckhi5DAGpKIAggggAACCCCAAAIIIIBAoAVO9eno/unc0c+nsb8aduyW5EMdTdEbJIn4oVd38sBvAjK7yNxntLo/FFIPRG9KPn+4AcglhDoRSd8gZY49XDm/v6a1ujrWmijYzQpIYPn9HUH8CCCAAAIIIIAAAggggEAeApI44Q6EefgVoqqVUleYiHqPtBXohEYhrLzRhnlWK2ulrczyjMr86fjWLR1u4ko0xb4hCa95bur4rawk6X4bm5T8UiHjJoFVSE3aQgABBBBAAAEEEEAAAQR8JNC1qOaI9C51vI9C7huqbxdw7zsI53GsLfnvjsbaL2utf9H/NZ57QuBFiWKFLLy+3E6n759w65Ynco2qo7n2/cqYL+Za3yf1Hpak7MJCz5AkgeWTo0+YCCCAAAIIIIAAAggggEChBdIvhV6nLBMqdLulaC+kzGOl6KdUfdSd1HldYmP0A8qoqaXqk34GFUjLK/+Q2YnLbWUv3z5i/INnXvtoatDSWb4QXxCbpWzzyyyL+7OYUZ06oi6KtSZ3F3oAJLAKLUp7CCCAAAIIIIAAAggggIBfBCzl1/WvVCiVCcwMLOft4sxW6WiyPq6V/bA8ZUH30n8PPbM3YWWW9+jhf5rUsumlAyF0HXiY46OOprrjlW3/VqpX59iE56vJZYM75Y37jthNyc5iBEsCqxiqtIkAAggggAACCCCAAAII+ELAPk1SJ76ItF+QXePbtm7vt8/3T+tb448mmqLXSyJgke8H4/0BbNFKr3bWsbLC6vfFSro4DImG6Gij7GXycIz3WXKOMKOM3Rxb2lW0mZEksHI+NlREAAEEEEAAAQQQQAABBHwvIAksX26P+zLqbIJOqS8ouQRLirKgezZe2ZfZJcnaPxtJWMkEt+VOsjD7qrmXfGTRlIja9WybtHBi7q14v6akwT9dt7Tr7mJGSgKrmLq0jQACCCCAAAIIIIAAAgh4WUDr02TNJd9tRquizfIoN0bvgu5N0S9JQiDYayUVH7oo61i5DXvcrmevkW+xc93W81N5ea/+WNa8uqbYMZPAKrYw7SOAAAIIIIAAAggggAACHhToaqw5Nm3UcR4MbeiQjAnuDCwZfd2JyetlQfcPsqD70G+FfiVeXcfqiGF7/jjmhud2Hng9/3WsDrSV3aN4Y+xLMuMr2JeDavXHaGfys9mJ5FeKBFZ+ftRGAAEEEEAAAQQQQAABBHwpYDuzr3y6yW0TA53A6rOg+0NyiHx5l8gSvbVeXcdK2/qeulsSpc9SDTLQjuba9yljvj7Iy0HZvT7VUzVfr1DObLeibySwik5MBwgggAACCCCAAAIIIICA9wQySr/Zl8u3K5VOVUWe9J5oYSNy1miKN8eulyTIfxa2ZV+39rwsvH6/s/D6vnWsnvHiaBLzo1ONUTdJbHJTvsBuW0K2Pa+u7ZkdpRohCaxSSdMPAggggAACCCCAAAIIIOAhAW3U2/15A0K1YeKN7d0eoixaKLrHfNHsXdA9yHevO5zfbll4fc3+hdfrToz/zZmddrgK5X7tmabx9RLvnRL38HLHUsT+d2tbXVh7S1eiiH0c0jQJrENI2IEAAggggAACCCCAAAIIBFsguaD2DNtWM/05ymCvf9X3mDgLuicao1+UReuv67s/wI+d5NRftVbLnVlWdiSyxk/Jyo3NJ4wK2933SGJ4XJCPkSS/F8ZuSTqXt5Z0I4FVUm46QwABBBBAAAEEEEAAAQTKK5BoiI6W5NWvJAp/ng8aK9DrX/V/d0RPSt4gC7p/KMALum+S2UrLjbbvs3r0/U7Srr+BH56bOSqcUN23SvLqVD/Em2uMckfFL9YtTf421/r51PPnB1Y+I6YuAggggAACCCCAAAIIIFCBAmaxsuJP1bzTaPNjSRhM8C1BKNgLuPc/LgFc0H27UuZ+bfTytAkvn3hLe3v/MfvxeaK29keSZHy7H2PPOmajbqhfmvzvrMsXuCAJrAKD0hwCCCCAAAIIIIAAAggg4BUBmS2hE/NjU2Qp6QsTG+wmrfUEr8SWaxy2rqwZWI5T74LuTbXXyuH8aK5uZaz3ivS9ypllZduZ++pP7vqH19excmvV0RT9lCSvPua2np/Ky2fJA9tHjvuIUsmyhe3Tm06UzYuOEUAAAQQQQAABBBBAAAFPC5gGFYqH66ZZ2m6Qk84LJdiYpwN2F9xLsdbk0XIiK0OrrK2jqe4YreynZNReX9A9IzH+XY6RrGNlL7erqlb7aR0rt++qRHN0ntxx8G6pF3Jb1y/l5ZtN3nfWNEmkvlDOmElglVOfvhFAAAEEEEAAAQQQQACBAgjIulbD7bA919LWu+QOaBfIbJeALiKt19S1Jny6+Hz+BzrRFP0PSSZcn39LBW/hmb0JK7PcSun7/LqOlVuVjsa6yVrba6TeUW7r+qj883Jsp0nieGO5Y+YSwnIfAfpHAAEEEEAAAQQQQAABBHIQ6F2MPWLOs5Q+35lppZU1Yu+0pCDPU7Afy4EqMFWirckb4pLEchIKZR7Udq30it47Bdrhe4OyjpUb0/YF9eO1nfmD1Aly8iplKdMQbe0se/LKOTYksNy8QymLAAIIIIAAAggggAACCJRRoHN+TSxtWfMspZyk1dskiRDZm7QqY1Al7bry1r/qyyuJK9Nu2Zdr23pY9pfykjVZx0qvldl9y+VSsuV1J8b/FrR1rPo6D/XYmfFoTOZ2KVc3VFkfvy5XRpr/kOTVA14ZAwksrxwJ4kAAAQQQQAABBBBAAAEEBhCQtY+OV8o+X5JVDRllpksSQ1dW0uoAijH68QPPKvPRhCVdf4031/5SGV3MRcMPWseq54UjVk1atmlPZYofPGrnbp6Jp1SLrMI29eBXgvXMaHVVfUvnzV4aFQksLx0NYkEAAQQQQAABBBBAAIGKF3BOkOMb6t7Qm7TS5mJl7FP2olRq2urVt4Sxq61/vvqsgh8YE/qyvD/eJ8nMsQVkeHUdK5nctbzcC3YXcFwFbSq+MXq11r03Ryhou15qTJLlbbGWxGIvxeTEIu93NgQQQAABBBBAAAEEEEAAgXIKHHTnQKPeK2dqteWMx6N9x+tak/Ueja3kYcWbYx9Uxvwq144lHbpN1k970FnHKqMyfzq+dUtHrm1VSr18zX3i9Eh4hH12zbVdctmotzYSWN46HkSDAAIIIIAAAggggAACFSKw/YPHjnxld/U8ben3yOVI75BhB3kx6LyPqsx6+X2sJfmuvBsKSAOSgNKyoPt9clJ/TpZD2iWGvQkrbck6VjcnmM2WJZxTrKO59jxt9DJ5GHFRzW9FN/eEUmedcPOz27wYOJcQevGoEBMCCCCAAAIIIIAAAggEUmDTwnFjq9ORdytLvWd3tzpPEgrDJHnFlp1Axa9/1ZdJElcmqc2lttJ/kffQcX1f2/c4LTmuh5yF1yVJet+2I8b++cxrH00NUI5dQwhsbqw5WZJXbVIsyMmrHUZb7/Jq8so5RCSwhnij8jICCCCAAAIIIIAAAgggkI+Aswi7NuY9km94j8qo6bI4coikVU6iJLD6sUVbOpPx+bEpyjLfkZfOkPdYlzLWeqMy9x8xvGfFmBue23mgSuLAQx5lLdDVWHNsWlv3SIVjsq7kv4JppfXF9S3xf3k5dC4h9PLRITYEEEAAAQQQQAABBBDwpUBHY91kpe13yWLI50tSYboMgnOvPI+kMdap9Uvj6/NshuoIZC2wvmFy1cjwjj/Jd++crCv5saDRH69bmviZ10NnBpbXjxDxIYAAAggggAACCCCAgOcFeu8c+FTddEuSVnJF4IVyh7gT9wbN9YEFOng9u9IjNxaoLZpBYEgBZ42xZGTH9fJ1zpCF/VzAmO/VLU16PnnlEJPA8vMbjdgRQAABBBBAAAEEEECgbAKbL5swzOrpmWkp6/zEBtWgtT2edFWRDodRT0xuW99TpNZpFoFDBGSB/Ctl2uTCQ14I0A75vPpDXbrzCr8MiQSWX44UcSKAAAIIIIAAAggggEDZBbYuHHfknnToXEtbDaYnfYFS1iiSVsU/LMZSrH9VfGZ62CfQ0Vh7sSSvvhpkEBnf34al9lwiS9Nn/DJOElh+OVLEiQACCCCAAAIIIIAAAmUR2NJw3JieSGiepXRDT0a9Ve4cWEXSqrSHwlIksEorXrm9tc+vma61/rUISI4nsNsWy7YvGNu2fZefRkgCy09Hi1gRQAABBBBAAAEEEECgJALxS2Kv1Za5SO4YeFFKqTfLmaxF0qok9IN1wgyswWTYXzCB3juGKvsOaXBYwRr1XkMv25b9rrrWLt/dlpIElvfeTESEAAIIIIAAAggggAACZRDof+dASVgFeQZGGYTz6DKkHsujNlURGFJgY/MJo7Tdfad8148ZsrB/C9jK6AUTlnT91Y9DIIHlx6NGzAgggAACCCCAAAIIIFAQgX1JK1mA3VysjH3K3kaZa1UQ3MI18u/YTcnOwjVHSwgcLPDIoimR6l1bb1Nan3rwKwF7ZvTn65YmnBlmvtxIYPnysBE0AggggAACCCCAAAII5CJgFisr/lTddEvb75I01fuUsl/b245cK8jmUQHD7CuPHpnAhDV219YfyYTLtwRmQAMP5FeSvPr+wC/5Yy8JLH8cJ6JEAAEEEEAAAQQQQACBHAVMgwrFw3XTJGnVkNioLtbaPo45VjlilqEadyAsA3oFdZlojH5ePg8+GughG7ViZ/qojymV9PUwSWD5+vARPAIIIIAAAggggAACCAwk0LWo5ojMTmueswi7rFT8Tq3so3qTVmSuBuLy9D7uQOjpw+Pr4OKNsfcYba729SCGDv5fmerwhZOXru8Zuqi3S5DA8vbxIToEEEAAAQQQQAABBBDIUmDzZROOtnpSb7GUPj+9S10oizGPyLIqxTwsYBvLlwtOe5iU0ESgfX7NG5Q2S+Sh5EgDuz2nLXXBxBvbXwzCCElgBeEoMgYEEEAAAQQQQAABBCpUIHlp7WsyafVOSVo1mJ70W2UdmyomWQXqzZCyq6z1gRoRgym7QHx+rEZZ5i4J5MiyB1O8ALpt275gQmvXpuJ1UdqWSWCV1pveEEAAAQQQQAABBBBAIE+Brktr6lJp6+0ybeJ8O63eLsuvh0la5Ynq0epyXNfL7JFuj4ZHWD4U2NYwZsRuy/xePjeiPgw/25Cd21J8aMItXWuzreCHciSw/HCUiBEBBBBAAAEEEEAAgQoX2NxYc7Jl6Qu10Rel0+pM556BJK2C/6bQyvw9+KNkhKUScG7okIgMa5X31etL1Wc5+tFGLY4tTbaUo+9i9kkCq5i6tI0AAggggAACCCCAAAI5C3Q01k1WcudASVa9SxqZQsYqZ0rfVtRaP+Hb4AnccwKJcOy7kvo+33OBFTQgc2t0aedVBW3SI42RwPLIgSAMBBBAAAEEEEAAAQQqXcAsVlZ8Q90blLLPl6RVo3w9sdJNGL/aiAEChRBINEY/JHcc/HQh2vJuG2b1nheGv18+PwM5QZUElnffeUSGAAIIIIAAAggggEDgBZxLeuLhummWzLRKbFDv08quCfygGWDWAsbSJLCy1qLgYALxptjbjDI/H+z1gOzf3BNKv3fSsk17AjKeQ4ZBAusQEnYggAACCCCAAAIIIIBAMQU2XzZhWCideavKqIsS2shsK3t0IKcLFBOxMtq2dbd5ujKGyiiLJdB7KbKyb5X2g5z/eCFj7HeccPOz24rl6IV2g3wAveBLDAgggAACCCCAAAIIICACXYtqjkjtVOdZ2mowPekLZNco5azEzobA4ALrY23J3YO/zCsIHF6gq7Hm2LS275RSRx2+pK9fTcmlkQ0TW7ue9PUosgieBFYWSBRBAAEEEEAAAQQQQAAB9wLJS2tfY2esC7QxF6Z3qbdoraqZaeXesXJr6OWVO3ZGnq9AoiE6PK3V3dLOa/Nty8v15e8AH61r6bzPyzEWKjYSWIWSpB0EEEAAAQQQQAABBBBQcnng0aFU5iJZQrjRTptzZC3hEEkr3hjuBUx7pir8dff1qIFA7wrmOlGlb1TGnBVkD2PU/9QtTf4qyGPsOzYSWH01eIwAAggggAACCCCAAAKuBZyZDnaVeae2dZPqSb9DGqh23QgVENgr0C3Jz1ad1p+f2Nr+IigI5CKQaK69SpJXF+dS10d1fld3UvILPoo371C56jxvQhpAAAEEEEAAAQQQQKAyBRLN0dOMMR9VSjeLwKjKVGDUBRDokfXQ7pfZJLdbKXWbrHv17wK0SRMVKtDRVHupVvrXAR/+I+ER9tk113a9EvBxHjQ8ElgHcfAEAQQQQAABBBBAAAEEDiewvmFy1YjIixdoZS2SC3XOk7KcUxwOjNcGE3hF3jj328q0pVPVd7627ZkdgxVkPwLZCsgdB2dqbTtrpwV5FmiXpc3UaEtnMluXoJTjh01QjiTjQAABBBBAAAEEEECgiAJymeBoO6I+KV18VE4ixhaxK5oOrsB2Gdpdcse0O+xIZPnEG9u7gztURlZqgURTdJKst7dO+n1NqfsuVX8yvp0hy8yKLun8R6n69FI/rIHlpaNBLAgggAACCCCAAAIIeEzAuQ19SluXy4nTpyRxdbTHwiMc7wvE5X3zR9vY92wfOf6PZ177aMr7IROh3wR6E+xK3S3vtcAmr+SY2NrSC6JLkhWZvHLekySw/PadSbwIIIAAAggggAACCJRAoH1B/XjLtj+fVmaRnBQeWYIu6SIoAkb9U2lzu22ZOyYs6frrgWF1HXjIIwQKJOBc1mzCO34rn1MnFahJTzYjf0T4TP2SxF2eDK5EQZHAKhE03SCAAAIIIIAAAggg4AeBvWtc7fiosjNXSbwj/RAzMZZdwJYI/iYn2PfITKtbJi7terLsERFAxQiMiuz4ibz35gR5wHKDg+vqlyZ/HOQxZjM2EljZKFEGAQQQQAABBBBAAIEKEOhorDlf6x0/lKEeXwHDZYj5CWRk/f4/G1mE3QrLnQNvSnbm1xy1EXAvEG+q/aIkr+SGEoHe/lS3JfmxQI8wy8GRwMoSimIIIIAAAggggAACCARVoP2S8adYobD8dd/MDeoYGVdBBF7WRi2T+07eka4K/14WYX+xIK3SCAI5CHQ0175PGe3MFA3y9vgePexivUKlgzzIbMcml4myIYAAAggggAACCCCAQCUKyMwFHW+KflhOCn4g4z+iEg0Y85AC/5b3x+9tZe4enupZNrZt+64ha1AAgSILdDTVTdHKXindBPdzS6utaZM56/jWLR1F5vRN8ySwfHOoCBQBBBBAAAEEEEAAgcIJbG6YcFwokr5BWpxXuFZpKSACCTlRXMadAwNyNAM2jMSl0VqTUg/JTMDagA2t73C6LW3OibZ0/rnvzkp/zCWElf4OYPwIIIAAAggggAACFSeQaIy+3ej0Uhn40RU3eAY8mMC/nDsHqox1R+yWxKOSwJIJes7GnQP3OvC/FwQ2Np8wyqS7nctYg5y8kjXbzaUkrw59x5HAOtSEPQgggAACCCCAAAIIBFagoym6SDIT18gAI4EdJAPLVuBf8l5oM5nMrRNu3fJEtpUoh0A5BEyDCiXMniXS92nl6L9UfRptvlTf0tlWqv781A8JLD8dLWJFAAEEEEAAAQQQQCBHgd6Tv0jUucPg5Tk2QTX/C6Rk2bMHZW7V7Tpi7uTOgf4/oJU0gkQk+iOZGHh+sMdsbpTk1beDPcbcR0cCK3c7aiKAAAIIIIAAAggg4AuB3sXaI9FfyGVhH/JFwARZSIHdctzvs5W6OxVK3XHCzc9uK2TjtIVAKQRk5uinpJ+Pl6KvsvVh1Ko9Lw7/SNn690HH8lnGhgACCCCAAAIIIIAAAkEVcJJXiabYz2TmAidGQT3Ih47rBa30clvZ98idA3/HnQMPBWKPfwQSzdF5sijUXRJxkCfgPBNJpc8a37Z1u3+OTOkjDfIboPSa9IgAAggggAACCCCAgMcEEk3RH5O88thBKU44SWn2Dlk/5466zs4H9QqVLk43tIpA6QSSC2rPyNjqVpl5E+TcxfMyvreTvBr6fRXkN8HQo6cEAggggAACCCCAAAIBFog3xT4qySvWvAruMX5GTnzvsY3VVrc0vkYey4Q7NgSCIbC5YcJxtp2+S97XI4MxogFHkbKNuXjC0s6NA77KzoME5L3AhgACCCCAAAIIIIAAAkETSDbXnmUbmYejVHXQxlbh4+m9c6BS1t31rfFHK9yC4QdUINEQHW6q1AOSkp0a0CH2DktrtSjWkrwuyGMs5NiYgVVITdpCAAEEEEAAAQQQQMADAslLa19jp/RtSpO88sDhyDeEtMw6WCmN3K7l8sBoS6dzqSAbAoEVMIuVldiglgQ9eaW0+WaspZPklYt3MgksF1gURQABBBBAAAEEEEDADwJ2yvqenBzV+iFWYhxQoFuSVrIIu7o7YyJ3Hr9087MDlmInAgEUiD8V/bbMTLoogEN7dUjaqNuiJ3Z+9dUdPMhKgEsIs2KiEAIIIIAAAggggAAC/hBINEbPNlouvZG7D/ojYqLcJ/DqnQOPGLbn9jE3PLcTGQQqTSDeGPuAJN9vCPi4HwmPsM+uubbrlYCPs+DD44dawUlpEAEEEEAAAQQQQACB8gg8smhKZOyuZ/8pvZ9Yngjo1aVAl6y7fqcxodu3jxyz4sxrH025rE9xBAIj0N5Ye66l9R9lQJHADOqQgZj2tKk6i1mVh8BktYNLCLNiohACCCCAAAIIIIAAAt4XGLtz2wKZd0XyytuHarPMIri7986BJ8XX6sVKrhR0tvjeL/yPQAUKdC6oOSljy7p9AU5eyS1Cd1pGX0DyKvc3OAms3O2oiQACCCCAAAIIIICAZwSchY/jG8wVXGLhmUPSNxDuHNhXg8cI9BFwbjqRSeu7ZdcxfXYH7WFGLo1sirV2Pha0gZVyPCSwSqlNXwgggAACCCCAAAIIFEkgvqH2vZK8OqlIzdOsO4GM3EFtlaxFdnskbN9Rc1MX06vc+VG6QgQ2zjuh2k7vvkOGOynQQzb6k/WtyXsCPcYSDI4EVgmQ6QIBBBBAAAEEEEAAgWILaK0/KEkTtvIJdMu6+auNMvfYqfCtE9vat5YvFHpGwPsC8nGlk8d0X2eUnun9aPOI0Ogf1i1N/CyPFqi6T4AEFm8FBBBAAAEEEEAAAQR8LtDVWHNs2qjzfD4MP4b/ssx6e8BWpq1HD79jUsuml/w4CGJGoBwCyaboVyWJtbAcfZewz2WxdOJzJewv0F2RwAr04WVwCCCAAAIIIIAAApUgkNLWRZJICfCduzx1FJ8T62W2sdt2pY/50+S29T2eio5gEPCBQEdTbYMkr670Qaj5hLg+lapq1G0qk08j1D0gQALrgAWPEEAAAQQQQAABBBDwpYAkVN7my8B9E7Rp10rfZSv77rqurhV6hUrvDb3LNyMgUAS8IhBvjr1JGXOjxCMfXYHdtoRse15d2zM7AjvCMgyMBFYZ0OkSAQQQQAABBBBAAIECC7y5wO3RnFLcOZB3AQIFFtg8f8IEZVJyx0F9RIGb9lJzuyUz957aW7oSXgoqCLGQwArCUWQMCCCAAAIIIIAAAhUr0L6gfryyM9GKBSjcwG05qV4ni7DfHcqY26O3dm4oXNO0hAACG5tPGBUy3XfJ99m4AGvYWqvmWEvy4QCPsWxDI4FVNno6RgABBBBAAAEEEEAgf4FQJnOGCfKFOPkTHa6FPXKyuVzu3nh7OJW+a3zb1u2HK8xrCCCQm8Aji6ZEqndtvU2SV6fl1oI/ammj/ivWmrzdH9H6L0oSWP47ZkSMAAIIIIAAAggggMCrAnIL+vFKMjBsWQs461fdY4xZesTwPcvG3PDczqxrUhABBHISGLfr2Wvks+otOVX2SSX5FL6+bmnyOz4J15dhksDy5WEjaAQQQAABBBBAAAEE9grIJW/jmICV1buhW2Z/fF/Z6qd1tyRYpQ4XEgAAQABJREFUfT0rMgohkL+ALNr+WUkYL8q/Je+2IJ/B920bMe5jSiW9G2QAIiOBFYCDyBAQQAABBBBAAAEEKldAaz2WGVhDHv+NRlvvqW+J/2vIkhRAAIGCCcSbYhfIHQf/p2ANerEhbZ5IRyLvO/PaR1NeDC9IMVlBGgxjQQABBBBAAAEEEECg0gS0MvxOP8RBl0t7ZIH2zFsTDdHRQxTlZQQQKJBA+4KaN0pyvUWaC/Jn1HaVts6feGP7iwVio5nDCAT5jXSYYfMSAggggAACCCCAAAKBEZBL49gOJyCX95ykjf6BiaiuRFPsNx1NNXMlqcWVl4dD4zUE8hDY1jBmhGVbt0gTR+bRjNer9mhLXVx3a+JprwcalPi4hDAoR5JxIIAAAggggAACCFSkgEwt6iYTk/Whr5Y1wxq0shriTdGn4lpfF7Yzv65Z2vVc1i1QEAEEhhTYHan+gXwuTRqyoI8LyB0HPxdbklzh4yH4LnRmYPnukBEwAggggAACCCCAAAIHCbxw0DOeZCXgzMqStXm+m9ZWMt5Uu7S9sfZcZmVlRUchBA4r0NVYc6x8f1122EI+f1HGd190afIanw/Dd+EzA8t3h4yAEUAAAQQQQAABBBA4IGBss0lbcjrFlqtAtVxNOF8I5yeaohsTWl2/x0rdeMLNz27LtUHqIVDJAulQ6BRlm0DnGmxlXy2fupLzZiulQKDfVKWEpC8EEEAAAQQQOCAwc+bMY4wJy5oz5hT5/W6sXLIzSis9QkoMk+e75GTxJbml9g45YUxkVOTva9fe/4y8xi+CBwh5hEDWAiFLb+CbJ2uuoQpOMkb9d1UmclWiMXqXraxr606K36cXO4vAsyGAQFYCWgV+VqiVsv6alQWFCirAn2oKykljCCBQLIFp06aNDlmRb8nprfvPLaOXr173YFuxYitHuzOmzfq03DZdEgMF29LS3vPyV/zntTbPG8s88cILLzy+fv36noL14IOGZk6b/Sl5h70uh1B3r1678tM51AtMldlTZ0/KhM152ljnSR5qhgxsvMvB7ZTyj0hS666ICd2x4s8r2l3WL2nxWdNnzZePo3PcdGoZ9YuV61b+zU2dXMvOnD77S1K3zk39VGbP5x966KGX3NQpRdk5b5pzXDpif60UfQ3Vh9GZz61Zs8Z5r3pqe2TRlMjYXc9KYlhVeSqw4ATzjNHmeqPDN05Y0rElOMNiJAgUR8AsVlZiQ/Qpaf2E4vRQ/lYtbWLRls5k+SOprAjcnwhWlg+jRQABjwjMmjH7O/IX0c/lFo6+Z/XaB8/Pra43a82YPnuzfIBPKHJ0u6WPB+Qk/bYjdlX/5t7H7n25yP2Vtflp0+acHNL24xJETrOTbZUet3bt2oq63GTatHNrQzq9QMwuk38ny7+CbfLe+4uRO4aFq3XbihUr0gVruEANzZo++08y4+WtbpqTmRynrV274p9u6uRYVksCy7md9ygX9XdKEvYoKe+5iTwzZ559vlyKcpeLsRSr6A4xOsaLRs6A443RlZKAn1WswdNur0BKvkPukc+na6MnJe9lVhbvCgQGF5B15T4js62/P3gJv7+iP1DXmrjR76PwW/ws4u63I0a8CFSggHOSLMmrj+U+dHNG7nW9V3Pq1KlyKZaqL0Fkw+VM9h1yPnvDKyO6k7NmnP3VOXPmOJeABXILa/u/ZWA5Ja8cEMuuOj2QMAMMavr0s6fNnH723ZK86pCXr5Z/BU1eOV3Ke+9NSpvWdI/91KyzZjkzujy1SXynuQyoZ8eO7Rtc1smp+OzZsydIRTfJK6cfJ3krw/LeJnd5cmtdnEFo5SQfPWnkDNhodX9xBk6rfQQikiS8UKyXJZ6KxmW9rKufaRpf3+d1HiKAwD6BYame6+ST6dmggmhlPhnUsXl5XCSwvHx0iA0BBHoF5CT56/LgiDw4Ym9+83mvyaO+p6pWW9WnSkCSwyrpdrRc2vU1SSasn3nWnLkl7bkEncl6TVPlrDS/WXqWHahE6UDsM2acPUtm9iy3lFkrv5S+S8qEBipX4H3HG23VFLjNvJpzLmmWBlxeIqmfKNUluSZt3CdTdW8CKy+XYlWWP2B4IoGlbe8a9doba3mxjgHtDiCgVa383LgirEKb4o21d7bPr32naSjJZ+IAwbALAe8JjG3bvktm8X/be5EVJiL5/n+Dc+fSwrRGK9kKkMDKVopyCCBQFoEZM2acJB1fmm/nVVUZT5wA5TsOp37GyuHktBAd722jTqYa/XHGtNk5Xs5ZuEAK2lJGO7OI8ksKauU+aVDQQRSvMWcNopnTZ90kC7I/KL3IGlel3Wyt2kvb4+F7C4WqczjW9mOHb7Vwr8oJg/vPO28nZ9yPp3Ccr7YkJyuluPzz1f7cPtg+csxDUme723qUz1sgrLR+t2XpexKR6OaOpujizvk1sbxbpQEEAiDQ88KwX8gvVx0BGMqAQ5Dv+2/Jz4b8fn8csGV2DiZAAmswGfYjgIAnBLQJO4mFnC/renUQdlmTPq+GUYgHcic3ZwZWObeQ1uo7spD8V8oZRKH6njlt5rvk5GNO3u0ZHcQZWHrGjFkfkQW0n5DfzxaKUVl+SctkwvG8j08BG9C2+4S4fM84l+iVZsthxpLcDbJ08blQmDx5sixKbia5qFK0ol412j/gM699VNZn0i37n/O1LAIx+ZC8MmNZ7fGm2P91NNU2OAvslyUSOkXAAwKTlm3aI39UWeyBUIoTglFTE02xdxencVodSIAE1kAq7EMAAU8IzJo2681y4nJBQYIxwUlgyQosOcz+KIjiQY3IXQu/Lnfty3t23EGNlv6JpbR1VWG6NafsPdkuTGvlbsVZa02O7y3a6J9LLEeXMZ7dDz10n6cWx5e/trqeEWTsUOkSRDnMBuxOR9aX8RgP2vXoEaOd9dUkiVX+zatGB8mE1a8Oes6TcgnIOZaZK39w+o3cHbLDWSurfWH9xHIFQ78IlFMglkrcLP3/q5wxFLdv800uHy6ucN/WSWD11eAxAgh4SsDoAlzWtX9EWgVpdky5Z2DtV3Xm4/xU1o+qO7DDX48kQePcQe/1BYq6at/JdoGaK18zsmj6GyOh6r/J8b24fFG82nOHPJKckYc2o10nkY2VKsklhHKjhWEidYJLreTDD9/3vMs6pSke8kbCXgbb6VmjPkei7uaEc5njI3128bD8AuPlA+wKK5PZFG+OLks0Ry9kVlb5DwoRlE5At6mMzEwMxKz9QdQmxyO1zYO8xu4CC5DAKjAozSGAQGEEZsyYLXe/U+cUprXeVibLiV3+lyIWMKBcmpozdU5U6jm3cffKNkLZoe95JRg3cfTOltLqSjd1hizrnZPtIUMdrIAs1H6OsfQD8vrxg5Up6X5t2kva39CdyaQK9bqhix1U4t9r1qzpOmhPkZ6k0+nJ0rS7zzrjzcsHHSI58Xc9260otNqUbgZdngMw2jh3VGXznoDc/0K9XW5K8LuxLz/bewfD+CWx13ovTCJCoPACsdbk76TVPxe+ZW+0KAm6r22cd0K1N6IJdhQksIJ9fBkdAn4VcH7J+0aBgx9ud9ueWEcln3GlwrbrmR/59JddXfPe6dPneGdWWHZBq6NHjf6YFC1oksY2lgePT5YgUmzmtLMvlIXa/yAPR2Vfq9gltTMDyzObzDicKMGMdBnQP1yWz7m4tnNYwN3LyRmTw3hy1hu8orEt3ySw6lo6fysjKcmMv8HFeOWwAkYd58zKUiGzYf9aWesbnPXe2BAIroA26r8CPLoJ1aP3fCi44/POyEhgeedYEAkCCOwTmDV9VpP8JeMNhQbJBGB2jGXKvoD7QIdFW8r+6EAveHWfzMYbIWt4faHQ8Vna+PZSVfm+m6+0uU1MnEvQPLMZZTyVwMopQVTCZEIuM5bk89a7yRntjRlYJV2EP8/vPjmeMsnHFPqPQHlGRfVBBORcbO9aWSMjO7bKWlm/7Gisc2ZRsiEQOIHY0uSDsvbE8sANbN+AjDFf3f7BY93+gSuoHEUbFwmsotHSMAII5CLgXNYlJ2CLc6k7VB3L9v9d4myvXE5zKPb7ZJdvfqZkUub/SbxjDx1GfnvkvVuo9bTyC8Rlbblhwnlyl6AbpZrnjqEkjDyVwBIn15e0mVLe4S+HBdyN5c3L4yTR7Nw8oNbl27koxS1jnLWlfLPVndg7C+th3wRMoI7AMfIzZJHW9uOSyLpPZmbN55Ik3hhBE9DKfEnGJG/14G3yx4Oxu7urPxG8kXlrRGFvhUM0CCBQ6QLHHHXsR+TnWlHWhJB1QXx9eZfz3pAfjq5PnqXaX6XmIL8sGOeShdHyL9+TxLFyadVpq1evLtmlUhJzTtusWbPGmIz5dE6Vh640durU88bJXfOeHbqoN0rMmDHnTGPsOySaQq/d8Ix8Lz+ktfVPW5lOaX+n/EvLv+HKNuNlBtwk+RV2irypp8i+QX8fkUsaPZXAkphPc74R3WyWXcIEkftL7tIjR4580s14SlU2lTKnCbVLbfWcVCnwe8YYq9p6olTjLkQ/ctN6O9GoPizJ00elvUG/vwrRF20UXMD5gX2ufH6eW31M94uSzPqNfBdcE2tJenemZMEJaDCoArIW1sPxpujtMr6LgjlG/flEQ/QXsbbkv4M5vvKPih9o5T8GRIAAAvsEnMu60j32F4sI4tvLuxyTKVOmROQX2pNd+mxbvXalkyA47DbnTXOOS1VlPqCN/rIUPOKwhQd50WSss+QlzyewjK2vlDhHDjKMvHeHw2knUfp/eTdUggamTZs2WpuMXDaoRxSmO/O0Mvr6jLJuW7duxaZs2pw6deqocLjaWXvrQxLHzP510jrS3n9fWZ+7v6TNHv7y8PWliHlvclaNc9WXURuWLVu2x1WdEhWWs3jXCXtJjP5k1ZoHv16iED3djVyu81i8MXaN/P2iWAl7T48/IMEdLcmsRZI4XyQn/Y/K42sjI+wlNdd2vRKQ8TGMChQIWfYXM7b1bhl6EHMRR6sq9XkZW8GXqajAt8qAQ/bcpQIDRslOBBCoCAFJXn1OBuru5MudTPTNbz7vNe6qeKf0sGHDTpRo3M6Syeovtiv+smLrmjWrvq0se7b0sSuXUcsaMZ5fJH/27NkT5UTgw7mML+s6tm/WwdJhHflfSRrVZz22wQv+U2Z6vHf12lWTVq9beXW2ySunuYceeuilNWtW/lrqzpJfSs6WXTJj8NWtZ926+7e8+qzMD+bNm+d8/7l9nz9972P3vlyK0E0q5DpJ7+W1nSSp6TqBpYzt+SR6Kd4L+/sYlu7+ikxhK/CMtP2t87XEAlPkWP4yvctKSGLyBx3NdW7vhlricOkOgYEFapd0PSV/kL154Ff9v1cWIfxk+4L68f4fiTdHQALLm8eFqBCoOAFn5oAM+jPFHnhVVcb9CVGxg8qyfctYrmN3e3IqlwA+Kj94v5ZlSAcVk1+sowft8OATO22+KWEV9U5P2ieXqs6cfvYn5K/5zl9A89kk2ak/JbP8zpAk1O+kIWky923l2pUrx9eOe7O08BX5l5HmEvJVln7zxvbyiy87J4yu/mIsIKW7G5zl/jJpiS+rJHc5joCxcpiBFdal8y4Hiss+x7Zt3yXfQZdItR6XVSnuXYHRzqw6bez1MivrkY6m6KKtC8cd6d1wiQyBQwXCYbNY9npy9u+h0brec4Rl0s4VDWxFECCBVQRUmkQAAfcCdqb3hHWU+5oua2Rs1zMUXPZQvOLGOt1t48a4P5lLZZxZOe6TBrK4tad/gZ41dZb4aedErrib9v7NAuZMnSPJxvzuUiaJj79ZYXX66rUP/lhAC5Zkamtry0hC7Bsyk+Y9Wmn5K613Nhmk+yRyCRNEckxcx6cs958RJToistavcns3tpdWrlzZXqL4fNNN7JakrEXX+zPWNzETaNYCvbOyejKRTucOhsmm2tdnXZOCCJRRoOamrrgsOfDzMoZQ3K6N/nD8klhR1vQtbuDeb50ElvePEREiEHgB57IuOVFd5H6g2v26Mto3l3cdyqGN25M5+d1Au55d8fDD9z0vJ445XHJiIocG7Z09xtJXSzRuf+7JLCD1hKtRGHWyczdNV3VKXDgVsn8oXY7MtVuZbXerbVIzJFmwOdc2hqq3et3qe0JV1vuHKlfK13UOM4Lkm7BkM4LkuLhOYIXT7j8jSmE+ffq5ddLP0e76Mo615PHY+gtEW5LfkX139t/P88AIHCVv/EW20n/bPytrW8OYAq1tGBgjBuIxgbDKOLPiX/JYWIUKJ2L2zjIrVHu0s0/A7S/ywCGAAAIFFzBpdZU06nZtJzkvVJ+Qei+6C8j9LCZ37RevtFza5/bkNNPdvfNfOUWk1Q7X9YwqyTo/ruOSCrOnz54td3Ga57auJARukfPhZS7rVR1zzDGnuKxTsuIzZpz9FhnXe3PtUGbaXX9c7bjmdevW7c61jWzrrVixQu4o550th+9BuQ6yNAmihoaGkLxX3a6Js3PFn1d0eEf4QCSW6XH7eSeVS5csPBCpPx7J97y8fa0PyKVn7hLy/hgeUR4s0DsrqztSnYw31/6UWVkH4/DMOwI1S7uek8TrD7wTUWEjkRuRNCWaozn8LCtsHEFrjQRW0I4o40HAZwKzp80+TX54NboP26xes+bBB+Rv7S4vMTKnyt0OXa1h4z62wtdw7tQmCZgJ7lrWmx599NEc71RkjnHXl5wdae3Zv6LJe8yZfeV2y6SN9Q2ZtOXyPSbd2CHXl3u6DS7X8rJuyldzrSvfb79Zs/bB/3Qu88u5DX9XdPeLqCR1161b8UwphpxMbp8k/Qx305ckNf4p5eXbw3ubzJh0Z+0MxJRwvTHvkQ0ZUX1r/AX5xf+tUjA5ZGEKBEHgKPnB/DFmZQXhUAZ3DMNTe74rP4S2BXSElrHzW64hoC55DYsEVl58VEYAgXwFZE2Z/5Y2XH8WyV81ehdHlBOwJ13GUJ3JZE50Wafsxaut6lMlCBmuq8315YNO63svf9PjXPXkFDZ23HWdElSYNX3We+WXo2muu9KqRZIPT1rKuH2PORieXGtNZqKdK2+jma4t9lZYO/LoIy+Vh/JtW3nbtGnTRsuoa1yO3EkQlcTLsmzXSVP5vsjpM8KlQU7F5TPefQJLMwNrKOxoS2fStuwLpFxOd5sdqn1e96xA76ys3ZHqLmetrI7Gulx/Dnh2gATmTwHnRhPaaOdcIJib1u9un18zPZiDK8+oXJ80lidMekUAgSAKyKVMs3K5rEtOuu5ftW7Vg46JbRn3s2MyyvWJXrn9ZbqL+5M5YzvrwbjeRo8a7SR7hrmtqLW1yW2dYpd3LquSS96cS1TdbhmjMt9yKqVVOocEljffY5JJ+aJbiH3lX7BVuGnZsmV7cqzv+2qhULX7zw3duyZTScaeW8LHeDaBJYlWt595JpPpdr8uYkmOjrc6mbCk66/GWPPkZ+lOb0VGNMUWkL+CjZTjvkhre5WslbVe7mB4RaIh6iTn2RAom0CmOvQz6TxRtgCK3LGlrVyuAihyVP5tngSWf48dkSPgewFtTE4f6LLQy9f2D17bluvkglzq5snZMfvHNNBX+bB2ZmC52rSynNkfrjfxaXJdSSpYxvw9l3rFrLO1a+sHpH3X61FJ0uvmNWvW9CZH165d60xt/7fLOF/vsnzRi8ui2K+VTmQGVg6bUZ9eu/b+jhxqBqaKtjNuEyrOlMmSJYjkpNR1fJZduvjcvBH23QTB1UxZsX76oYce8uxlzG7GX4qy9Uvjq5W2SWKVAtu7fbxOvm+ultuvyB0MY7/paKqZ691QiSzIAhNvbO+WP8J8PbBj1GqWzHp8S2DHV+KBkcAqMTjdIYDAXoFZ02a9Rx65n1KrzfKVa1eu3O+ow7brGVjyQ9L9TIr9HZbpqyxY7/rk1NYh1zOwZk+d7ayjc1kOw/z3ynUrPTX7QdY6G2aM/moOY8loK/PtvvXkl3y377Mxc94057i+bZT7cUhn3i8xyFBcb6tWr1t5s+taAauQS4JIVpdy/T2YK1sun2t7MlU5JblzjTHbeqNHjD5ZylZlW94px/pXbrT2lq1v6VrjJLHkmcubobjvixqeFhhmlGmQP3r9X7wx+vd4Y+xjTzccf5SnIya4wAlEtyRvlJ+zbn/X8o2DzHr8lowvl9/BfDPGUgXqu4WMSwVDPwggUDwB57KuLZ3bZHFs+Sh3ucldlA76C80rr7yycXj1kSlpJpJtU9Kr72ZgydjcJrB2yYyZzdmaOOUk4TMi3WP/Vh66OnHs7UOr++RrSdb66e0vi/8yPeaTUiyWRdH+RX69evXqDX13yi/3MtNPT+u7b6jHmXDGeZ9tHapciV6XCXL2pbn87qRt8wWJ0f03a4kGVqputNKnukXIaF09c+bMKcWO0cpY1bbrmzyorocfvu/5YseWS/uygLvrGadyWvBiIa3lM+BvErunPtNysRyqjpPEctZD0jpzj3w+TBiqPK8HXEA7vx+Zn0YiPd+TWVl32ypzbX1r1/KAj5rheUBAr1DpjibzFfkc+o0HwilGCGcmG6MXqaVJ5/dstjwESGDlgVcpVeWkNtzTY9XKLzd18hfeCVrZRyttjTTGOHdFO1ocRsqveCPlB95IZ/9+Fznh26Hldlf7nztfZZG+V2QmyYtyKvSi1H9R1sx53mjTLmsxxI3ZE5fbsru9TKdv8zz2icCW5LPvl/fOZLfhyp8t7l295sFVfevJXfZSM6fPdhI1bi43qZX39bErVqx4rm9bXn08bdq5tbISk9s1KpyZFQd9/x1ufHLid2I6ZbdJmdMOV26w1+Ry0FsHe60c++X4Hi3JuCty6DulLPubh9bT7v8qaPXO9PvToW2Vfo/c7fMMeTPU59Dzg6v+vGpNDvWCVkV+/Ln/zJJp7n+ShfqKbiHJK/dbCdfnch2czmmW7AfF+oOu+xq4wguy2+1n7sAt+WCvXE64vqux5k1pbd0hv8vN8EHIhFh8gf2zshpk0fcn5efHjRFj/6pmaZcvfm8qPg89FEOgrrXztkRz9CE5T5xajPbL3aacA3/LzFF3Osm6csfi5/5JYPn56BUwdmdGjHML7rDOvF4Z63TJNNVJAkpOdnS9nATWWHJP+P1/f5e1YeT3G/lV3tn2fXF2Sdk+O/Y+k9v3Oi+8uvUW31dH673lnbMCSYrJfxEliYiXZO96qfaY1H1Mvj7e3b1LchSPvvJqIzzwtYAkFobJe+rKXAZhLOuqgerJe+ZJeRu5SWCpVMo4iZoHBmrPa/tCys4hqTT04sxvPf2tR+4a0T1DTq8vkW/BhTLurGex9TN6Lm3Sf+i3r6xP5T32XxJADieg5kaZefFM/+C1zMDq/ezr/8LhnhvvrLVmLDO3/+fx4ULf/5p8BjsLq1b8Nnv27Al2Wo0KEoSxrZKtz+XWTT7TT5PP9LJt0rdnbYqF4iQmuhbVvDW9UxZT1ub9xeqHdv0nIN8PJ8v35NWS4LxSklm32ca6tncNNf8NhYg9LiDvMxNXztIPxhN//CsC14mJ2tilsl79DUVou2KaJIFVMYf6wED3zqgyb5AZE2+UE9fXywnK62VGzGkhrY7sPUFzMkq9m3yMlH4bJb1Pk8TYNCc75oTiXB4mia2/SCir5CRy1fBdw1fc+9i9L5c+NHoshEBqj3255C7rXLdl1LLVq1esHqjevsu73j3Qa4Pus23n8q4HBn3dQy/ITMbT939XZh+WXijfN+87TPnIK6p7RCHmhkgy+ifr1q7bfZi+SvrSjBkzauTj4xM5dJqywvqgta/2t2Fr+0ltQvufZvVVjtnpWRUsQSGJ5dwcunkxErHuyqFe4KqYtJFjWZafiUWzlM9hzyZp5P2aQ9K+cFRetincKA9tqebaLuePhZdJkmKVHIOfyOPhh5ZiTwULDJf3xUJZy2ehrJW1SqfV22JtSc/87K/g4xKoode1JO6Vu2M+ID9xzwnUwPYPxpgrN847oWXSsk179u/iqzsBEljuvHxbWi4POl4mUc2VjNBcmZkwV05aj3F+F5cfRHs3b/9e7swKcRb7ni4prSteGdHdPXPGrNXK1vdYEfW7lStXJvaNgi8eF5g7Ze5Re3TPf736vnMTb8j+2qDFjVze5fI9LCconkkuDDqufS8YZct6MC4HqNQwqe78K+omUT2ftnuuKWonLhvXxlosVY5wWc0hvkE+TzYPVC8SiTwtn5098pqb9cFOmTdvXvWyZcvK/UuK5P51DpcF6eVymW33QB6Vtk9+9pQ1oVIMb1tpTyawnJ8T3aonWowxZ9um/FHEuQS7YrdYa/JXicboX+QPnEsEIXDv/Yo9sIUb+KNpnVl4fNsWkleFM6WlPgIhbb5oG72uz64gPayrGr37ozKgHwZpUKUcSyH++F7KeOkrS4Fp06aNnjlt9gdnTZ99i8zC2CbrQjwt6apfSsaqQZo4JstmvFpsmJyMSTJO/VAu6eiYOX3WqlkzZn3I+aXXqwET116BPVWpKyR59ZocPH4vl3U9NFg9+SCTBbbdbt65vGvoyOWyXo9utjZf9tLadc5aXpKJ+kAOXKlwxrp6sHqSyHHWK5DPUVdbeMeO3ae4qlGEwmISk2ZHum3aaPs+t3UCW94E7iQ+XVWVy+dm8Y9w9/C0kzBxnbEvZGRWxruz0wo5zsO1FVuafGxn6qgz5Q+fzpqArNdyOKzKec2Wof40UxWeeXzrlo7KGTYjLbVAtKXzz9LnnaXut2T9Gf2F7R881vXvZSWLz+MdkcDy+AFyE55cGnj0rOmzLpPE1R9COrJVfv37lSQLLpE2xrhpx2dl5ZdcPdMYfV13dc8WSWa1zpw5Z6bPxlAR4c6aNWu8/FX7k7kMVi53/frh6qVUKocElpo8ZcqUXNd8Olw4BX3NueRXks8nF7TRAjUmny/3r1mz6toCNVeQZmRdn29JQznMLjbXr/jzivbDB+F+IXe51MK5VLWsm87onJJocnONR8sauJc61wFLYBm1wbOz62zncs3ybqFhofXljcAbvU9uW99T19L5Zbn771nyu9ZfvREVUZRDQH7ePyU/E86ua01ePvHGdmbmluMgVFif8n77kgw5E8Rhy8nr2O7dwz4TxLGVYkwksEqhXMQ+5AT8CElaLZCk1V1yectWuczhfyVxNU+69PyJeRFYhssvWI3Ktlc5a2bNmDG7efLkyW4u9ylCSDS5X8DY+kp5bx65/3nWX426e9W6VQ8frvy+GUDbD1dmgNeqhw37/9m7Evioqut975uZhJAAAgICCQEUNxCXqDgzmUmKiMWlrbWpQtXaxaXqX22r1VaraF1rV9tqta0LCqhpa60LrSINWUXFHXfZkrCICztJZubd/3dDwBCyzHvz3sx9d879/QIz79177jnffe/Nu98959x+8NZRuyQSCaljrnJacrYuEDO+Bb3kiqwSJRQqOwYvBV+3oUybyQK399mOC8tEKcjXjE/G8btghwAViUTLe31ikgUVZBgozJygk6kq53jCPSM9sDJZGkHubcykAqr1XTxv9dKiAxuPwSLUt6Gb1d9a1cwhfawhEMfv6p2BAvMoStxuDTiqnRoCcndUzOvmpiZF3dbYPfiKD88eMVxdDdXVjAgsdcemV82CwfID4G30ayQ4b8Lk5CEQA6eigXqT3F6tcPXk0UgA//DgQUM/ioTKfkBElqtY9yk8OiU6AeGr3+2zYjcVTM673Xmwm6rWyQXTn3FyoRs79jyUUDJX12aeECdXvVS1bk9lM/vNYOJWaIB3bYuFs7/U1y9a1VcrTKytEzoK5FrjjI/oy7Zuzm9esmTJ5m6OZ92hjjBQG1596kIFbwol819JxISRWW83PECUxSaTVxSfzcziec1zDL84BLmx/gBdZE5AKlojwF/B7+oxyIl2WUeCf62tJePUQyBh+q6HVlo+a/BbMyAnEbhSPdTV14gILPXHqLOGBrytTt4ZImhiIsV/hJNez2fV2T43PhdixfCuwYOGvC/zZHkhZMwNEDIt0/Szm6FDwLoe/F/19YvlDpRJFOveMcjtkfHwrr4MA0E9sa86aT7/OTOMk2teqFEqnCQSjJwIHI63gUWLP95z7qvO8kzus0ySIl9fxq8xYYiBne1I8vOWJOtpX80QpvpEt8VRAAGhKkmDDQdYRp95KpN7FofZleqFc5o/LZ7bdKnfb07ABEyGkGsZ4uMKeN4R2oL74IYtsYHBwnnNr7mkNi4fKoRA7wiMe2TlSvxe3dN7LU+fvaT5zFEyTykVCwgQgWUBrExVleELIK7+D2FxH2Ay+1RHiCCNnaUB4cUyTxY81l4PhaLTLTWlyikhEA6XH40JyTdsCBHYJeuG5NtZz08EvZSfmOINTyEdxUcJYYRqa6tqkx+XtNTkgvNbbPZ0b9WSqqZk2gYCtpJeD5P535KR72Idy4lCMXmhpM0dA8Iz7BHkxnXh86lJYHVsOLCPGzYnKxMMWlbvQJgsTqPmrFkNz5wLBDcm43fqIbSjZ0ay4Kldr9pIiMOL5zXNljnQnFR1ypQpA8PBsl9iIX55OBwucFI2ydIXgYQZkIvg2zS1sJ9pGNdqaptrZhEJ4hq0qQuW3kJ4yJ+zZeO2d0Bc3QmJ41OXmvUSDsFF/9/ScOS56HFRW4mNsx5BiwBwlrAX1iXY4/X1VUmv/GHSYd07hrOMe8f0BScSTKlBYHFW6c/xHd3QUGUd576MTPF8abDsTIg4yoaYloTw/zLZdu15cZD7K9n6u+qJuC+z15ng/Xfpkuz/mJAOTbau7vWEfjsQbq2url6p4rhxk2c6/xVCGIWq3mkqDhkrnrv6bRBZ5yRM/wQo+Cf87VBSUVKqLwQQMs4vwliWFz7a/H5fla2eR17akwK+3Dc5F1diIX5AXV0deflaBTFL64+fv2I9gst/q6v5WDD8buOsQvn8pJIkAlrldEjSZuWrSeIqLyd/JsKbroOy+yuvsBcVFHyaabBX4NV2+47WbTcvXbo05kUzVNe59LjyaUyY0+zoCY+azRifq5Jtawo+Ai9GyVbfVW8UdvnbF8TEJ7sOqPQ/VigHwKTijOok2NvISXNlXV31MxnVo4fO28OCuYk8aaBcLBf+kY/Hz8J1lnxLwSw/K3BdShLyP8l34nBNLtrgbWi1DMC90U/ZneqsWpNa/YyTKqmpv1dr6WFk/YrYS4zzB+ApfZitW9k5VeIDBgxQjqR3zjz3JMlQH0i/5KOK8df4A23n4rdLEhWj3euRJDuIwAKEhF4oveoclNkuCl6Vg5mJMH3Bzu8ke3mnz/SREOgTgVgs91eBQNsPUFHHxTU/0t3cCNtm9gkEVWhHgAgsxS4EeBKAuJKTMUlc2ZmQKWaQ2ur0g3rX98/NPwlEwXewGoTdLqg4iABnhrjNrjx4VJ1rpa0N8qpdvNnWnt9mkZW+0lVXCP8k4JCJBwGcTtj/8Aj6fV199VOw10yXzVb7AdkvX4ptEv1C5tqxfY0mq6vIdK41IeB6b+MyamH7wcaVydqpY71gMDgEdo2yZBtIX7jxXGapjc3Kwkh8CUn6f2atuboeRtgdcZJVZg32X4Rdbj+whkH3tYVPtC5YsKC1+7N0NBkE9q9cvgn1fr+sYuLdBYGNZ2J8rsB33UjgZKDwQp3Pcb9djXDBe91QFnOaCmYK6ZU3bE/5nAisPQGhb30gIJ8rjTMLb8cbcdJe832IVOw0P2PlmaN+OfaRNa8qppiS6hCBpciwgECZyE3jj/C6Krc10VDEDi+qgR/vY7jwLYUXxjW19dW/gQ1W35+9aLbrOsNd/JtMiBLXO0qxgw5yQUkCC+Gu6Xzp34grvwFw/pf5zMframsdX4lNcaj2aj598vT87UbLtcrfsRnOtcY53yQZSaslzs0Q2qy02k6n+n7mP8wydFwsqW2oWpgOHPC7VWq1H1CZyobIAWurIdPgruIP171A4UhWrwO363fkT5qDfuasmjmm1ODmVRjfk/HdBpvutrbZJx/EYqU/Frt4ZOW6DU5bL/M+4sb8E94BT+tONrzzVnR3nI4RAr0hEM/1/8HXFr8UdQp7q+fRc5wbxk3QXT4jqfSBABFYfQDk9mmEv/RHYvGfYAL2U/yk57jdH8nvEYFcnPkVcmN92d/mO7vqpSrLeW56lJyFJ2RYF15QpCeh8sUUhtUJU9psEsyEB5bFd33BHkOTvl4O4zBiC2RvRsjOCsM0P6peUv0RjinradUd6Nvyd/wI2dull5Dq5eCMhuMJATLS4nUkEeWsDP/OUx1cN/VDqPlheJZZKvAiSh9BJPNzWR1awd6wZFCaKreHAzN2kMXuVlAuHYuIZaB68fzVtei2tiPPyyW4pb6P75Zz82VAdR27XItn1MVFcxsfd8E4XhoqO08kxB2QPbBH+X2/o/TYlE5kLwLjHljZsmrm6JuwKPdnHVHAT/lJjWcVlhc93FSlo31O2kQElpNoWpQFD5Uz8GL8azSjHAEWsXOtOnJjxQPmy+Fw2cy6usU1rvWjueD+uQXfRzy3RxISisPVHQ5uWbcEM65pqK/6UF2bnNFM5i6Lt5kyNMULxW+2mnLTiEy5htsN15gGnSU9YpHC8cKQJKcjCFLLXpAi4UsfgcWte2m2JnJkDizlSn5O/sFg0C0t5OHCTB/WyiHmPYWQIFyGel62tmK/m9oC/u/i4SK9KayF6HrPbFU0lvkIHkYWx8uLKps+c1qpUGjq/pzFEYoopvYpW5h2f5P6FE0V9EZgTLz5r02Bwsvx7D9YR0vhuXgT7LLsWa0jFr3ZZPR2ks65gwBca4eFQ9F/gbx6BD0QeeUOzKlIHc2FWBQJRf4vFSHZ2hY5Y/JAXl3jFfvxQndox8q/cirjAT3RolLbGxqqsuLFMBEz5TXW8wqvReDcrp7JPFjYVe0dm/aNx3PwJJttdWk22aohMZEeAks+a6HbeIv6rXnxxec/tdgmLdVBXlkmC/H8JgIrLaPjbCcybA15l25v/bzfeLwvfBsUuZKkqrNWZ1TacvwGnSB3i3SavMJikh87pl9miPjruB/7Jq8AA3LNrcgoGtS5ZxHglSwhGL/Bswb0qbgIw1M129+7+kSJCKw+IXK2QigUnS4S/DU85L/qrGSS5jAC2BGC34n8IveoSm44bK9j4nw88CMI8xIxm5ubO8Bq2IpjePUkKBicOhorTEN7Ot/DcTkJwDxQ74KV3mLkdJK70XimZDJUtba2VpKa6+2AZTIu7+dsLfipZodaNP6TJUuet4W1xX6Yz+eTuvkstlOX8EG4pkVb5BYXRHxYBU2h+hMWfNhaPK95zpj5TYcJYURwwz0F9fDTR8UhBOLA9M4cX2xy8dzm5x2SuVtMZEpkMjyhG+Cn+zv85e8+0fuH+I4dOxp7r0JnCYGeESia1/gonMNf6bmGt8/gAXibmM2Io+llGAmcXsBx8hRIkP6RYPRuAP4fyCV3aSfBdVfW+Xn9+j+DJPsD3O1GD+nt2yUz9mOvWWOI9p0IlVLbx0zLkzm89qs7OXUQXYPHb4Q4mbfOOyXjOxGyF+2AhcnP1Egwcrydtl5vE41Gx8IGS15+ePFMW34pbloPb0xrfi6rF4DM52WxGIa6OypaNCXrq8s8WfAQOtVIiIMl6QJAdmQ9KKkB8CbjPARML9vvofXYida5InM6YoF3tvDxlyD1aEuSBWtcunRpzFIbqkwIdEIAzweBncev7XRIt4+HNb5f9E3djHLSHiKwnESzB1nhcPnRebkFr2Cl8EJUwX1HxVMIIC8WF/7/hUKh4Z7SOxPKmlz+oAzORNcp9ZlpcqEb5bmRsDyZgxjtCaxQqHwSiLpvdQOZ0ofwY2s5n5mTBiHp6QK78vCm+OCxxx4/1G57r7ZLJKwTKviBT5tHEMgyy88IYSr9jLBqT+v27ds/8Or1RXp3j0Dho83vS9IlEfOPxzxV5oP5pPuadLQHBFowvb/244IRJWPmNkqCydESOS4ShteVzOd4Pf4s5axrV4SzrEhz4CjoJGwvBIrmNsl3muq9TmhzQNz48vklAW3McdgQIrAcBrSruAh24+DCrMOPsHIhSl11pe+9ISBKDOF/IRgsP6C3Wtl8Toa8gZ/1VFjX7vHilrdu393UrQ8IkbM6mWNGOnc/c8vwPuQaTNyKKlbDpvqQ6v5pkA1D4cmZOe9bn/kvWGk3vHR0jj/+V7R37Z0BK/oF2DxjhvsjkXwPyFNp+R7EqnAaSWTrHlgYwDTqlzzW00qmDULtouRbyJr8XfLksIaYl2qPq1y5bsy85p8jT1Zhe54sxt72kv6Z0BUelvVmInHUmPmNNx99r7NeTtMnT8+H19VtwuCSNLCdQBvpOVZkAhvqUz8EBDd/pp9Vuy2aMGzr+u/s/kYf9kDAtZfRPXrJwi8yb1JpOPpH/OhiRw4bKxRZiJnyJnM2zsfNxZiEEhnZzWAZPCFXSvO6OaX+IWF9tz/3jTIsJ4+Os3javD/ct3/vHkpLy7Ezizhl7zNeOeLPmBdWTU3NWqBUYx8p8TVMXv5SUVHhOHkYDUWjWNFfiheSY+zr53xLeFNZJrCQKDmdBNEki1bHjVzDbkJ/i11Zq96SF5dYW/JQBymcTqytGUS1HUNgV54seGVNEsw8ARcJ5cnaG93tuB+uLmxrio59dK3j97hcXNhe0CIJxKvwl9LcEQttRGDtPX50xAYCxXPX1OG6f8ZGU080wbPu+jXnj+rvCWXTrGRKD6E06+qZ7mSoRb/c/P8gzOVizyhNiiaLwCgufIuxk6TVxL7JyvdkPXimIWeFOMuTyu9UeqRKIaJyVx8QNdZWODlbV19f/7GHx6Bv1YV5W9+V1K3BTZExAqsdFcH/lCI6313bvP7pKVOOH5GinPbmyJl3IBZ65sItrAoHDmTCXO2EXKdk2PCCFChp8RLBDoRDYOdIi7Z+UFVV1WKxTVqq496wTBbiBZYIrLSMjhqdYDIniuetWdieJ8sQR+K7XCBW8npOK2Kc/SfOEofKXR3lDm1O9i3zmsrNjLAztyQJxjgiW5gUQugIkCREIgBC9Gr8Z9e7XHUQR8W3+i5SXclM6EcElsOoyx05sNvHS/hhneqwaBKnDgIjsJPkouhx0UPUUSmzmvi5eTs0AOni3eITPssTKLesTSQSB0J2riX5midwD4ejX8GiQNgSJqpV5sKyV52TJuxo2yrDCJtSlHliwBd7qzRUdtHEiROt5z/B+6ZMCh8ORf/OTGMZxnQW9MFPpvyHK0NgzZgxIxcKyfvQSllRV1e3xUoDu3V9vlzr15LCzwh41lh+/ppcaO1xavfayIZ2hQ83vw4i64K4CIyFB8YNsPnTbLC7i40bYfsFyAV00vh5a1d1OZfy19JgWQWe0e9B0PkpC+skQBiCPLA64UEfU0MA1z8WMsRjqUlRubX42Ypzx+6jsoaZ0M3TE85MANZbn6XB0lMQ2/0IXnqT3Uq2N3F0Tm0ERpgGezYUmlpaX7/I8RcHtU3fUzus0E1BYuBT9zya7Df+49r6xb9JtnYy9WQulZbcto3J1O1cR3BDesc4vs105z6S/Wxid7H2GX2yDdrrpTV0yZJmDlQ2uOA34iXFhii+DNeYnOw7ukIHAqcS+nzDkkIZDlWV+YKg9y+g9z2W9N678r6Q8afBg4ZeWxqKPGQw/nT+oPwlCxYsaN27KjPwnBznY7GgyYwyeGqeilEc0d31HROGMgTWpk07DjEskvKwK20eQdxMHIb3jW7g7uWQ0jnyuNVwSMZNtm/pceXTerHY8qkEN95paFjUbLkhNcgIAuPnr1iPjmd/MOOAW3MG7zgDOaCuRgJz7RcXcec/JUx+QfEjjWucBh4RBiMh+09MiNOcli3lYUMR8sByA9gslonFr+vw+3s6INAx6flgIxb/IWy7PouHeC/TicDaCxJ7B7BSMZNx8SBa63jz2ANF/1aFPhZfiNCzsPahW72NZYLfhnmUxZlUu8C1O1q3/rk30XbOLVy6cBPCktaB69jPSnu4yFv3aLDSgYW6tpJHp3HybMEUR6pGQpFzkE/QVvgdchJdByUcJa92GiXkyrS1Ao8euf14JsO4/Dn8vngb+xEIKCdy+Y3EdOQnAPcnWzZtS0RC0RUIu/uUGWILJpFYMeQD0M84xuI5kmwBedUbXmKfffIae6uQznPYLMCyRxAegmkjsICndcKHKU1yW8YbF9SDksVysvgEmwF5RGA5CWoaZMk8WehmjpjNHl79/qipBjMuw9PGw/kSewANqQJwyV9SNL/pHz3USOUwxwLHeSIh7oCQgakI6qXtVuRj3NDLeTpFCFhGAN6YH6yaWfgACOzzLDf2QAPMCX60fOa4uzoIew9o7L6KWGCkkioC4XDkQpBXD0MOkVepgumx9nhBOsDH/E9hUlrgMdUdUVd6HWI5rdyOMExmb4VHyHY7bftqg0n0+33V6XpecGaLIOkqx4nvmAhbn8yZ7A0n+lZNhgxTE4JLEspOebOurlqGzTlfbFxjUMKfaElkNH8eyLM4yBmZU6FXNskGYJj7swNAKkwBeSW9Yo7uIMmSDTNc14MHlw1VUm9iI/8VzGZpC2mz84xA6E7aCDYrIxCNRuXug0qESCSYoSRGVvDM5rp8NjN35ckyTfMo3CcPAY+YBpjg8cIe4m1sohvkFbxk90dY90I8s+8BVm6RV3IYVmgwFmSCggjAS3821NqhoGpOqFTgZ3GZ64tKBwJEYKV4KYC8+ilumrshhrBMEUuvNsek7Zh4q/mYG7tzKY4JIocMhCPZKmviIv5XWy2TaARyzLp3DGOH2szpk4RG1qrYmDwn4jz+jrVevFF78KB9LwEpMs6Wtga/Bu2cddHYpYjPtHONMWG0h6rukpKR/6vrqxehY/m7pU4RbLU6ysB3zLCek8lIH0GEBVk20RJegm2rra1daalNmionEjYIe3d0+5zCB90BNhNSxz6y5lV4ZpyTiPnH4H65ATp8lgk9HOhzBXLETZe2FFU2OWoDFl/9pcHoZYaIvw6CbKoDuvYqAuOwvNcKdJIQsInAmPZwWqHWe41NW7ptxsVFK88utvcu3K1Abx8k0sX++MHVNnI7yKtb7IugltogwNmMdWvW/0obe5IwBC89ctfBI5KoulcVEDQ3NjQ07NjrhGMHuB1yIWfowKFOhFWlZEU4HB4AwmasNSH8Q3fxtKaNU7XbsWDiKnvy+NLa2sVP2Wvbdyu/32/nGoPDohqhqv239vsJJhOv9m1pmmpw3pimnpLrRnCrXpCt27dv/yA54anVKj+uvBgSrHlJ7Mx/5Q6Zm5o5MgpwcooiHGmO+4G8rxxBUi0h4ypXrsMOfbP7xVqLMcYX4M/WszsDVpkgle6F3pOlV5nT/ctNpxJtZj3eN36Hv3yn5XcrT1D+q25xoYOOIOAX4lYI2uyIMPWE5BjxxLXqqZUZjYjAsok7tpX9rcz9YbM5NdMQAZAyl0eQP0BD0/Yyqd1TidtNKChWbdz86f17CXXygLDnHZMwMj+REsIvc9vgvdVC4ULL8EEufJK8Gm4BiS+qCi5/6DFXcacgFG8jJH9sVTqeE0qEqj77xrPbGE/IHDHNVm1wp75Y5Y5c61KDweAQtBptrSV/VybJt9bGXu2433p+LtwK6pIzhhoeWMifoi5G9i4VatUJgeGVG7aCyLp3zIFNhwphfgU/s46TQp26S+2jYG/hJSAod1qUeqcmbM/W8LrqhznMbOHjL+EH8pg9z7r7zeDmCnd7IOnZjMCo+Ws+wTWN+bmmhbNvrzxjpPabVCQzekRgJYNSlzqRcNmNOHRZl8P0lRDAbFn8CVvEl+kOxT4Dh8gcOuNt2Ynd5JYtW9Zmq22yjXzWc2C1izZ5xskFPJSten4wYSo8OU12zLrUw+YIkri6tMvhZL/W1zZU/SfZyinUs7OSn/FrbJe9dXV1a7AzoCSxPtl1LFP/CyGaMtV31379zG/9Hkyj9452mzwI68+8rmPmxHf8fqcth5kT+pIMewi058mav+bJMfMaTzANswREkcyTFbcnzfFWMehze+vGfkeDvHrRaemR4yLheJv5CuRej79k8xM6pgae80RgOYYmCeoOgbxY669AYlleXOxOloLHfD7DJzmIrC+YK1GxggB26LgUD+CfW2lDdbMKgYDg/LFgcKrF1XvvYCQT1mMb5J/a0RgvZh/6c405dtpaaYPwLplnwbI3hArhXdgN0fLkGQ9y7TwHDOabjTEcYGXcd9UFHul5RttL5D5EpedDfX3VayCxvgTs5Hb0mSsGX525zvfs2bThEZTOexDeI9JL01IRhk/JZ0RJSUkAhmQ8dFuCaST0e45aukiysPLYh9e8InNLmYZvV56szzMIwwtCGEdCn6s7dlV0TBXcZ/3hdXWbMHg1hGbMg4P7KYTQsUElQd0iID0WMUf5ZbcnNTiI3RxObzyzcIoGpqRkAt65qCSLALZyPxdu+L9Ltj7Vy1oEhvt5vLLjxVw7EBIxIUNnbYV1Yev3G+UuaG6DsrMPGy9KCuxEiB8nywRWggeUnJzaHWfsSjYO4R3fs9de1HYkKbfX3EIrbtjaLIAZRlwZLyxpbn191Vv+hHE0Pr4gv2eicG6uykS/3fWJ3JaW70Ekq0njPWhdP84Ty7qzNdPHcnMHSPIq7Z4g3dgtfP18SmLUja50yGEExj68aq3Mk5XXr6U9TxbEW97JOAWVtsNj5OqiWFNp8fzVjl+D4XDZjLzc/HegnwzJz+S8TyBP4MoUcKKmhEBSCCQCvj+holp5NZPSPKlKXBjsxqRqalwpkw8yT8EK8up0TL7/CqW5pxQnZTOCAF5Ggv1yCm7OSOcudhqJRIbBA/Fym12878/h8222tdzM1k6Egu3XEbpmuT+nGuABY827AruL1dcv0sotX8TZrcDT1qQW4VXXOjUWfckxma3NAiBWKEVgSTurllQ1+XOMLyGM6g/4mvZk31gxXS31UKHgHrRMYAXiPC0EVsfCyIEWcVpbU1OzwWKbtFQ3bHicuqRYY0deO5fEk1gvIDDsvk+2yDxZRQc2HdKRJ6vOZb2r8bw5An3ezitZwsm+SktLB8Pr6h54dT8DuWOclG1LFmfrkSdwu6221IgQsIDAuAdWtmAedpOFJl6rOn3lzNFTvaa0k/oSgZUEmqFQdDrIKznx9iVRnaoQAu0IIBztChCfX9UJDmHy62GPrbAueBZdlw7vq114m8IeuWCYORnbEQu77o3Cj+7QXTYk+b/M25J2wiFJ3SxXw0v34cCgwnLDnQ2eq2moWWyzrY1mCTs5sBiWzzJ2jfVmJO7Plrr6mksFN8JYq3m9t7oOn9sOgiXjebg6bAIHyiZatG8TCMBmi21sVc/PyT8YDS2Ru5ggp4Vcs2OQHbLQTj9JtFEWoyR0pyoOI8BnM7N4Z56sUsGMo3GdOp0nayOeMxcgXLAcfx84rD4rDZZVMNOQv0/nOy3btjzBlttuSw0JAYsIjIk1/Q337bsWm3mmusH5rXiGwMTsLERg9THumFAeBJAeRbVAH1XpNCHQFQFMhPgDodDU/bue8OL39rAuwc6zpztfVldXXWmvrb1WhmHaCwEwzIx5xximYdnzAznX9Jp4mcYdGHFbv00gXq6zd7XYa9XS0iJfyC3nWlPRA6szAnV1VS/U1i8+ihn8K3g/Wtr5nMOfP4e8e5GDS+ZzwLtY5kv5ceXF0GKgNU3aN1FIi/5gqq0/IxQmsOyETFsbmyRrpzUENEmdqJoSCBTPW720PU+Wz3cgZou3Qym5A63tAhlPcT+bJD298NnR5wa85EeWhqP/xCrJY1BwmG0lXWgIW1e4IJZEEgLdIiA9GgU2jer2pB4Hj208q+hUPUyxboWtSYL1brzZQrrfYhv3J6H9Pt60gLRWAIF9DB7/J7Zlz1NAl5RUMOPiZgiwtPK/q0PBhSQWMPdKX8Gk2JZ3DNYzMucdY1jvGy+F2hBYHTt4nmDnKiVC5sYAAEAASURBVAEOz0jixU5bu20QDiHJq5U22h/ogWeCWVu7+EkQWccgaVcENt6LP0k4pVY4W4c52/0gLk7/fNOn+9XWV19QjxxcqQl1rnXMZ9q5/9N2D3LGrYUYAxpgnTb9rI+EaZmQs95H3y3AIihzDfatLdXIBAJjH1q1QiZYR54smfD9cvzmrLKmh1iPEO1vQsapRXOamq217bM2Lw1GzxEJvgyU2Gl91s5EBW4jL2km9KQ+tUGgaH7jI7hPX9XGoK6GJMTNYra9Bd+uorz23e81hdOlL3Za82OrWekxMiFdfVI/miIg2GQfD8jk/xd42UK/6ftZ3B+3lV+orrY27StvLS1bX8jLy7Ps/YZcPDsyNU6tsZz7cnJa/2Gl//6b+6+3Ul/luq2JnLdgv+Uxkza1xWIZCUETPFGOa6afVVxz/bk2PLes9uJIfVFbW1ULSbUVFRUXrVmz4UhmmuV4KTwGxMgE/C9/Iwt66OkznH8Pk703QWK/ibDqhtra2ldQF4fULPF4a1UgELB6DaZO7CULh9/8LRNC5uNMupiJxNqkK6e5ouHnXzJNpMDPcFEZowxDQ913QUDmycKh32Pi+IfV7406mXHjp7iAg12q7fEVxHMl94sfFM5p/nSPEw58kV7+nMXlAsNUB8S5JkII8sByDVwS3C0CuC/FKiygY2OWJ7ut4PWDnE1qeq9wFmNND3vdFKv6Z/ylwarC6aqPxIdyB4OL0tUf9aM/Akgq/p2a+poH9LeULCQECIFsQgCh9gMCbYH8eG68f4fdn4OokmE2yhJV2TQ+ZCshQAi4i8Dqs4oiwhSXYVJ1MnrqvKDxAnJJXF00v2mx0xq0L7S3mhdD7s3wHM93Wr7T8pBMvjy9OSqdtoDkeRWB1bOKsAgnwl7Vvw+9l2+JDTpkYuWytj7qaXWaCKxuhhNuuBfjx+CP3ZyiQ4RAKghsh7fGsXV1dctSEUJtCQFCgBAgBAgBQoAQIATUQuCDbx0wMEdsP9YQxiDMI95wI0G7tDgyJTKZ+fhfsUJwjFoI9KKNYRZjYWN1LzXoFCHgCgIgsKIgsBwnkV1R1o5Qzi8ZM7dROt5kTSECq8tQh0JlxxhMyHAJW7l+uoijr4RAFwT4sh2tW4+lrYS7wEJfCQFCgBAgBAgBQoAQIAR6RABeV/0SreI6hGRfiUr+Hiuqd6Jt5OgR/SsrKxPqqaauRkjKPywej29taGjIWGoLddGxptnqbxUugE/4l6218kzttTm+2IT9Hlq/zTMap6goJXHvBOC0kmmDDCHkjoNEXnXChT46iYCYmJeTf6eTEkkWIUAIEAKEACFACBAChIC+CESD0RBy874C8uqnsNJL5JUclFVEXlm7NktKSvqzBH/CMHInWmtJtbtDwODiahxP62ZS3enh0rGRrfHA/7kkW0mxRGB1GpaW3Na74fI7rtMh+kgIOI8AZ98rDZWd7bxgkkgIEAKEACFACBAChAAhoAsCkshAXt7bsNVBDWw6xIt2IdxnhRf1zpTOGPMAFrv/jhDRIHKHKbFTa6awcKrfwoebX8dmCpY2SXKq73TI4Zxd1VhROCQdfanQBxFYHaMQDkcuZIzPVGFQSIdsQEDcFQyWH5wNlpKNhAAhQAgQAoQAIUAIEALWEAiHy2bk5ea/g1ZX4c+7czbBlluzPKtr8365BffCoWLGThQEeWA5dDnwhCl3Uo87JE41MfsIP79CNaXc0se7D0MHEcEOShOxxeavHRRJogiBvhAo8HHzsWAwmNdXRTpPCBAChAAhQAgQAoQAIZAdCJSWlg6G19U98L55BhaP8bzVnJMHVpKDGAlHf4ldy8/dVR3ea7Y9sD6qGD9olxz6n7HCR5vfBw4PaosFF5euPKt4pLb2dTIs6wms6ZOn53PhqwQmu7b/7gQPfSQEXEXgMB/3E3HqKsQknBAgBAgBQoAQIAQIAW8gUBosq2Cm8S60Pd8bGiejpUkeWEnAVBqMXiwE28OLBmGEk5Jo2m2VQE7bf1fPKvyocVbhPatmja6Qu2R2WzGLDvr95o0wt1VTk/MNM3GNprbtYRaI3ewuWOH4PRC4NLtRIOszioBg36ptqJ6XUR2oc0KAECAECAFCgBAgBAiBjCCAaJABTPgewsTsqxlRwM1ODfPo2trapW524XXZIC5nMi4ehh17OZe0xQP7vvji859atXH1zMI3EYrYmQBrxfVVh0zmz/qY+O/oeTIvFPbmy7KyembRb4H15Zqa3SaYcUjxvNVak8Z73SSaDma3ZoXD5cfhxMXdnqSDhEC6EODsz3AXPzBd3VE/hAAhQAgQAoQAIUAIEALqIIBokPlakleAOJFIUAhhL5da6XHl00CoPIAq3c7Lc31tnUmoXiTteYobbNWeR1gu2KqpuM5uMxl/FZ5Z6xtnFT22albh+Y3nFI7uUlfbr36WuBk4bNHUwByDmbM1tW23Wd3eKLvPavxhxowZudw0/wYTfRqbSaZ5AgH+PNTc4AlVSUlCgBAgBAgBQoAQIAQIAccQiIaiUQg72TGBagna1NDQ8JlaKqmjDRawS5hh/hMa5fSklWDcFoEF36q3epLZcXyYYKIChNY9Is6aOsINf79q1qhpH8w4ILePtp49PWr+mk+QZ0xGYGlZQM59q+ms0YdraVyHUX6djevNti2bt82GW+WhvdWhc4SAywi04sflqtqGxXeiHzxvqBAChAAhQAgQAoQAIUAIZBMCgrNTdX0LxMut1qFMqVynodDU/ZkZfxoyBvQmBwSTfQILjS2U8RivSzkzLs0d3LJ99ayiehBcC+EYthAhaVqFgMZiub8KBNp+AGyGWsDHK1UN0+Q3QNmveUVhq3pmpQdWKFR+BH4ofmwVLKpPCDiFAH4gVmLFpQy5r+QKAJFXTgFLcggBQoAQIAQIAUKAEPAQAkjcfYiH1LWqKhFY3SAWiUSGGSwud5kc0c3pPQ4JLmwRWJyLvjyw9uinyxdsbiamgf+6jTPz5dXfKlyLkMM5Mhn8qlljBnep67mv+1cu38Q5+6XnFE9e4a82zRwdTL66t2pmHYFVXl7uR2yoDB0MeGuoSFttEBDsn4Ec40gktFyijU1kCCFACBAChAAhQAgQAoSAHQTG22nkhTYGZyu8oGc6dZQJ+0WC/wd9Jpn/lh+GutZ8qdBgx+d57+C/OP5SL4Lth9X2sznjj4HQ2oBww5dBaN0mww1fPr/Ek3PqeMAvI2CaUgdHTQkm57epqVnqWmUdgRVvM6Xn1VGpQ0cSCAHLCOzA788F8Lo6vaqqaqPl1tSAECAECAFCgBAgBAgBQkAnBCQxUayTQZ1tEYITgdUJkJKSkgAS9lfikJW56KDyKeWWk6xPWPBhK5LDf9Cpe6c+yvzRJSC0rkK44XPDt67/DGTWkzIZ/PJZIz1zLY97YGUL5mW3OAWKgnKikmBUUK+UVcqqHFihUGg4EPtZyqiRAELAMgL8PWYkzoDX1euWm1IDQoAQIAQIAUKAECAECAHtEIA3zkgkkkC4lqZFcAoh/GJoeV6//L9ivE/84lByn+JGex4sy95CXBhvIY+V2yGqBSCzTgETe4ofe6PBO2s5Pi80kT+rjef9d8LcDzcnZ2X6a31cMPyvIOCkc8v+6e/d/R5BMN6KsXke44H/9ClZRWAZ3H8jhm+gPsPnqCXywv4Q+HwItv4TfN7ABN8Ah9VdF3wejvXDThhDcWgkPkt35wn4y6prCPbaKOIhf45xUVVV7VYbjakJIUAIEAKEACFACBAChICGCBgJY5zQOB5GGLEVGg6bLZPCwbJfMyHOsdOYGwkZRijDDq0VgTxYnFVYa5RybZkM/nyEG56fK1riILRex/enkAz+yTHzVr+iEply9L1LY40zC2djI4WHUrZaTQFHN80qPI3Na5I7XWpTsoZ8QOL2SUyY39dm5FI3JIGHSZ3BxVMmM17Oawm8snDpwk1WxE6cODFnyIAhk4RhlOKBXIYH5HS0L7AiQ/O620H2XVxTX/OA5naSeYQAIUAIEAKEACFACBACFhEQnGvp+dEBgzlw4MCVFiHRsnokVPYTeEL90LZxJp9oq63B3tztimBLQMqNJNdQAtKqhDHzeoQabmhkvEp6Zxl+9nTRnKbmlHtIUUDhQU3zGt8rvALz2MNTFKVkc5OxW0Q5+zevcigfmgJWZg2BhcTtvwLeMmY328sL2O3kgbgZ+NeSJc+vTwWMZcuWtaH9Kx1/dyJBfr9EW+JEsNgXwntLusfieZWthS/jPvObNTU1b2crAmQ3IUAIEAKEACFACBAChEAvCHA2rpezXj+1ZsGCBa1eNyJV/UuD0Vkgr1JKqI25lT0CS7BUdiJM1fTu2g8DFhWYIFYIpJfvCDeEM4X5ZNvn/Wva83Z118rFY3w2M1fP4tcjyu5fLnaTMdHA+qDGUUVnMdb4QMaUcLjjrCAYSoPlX2bcXOAwdl4SZ2Kgn4Kn1B21tVW16VAcMf0HIUnhpehLuspml1eWYH/b0bbt0qVLl25PB9bUByFACBAChAAhQAgQAoSA9xCIBKMPgJz4tvc071tjRHpU19VXl/VdU98akWDkeHjZPQMLc1K0cnttffUAyIBDTfJFzGZG4/uFMgdVfvKtMlYT8yZeD4JrIcINFxbPW700nZogCX095svBdPaZrr5g16qWz/sdlAmC0A0bs4PACkWrAV7EDQDVlylqeYJdXLOk5o1M6BoMBof4eOAX6PsC/OnuAbdVep/V1VXPzQTW1CchQAgQAoQAIUAIEAKEgHcQKNV4jsIFe7Cmofpc74yGs5qGQmXHGEwsglRHFvJN5j+gvn7RR1a1hJfTS2hztNV2Ga/P2TpcQ88h3PBJTCElofW5mzqtnlUUhRfWYjf7yKRsEMqXFc9rujOTOjjVt8ZpA3dCJB8e+JSN5NXniHm+vLa+pixT5JUcgYaGhs+wYnAx8mwdjYDCup2jouG/gr0teOI4Iq80HFsyiRAgBAgBQoAQIAQIAXcQkJsiaVmwqLtCS8OSMCoYLD8A5BWIF2fIK9kl53F7YYQMidy9WATbD6TL2UgG/xhn5gYQcS8jh9Ztq2aNmvby+SUBp00aM68RDi/iOaflqiIPXkvXbvjuvtKLz/NFewILBv7E86Nk0QDc7ItMFj+4tqH692hqydXUYldJV6+vr3qttq46gofQRWjUknRDD1TE6sCf/blGSV1d3TIPqEsqEgKEACFACBAChAAhQAhkGAGZOxYqyJ29NS18uaaG9WpWJBIZaXBTEiEjeq1o8aTB+CSLTXZW54Y3Caw9jZVRPCWY417FmfHc8K3rPwOZ9STC/s5fPmtk8Z5VU/hmGj9Da3SjZRm2oyXvMh0s05rAikaj43ANnqbDQCVpg7zh7mxp3fbl+vr6j5Nsk85qoqZ+8d2GYCF0qsOP2hYkq58F9+gfVFVVaUXKpfOioL4IAUKAECAECAFCgBDINgRaW9lY2KzvXMzgK7JtTKdMmTLQTPCn4e0ix9bRgtxQ9jyw1Evk7gQuBZj0ngKc7/Ez30p4Z30EQuueVbNGV3zwrQMG2u1gzCONL6Pt43bbq99OXNF0zuih6uvZu4b6PjRht5lgP8Z/uudd2jXCbXDVPRPhepcheXhs10EV/69uqH6VGSZisflTKuqXnE58KWLRj6xtWDw/ufpUixAgBAgBQoAQIAQIAUKAENiJgGGY43XGQoiYDovVSQ/RxIkTcwK+3L+DVDky6UZWKgpuj8Ay2ZtWuvFo3fEgtM6X4Ya5ouVj5LN6rnFm4ZVNZ40+HMcxJMkXwY2fo7YSEUzJa510zUGJBL8q6dqKVrQ0oIra0K1acMstiLea63DJ5ndbQa+DrZyJ02vqa572mFkGklfeDZ3P95DeAisgfxw4qOBK2hrYQ6NGqhIChAAhQAgQAoQAIaAQAuFw5BIu+B8UUslJVVqwqN4fAsEfZEUxSsPRR2BthYvWtvpzjAJEfcSt9gEPpU/QxvOeN1bt7qi/AcRWFZLBLzT87OmiOU3NfckB+VUJx5Bv9FXPo+dbDC4mFM5tbvKo/szvVcX70jvehtDBLCGvmMEramqrvUZeySE08eN2YSQc3QxW6Iq+xlSB85vxMDuvrq7mMQV0IRUIAUKAECAECAFCgBAgBDyKAHKojvOo6smovQKVsoW8YliQ/43L5JXEPBdhpwfg/3flF4tF5umNWmyjS/VhcD6ogNdOhQD1BzLvbXx+0mTmwrbP+9dMWPBha1dDORc3C8ZPx3EdnX36YXO1a2HbhV3t9sp3fUMIuTnLK4OQgp64/nhFbe3iJ1OQkemmoqau+kooMTvTivTav2BL/KZxOHYZJPKqV6DoJCFACBAChAAhQAgQAoRAnwhwri2BhVm/JLCyooC8ugaGpiU5tp8n7IURsqwII0z2ejsUzGp7MvjcwS2fyXBDJIO/atWsMSW7BBTOa34N3NXzu75r978Q32s+a9RBXrVLSw8s7P4wTCT4NK8OigW9b/Q4ebXbVHhi3VAaisDVmKu2a6RcPfrD55s/vXLZsmVtuxWmD4QAIUAIEAKEACFACBAChIBdBARHDixNnZSEFps19TmykVDkLIzgL/qs6FAFeAXJnQj/YVkcF29h4ynLzbKgAeaeYhqQAW9gSu+sFYzzZ5Ga5784fhcihHTlE/wJ07gO4/stL46xnh5YCXYmBkNLcu6Li4w/BdInbQ/ML/p171Ntfc3VcNSc414PliVvwgPsm8D5MiKvLGNHDQgBQoAQIAQIAUKAECAEekRAaOuBJThf0aPZmpwAeXUyCKX7YU76mCHObHlgCdP3liawu23GOCbEBSCu/ok/3aNuzmg6Y/SBbgPqhnw9CSzGZ7oBlkIyt8YS/u9DH912SBCfb/z0PKxkLMo41pzVIdHfYUiM//eM60IKEAKEACFACBAChAAhQAhogwA2m9oXxgzUxqCuhgi9QwgjwcixQvBHYXZ6HSZMewRWPO5/E7piikXFAgLpHVsLijlU1Wca3tyRUDsCqz18kLHjHBpYVcX8esmS59erqlwqeklPp7zWnK9DxvupyEmhLRZT2G3+gFFeXV3dmIIcakoIEAKEACFACBAChAAhQAjshUCiNTF+r4M6HfAllutkTmdbolOiE+Bh9iTmC+nf6Z6zA2fMmJHbWZ9kPu9fuXwT6vW5+14ysqiORghwdvaKM8eO9ZpF2hFYIm6UYxDS58qZ/hH/WPDEr9Pfbfp6XLh04SZkp5c7P2xPX6/tPX2C8PBTauuqf2pni9o060rdEQKEACFACBAChAAhQAh4EQHOtCawYrGYliGE4XB4lOkTz+GSG56hy86/beM2u2Ff0guLCiHQGYGAzxeTm6l5qmhHYDFufslTI2BRWSHEn+vq6rZYbOa56vX1VW+BTDo/jYovTgj/Edhl8Jk09kldEQKEACFACBAChAAhQAhkGwLc0JnA+mTJkiWbdRvSaSXTBnHhxzyBF2fSNsGFvTxYnFEerEwOnKp9C/7d1WcWjVJVve700o/AYlxrAosZpu4J5XZfpyCT5iJa+2+7D7jzwQQpeOPI0SOOb2hYRK617mBMUgkBQoAQIAQIAUKAECAEOhAwBRunKxgIg9HO+wo5y/q15LY9iTRSh2d63JDrxBaBBd2XZVp36l9JBPoJn7hASc16UEorAgv5r0bCzoN7sFWHw2/B+yqrHj472rZdih/CD10avA1ciJPqGmqur6ysTLjUB4klBAgBQoAQIAQIAUKAECAEdiOAXa61JbCwe5tWBFZFRYUvHjPnYfAiuwcwox/4JFvdC9qJ0BZuWdCIC3bey+eXBLxiqlYElohr7n3FxLNeubCc0nPp0qXbQWBJVlg4JbNdDhcLY4nAYTUNNf91VC4JIwQIAUKAECAECAFCgBAgBHpDQGicA8tgWiVwX9O87reYhZzW23Cm95yYbKe/QEH8HbTTbQd7O1BQm70RGDli2/pT9j6s5hG9CCzGj1ATZme04sx41xlJ3pJSXV+9CGn573VIa+lpdcPIUft9WdedHB3CicQQAoQAIUAIEAKEACFACDiMAMLR/HivLXJYrDriBNfGA6s0FL2eM/5/6oDbrsk4JJMfYFWnUfeukZtjaTM2Vu2n+r0jAM/Js3qvoc5ZrQgsw2ZSO3WGow9NhPl+HzW0PR2Lt/4Exq1O0cD12PZ2Rm199WwKGUwRSWpOCBAChAAhQAgQAoQAIWAZgbY2oxiN/JYbeqWBybXwwIqEys4D5LMVhJ2jHGpLL0F5sGzhlh2NTl5x7th9vGCqVgQWmMNDvAC6XR2RYC1rWXO5mwnIpwvtYgfX3wXcJw6rq1sst76lQggQAoQAIUAIEAKEACFACKQdAcM0tc1/JcE0DcPz85XS0rJTBRN3pf3iSLJDLvhhSVbdsxo3aCfCPRGhb18gkGvEYl/94qu6n7QhsKZPnp4Pd1y5oqFtMU2zRVvjkjAM5NMCJJl7MImqnavE8eXq2obqk2tqajZ0PkGfCQFCgBAgBAgBQoAQIAQIgbQiYIjxae0vvZ0lWls3pRoxkV6Nu/QWDpcfx0zxCA4r6yUnbBJY2Dzg7S7m0ldCYDcCmGd/efcXhT9oQ2BtH7hd7j6ojT3dXTNwF1X2Qdqdvm4ca00Efgy5yRJRqw3ByhAyeDvaCDf0IZmEACFACBAChAAhQAgQAoRA0ghwjXcgZKwRGzDFksZCsYrILTWRC/NpqNVfMdX2VEfYS+TODUEeWHsiSd/2QICfKCqYb49DCn7RhhDhJj9Ed4bCiBv74hpao+B1lDaVXnzx+U/D4eiVYIgf6LVTwZ5MsNi5tQ0Nn/Vaj04SAhYQmFYybdD23HiRjyWKTcELOWf7YhVsqMHEEDx/hoBCHwKqNA8id8WQF+Bz121ppSflDtkt2mzCf5/LP6yKyWv1c8hchxON+FuNtb9GeA6uxXEqhAAhkCEEkHC5oLWVFfpZYoRp4L4XfATu3uH4G8g4z0f6gnzOxSAmuLzf8zv+OmnLt+CL9AZGMXHvc9z3YjPabsZ9vlH+of06YfqahC/WCG/r1Q0NDe3PiJ1t6F9CgBDQCgETOxBii21Ni2fzXwWDU0dzEX8G4zJE+bHh3NZOhDs+zXs3d3CL/D3ShgNQfqy8peDgVbmjDgfd8IrKamt08Rqj2qeDKqOdqm5G+5a7b6Qqxuvt6+qq54RD0XPw2z+1G1vkQ/lmhAzeiP9pq9huAKJDvSOAyeo+8Xj8oJ2kOIdnJz8ILSbg+VLUwtoGSjdPgTdPEE3tBRNPfO8ouz/sOtD7/3u+v+78hsnwziK/Ys9M7IDTCh1WMpl4k7O3BWdvCWEsa23d8p6XVzl7R4bOEgJpRcAoP658TMwnJuB2lvf6gbipD8T9Ng7/F8XbzHwf7sf2+779/ux0k+Jj+52LG7Pnsqu+rLGrXrvAnU3aP+Ifw2Rc+JiP++R9Lz2NG1F/uRDmG9iF+C2T+96or1+0Asfpt20ncvQvIeBNBHj7+7w3de9DazxD5TPKc0UuULYYbc/gQT/GI8oPiUQiI60uck5Y8GHrqlmFH+EXR77bUiEE9kLAMH1TcJAIrL2QceGA4GIwHjpaFyQxByPK/qW1kckZJ3wmu8Q02GuonrO7CX404cVyZk1DzYu7j9EHQqAXBKLRaJGIi6NMwY5CiG4Jqh6JySrIcPhU7W73xafdh9L7IRdT54Mw75UvG1/HyyE+miwvNz9WGoy+wg3WIExen2C++oaGRc3pVY16IwS8hcDEiRNzhgwYMgkO8keBLD4KXlNH4YaaHGdmnry3dhe83beXXf/vPpG2D8PQE/6EfDZ9Q9JnBpy4QGxtxcdlUOtVsF113M8XV1dXg+iiQggQAl5BAPfvuM6PG6/onZSe3HsEVjAYzGvhrU/h98CWV1NSuLhQKZFoT+S+1qpoXH/L0IYILKvAZU198xiYerfK5mrjgYUwnn1BXqiMdeq6CVEOITekLsj7EqpfqH4HL/J3wJJrpDUY+Se4z/xOTW2tDMeiQgjshYCcuA4dOPRoYYgwCJ8IJq1TzDhDGNAX3lR7NVL7QEDagEn4FExkL/ftnNyuxt3wPMju/3BuPldL94PaI0jauY5AaWnpYMZ8pUjIW4bOIvg7Ar8XObtfF/Am77FS0H7fM9z3jF8o4HMMj+SV8AitBq+9mPnMKtz3ng3h8dhYkLqEgGUEpkyZMhDPoKGWG3qlgeCeev5UVFT41jatfxjwlnoF4l16IiJA7kT47K7vyf4vPfmxYPP1ZOtTvWxDwOYOl2mESRsCiwsxBC91ehfOQ8cee/xQmQdKb0OTsy4hYjf7WOA0EBJ319XV/DG5VlQrixAwsJPMUUjGeSJsPgF/xyLuJg8rbJKz0rXA9Z1/By8m32HCSIDkXQJDF2AzgyeqG6rf1NVososQ2IVASUlJ/7ycvKmMG7jneRmIK7zgCxn5q23B42wsCLmxeK6dg/3r4aVVtkww8wn4bP2rvn7xyzAc82UqhAAhoAICuUbu/ngX0bYIg6/wkHEc5NU9eHZ6kszBu54ksCwXLNtiJ0L6WbAMXPY0GK+6qdoQWHj46Lua8cVVlJPjj5+Br3d9cSh7P8kkt/CqOXLZsmVt2YsCWd4ZAZm/KhYzT8aE7iT8Np/AhCnDcLK1yF1EQvLP5OwXCDd8mxv8UcETj8BD4/1sBYXs1g+BUGhqMTZWOAkv5KfglfxLsFBupICSrS/oYiImKPgTPwOJLcOKn8Ai3z8RXv8/fNZ57iwHnYr6CBjwjBwk1Uwkcvr7fG25ppnDDaNt1+YnKVsghNiK0Nsed8KLxXK3BQKt3b47+v3+LVVVVTKfqislYbBxIB60LUK0LfeKcXg+/gK6fs8r+nbVE+uxtggsRCG8xXW+CLsCRd+tIjBk1awxg4vnrVY2qgnzPD0KHkIyubmtG9ljCLxfW199CHSml1CPDRyp6w4CoVBouMECX8NkVa6gycnrF3nR3OnS81Lx7vwqksLPMVl8DojgzzxvEBmQdQgEg+UH+Lh5JhavKsBTeSpvSeYGS6yCV9r9JvM/gGTw+EyFEHAGASwe+RM7EofC++YILJSMhefjMPg9job04bg/R+J/hPK279Cp/O8z9lI4VKapgL6ulHAwegVCfmUKDP2KYNuwiZLcjVX5Eg5HLsSOskrn+UkCxFZ/jlFglXB9+fySwPCt67dCvvL3YxIYUBUXEEgI85Bx89e864JoR0Tq44GVPduBHghPijPxAzHPkSuAhBACHkQAL8sF8LQ6HQtIZ0P9cpBX0tuISpIIYOXiSGyjeCRCcG8tDUcfwwv7PQgxrE+yOVUjBDKCALw2xoiE8U1M/uCJbB7droTGngzOg8yLIXM2ksFfh0W/5+GhdV/BoILHFyxYgJ1OqRACySOAe3E8Jv9TmclL4AVyFDY/mYztM/tJCfB+Ak8qPyQvT6GaIsZjK93UB8+vcW7Kz6hszjzhfRUJRb6K3Mk6pB7JbW1lB2DMLRENR9+7NLZ6VuEHaDcxo9cLda4sAj7DN0BZ5aCYTgQWNpzPksLZbcjz8a+lS5duzxKLyUxCQCJglB5XPpUZiXPirebX8RKYT7CkjEA/TDLOQYjhOZjQvomwoz8UDOo/hya0KeNKAhxCAGR1P3m/YzZ8HibLZbjv5dSYSmoIyJxgJwjGT9iyadt6eCL8PhDw3Y1V/I2piaXWuiLQnuh67dojkGPtVLBTp8DDqqSdn9Lvblwr01O4Oo5cjG/PxelqJ5kRjsthRWZ6Tr7XSDBShmffI2ihxcKnj8k8j9YIrHa0OF8GtpkIrOQvnayqiTyaA1U2WCMCi4PA8uZyj40LpKh/Tv7taPd/NtpSE0LAUwhgArsPJrDfxk57uN7N/duXdvV7aVZhTA4TTNyLCe1NILPuhlv672hCq8KwZKcOCBE8GCGC58Kz43ugrPbd6dKRnVi4bPUIeNLcApxlvqz7DD/7VXV1daPLfZJ4byDAo6FoxGTi+2ub14O4MjpyVGn8rs3TQMAIrnyCZNuXp+IeWKFQ+SRMzB+Hfe3egrbtVKghN9rT51RaVYmbYpnc04gKIdAtAnBR7Pa4Igc1IrCwh3wWFVxWF8MF9j819TVPZ5HZZGoWIRAKlQUNLi7BxOp0TGBzaQKbtsEfjp6uB+6XYkJ7VweR9UnaeqeOshYB6eWxrnndaYLzy7EBQzhrgciM4TJvzaVmnF1YGorMNfz8FyCylPemyAxUeveK8MDBzPRVYFH4EiRbhXeH0vMYZwdDCLdD4KT3Y7GzSqsjDXNeZZ8Z5VPKC+PMfAZoyXxs2hRE7OIetVE4e8tGK2qSLQhw5q4naoo4akNgIZeDqfGaUHfDjPQ//GGsUh/T0FD1YXcV6Bgh4EEEsDtR2cm4nS+Fa/O07HGqVHKk5EveNSCyLgOR9adYovWWJUuWbFZSU1LK0wjInHbxNjFrbfPHP8Jk+SC67zM6nEjqy78DIuss3PdI+B7/eX19/ccZ1Yg6TwsCIK4O56bxU2Gy00BeZWVyZ5ABrhIwIFFGgUTBgpymxXAXP7uo4TdmX/zGLET7Irsy1G1n2iKwDMNcljAln0qFENgbAZFgSqcp0obAAvRZ5YHVcantgxCLf06fPD347BvPbtv78qMjhIA3EJgxY0bu5o3bzkV+mx8jt8aErFrxVX+IpGfGVQF/7rcjobIbt7du/Svy7/W4Pbn65pCGqiAQiURGIq/Vj0CSngedBqmiF+nRjkAA/55vMH9FJBy51Rfw/QEhxS2EjX4IRKZEJgs/vxZ7W38DC8FZ5G7VzVga3FUPrISR2JkGoZuudTgkRNxV/OxghJzB/fEb8wTaHmSnvfpt+BjoKO9bS34co1rXfNgYKJTPdG3CKdUfK+9oaAif0gvW2lCvgotN3rksHNX0sO35LXMgMbtfOhyFlISlCwFJXGFXzYuRd+lDkFd/Rr8gr6goiYBg+yFH1l15ufnLwuHoV5TUkZTyBAKSuIqEo78VCf4RPB6ugNJEXqk7coMRFvTLeFvi3dJg2Ux11STNrCKAZNbHwsvuKeHjr2Hqi5BBeo/0ueyBBYTHWR0nD9UX+VvyV6qkL8irQP/cfJkfKqSSXg7rEoAjQ3+rMnklS+C+f89qO6qfFQiYrZtzm1S2VBsCCzfhWpWBdlU3zr5eGir7oat9kHBCwEEEJHGFna8uAXH1EV7o5FbGhQ6KJ1HuIjAB8ctPgHj8d/lx5WPd7Yqk64QAiKthmDDfBuLqQxBXl8O2PJ3s09sWXoyNNOaVhiML6L739kiXH1O+H/KczUGuuRdgycn4owXQjiGNCf9Hro4uN8a7Kj+Twjlbr1g0CM/L7X8P3JJOyiQsaej7Y9u4c7YsDfpRF95DoHnCgg9bVVZbGwILD6jsJbDarzDxy1AoOl3li410IwSAAMcqfgWIq7ex89Uf8H00oeJRBDg7NW6Yb4OQmC0JSY9aQWqnAYFpJdMGdRBXq9DdVfizvFqcBjWpi2QQEPzLcW6+FQ5GLpdJ95NpQnXUQAB5gPxYeLgsHjDfxU/x2dCKiKs9h6aloWGRq3MJJOsdt2eX+nzDwtYKlawpDUdvwSX+HZV0ckcXIcMjbRVEL1Eid1vIad9IuVDgrohrQ2DhZ9jVH52uwCn43YfBfCgajWqYoFBBtEklywggXOF4TGJfxir+Y2is7yqkZWQ83UB60Fy/ZdP210tLy0s9bQkp7zgCMnwD3sHnt+S2yTAFSVyRx5XjKGdAIGf5nPPfrmle/xISf5dkQAPq0iIC+P0tQx6gV/Gu/Ds0pZDdbvHjkmA3uz3l0EFsOKXtuw92R1eGwJJELSJzrnZo2FQWs5EZ4ia7Chomf9VuW2qnMwJiqerWaUNgGdkcQvjFVTY8EWdPIBY6/4tD9IkQyCwCmOAcGAlFn0a4gtwB5qjMakO9u4OAOIiZ5mLkNboDq/yUENQdkD0lNRKKnC7zpSGv7D1QfISnlCdlk0IA7jtHMtNoCAejMo8ZvlJRDYH2PJMybJfzRdBtkmr6KaWPEOnwOhinlM1OKqOIBxZydJ6Bp9FvnDRNUVlxLsSZtbW1q+3q1y+vpQ5tZSJ3KoTAbgQQIVO/+4uiH7QhsAB2tntgtV9i8oWyI6m7NmOr6L1DavWBgNz5RYaXYYLzRhbkIOgDjaw4bciE3PFWc2k4XH50VlhMRu6FQHRKdALu+2cF43/HSdqUYS+EtDsQwAYcdyA31rMyt5J21nnYIOScOxTh+jLPlfR+pHfCvsbSYK4SWMFgUHqg6nuPCHfx62v45PlwuOxLCGV8EB91v96xpw67oKah5r/J4NJTnWH3fbIF88bbejpPx7MTgYTPRwRWuoYeW9OuTFdfyveDpO7hUOQXyutJCmqLALwvzoT3xfsw8Hr8UX4kbUe6G8M4O5QLswEkxvWUI6cbfDQ9JCdnkrA2fexNmHiCpmaSWT0hIPg05FZ6nXJx9gRQWo9zGbqLzRJeQq9HpLVnL3fmsgeRYbQncAdfoGnxGa4SgH2hFg1GD4NH0j9RT/d3TmwMKy6qbai+ry9MkjlfNK/pBjjQXgRv6ZXJ1Kc6miMg2OtjH16lvFOQNgx1XV3dGvwqfKr5ZZW0eZzxn+IFRibppEIIpA2BcDg8Ctfd4/C+mI9OKUF72pBXriM/NJqNHDmL5DWhnHakkKMIIGTjKz7ufwdCibB2FFnPCRuOl8pnkOD9BiKvMzN2U6ZMGYjf4H93hO7SZgkWhsHtHE6c+8dbUMdzVU3TyFgOLKSqGG8a7FmAto/ngLOoMOZ3V9fV1fzZYrNeq4+Z13h30YHN+wtulmIufTty1crfcyrZiADn//CC2doQWBJshCnRbgpfXHV4Bom/ysSdXxyiT4SAawi0r/hy4XsX193XXOuFBHsKATyEorgmXoNbP3nkeGrkklM2FAoNx2S5EiEb2AWJFyfXimppjoAPCd6vW9u8/gmQ1wM0t1Up8+QkPuDrh9APcYpSinlEGc7Nj1xVNaFvAnfgFhs9emiTq/j1IBx5N/dlpu8ZTAL1Dc/8wvbZNfWLf/nFV+c+cST8KJ67pg4eWVePmdt8qOnzjce8+gK8xz2FXtqc64kkqYwA8iUSgZXuAUJA8Bvp7lPx/nJwIf49FJq6v+J6knoeRkAmaUfoUC1emmWyZpqweHgsXVJ9GNz6F+AauQbytVo0cQkvT4gtDZZVGMyPRSPxDU8oTEqmG4GTQV7Xlx9XPjbdHWdjf5HjImGZUB/348RstN8Jm2Ox2Aon5PQog7NxPZ7z+AmQHKsqKysT6TZD5lrF7ppP4ro/KN19Z6C/39fWV9+Qrn7HPrRqRfG8pntBaJ2a44sNEcL8Csb5IfT/ebp0oH7SjsDS4rmr3057rzY61GoywZlBHlh7XwT7Giz++LSSabRt8t7Y0JEUEcBWxefgpXkpxIRSFEXN9UbAB/NuKg1H/067pHp7oEFYDy4NReYgxOAxWDLM29aQ9i4jMClumC/BAzPicj9ZLT4SKjtPGPx/AGF4VgORgvGYmH+6ZMmSzSmI6LMp+hjXZyXvVkh7/iuQVwHkWpU5r47zLmzJai7uB3n1w2RrO11vv4fWbyuev+ZJkFnnFMWahglhRHA9U6ih00BnWB686X+XYRWS7l4rAgveRuSB1f3QH9aS2/aPiRMn5nR/mo4SAtYQmDLl+BEgr/6NrYofRMsCa62pdtYiINhp2wta66LRaFHWYuBhw7E5w8kgrBEmzM/2sBmkenoR2BcemM/CY29mervNjt7g2XoVog/uhbWB7LDYNStdJ2AQjjXeNe0zLNjt/GHdmMf75+T/BcdP7OacVoeQU/bh2vqa78MoXEKZL7ySJYrnr67dFWoomLE/FLsc7wULoV0s8xqSBnYQwBh+3LKxX6WdtplooxWBNXBg3qsAcUcmgPRAn8cPHjTkAegJ0pwKIWAfgdLSMulOvAxX0qn2pVDL7EVAHG7GWT12DDoyezHwluVy8SMcLPsNXqQRqkFeHt4aPSW07QePvbnhYPQKJbTRRAm56ydMuU0TczJthusEFgwcm2kjXevf5R0cu+qNa/8OkGbf7npcv+/8X4Ec/h3YZapqW/G81csRavh7JII/wfCLkSDUv4mJpgw13KSqzqRXNwhwceuEBR+2dnNGyUNaEVgLFixoxUtSnZJIK6EUn4mH/o1KqEJKeA4B6a6N6+dXzBRPgKkf6jkDSGGVECg0Oatu9+hRSSvSZS8EZA6jwYOGLuZcyPAFWgDZCyE6kCQCyO3O7sBvCBEuSQLWSzUuCWWcv76XOnTKCgKCu0pgSa91qKOvt7rL+HUeyg4i/Medj2n6+bkBg/qfWVVVFfeKfYVzmj8tntdc2R5quKZp345Qwzuh/2qv2JCdeoqVbZ/l3e0l27UisCTwmFgv8tIAZEDXa7Fr1EUZ6Je69DACMuQrr1/+/2CCfGmgSayHx1Ih1Qvg0fNEex41hZQiVb5AAGMzCzmMZGh+FuQY+cJu+uQqAldFwtE70AP9jtiD2UAuwbs7CGV7EqjV3ghwtmLvg84d8fni452Tpp4k5GBzFb9dFstQZBDht+/6rvH/9f239jut3THDo0byKhbvCDW8bMy8pmKDCXjd8+tgzkv4w3SdiioIcMav9ZL3lcRNOwLLMNnzqlwQ6uoh7oTnw1fV1Y80UwmBSDByIkK+XsPPTVglvUgXLRDwYRp7XyQckfkdqCiCALYl97d7ynA2FyrRzqKKjIsuagjBrpAkDOzR7h3U7TEC+fdr/BZf4HY/2SZfmO4SMCActSawTLPVVQ82eT1GQ9GpiLK5Hx+1fm6A2XnVn2Oc/Owbz27T6T4snNf8GsIMfwEy69hALD4CoYbfBnFSCXu36GSn12zBStLzhfOa5nlNb+0eAvsV7id3RNvotYFIs74+mRQwHC4/Os39UnceQwAeGJdhc4SnofYQj6lO6noHAZ8Q/F4QJtkQEqD8qIRCoeHYllwmY71KeWVJQe8iABImHCr7W0VFhdyhlEoSCMjQKZB/SJZMxXEE/HF3CRhTawJrU0NDw2eOj0kngXK+YjL2BA7ldjqs48c3Y/HACQgb1HoeO7Jy3QaEGs4pmtf4TSPGQGaZJ4BIuRPkfLOOg6qwTZt9fvO7wN5zHnHaEViVlZUJDMMihS8WVVQr4MJ8OjolOkEVhUgPdRCYPnl6fiQUfQTeMb+DVjTBUGdodNVEhhP9CiQWkSYZHGGZWN9gvhehQlkG1aCuswQBzsS565rW/w3myvufSi8IhMPRM7IkdKoXFFw7Fd+xY0eja9IhGGM3zk35mZSNma+r5F8oNHV/zFeego365hDbOYAfcJ848cUXn/80k+OZ7r6LKpt2FM9bsxB5sy4rmt9UhJvlWPApN2Eu/3q6dcm6/gS/fNScNau9aLd2BJYcBGGwx7w4GBnQebjpY8/TlvYZQF7hLuX1sL2gtQ4vJWcorCappicCt1GOvswMLMLKz0Ji/XpMtYozowH1mo0IyJ3EEE54SzbanqzNCOMv44I9iPpavrMni4Nr9QRrXLp0acw1+VKw0JfAwrW5wi3sIpHIMIPFF0D+CLf6UERuo8n8J9TU1KxVRJ+MqIGVDDFmbuNLY+Y1/3zM/KYj4iwxFnORC3BcEphtGVFK2075n8fMb7zfq+Zp+WPY0rLtSQzIVq8OSpr1LkJ+o2dKS0sHp7lf6k5BBCJTIpNxPWAnT3G4guqRSlmBgPgjvA2+lxWmKmJke6gw43OgTj9FVCI1sgkBwa5GHrwrs8nkZG2VXvII48+G0KlkIXG8HkhU1wiY3cpyPn73Z80+cMMdD6xwODxAJPh/AJfukSLrBU+cUF+/aJVml0bK5oyft3ZV8byme+GddWoixz+CCT4L85NHIXhTysKzWAA8Quu3xAZe5mUItCSwsJKyHRe4JLGoJIfAJGYaz5SUlPRPrjrV0hEBmaxd+HgNbCvS0T6yyTMIIN8tuwe7DVV4RmOPKtqerD0c/XNHqDAWOakQAplBAHnwbqfNHPbEHvdnv4SPycnaoD3P0DcnEUAo60dOyusqa+LEiTk4NrrrcV2+4951nACUmBnC93dgdJQuOPVgxycgr46vq6t7r4fzdLgDgXEPrNwIj6H58M46syjWNFQII4KXFrkj5QcEUvIIwKPtvZgZ+PrEymWe9mjTksCSw4iLWv7oU0kegePycvIfkROa5JtQTV0QiITKftCRrH2gLjaRHZ5GALsTiofC4bKIp61QWPlpJdMGxWOJBQhtoR3NFB6nLFKNYyL8ZxDXp2WRzb2aGm81/4h32SN7rUQnU0bAbQ+soQVDi6GktrlEXcCPDx405K+YaE9PeXDVFrBJcGMGyKtlaqupnna8kiWK56+uhWfW1djV8ECQWZNwvVyN2T8iSPBWQ6UnBD4Qhu9L4+evWN9TBa8c15bAKhhUIN1OP/fKQCihJ2enxtrE3dCFVuKVGJD0KCETZ2M727vQm7YvWOlBknpxGIFcQ4jHg8HyAxyWm/Xiyo8p36+lX1s13PGnZT0YBIBKCEjieh68gZHEN7sLwnpn4U2MQqnTcBkYLuZwkuoLQ+sdCGGhszs4RsLR32AacnYahj6TXWzHovGpdXVVL2dSCV36Bpm1DKGGt4+Z11jqM81ivNtcDNuexZ+nvYwcHp83uZ99aezDq7TIs6YtgbVgwYJW/Gzc7/Dgay8OrtTfB6HxW+0NJQMlAhxj/Sv8fxvBQQioiACW0Yb6uPkkPEP3UVE/L+qEfIdj4gFzMdYoJ3tRf9JZewT6CYM/kc2by4RC5ZNAXv1F+5FWxUDhTg6n3eZxY/zuz/p9EIFAYJVTZoXDkZ8KwS53Sp6ictrAap5eV7dYpuyg4jACox9Z04hQw7vgmXWiv8AcLIT5FXhl3Iv3yY8d7soz4mD/87FYTqRoTlOzZ5TuQ1FtCSxpt8kCd+K/RB8Y0Om9EbgMxMY1ex+mI7og0J77JhR5EPb8WBebyA5tETg43mZSeLMDwwvyajxLGFUQdaAD4kgEIeAOAoLtl4izJ6ZPnp7vTgfqSpW/zQYTD0BDykmapmHy5fqWu9mVqfEOhMBtTVVVVYsT+GHzlm9xwW92QpbCMmLM4N+obaiSUUJUXEZg1L1rthfPX/MkQg0vGLOmabQpxPEgc36Pble43LU64rm4a33BiBn7Vy7XKvG91gSW3NEBjKvcepOKdQRuQkLVH1pvRi1URwDJ+gPxNjE/C1y0VR8K0i95BE4EiUWegsnjtVdNkFeHY7OOenh2jNvrJB0gBBRDAJOMI7fnt9wHtfAxe0qiTfwI0QMl2WNxxi3dAgLmE1e14FqHEDpC/oG8OgmbtzyAcdD5fk8gtO3btbWLaZMxV2+47oXzKhYfO795Ecisy+GdNV4wY39wBPD20zZv1ibG+Zlj5jZffPS9S2Pdo+Ldo1oTWO3DwrlkWqnYQAAJVX+NPAzftdGUmiiKQEVFhS8vt/+DeEH+hqIqklqEQE8I/CgSiny1p5N0vGcEosHokSCv/ocaI3quRWcIAcUQ4OybeAe5VDGtXFOn/LjysUKI61zrgAR3gwB3hIDpRnDnQ+M7f9HpM0inlPELhcqOgRy58ZbOm0gh1z3/QW3DYiweU1EBgeJ5q5cjb9bvZd4s5IYqwrP3Qui1AH9IQeTxItjjBheTxsxt1HZDO+0JLMQYy5f2Nz1+KWZKfTxv2T1IqPq1TClA/TqHgPS8Wtu0/jGsNsx0TipJIgTShgDecfn9cpKXth416Ajk1WEmb09mOlgDc8iEbEOAsztwDYeywey4Yd6Ld66sC5vM6NhykTIB05f+cCka11cdr55PdQdCuUkLQmZlpEyBVzFIUu8ra+oXU167JMFKdzWZG6p4fvM98Mw6qV+sdV/BRQXu24egx6fp1iXF/j7knJ00Zn7T1wvnNjelKEvp5toTWBJ9PGBvUnoU1FbOj50yHi0Nln9ZbTVJu94QkHk18nLyH8HL8dd7q0fnCAHFERgc95kPy+tZcT2VUC8cDh9kGu3k1b5KKERKEALWEQiAgJU58LS+hhFC9W1Ac4J1eKhFKggIk69MpX1fbYPB4BDU0XcTkhR2cMTv0yiDm88Bn+F94ejl85zza2rrq3/tZRuySffhlRu2Fs9t/jtCDc8pijWNwMppORNCjt8yhXH4EOGC3/u4YMShRXObpBeZ9iUrCKy6uupKxLm+qv1oumdgDuPmP0pLy0vd64Iku4iAEW9L3EfklYsIk+j0ISBYONaWuCF9HXqzJ+S8OpAL3/+w2+B+3rSAtCYEdiNQlGgz/7b7m2YfQM71wySJFlozMa6G6aoHlmHkjs+EWWnr02fYwm/KlCkD8fv0NLxcxqZN1wx0hFQsv62pW3xLBrqmLh1AgFeyRNH8psVj5jdfAe+sSX6/WQwPp/Mh+p/42+xAF6mIwIadDFFmfCaItoMRLnifjrmuegIoKwgsGC/govrznkCg40kh0J+Z5lPtuVSSqk6VVEEgHCz7FR5wZ6uiD+lBCKSKAGKbfyLzZqQqR9f2odDUYuS8eh72jdTVRrIruxDAi/pXdM3JiQ0qLsNoFmbXiKpirbs5sLgpxqliqRt6JBLGCqtyJ06cmBPw5/wD7Y6w2tZT9Tn7U13DYmzKQEUXBEbNWbMaHk5/AZl1etGapqHt3llcyJ0zq/G3PQ12CixKvg5a4xdIQn8AcnhNRQ6vRyTRloa+leoC5Hf2lHAouhgGR7PHYlcs3ZAQRrShoepdV6STUEcRKA1Hb8XD7mpHhZIwQkANBN4ZMCj/yAULFng/4aaDeB577PFDc/yxWog82EGxJIoQUAGBrSbzH4Edpj9SQRkndJhWMm1QS26b9GKRoWZU0owA3mcPcfN9tjQUvQom6bqDbgtC42TONtPCsBmloTIkltZ8IyHO5tTWVX/HIjYWYKSqqiHw8vklgRFb1x8Jr7ujmcEmIyn8ZOg4CbzDgBR0jaH9W3C1epUZ2C0xwf4z5pHGNSnI06ZpVuUR4YZxPbyI4G5HJQUEhvl44j/RaDRSXV3dmIIcauoyApFQ2Q/wACXyymWcSXzGEDhk88atP0Pv12dMA8U6Rr6VPB+P/RtqEXml2NiQOo4gUGCw2AOQVIY/K5NmRzp3Q8iO3NafwKOUyCs3wO1bpsCGY6v6rpZCDc7GYRFR17IShlm6D0Ho/VZ78kqwf/pzjO9ZxUbXiyRb7OoI33sR9sq/3WVFxdj9fDmJInhjjjENUcSFMQBJ4gcYgg3aXQkfTME2Il/aVnxs5EKsE37etKVl4PsTK5e1da5Hn3ciAGIvuwo8Uh7Dj0lFdlntirUfcJ8oq6mpWeuKdBKaEgKRUOR07NiGHQexDkCFENAXgRgzzGNqa2vhUp3dRSa2RyjSv4DCydmNBFmvPwL84tr6xXd53c4pU44fETBiH9HOgxkbyTXwIBrtZu8gbJ6FfD2T8wu2oLah+qRk8QsHIz/HBP3GZOt7sR4m1c8WDMr/CnmGe3H0SGcvIZB1k1t/m3EpBmiTlwZJUV0niAT/rwxXUVS/rFUrEowcC/JqDgDIuvs7awc9ew0PcNO4G+Zn3WJM1yGPtQm5RTeRV12Boe8aIiBuKT+m3PObEwR8sR8QeZXRyzMNoahifEYtdLNzgy1PVnwkHPm+7uQVHO0W+XKMrxJ5lexVQfUIAfsIZN0Et+qlqnUIq5ptHzJq2QmBw5BrZSF2uxrc6Rh9zCAC0SnRCYLzp6FC/wyqQV0TAmlDAC+NwdJg2Zlp61DBjpDc+mrOxLkKqkYqEQJuIDAonmN6elv6kpKSAID5vhvgkMwkEeBsRZI1bVWrqKjwYW2lyFZjLzQSyeFXGiw9BXmB5EKTzuWFAMirqqqqFp2NJNsIAVUQyDoCSwI/qnC/P2DS86oqg+BxPY6AB8TTCF8p8Lgdnlc/HA4PMH38cRiyr+dYZJ4QAABAAElEQVSNIQMIASsIcPHL6ZOny2SyWVfC4bIZ8OK4KesMJ4OzGwHBZoXD0aTDl1QDq39u/9Ohk6vha6rZrJw+SRIwdvXe0LhBklc5dtsr307wPj2wsMA9BcEAj8AWjXMu89cTInYyyCuZv4gKIUAIpAGBrCSwKisrE4YQFwLfeBow1r4L6QERjyUeB4nVT3tjFTVQrvQZwoeXBDFRURV1UguXPFuPvzcZFwu7/skcCKhQjVx7b6POBvzJ+lTcRaBwe0HLle52oZ70UKh8EpJ9YkcnhpV+KmlEYAf6+rzjrxF3+IpO3+l+T9NAYAvzX8vcb2nqztFucJFc7KhAEmYdAZF8CJx14UjKbJj6hg8CEJNz+dzrsUQikUMBwjOah8m+H0v4T2xoaPisRyDoBCFACDiOgCd/+J1Aoaah5kUkFLwFMdnXOSEv62UIPk0mEJ4xYwbFf2fgYljbvO4WuKp7djU6A5Al0aVYhVxir4GQek1w9gbn5iqEH68NBAIfY6XNCvltIFnvsFwjNgovfJPw2jeJCX4YXuok2TgmCUWoSnIIXAkvxHvr6uqyYothTNz3jbea/8Z1lMoWzckhm121NuKefwfbVr8NbFeCnFptcNYUE8Ya0/R9PmRIzsa+cpwgPKx/Xl7evqg/wsfM4QifGQuiezzjHDuS8UPBaU8ApFm5gOjwpXRwok2cB5meCk+SxDN+B0odxoLEWUXAZ/TpQWRVZOf6Cc7GgWTVtvRv9fdIYAWDU0eLROwZGK/xDpviI8HNLy1ZUi0XNKkQAoRAGhHI6sS3cuUu0WZW4/clmEbM9e5Kbh+ba5xhcYKvNyYuW4f8N7Mw0Zrrcje6i4/BwBfw9yxmlfVYOX0VO9tJDwtXSzAYHGIYgXI8iKdjonwCOtN6xdZVMCFcMPGHuvoauVGH1kV6XK5pXv8srpupWhvqvnFbgGED3gFeBEn9kmn6lzY0LGp2u1sZ7rptQNthhkgcg5yFEVy4UfQ5wu1+NZW/XvDEBBDXW7xiX2kogvxd/Ede0VdXPRPCX+jm/Y4dCGVo9zU64ofn5qc19dXdpquYVjJtUEtubDF+kQ/X0fYOm5oNP4tUV1f3SOJpbDuZRghkHAE8g7K7ID57PFxcXwUKA7MbCSetFw/V1tecC4km/qi4iIB00RZx/iIIrHwXu9FV9LsgPJ7jhvGc38//p0L+glBo6v4+lphuMnEmHs4RAJ/1z2iLF18LJiUHuDkpsaiPK9UxMfoFBF/rinC9hSZAVtXhpnrWZHxRTg5/SZXFlvZwUJ44lZv8q7jrj8EwkIdW8tfiTbX11T9Pvnpma+L+/Qga0GJFZoehBdeMfG9y7T0VROU8/ITPzKyZrvX+MvCTz6k9Chbl8nw88F8clO8vupYNhsnKql+ofkdXA8kuQkB1BGhyhBGKhCLnIlToftUHy2P63Ycft+9DZ8wXqLiBgFzF357fIskrhKRQSQ4BsQovlI9gxf5+rNi/l1ybzNSKRqNFZpzNwkP6+7iJDsiMFt7rVXcvrNJg+ZcZN+VOo0RwJHd5tuD+eZoz/kRb3P/Miy8+/2lyzTJXq3xKeWHMnzibC+Pb+Ak9KHOaeKRnwbZxvxhXU1OzQXWNI1Mik4WPv666nlmg37t4Rz3ETTvhHf8C3s+muNlHxmQL9lhtQ/UZnfuXnsFrm9Y/Bpu/3vm4Zp83cVNMrXmh5hXN7CJzCAFPIZC1ObA6j1JNfc0DkWC0HCEEeFmk4hAC342Eo5/V1FVnXWJlh/DrU8z2gh13g4wh8qpPpNhaztmjzBTzZe67vqurUQOu6Y3Q5Hb8/TISjEQFN67AZPZkfKeFh16GCETFeci/cbuOXlg7SU3zIZhP5FUv1wBOgbNiVbhVHurXGvjnwqULN/VeXa2zVUuqmqDRrfIvGopG4S32Q5j0FXynce9uqOCBLMz2kLyfdndapWMgr05TSZ9s1QU/oq7mv2rHlWvsZWfsjd+6pvW/05q8AlHOfMYpNfVVRF5l64OD7FYGAXoZ6hgKX65xIV55lygzMhoogiS4V8BVfrYGpihnAlb2vovJ2dnKKaaWQouxQ9tpI0ePKAKR+kMvkVddYBTQfXFt/eJTTWYchefUYzjvWthDl769+LWfj8e0yy+DxOABEQcRy1i3eUe8OFAu6PwJEqbfkRDGgfCumIp75n6vkVddMamur66GHacZCXYw7v2/4byVDSS6itP3u2AXy5yCHjDwax7QUX8VXd6BEDl2CwDiMG2BFHxFZ9si4bIb4QRwSedjmn3eIcmr2tqqWs3sInMIAU8iQCv5nYat/Jjy/eIB82UcGt3pMH1MHYGr/5+9L4GToyjbr+qZ3c0dIoQrkEsUAUUxkmR3djcrgWgAAcGoKF4oooCKfor4eeJ93/4RPEAQD6J48RmFEDa7OzNsMIhoEA8gEELCTUKu3Z3p+j+1OdhjZnamp6u76u23f79kp6ur3uOpvurt98BiQnuS8BYCAu0L2p/np4T+AqRfkHgbjkA/PBV+KX3xTcou3qi2d6QUqU9gQavza/B9fPg5oPeeTjd6h9uQ12y0aMFaBhcISn082Gjyo+7B4umrU6ZM/OlYFQJdR6K5ueMFnvQ/i4teh+nwtT9kQlEl9tPZfPcnhzRZ9RP37UOlShkvEmCV0nuEgUvkek+J1cJTPfgQszHlq82e7z1WaChsj0PeYrG4K5/P7zTFm3qoKIpPLMlmV9+s8cs0t58PL/fvm8LSArr9UqgzEa2jQ/d5YwQYAQsQ4JefEZOApO7zkNS9G83jRxzi3eAIYG0hL+zOrUbIG2/1IKC9MMY3TdRfgObXQ4fg2G1Sye+ItP8d5EHZRFC/kirtDi8S38XBF5XskOhGeSE8V/4fBQgymY6FUvn6ucRh/8Mn9C/wsvwcPBR/j+ZEeSXi2j8BCutn6vOHQ5LovacmbBt3+E133RSLUWQs5FubF71aSHXDWP0IHX8auvwEHpHfz+c77yGk15iqIOz/DBh5fjNmR0c7+CJ9RC636t5Mpv00ierjUCPlqCpjiV3EAuYN2WyX9nznjRFgBCxBgEMIR0xET0/PWtys3j2imXfrQwDPN/VdhL29uT4yPBrGq08ABTZePXsqDODnlekB73nd+dX/myTjlYZAhxfB00iHFV6MXafy/Gj5zW7qfaDv/DNOF2uA8eoa6MLGq2dPmL/r8GB49s6H8eq3aE6U8UrDgGt/Fa59Xab+s/jHYYUaFCGmbZ+809rQenwxPn63mMT/17mChLgUxsTDcI1enDTjlZ5d5KycS3iWi1u2PLJBf0DDy70Oa6dqvEJEujifjVeEz2RWzVkEqN506pqQDRse+NvMw2dp77SOugjx4KEIwAlLnHb4zFn/Ar7rhh7g39Uh0NKyqBkn5Y/R2/lFeXUaV+yFvMbi58Lzz+rJdl+7/uH12yr2Jnxw/fr1/oMPPdA79+A5V/tp/4WIKjqCsLq1qLb/YYfPyuF+c28tg2zre8gRM74DmZbYJldM8jwMY+1FqH51wYMPPfjPmGSwhi2u/cKDGx64ddaMmatwP1yMa38/a4SLSRB44s7F/dBKb++Zs2ZeijmibNjQMa2/Fyn/VDyX/3jvI/fqD0yJ3A4/fObZeOldQFT5vvFNE9bDuPMT6Ec1lQWMV+qCbLb7B0TnkNViBJxGgBfCZaYPX40+hUMkwk/KqBhHcwpfa65tbW49NQ7mLvNcunRpkyeUTuDLRmcxmENjXk+2643wmLzP5XkNU/bO2zs3Y9FwspTqEtBN7MJhKKZYTL1z6L5rvzOZRUthsHFah5Aw3wU6n4PH0ZEwXl2D34nzuKqEI/L9ZdONqZfAOHJjpX6JOCbF0QjfOsFCXZFGR77MQrnCEklX/rysO9d1Bp7LD4ZF1FU6MF7NdVX2KuQeD0ulNl5RNph/BMYrynm9qphm7sII2IuAZ69o8UuG6mXvxRP5d/FLQkqCBiG967EwezkprQwrs+3pHTox7VGG2dhOfosOlevJdS/K5TrvtF3YmORT3dnuryB8oQXGm//GJIM1bIHBq+bPX7y/NQLVIIiuYoUwOf0CDTUSvd0KT8sX46PSxygl5Q97RoHN08j5drquwhg2bdfoKU9eaJvMyK/6PMhEdcG/C8a5s/Z8+NWGLN6EoGzAoj6/l+Fc/hJ1JVk/RsBlBNiAVWH2li9fXtzVt/0N6HJbhW58qHYExmNhdmNra0dr7UOTN6K9uf04uDJ/KHmaP6sx3oh/rWTxaHhffAut7H3xLDQlf2WznX9p6mt8GQx+K0p2SE5jY0Nq4DUuqlvo9z8HuWe6KHtIMj8N2925WEgshkfHv0OiSZ2Mn82vvgRemOdB0SJ1Zcvqp8QpbW1t08sej+GAUh7Cu0luiCRT5/XkV5NNWB5g1vRHh9kBxvGQ+BH49h5DbPySsASMACNQFgE2YJWFZveBtWvX7pApdRr2/jNGVz5cGwIThO/DiIWqj7yVRQBeGOmiFDp0MJkJnKXYjJfjM7K5rtdks9mHywLFB0YhsHLtyi3pJg/3LnXVqIMJapCeeJNr6iIEShdqsM6LJCocYbBe5aXFsfAo0ucudnmrBQF4Yf4QVoU3YkxSQ4kbVdE7uxbMTPdF+gTtgUVug7H0w9257p+SU6wOhTKZzCEYPr4OEjw0FgTUVTBeXRwLa2bKCDACNSHABqwq4EJls8cQwqDzNj1eRXfuUj0CU4XvrWhf2J700LiyiBX6/AvxKe+4sh1oH1gtPfVSvBxzGG/AeUZYUQEhl+diOJIHJ3RTIgND+fNd0X7evHkNKL/+Q8ibxHx32uDyQRisT+rq6trgypzZKCcqZ/0SYV2vg2yJrFCIysdvtWxenLkH1YDbn3XIeg39E9FVyoa5iVCUlJLyV4fMOFh7rvIHE1LzyspQRYANWFXOrA5hQNjbKbi16fLAvIWHwHTfEzd3LOyYHR5JGpQ6ju84GNlvLqOhTU1a+EqpTyMH3WIYjzfVNJI7l0RA53NQSrwLB5MZfln0ziwJjIWN4xsn/g/EepGFopkVCd6WwvNOwLn6NTBK5nkaMsI6rEuHd4Fs4hZl+sMPwu8tuo4UNQPWTl+kE+slWvFSLfpswKoIkF0HcXP8XbpRnq3TxtglGUvDCDAC5RBgA1Y5ZEq0d+e71+C9+vU4lMgvmiUgCatpRtHzbx402IRFkQCdYoP/VagxlYAqtajwmFDeKdl89yf5ZaIW2Mbum813XYFcaslccEjxqrERir8HQk8OhdH6o/FLErkEtxX99Mt6ejp7IudMnCE8WK/WYV7E1Sypni/FWSUPxNIoqRmwvpTLrbo3FihtZyo5gbvtU7RPPqlWNjR6r9fe6vva+AcjwAhYjwAbsGqcop58D8pU21fhpkY1rOuOLyBHFBr8mxDqM8064WIQCDlwFgETXUAgSdsdSNT+kp5855+SpHSUuuqy0FLKJBpIFra0tBwYJdZBeEnlfRHjJgUZ6+4YdW1RDZyQz6/a6K4Odks+GOalBnMp2i1o2NJJ8eqwSQahd+K8E/WHKOvvPzXo1u+LwuU19E9WVynmJEthZ7XNpRtSr4bxapezGrDgjEBCEWADVoCJR2LZKzGMS6wGwG6MIS9CTqw/Ljl2ycQx+lE/7Cnp6TAaREEkZMNXsIFi38s5Ubv5+e7Orv68lEJ79yVp81IidbLNCsN4vwCX/Dk2yxiybP1SyHciR9ub8/n8zpBpM7kRCKCgw0V4oNw+opn2rhLHtrSc8Ny4lexr7DsybhnC5K+EvD6Xyz0aJk1StBQbsByYzzvTjd4pMF5tc0BWFpERYARGIMAGrBGAVLuLPB0fQVWZn1Tbn/tVjcDCHZN2/Wbp0qVNVY8g1rG1ZdEbkbIkSdUZf4yvYEt7e3u3EptKa9XpznZdAvPoNdYKaEAwpaTNYYQSxvtvQu2kGK2fQU7Jk7tzq39gYKqZZAkEtJeBTA+G1D1V4jDZJk8UzohbOd+TtCoQJuzZEeD8mRtgDA+JDoG/9xcaTsQ98enoWDInRoARCBMBNmAFR1Pt6N+uk6PeHJwEjyyDwEnPPL39Z8uWLUtcFa7m5maUXlafLYMLtWadWPhTMAa/HS8SnH8g2tlV6QbvfEzAX6NlGyM3KU7q6OhIxyhBWdaZTLsOF15YtgOtA49KX3Ugp+QttNSyXxtd2RFJ3S+wX9JQJVwaKrUgxHxSCdx3TJkyoSsIDEkYg2fMOOh5SBJ0dVFHfCH6r0ypV6xZc8sTLsrPMjMCjMBuBNiAVceZsHbt2gGEPb0GH83X1kGGh5ZCQIozNz/0yHdLHaLclhIN74N+MynruEc3OMSo98J4dVkCdLVSRe2RoUR6GYTbYqWA4Qs1ub9fHRc+2foozps3rwHeSEm5DjYKz2/rvq37jvpQ49FBEUBS919gEXdd0PEOjsvsMSrEJrqUHqUE7t0rVqzoiw1Myxn39YnZEJHXVnbO04aU753E1a3tnByWihGoBQG+ydaCVom+OuxJpnx84ZP/KnGYm+pAQEnxrtaW9qR4I4nBBPZSJKVa1IeQUDxxBso6LgcjQwerSCn5NhDX3nDkN0+odtuUHDduwtvx/Ig9T08EuDxUVF5HT0/PvyPgxSwqIFBQA+/F4ccqdKF0aJzf77fEqxApD6xk5VGr8cTxPH9ujUO4ezQIPIoiQSd13ta5Php2zIURYARMIsAGrBDQhTX/MS+tTgKpDSGQYxLDEfhoW6btQ8ObaO5JlXo/NNuPpnbDtPoYPK90knreLECgJ7/6N3CH0/mX6G9KLLJJSR0yLJX8mE0yGZJlI4xXL8/nO/9riD6TrQEBJM1/EkbTpHwsEUWhFtcAT9hd4fAmyOTAQgjqnWEDRIueYgOWfRP6OIxXJ6BIEDsa2Dc3LBEjEAgBNmAFgm30IJ1bwlPiFBzhpICj4amrBYvrL7U2t59bFxHLB8+fv3h/pZQOH6S+fRbGq89RV9I1/absN+EjkPke1+SuWV4pWjHGmudeSjbofEQzatbDrQFPYvHwCjZe2TVpqKZ8NRwve+ySyow0qHbZYYby2FQzmcwh6DV57J5u9JC+vNsNSeOREsWd5sTDmbmWQWArqnovhfFqXZnj3MwIMAIOImDNi7yD2I0SuSvf9Xd9o0QwzvZRB7mhHgTw/imuRKLj0+ohYvPYplThfyDfFJtlDEG2b8N49fEQ6DCJkBEYzGnie+8JmayN5Ka1LWh7oQ2CIS/PJMhxqQ2yGJMBz0I8E0/hxYMxhOshjDSEQj93khA+fJzONVcPWEHHStlAKf+V743z7g+KRTLGeXOToacTWu7AIvdV2WznX5yQloVkBBiBqhFgA1bVUFXXETfK24TwX4/eXFWtOsiq7ZXCy/bP25rb5lc7wJV+g95XUtE2Hiix4pAZB33AlTlJopw9t3WuRKzLdeR1T4mX2qBjoV+9E3IcYIMshmRA1KB47e5noiEOTLYuBFAJcg2sVzfURcSNweMnNEx4USyi0qpA+JAu/hELju4wZQ8sO+aqX0n5mq5cV5cd4rAUjAAjECYCbMAKE809tHryPTciAflbsesbIJ9kkhPwQPptS8sJsyiB0JgeuAj6aG8Mqts96SbvDcuXLy9SVZCKXv3FBu2R8RQVfUrpoYR8San2KNt2e4MQDxmGd0822/XHKHFlXrUjID3/fzGK/Ac3PyVi+fglpSKT/wrGTs5hN+YlxjmwxoTIfIcC1mDLstnVK8yzYg6MACMQBwJswDKEOl7cr4N/fhJyGhlCsCzZQzxV+ONgxb6yXdw5oJM4Q1qdB4fq9iTcMF6Fr7acG86BGe7tveURJOn9pAOiBhYRi7DjAg8OaeD4pknngNTMkMjZR0aKK3ryXd+yTzCWaCQCg1Uhpbh+ZDu1fXhwx2LA8hWdBO5I/H8ftfMiTH3a2tqmgx6ZfGdhYhMhLYWg6POxBvt9hDyZFSPACESMABuwDAKezXZ/F+klvmyQRTJJS3G08L3lyCGTdh2AlGx8G3Q40HU9yshfkEq9lpM3l0HH0uZJUyddCdEeslS8usVCmKT2wMKf2DbYCNUHY+NumrESvU89/cR7TbNh+uEhIAvqS6AG2y7dDYk0XxiHdrjRPDcOviZ44nl+rwm6VGiiEM9cKrq4qodS4hJ8PPmxq/Kz3IwAI1AdAmzAqg6nwL16ct2X4rXwR4EJ8MByCCwuDvhfKXfQhfZly5alsJJ9vwuyBpERHoifQI6VW4KM5THxIaATuuO8pGx4nwIPzjlxIdzW0nYazGdHx8XfMN/HvQaxbN26df2G+TD5EBHo7u2+S0j15xBJWkcK1rmjIFTUhmvcSulUpUNOu/utm1iLBEKFxtieKxbBEJ8oSvwhm+/6anwCMGdGgBGICgE2YJlHWh1y2EHn4+Xp1+ZZJYsDvrRcjMqEb3FV680bN5+K8+IIV+WvKLcU2UMPPZiyEaSi+q4fTDWmfgAdHnZdj3LyY6GhF7OxbPq+FQtj80xhs1bndHV1bTDPijmEjoCfoh7yOQn5MyMN20VI2cEwmU0Mfa5iIqgUhxBWhF5yBcKK+Jg+KMWJuMbJeDyahovpMwIuI8AGrAhmTyevbmj0zoGxoisCdoligbwWl7ctbLOiqljtwMsLah/jxIgt6aJ3Didtd2KuSgq5u9KU/FrJgwQalfBiecltX9h+lJByEQEIR6kgpfgWPC5Je/GMUppQQ0++U8/dfwipNEoVT/mRGq6VSsVynxmleEgNjY3y/pBIkSSDfGfsgRXvzI73ROF78YrA3BkBRiAKBNiAFQXK4KEXhOP7Gk/DzzsjYpkUNuPh1n69a0ndm5s7joBB80SSk6TEeztv61xPUrcEKbWzb9v3oS7R5PsqloUlKqFdCEyjDmMyf9YqcXfBH9DV7HhzFwEU+VXa85Lw5h8ZqXJFf26k/MwyewbvsY+bZeE2dcSLsgEr/il8RWvLojfFLwZLwAgwAiYRYAOWSXRH0F65duWWgWLDK9FM+ivnCLUj2JXPRVL3a8HImYVhShbfDXkJXn/yV0igeU0Ek84sDCOwdu3aHbiifmmYTVzkIzdgZTKZyciH8+a4FDbIVxdreFM+n99pkAeTjgCBVH9KP0eLEbCKh4UUh0fJGOXQIr/PmNOPwwfHwhYfJQnN91ja2nxcfae9vZ2NiTZPEcvGCNSJAMEFdJ2IGB6uy9R7abEYbB40zCpp5E9pbW53IiQP1RPHwdb2VoITtDU9IN9DUK/kqiT9q4gqH/lCQ/opbbwiWGJdfb37tu47iJ4niVKr8/bOzaiQ2U1WaRWtAUtQyokk1X1kz4sQFNNVsfEF9bAQSDGJ+hGY6hfFtbpQUv2kmAIjwAjYiAAbsGKYFZ3kVsniyXjYPREDe7ospfhqS0tHLKWyawG12F88Ff2fU8sYN/rKywYXQG4Iy1JWgUBPT08vvIburqKra13011ncgiPcpDwvQm4RsVL37uzbcVlEzJhNBAhI6V0fAZt4WMhoDQweJQ8sJdiAVeGsLRQKM3E4XaELH4oSASUymx9+9KNRsmRejAAjEB0CbMCKDuthnLLZ7Dp86TwZjduGHeCdehAYJ4V/zTHHHNNYDxHTY5FA+i2mecRA/5/ImfSdGPgyS8MISE9dbZhFHOSbkDdvv6gYty1oO1YI9eKo+EXGR6UuGgw1jYwhMzKNQFEM/Bo8qIYRRhxCSCikTIn7TZ97TtMvpOc6LT9B4ZVSH29pWdRMUDVWiRFIPAJswIrxFEDFpjWYgNMhQl+MYpBiDZeK454z5YBP2apUS0vLgVjIvsJW+QLL5XvvxUJ2IPB4HmgvAp74KYTz7RUwsGTTA4+sdWBavqnWIfb3lzeict2f7JeTJawFgVwu9yj6d9YyxqG+kV3zCCmbBFzwvKexoVgOG7AqTaWn2IBVCZ94jqU9pa5bsGDBlHjYM1dGgBEwhQAbsEwhWyXdrlzXKqEGFzdUv3hWiUR43ZRUl9j61UWq1BugaUN42sZPSQnx657bOlfGLwlLYAKB7u7uTaB7lwnacdL0it4BEfHHO7R4fUS8omJTULJwaVTMmE+0COB8XR4tx8i4jWtubh4fBbfiziIpg4bvexxCWOnEkVyBsBI8sR2TYk5DuomjA2KbAGbMCJhBgA1YZnCtiWpPfvVyJcXbMQi2AN5CQCCF3BNXzps3zzpDkRSS2kK2KGSR8wyEcNLaTEIpebPN8gWRDYbuSLwxMplFiyEfreS+UlwxGAYfBHgeYz0CvkjfaL2QAQX0PG9awKE1DVOe99yaBtjdWTU1ifV2ixizdL4gZbCMGc1w2aP6b2vzorPDJcrUGAFGIE4E2IAVJ/pDeGezXT/BgooNAUMwqfPnCyeMm3BRnTRCHd6xoOMwpI2eHyrRuIlJ8UssZP8VtxjM3zACniBnwMK1GIkBSwp1juHZiZr8TuRF+1zUTJlfdAjk86s24nvavdFxjJRTNAYsSgnchXi4s7NzV6Sz5BgzCU8fx0ROlrhSXd6xsGN2spRmbRkBugiwAcuiuc1mu78AT4evWCSS06IAy8uam0+YYYsSBc8/C7IgTReZTXm++CIZbViRsgg0NMhuHNxZtoODB5DUy7gBa9ALVInTHISnrMhYqH1vT1hp2T58gAICcjUFLUbqgNDhSIo3SEkpJ5Li/FcjT6TR++yBNRoTm1qmFrzitcuWLUvZJBTLwggwAsEQYANWMNyMjcrmV39YCflDYwySRXhyWha+Zo3KUmgDFpkN8a43dOW7/k5GIVakLAK7v76rtWU7uHjA94wbsMaNm9QBaCJZMEc0BTuEp74cES9mEyMCSGvQFSN7Y6z9lBdJlWKkC6ATQigl57+qcEZmMpnJeB/av0IXPmQFArJ108ZHOHejFXPBQjAC9SHABqz68DMxWh0648B3wVHntyaIJ40mXipe17qw48S49V6wYPFBkCETtxwh8lcpJTiMKERA7Scl77BfxuolRBic8QWHVP6rq5fIgZ5SXAXvq8cckJRFrBOBhqJH0gNLKRVVbkw6HjmKKxBWupxwStExVlZSlMaxT2UyHQtpqMJaMALJRYANWBbO/fLly4vpRqkTDt5qoXjuieQpHeYWa+hegzfwCshA6Xq7Cd5Xf3XvZGCJAyOgBC0PLCFMVyPDPUe+KjDe9g30i773TfvEYolMINB5W+d65MF6wATtOGmmhHkDlg5TwsezmXHqGSpvJdgDqwKgKDM7p8JhPmQXAml8WLpOe83ZJRZLwwgwArUgQGlBXYve1vfVITsDxb4zICgpr4d4gFfz2prbTo+H9x6uUr0yVv5hM1fyirBJMj27EfClR+tepKRRTwzcc47HjBKqPih/n893/tfus5SlCxUBJXtDpWcBMaXMhxBu2rRJ596MJFQxCkiVJ++Pgo+zPEjlO3N2FmoRfK5U3rdqGcB9GQFGwC4E2IBl13wMk6a3t3erTGnDh+Qqb8OQqX1HSfkZjIrrfAdfeVLtUls6QorNO/u3kS2zbinqsYs1Y8b0f0IIOonclWoyCqrnnWqUfsTEfaEuj5gls4sZAenJdTGLEDp75SG7l/EtPdc4iwgZ+H6KPbAq4c0VCCuhY+kx+ba2lrbXWyoci8UIMAJjIBDXgn4MsfjwXgR0vhEvrZZif9PeNv4bCIEXZjLtrwk0ss5B8MR4GUgcUCcZm4ZfvXbt2gGbBGJZzCOgQ5vBhY4x3TMcSqRU7Ln3QjsrkAMnl+taGRo9JuQEAjBa3uOEoDUIKaU0/+zySYWU7crnV/H7Z4VzTCrBIYQV8LH1EApmXd7a2kon1NdWoFkuRsAAAmzAMgBq2CS7urru94W3BHSfCpt2kujhJeMzHR0d6ah1hvcXHe8rJEVBHpwfRY0h87MDAbgu0PHIUNKYB9aCBQumIAeODiEkscFr5QdQxCehDCtRAwJFOtf7Hq1l0e+vAYBAXSUtj5z1AIGv/QpnAu71pDzuKqhK7dB+wvd+qnPWUVOM9WEEqCPABixHZjiX6/wHJkvnxNrliMg2ivn8Yn9RYxjphkV/e6QMDTLDi9qtnAfHIMC2k5bybttFrEE+YzmwGhrGLYIckRvLa9C9lq66cNvPahnAfWkg8PTTT/8HmhRoaLNbC9/zjBuwfEIeOXh/uY/S/BvQBRCJWQboMsloEGjb9NAjH4qGFXNhBBiBsBBgA1ZYSEZApyvX1SU8+VqwIvVCGQF0+1jAZfiCfTsR/NhTjWhBBKwiYeFJ9fNIGDETOxFQPiWPDGNJlqVSJ9g5gUGkUtlcbtUDQUbyGLcRWLdunTb2kErcH0UIoZR0QgiRMex+t89is9I3N59wKDiYrmhrVomkU5fiMwglJPOenvTpZP2TgQAbsByb556e1X9AQvBzITacYXgLgMDLUT73mADjAg3ZvGHzizFwaqDB9g1CJKv4P/vEYomiQqCgUnQMWNKch5RSYnFUc2Kcj5K/MM6DGViLAF406OS9A8pe0d9uHGxCHlh402QDVoUTJpXy51Q4zIfcQCAtfHkd1gaT3RCXpWQEGAE2YDl4DvTkVl+Ll4r/dVB0K0SWKvXOqARB/qu2qHgZ56PE7SgqwMlcjQNtL4PDDpuuFzM0KhH6ZvRAnr39gFFkRnLDZ4uSaXWDYR5M3mIEkM9ps8Xi1Syan/K31DyohgG4/seh+yE1DLG7q5IcQlhphor+3EqH+ZgrCMjnSuV9zRVpWU5GIOkIsAHL0TOgJ9/1RYjON9tg8/eWJccumRhsaI2jpFxY4wh7u0txo73CsWRRIKArEcIjg0hlMmXEEDcwoI7HXJB4tiK5y1/YaB3FlWUvD+WrR+yVLpBkRovh9PWJ2ZAKlw6NzZeSPbAqTSWthP0jNU1Y8n55HqqVnzkSBN5nBBgB+xAg8ZJtH6zRSNST6/oQcjr9NBpupLhM3Tmp7w0RaXRcRHyMs5FF9XvjTJiB9QhgZbbVeiGrElAaMWAh/xWZXBowVnLIcFXnEt1OUshHCWmn0un0Myb18Tw6+a80ThP60mzAqnDCoLr1nAqHHT8kUcRBXeu4EjWJj/n8IfJhzaxpEHdmBBiByBFgA1bkkIfKUO3q23YuFpR/DJVqAogpoc42rSZCCSbh4f8803yioa8e6O7tvisaXszFagSUmG61fFUKh+TEO6rsWls3JebXNsDe3jDGrbBXOpYsCgSQkJySB9b2zs5Oo0VwpK/mRjEvUfDAu+UTK9euNBpyGYUeJnngOUJmvkfhpNR94/qa3oP32AdGHaPbME343jW6ABNdFVkzRsB9BNiA5fgcrl27dmBH3/ZleNHIO65K1OK3zZ+/eH+TTIu7ijqBO5VrbJVJrJi2OwggJ85B7khbXlIplBkDliRjwNqWakrdUR5BPpIEBIh5YD1tfM5ohZRx/quxTxi6BixP3KcNmEp6bwIMxbGhINNj0eaHN3+AjDasCCNAEAEqi2uCU1O9SjBi7egrNLwKI/5Z/ajE90w3pfs1ZsY2PyXIhA8qJXuNAcWEnUFAf5VEWNk0ZwSuKGj4IYQtLSfMAksiBj6RM+2tUnF6+KAVCAwoj1IIoXkDFq2QMjZgVbgKly5d2oTDdBL2j9R1TwXKbHZ1Nw59c+Rhyvt45/1cS8sinc+SN0aAEbAQATZgWTgpQURas+aWJ9JFbwnGbggyPoljfCHPMKk3vly/0CT9KGl7vmIPvygBt5TXgw8+eQBEI/HcgCdZ6B5Ynup/kaVTV7NYMFR21TyIB5BDIJUqhH6dxAjSY6Z5I6RsjmkeUdGHLpz/qgLYW7dunY3DJJ6HpdQcOv/pRu9jqH5+d6l+RNsaPKGumTdv3gSi+rFajIDTCJC98To9KwGF7+ztfEjJ4lIMN1plJ6B41g1D2OUSo9UIlTjaOqWDCfTMwTMPXhdsKI+ihEAqVSSR/0rPiVIidG8MKVNUrnmhpFxD6dxlXYIhkO5L9wcbaeEoJYwbsPBeQcaAhZsAG7AqnsbpuRUPO35QKW+fBx68cXeJlH8uVEpSKOELJjRO/Jrj08jiMwIkEWADFrFpzWaz65B499VQaxcx1UyoM37nxJ0nmSC8h+ZRBmlHSXrN8uXLk/TSEiW2TvGiVGELyak3hg2+LwSVax4GvoG/hY0P03MPgR0yNeCe1GUk9swasFC4ZT9w1v9obL7cZ8CgoVC4WlBK2F8KmZEVKHt6enrhufyNUn2ptsEL7V1tLW2nU9WP9WIEXEWADViuzlwFubvz3auRoFgnXcR6irfKCMjFlY8HO7pgwWKdB0eHWzm/oWIj579yfhZDUsCn412gfLU5JFT2kcF9l4oH1qZcLvfoPsX4R2IRaGjYxR5YVc4+CrfQ8shJF9iAVWnuCYWLjlQTnoQlK1BOmjLxY+ibqHy7SsgfZjKZQ0dixPuMACMQHwJswIoPe6Ocu3Pdv4KHwQeNMiFAHGEybSbUaEoNHGOCbhw0cZP4exx8maeNCKjn2ihVEJmkkg8HGVdhDN75xQsqHHfnkFTsfeXObBmVdMqUKZQMWI8bBcujY+AHTsWdO3dyTtVKJwythP0jNS1pvFyxYkUf8se+XZ8fIwcQ3j9AqtTV0E8/43ljBBgBCxBgA5YFk2BKhO5st3b1/bYp+jToqhftcfsPVZ2iJOOJIXyZ+m+o4DAxhxGQZDwMUsVUqAas5uYT9BfaKQ5P7j7Rle+x0XofGsn+gQUrmRBCZTiE0FeSTP4rFHHYgArXZObeyFUsBZnn4Uh8kCOybP6zXG61LurzvZFjiO+f1JZpu5i4jqweI+AMAmzAcmaqggnak+t6PyqH3BBsdCJGecW+4rywNUUFQhqeGABGysK9YePD9BxFQCkqL+zF6bOnh5rQWcriTEdndZTYyHOyflQjNzACjiMgpReq0XokHLhuyBiwoFtJD5yROid8fzZZ/b3K87+zb/tH4I6UqI+bSskvtLR0vITsnLNijIBDCLABy6HJCiiqXxQD5+BBo7+Y8FYCAYQRhv9A8hWJEEKcN08gcSdXtSxx3iSt6ZhjjmmEA/0RRPR+NOzCBCnhzyKCDabZf4CKLqxHfQjAQ3lCfRTsGe37ntmQOFIhZZzAvdKZ29zc/Bwcp5Owf6SyY1SghHfeDuV552EYnPUSszV5yr9u3rx5ZO6JiZk5VpQcAmzAIjeloxXK5/M7U43eaTjyn9FHuQVGmuNCR0FKEtXI8GbC3lehnxxuEtx/yv7aKNvopvSjpA69AiGsPoeP4uJqQ1GYXei7iksC5S4Wi+OJqO1v2fLIJqO6SDoh1p4sH0JmFENHiHteExVv5NKIV1GBsqens1MqcUVpAkRbpTh6/LiJXyaqHavFCDiDABuwnJmq+gTt7Ox8XMniq0BlS32U6I2GkSZUY9P8+Yv3B0q6CqHzG4x7bPR0fhbDUaDoiZeGQyl+KqgqdE/YUviKjgFLNSg2YIV9gjhKr1hsoOFtIMWj69atM5mQHo9LRcYLU/lswKp8yfqkDVi+591fWf/dR8dvH6eLRSUr3FSJC1pbF+n1FG+MACMQEwJswIoJ+DjYZrPZfykp3gzefhz8Leb5vDBla2goHB0mvThpwbj3UJz8mbdFCCj1YoukqUsUeBeEXgZcCo+KB9YAhw3XdXqRGqyUT8MDS8nwvS6HzHQmkzkEu+OGNLn9M1VMllGixtmC59GcGoe41L3Y17flwWoEvumum7ZLpd6JvnhdTMyGKHv1o7a2Nn3N88YIMAIxIMAGrBhAj5NlNtv1e6XUp+KUwULek1taWg4MSy5PCTIJ3IEJ578K68RwnI6UkowHlvD9u0OfDqWovMxuCx0bJugsAmlVJOGBJYUyasDyih4pgwbu92zAqnTV0krYP0xTWKJqqkDZne++BQSuGkaE/s50UZRXQ014XvLGCDACUSPABqyoEbeAXzbf/VmuTDh8ItIqHVpyaoQSherRNVzSaPdQSvnpaDkyNxsRGEzg7ovwix3EpKxKqfANWFJMi0mdsNmyAStsRB2m56e8iQ6Lv090097ESGg9dx8z939s6+7uDrVKq/uQjNBACUrzPUK52kMCx/U1fgBEEuWxj3vKktaWRe8ZCR7vMwKMgHkE2IBlHmMbOah0k/cWCPZ3G4WLQybk9zksLL6eVEeGRSt2Oh4bsGKfAwsEeM7k5xyP74wkFrKAsy+dTpvwLtBVqShsbMCiMIsh6YCqW6F5J4ckUiAySiqji2tJySNH1m7ACDQpDg+C2w0pj7uhU4HwyPuH7lfze+XalVvg5fiuavrS6qO+3NraSia9Aq25YW0oI8AGLMqzW0E3JHXf5ov0q9Fla4VuyTnkq0PDUhZfZZ4fFq246Xi+Yg+suCfBAv7Kkx0WiBGWCP/G/a8QFrEhdKYO+e3yz+0uC8+yh42AR8KAJX2zObDgeU3GoAHP65oNGGGfdTbTW7ZsWQrveTNtlrEu2QJWoOzOdf8fCqT8tC7e7g1uEkXvZ83NzTRyBbqHP0ucUATYgJXQiddq53Kr7kVS9/MSDME+1fH1NJT8NR0dHWkQpeRabmKhvw93/uEIAlJ1OCLpmGLiy3no4YNI4DwZjBvGZO5EB9wNeWME9iDgK/9gCmCgcINZDyyhyBiwhOL8V5XO+Y0bn9Ae+42V+jh9rI75HyikL4a39man9a9VeCmOTsmGL9Y6jPszAoxAcATYgBUcOxIjkdT9+gR+MRk1d1LJg0Y1Bmjo6xOzMYzSi402yPGWYAR257+SzVQgwP1uTdi6IOExlfxXgEZRun+FPdWJo+cJScIDy/d8owYsnBhkDFie9NkDq8KVLmWR0kfK0ZrWUYFyzZpbnoB32vmjiZJveU9rc+up5LVkBRkBSxBgA5YlExGnGA2N8t3g/584ZYibt5IylPAfz/PJhA/qOVFCEfEqifsMc5f/c6Y8p41Q/ivhC5EPeza8Ao1E13twaQobH6bnLgJYjJIwYCHv3cOmZmHevHn6OTnDFP2o6aJSNRuwKoAufULediX09P36DJi62jleHq8vQZpykxTS+1HH8R0kPFYpTxTrRgMBNmDRmMe6tNidD0u+EUQG6iLk9GClQ4Dq3jxBKIE70MATmT2w6j4r3CYA4+6ZbmswTPq+qVMn3DGsJYQdP+2T8VqCwYKMLiFMLZPwRCjeyTED+aR+zzElQ2Pj5FmgnTJFP2q6Ms0hhBUxp5Swf7Si23K53KOjm2trQaGoCzGibjq1cY2994GFxuJVkILD8GOfChaAOgJswKI+w1Xql8utvh1f3T5TZXdy3fC0mRKGUkh++rww6NhCw/ckL2ZtmYx45NAvYqfHw9oAVyn+smLFir6wKft+isx1ggmfFDY+TM9dBPBMI+BZJI16FEnpUwopUzt27Fjv7hkbgeSSVJ7TkYCFcq3AYPw4qhK+byRx8vtKvrK1uf0C8nqygoxAzAiwASvmCbCJfUNT6guQ506bZIpKFrykTwyDF/LrHBkGHXtoKBLhI/bg6ZYkLS2LFkJiAgvYPbgr0WNiBjxPUgq7238w75kJoJimUwjoamswaOqE1a5voSzKy4EgCVUghI6b165du6OcrtwOBBRdA5YS4r6w5hhVCX8BrG4Ii54zdKT4atuCtmOdkZcFZQQcRIANWA5OmimRdWl5X8h3gj7SxCRskyKUawEv+6Q8sJDcnuP5E3YpDFUXC7NXD913/bdU6jYTOng+nRBC4COnT5rOhmsTJ4pjNDdt2qSN186HkeMDlVkDFqWQMhmeAcOx070WcefU0tmpvnVUICylZ7owGEr4ZKljhNvGqZT3M1QlH0dYR1aNEYgVgVAW7bFqwMxDRUCHEmLRem2oRN0gVnf+ij0PKzreKrvn7RA3po+lDBuBQe8Lqd4QNt0Y6amiLOZM8Ef4NWzXdLaBtGDDNZ3pDKyJUqlZgQdbNFBKsd6oOIRCynArM2rsMzoPERBHwv4JYEPWwB92BcrO2zs3wwvr/RFMjWUs1DEDferzlgnF4jACZBBgAxaZqQxPEZXyPw1qA+FRdIGSqvta8Hf5+qtc3XRsQgurcl7I2jQhEcqyeePmV4IdIYOsvCuM5LSlpkBKSex+6R9aSk9uSxoCaiYFjWFeNmuUUXIuBZwGdVB+aCFkZDAZokhT02Q916Q+WAxRT5ioQNmT77pGCfG7oXyS8FtKdXEm035yEnRlHRmBqBEgtdiOGjyq/Hp6evQLTMK8sOpfgPrSfy61cwKhF7Op6cT6VIcAvsSfW11PN3rBs/SPpiQtiPrvH6ZkC0KXWjXVIBjwGKzSydz/C4aNMoqMAcszbexz/MIilrB/1GwYq0Apizqx+VOjGNJugA1LXLVgwWIKlVxpzxRr5xwCbMBybsqiEbiovK+AEz6aJGODojvr19QjZ8DCd8bncxx//WeGaxRaWloOxNy/yjW5K8mLikg3VjpezzFyHli+PKYePHgsGQQoeGCphoaGB0zNyInzTpwK2tNM0Y+arhTSsLEvao3C5Sd9MSdcilZRM1aBMpvNPgxrziVWaRuNMAc2eANXgRVZr71oYGQujMBwBNiANRwP3tuDQD7feQ9+5pMCCJ4s9RuwKCVyfXbi036ff9Szu/wrCQh4Iv026NlASNfHDzrsoF5T+khZIBVCiJArNmCZOlncojvLLXFLSrsJBWp2lTwSQmNfQx+tD1dpw+GWIWAeKwma73l7ITVagbI72/0jMPrzXmaJ+SvF0kym7fzE6MuKMgIRIMAGrAhAdpeF/KG7stcouVQ7ahxRoruk9SK7R8OiJ7gccInZptq0dOnSJuj2Xlr6qRXLly8vmtIJeUOMLZBNyVyRrhLaaM3vBxVBSsRB9z2wTIfEeWIuoTOhv6urayMhfcJXRZGa7+H4mK9AqXyR1oacZ4Yzpr+Hit7faG9ufxF9TVlDRiAaBPgFNRqcneTSX0j/HoIbW/TZBAoeLk/ULY+ikwdjKBZSKTZgDQWE+O9tW3a8GSqSSuIND0tj+a/06VAojHua1GkhxcS2BW0vJKUTK1M7Ako4b8AyXlWPlkfOepwkfu0nSoJG0JrvYRNn/FoBt1xu1QOIprt0GONk7IzzpfgZp+RIxmSzluYRYAOWeYyd5bBmzS3aqGMs7MYmYBAy83id8iB1BNXcCLK9Tmx4uCMILFu2LKWE+pAj4lYrZkF5ymjYwrZtm8klp/XTgq/7as8wgv3a2tqm45k20XXVTCclR6GTOa5jtE9+qe7b95t/lENgdrkDzrdHVIGyJ7f6clSIWOk8XrUr8MLigP+Z2ofxCEaAERiJABuwRiLC+8MQkFLeMqyB6I7yVV0eWM3NJ2iPlfFE4TmutbWVTJJaonMUilqbN25+NQg9LxRithDBizIqqxo1MK1bt64f6pIKI4RFng1YtpzDMcjh+ykK+a8EDEz3m4VP0gkhNI6V2ZkwTX1PNblJpvnERd+0sXeIXspLyXdif9uQtkT8xP3oA60LO05MhLKsJCNgEAGSBqy2lrbTW1o6OPwhjBPH9+8Ig4ztNDzpba5HxgZZIJn/ag8mKVmUi+rBh8faj8Cg95WSl9kvaY0S+vLaGkcE6y4FrTBCJfQ1j+hL3pKIgKeKJAxYwpOGDVh0ciJJ0/nCHL+QUqkCHWNlibmIsgIlcq3dj9yRHy8hBvUmT3j+T+bPX7w/dUVZP0bAJAKkDFiZzKK2tpb2nBLytyiZ/j8mgUsK7aJs+GsydPUfrEdPX9BM4L4XE8Tun7D3N/+licDDDz3yDpgrjialnRLb002ezuVnflPiMfNMIuVwYNvCtuMi5cjM7EFAup//SoOZLoj1BkHV79AzDdKPlrQSHEJYAXFPKTrhoqX0jLgCZTbf/W0hVE8pUYi3HdqYLiSnSBbxyWT14kGAhAELuRqObs20X49k011KiGYNJQxYZ7e0tBwYD6x0uCLh4gZoU6CjUWlNfOmvL32k2laaCdz3ao8k96fiN3tj7AWE2N8lxy6ZiK/vnySmlj5hf9XZ2RlNmIJU5Kp3+Z44i9o5wfpUhwASOlPwwBqYfvh0/Q5jZENo/WEgrKu2ktjwnGcDVqWZlHS87Uqo2RdDBUpfSf8dkGVnCXmIN6kz2loWnUdcSVaPETCGgNMGrI6FHbNbW9quUUX5d6HEshEoNXki/bYRbbxbOwI+hjxS+zDnRjxYl8S0X2y06WpOS8uihXVhxIOtRWD7xJ0fgHCHWCtgQMGU8n4acGjNw8DroZoHWT4AISWvsVxEFs8YAiQMWBuWL19usJJyeq4x+GMg7DV5psMtY9AqVJaUPbAeAFL6fT/SLZvN/gsML4uUqSXMEEL5jebmjhdYIg6LwQg4hYCTBixdHae1pf2bBc+/ByvrNwHxcnpcMG/evAanZsRKYWW9Ffqs1GqIUA/jIfrMkP3af/qCcg6sQTyk8M+uHRgeYTsCLS0nzEKxhktslzOAfA8fcvj0WwOMCzQEXr/kPLAAxPMzmcwxgQDhQU4jgGqkFDywzBpkfFIhZU/BW5VWHr/wr0C6BqwYK1AeMuOgr0ohbg9/uiyniCqvKelfd8wxxzRaLimLxwhYh0A5w491gmqBdJgLDFcfhsfVf7D7Pvwby3V75vjGibzo1uDVseFFNvKvMnWIW/tQqe6ufdCIEdQ9sKAuvDFeqxN9j9Ccdx1HICUKV0IFcpWVEAJ1nVnvi+ETL6Ui54GlNZQqpT8S8ZYwBPByONN1lZEP1agBC2HXhAwaHD449vlOOFVEjOGj+jktffEW4E+qku/Y59Ngj5dO22//RHqgVYkPd2MESiLghAFLW6czmbaLdkzadS+0+CL+TS2pTenGD6PZCT1Lix9/K76MqPilMCcBytr+sx7qCxYsmILx0+uh4cjYgzZv3PxKR2RlMatAoLW5/c24uJdU0dW1LkWZKn4/UqF9YXSxHKkuw5m9vaOjY9zwJt6jjADmexLuC85XyfJMV9VThAwaMXrguHAt7Y7mkDrnGckN78GxPr+6buv6J0LqPk8S3LGUUuKS9pb2E8bqxscZAUbgWQRsN+x4WGC9YdrU/f+J5JLfgdgHPSt6lb9QVautue20Kntzt5IIqFoMhiUp2NwohfePeuRLpcbPrWe8S2OVFBe7JC/LWh4BXeQCHgRfL9/D3SNYfN/Y09NzX5QapPyUzuVBcTug0OefSVEx1qk0AgMDA7NKH3GrFb7jphfldJ79SpnGyq2TZ4S0jY2T9TVB1gPdk/HPf0NT6gvw+V07Avok7HoIc7lm/vzFzn80SMJksY52IGCtAat1YceJCBe8HXFL1wGqul4SlJQfsQNuR6VQ8mBHJa9KbF/INVV1LNMpJYrk81/tU13JE1F56cX79vmHqwjAdpW+UhHwsig1AdLzvlmq3WRbZ2+nzoEVTcVDk4qUoi3Vu0s1cxtVBFJ6se785kux3qQS+KBDJoQQurABq8LJ4nmk8p2N0tSGCpTIwVYQXvHtEG5glID0G2Y0pgZ0OgfeGAFGoAoErDNgwVtqPgxXq4Tn3wz5X1qFDtV0mc/umdXANLoPQgn2gxFx4ugjZFp2NjaKujywEKGaHAOWnnZf6vxzvDmMQFum7WKEBp/usAqVRP9HT0/n6kodDB1DFIbQ+RkJbhJ2645WgoqxSiUQQD4aEoaZYjFtzAsTIWUTkFyh9qiAEnjb0IScgcawskG/umXwCYWLlgDDlgqU8Jz+G4rK6FQxydukOBNRR+cmT3HWmBGoHQFrDFiodHRkpqX9V/CWug1qvLx2VSqPgHvmpZV78NFSCBQK4iWl2sm0SXHH4FefehRStL/MjYZGvqG5+YQZo9u5xQUEMpmOl2GxQvcFUYlvYB5gS4p+QyXCe6LnGg1H6fsfj4YTc4kdARqeRTt6e2951BSWTU2TdWQAvgPQ2JTy2IBVYSrhskzCqFtGxSdtqkD55NOPfxZy/r2MrNSbv42vRc+nriTrxwjUi0DsBiy9EG5tabsSlY7+gTeBs6CQ5CHRrgAAQABJREFUqReCk/TCrV7AEjfeV2F5wdkJnRI99QoG1/tkeWCh+mdKFj5dL248PnoETpx34lRP+T8HZ6plmx9LN3k/ix7Z3RyRT+/OuHib5guL4JJMZlGbaT5M3wIEFIHFuhoMHzRmyCYWUubvt9/4DRacefaKQLvStFXGy3Xr1vV7arAqYfJCCXXEi5/6mS5eZu/FwJIxAvEjEJsBCx5XkxEq+CkshBFyIc8DFGnTcEildEVC3mpCQJ1QU3fXOiuvs36RabuWl8HnLS0tHS8sc4ybLUQA4cDpXeP6foEV3REWiheWSN/Dl+RdYRGrlQ48sP5S6xiX+uMZ+kmX5GVZgyFAIreT6ZxORUrPfbVhxYoVfcHOloSMomDULTdVpq+VcnwrtHflu/6KwySLzFRQe88hNQ/Fyz4xdj/uwQgkF4HIDVjNzc3j21oWXQKPqwcAu34ZHh8d/OrM5uaOF0THz21Oeq6gwcvd1qKi9AXlDWQr9hjj4LJly1IwwM4coxvFwylP+HTD0AjOWLHP/4ZQ8pUEVdur0hbkTvz23p04/jb2NeoKSsa8PuLQaQTPxchTecaINt4lhgDc4Oe4rpISyqxXCaWQMsUJ3Ks43+dW0cfNLkqYvVYCojJ56sRP4ml6d8Dhrg/7CDyeKa+/XJ8flj9mBCIzYOmv/0gc/I6UbPg3Xiy+BL2nxaC7l/I4j0e1uKdEo17sTqi2v3P9pOjNZrPP1CP3pk2bdC6ohnpoODz2FDxgT3JY/sSI3tbS9h54VVxEWWGl1NeQAPapOHVcuXblFvD/b5wymOaNPJXfXnLsEsqFPUxDaDV95F/R72b7WS1kFcJ5pr1KVH3VsatQIboukhO4VwJbh97j+HMq9XH5GKqP3G+j/NorUHne2yFb0Ub5DMvkweP5GjgSkD3vDOPH5IkjEIkBq3Vhx4mFAX8tEgf/AHgeFiumSry+vbn9RbHK4Apzz3+nK6IGkVP54rdBxg0dI4vS+S/VQ/Wp+bdSV8I4PanmcTwgMgQymfbTlJA6sTnl7cmC3/8tKxSU4nYr5DAnxOE7Ju/6mDnyTDlOBGSBxjNN+d56ozhKSckjx0oDhtH5q4H4jqYC7fc8z14DZjbbeRvWjrF6VtdwqoTd9TBPNlwZNlGmxwhQQMCoAQtltztQEvQ2hHXcDDfQYy0BzIMnwkctkcVaMdrb2+cg3GiJtQKGIJgvvLoNWCg5QPvFZgycpRCzEZr2hTG68eGYENAfD6QSvwR7hLrS3aSUX+vt7d1qg4YwjHfZIIdRGZT4ADx1XmyUBxMPhIAOa9dG60CD9SCPxjPNl9KwUUbNCoyxZQPxTmwYK8sUrlEcKX1KxspR2vu+6WtlFMuaGnb1b9MfTJAvOXkb3rHPwjr6zcnTnDVmBCojYMSAhQTtx7Rm2q8Xvn8rFvgLKosQ/VElxLK2BW22GNSiB6AKjn5BfQTdjJwfVbA330WKu/L5zrpDfeDZMtu8sHZzwMvvBciLs8huKZMnHTxNW/Dx4DfQfBxl7fGC94QvCt+xRkev2GmNLOYEaRRF72fz5s2jG2JuDjtjlLXxavNDj/wI10RzYCZEqq1N6EsbM8p0HN9xMPAl43kMDxcrcyAFPofDHugTChcdjU1x69bHHhzdbE/L2rVrd6Aq4VshkW+PVBFKIsX32he0Py9CjsyKEbAegVANFNprp62l/adI0H4XPK6WWay9p1Le5yyWL1bRBr2vhHxrrEIYZq58Vb/3FWSEd8tsw6K6QB5ejfLHe3KnuCAveRkxFwt8KVZAUTKLrHKThg8SX6k3l1052kHaIcu/MG5jkLFOjZHi6AmNE7/mlMyEhdXGq00PP/JjfFB4C7ynAxtvkA9njuswaaP2nnx0RlTpb1DOYzQUmGIxzQasoYCM+C1Je9qrh9atW9c/QmXrdlGVMAeHiMutEywagSaplLgOH4waomHHXBgB+xEIxYCFHDgHtLa0f9EviH9iMfFGqB0KXbPwqVNbm1tPNcvDTer+gPgqJCd9o5QpdUMYs4PFwuww6BCgMVf43i93V2UkoI3DKujQbczFn6HCFIfVqFb0DTv7ttvjfbVXailW7/1J+S/uf+9CuNqZlHV0QTe9sNm88ZGf4MPhYKgJ5iWwAYtCWDw8o9ebnDcp1VyT9COmvaO395ZHI+bpFjsCRt3ygLvjfTfhmXEfRpHfe8vrQvcI1tbHj2ucwLkn6U4xa1YjAnUZmnQlIhiuPlzo9/UNBTcW0VQj/3i7S/ldDoEYPgVYjJyMF1jSCxI8CNajWtnfhmseeI/Ul9jAKOweeNLDD23+RJ00eHgdCKDa4OkI3daeV7pqEvlNCvUBHV5gm6KoHnSzbTKZkgdeqFdzSL4pdMemiypV48c3Tbphz8fDwQFKpYJ71CiPwjMtuAFvbMgRyETKgKXPFZw+vJVFgFbC/uFqKhH8XjGckvG9m+66absnpC4ulcjzFbk+P8bpOoyfZszAEQQCGbCOOeaYxtaWRe/dMWmXfkn4Iv45+qVfzhrfNPESR+bKuJjz5y/eH4uRK4wzipkBFr3XhyHCHnfeGWHQokJDP2BbWxe9ioo+LumRaW4/H54Hv4bMpHNe7ZsTpTq7c92/2rdv0Y++QuMfIE5SSn9PVin5x+bmE/heGPE5CO/3/VKyAd6Waqg3ebGvb8uDAUWRoDUr4FiLhvlGF+WkQspUHd56Fs24QVGIXBNlEKrHW7MMSZPNXbmuVbhH/dAkD4tp63Qd13K6DotniEWLDIFaDVgevvCfM23K/vfgBqJLlk+PTFJzjD7MyfEGwZVN6YFr8Oswc1BbQVl5RRnKw2/8+PGHQyPS1d0CzJgniurngwnEAwzmIYEQ8FA04wtYVH0fo5NyPhalL94XCK0IBq1Zc8sTeEbmI2BlC4sZKVm4QXsD2SIQdTmQq/LwwoC/Gnq2DdUVrgkb4JU4MLSt2t8wQh6Kvs4bwOsKoawKLDm3qm4udJLueODEAWfHgg5tmHf+miiLnYMGzIFi/wehz4ayOtE+cLhQHnlHA9pTyNqFgUDVBiwdWoZF0l/xhf9aCjkShoA3TifH015lQ9oS9xOhoB/Fi+/J5BWX6pau3q7/hKGnLEoKoRZhQDGchhQTkUD8j20L2146/ADvhY0AKr5OzrS03wCH+kvDpm01PRjrunu777JZRhgUf2+zfAZkm5+WDb+FVxDdxZ4B0IKQHCzSUBRrcN2XqqYc2PsolfJJPNM837hXEQmcBs89Bw0YQa6ZoGMG0rQS9o/EQXle4PvFSFpR7ff29m6FJ9L5UfGzjg+KpGFN/kbr5GKBGIEIERjTgIV42/kwbqxCaNn/lXlZilBcM6xguDl+vykHfNYMdfuptjYvOhtSftp+SeuXMMwQSd+Ts+uXiCyFqcqTf2pu7ngBWQ1jVkx7jqLia68U4vSYRYma/VPpBu9TUTOtlZ+S6ne1jnG9P56lSwp9/g1Lly51Kx+mQ8APPq99rxPvYweXEhvPuPtLtVfV5tNYrKuUCo7BGEDt+dipvXJobCl3knjHAzipfGejIFSq3zkDllYim129Ave6n4xSKCEN0P37eL8+IiHqspqMwCgEyhqw2he2HwWPqxtg5e7FqJePGkmsAVVl/ieTWbSUmFpjqtPa3PFKIZV+CGAdTHyTYvOOvh2hLSrxAJlNHLF61Zuekv7N8BI6pl5CPH44AljELvNT4na0HjX8SBL25KWdnZ2P264pCkX8GzLeYbucocsnxdJtW7azEStkYOHZls40L/oyntfXgXRZLzfpBTdIEMnt5E+ePPmBkOHfR27/SfvPwg6ZUG3fl8aMfftAc/gH3vPmOCx+ZdGV2J7L5R6r3Mneo039jTqNwEZ7JTQq2aSU51/Nlb+NYszELUZglAEL8d6HwePqCt8Td+EL36stlj1s0TxUjvpFkqop7a446P8GQDaEDaaV9JT4UdDcIKX0gcWP7otNKYWDtR0GL6FuGIeH5WkJRopH6RxDuD9/C4tYXYhgagIRubUnt/oH7ugttbEhcZtCOPozW7avamtro5AnM/b50+9lhf7irfjQ9iEIg0dPhU3VkcCcRnW9h1esWNFXAaG6DimPlkdOY6NYXxcg1AdLwu95u/Of4Xbt5rZy7cotQvnvclP6EKRWIrP54Uc/GgIlJsEIOIfAPgMWFkbP0V/3CilffzXWZUrTzmlTv8BTkA/r9x3Hd5R0za+fvD0UYLx6Hb4s/RYSlf2Sa4+0oUji+yId6sIXiWJnhyIZfSLTYBy+GQUgXkNfVXMaZjIdL0PFsTvB4b3muFhNeQeu4fMgoTMv3DLl/xzyJqUa4ciTp0UVZQ+HOYyEpbZ93DdPwXvZX2G3aq1mJAwsgT1qiDzTAutfDb5CenOr6udGp0fgzbrNDVFjklLRMlgORRGWcLPXylBmhn735HtuxL3xF4bIW09WKfXxlpZFzdYLygIyAiEj4M2bN29Ca3P7pVgY3bvn617CqwjJWYUG/w+6PHXIWNtCTsKD41MwXumFVTI8rzTyUvwul1v1QKiTwCGEtcDZhAIQv2hrWXTJ4GzUMjLhfXU+od3XrJ8DFM9PLhzyI7iG73VJ/+7u7k1YJNzikswhy/r8tPRva29pbw+ZLnlyCxYsmJJpWfQD3Df/AGUPqFZhKYOHEILHnGr5WNtPml2U+4RCynBvcjL/UbTnHqGKkyOBI1KBsr+QvgiqPTJSvYTspz2lrtPPi4Toy2oyAoMIeOOaJvZgcf8F7FE12ASZ6pcV+v2bUelnWpDBto5ZcuySiahYthzyfRL/8O6SmE2hKtFnwtR2T5LiQ8KkmQBaKSXUl1pbFv1ee3wmQN+6VWxvbm955untOo+SvmaTY3AegRxuVnmEDn53RLMTu0rJq50Q1JCQSoj9fRjxYIT9KOfrqA7klpb2JQ2ppr9Lod6BEbU8q5+B0TRQThsyycnrSWJfzfRIOh458Lhz3gOnmikL2mdPRVWyERl4NpGY/zVrbnkC53JSPdP1E2JOQ7rpO0HPcx7HCLiIgIcXpJtdFDwCmV8mfG/l/PmL94+Al3EWOrfXjkl9umLZWcaZ2cZAiRu78l0IwQhve+aZZ2aB2r4Q3PAoJ4GSOlWHwmnjTBK0DaKj/pqmc135UnTj5eToIDQIjemTvng79IEdxL3tqa2P/xpzuNk9yUOVWKck+Oymhzav1PmcQqVMiBhyhh3S2tJ2DR4sf4JaM2tWrQ6DxLRp02aDn/PJyU0bZfAONafmebF1gGIPrEpT09cnZuM43fc8VSTjgZfNdl2PjyW/rjSfpI8p8eY9FeVJq8nKMQJ7EYBjSsOV2MF1z1sJBF7amO7vxUulywtIhAwueqdKyTym+ZgSOpJv8qUM1ftKA+b73mzywJlV8HAYZzpR6fQLOjG5WVZOUfcQ0n0uvC/ugdT6iyLdl+eqp0X+b9dtXf+surtlHdetW9cvhQw1/55lKlYvjpQdxZR/J87xN1Q/iH5P7f2UaW7/IHKG/Quf098EjWEnCbCpOsIHi+m5AThaNwRuvqa9SkjgNDhx5rGy7vyoRSDP8+nMdQnF68mXV4Jc7E1eSr0bQgTyQI1d+DAEkOryjoUds8MgxTQYAdsR8AZziii12nZB45NPPhcvlbnW5o5XxidDMM46eS68OOBhp64AhQnBqDg+SokVudzq28PWAjnE5oRNM4H0GmA61/n3/tHW3PaKBOo/TGUkaV+I6zWLpeuPcIDDUzU6uH4ROviNYUA5uJMqSP2hqOCg6KGLjK9l++Mcvw7n+k2c4F14KKjy2mlTD7hLSvEVgD25HsBVPQYJKqFxaXMGrD2h73TSbaQ8Mh449Vw35cbC85fye57atWuXaWNvOWiNtOvwaUQVfcAIcTeITi14xWs5VN+NyWIp60Ngz9d9/jo8BoxThfRvxAv3F/fkPhqje7yHtUdLW2bRp1PS/zskWRyvNPFyV573aRMSeELOMkE3oTTnKin/1NbS/lPknas9bMZx0HR1QXik/FEqH16SYqHj6oQp/kaZVm8BQdg83N46ezsfglPNb93WInTpT9LPKDyrPqGLyYRO3W6CEoarM/FOcSc+hvwSp/iRoYjr+XUYJEjkdurv6uraGAqWJYikUilSBg14kpMyYJSYsvqakFuoPgIWj5bikbVr1+6wWMJAonXnun+a7GetbN208ZFLA4HHgxgBhxAYNGClm7wbpBBPOCR3HKLq3BAffmbr9jVYZL84DgGq4Omh5PbrPdlwty6tiv7jqhhDtgvO6Zuy2c7bTCiIPBt0X2xMAFYFTVgp3oi8c/9BWOF3M5nMoVUMcbpL28K2l8Jo9zsYrtbAI2Wp08qEL3xReN45QRNShy9O/RR9Ib5cPxVyFMbhWXXZ+KaJ/9Gh7kiarHNlkd30BzA8o98KXf8Kw5XO1/KiMJX16vLAEhTCpR4AnrjUDG3FFAWM9oIzMGPG/jCs81YWAUnimiitHuH8ZzLlXwClnyqteCJaP6U9+hOhKSuZWAQGDVidnZ27sHiE1Zq3MRFQ4lgssv+CL6dXLFiw+KAx+0fTwWttXfQqVBj8C0pu/xyGm9nRsLWai+9L76PmJFSMsRlwG+Fvc6FUqf8imfHXdFJjM2xioyqxgD0F1+otypNrcd89DZLgkuVtBAKf6enp7BzR5vSuDmXGRN/ktBLmhIfBWl1R6Ff/0B9hqBmy9H0s09x22TNbtj+IZ/RV0NXIRzDp15EDS0nnjTO4vu43d4qCMpUwS62KEA8sX768aBQv14kTuCbKTQHuQ3V4a5ajakc7PnxtwnvkB+2QJhYp0vgwep0uBhQLd2bKCESAwL6vnUoWf4BF4/si4EmBhcbtnQ2pgdch/OHLwO7ynp6eyK39J847cequpoE3CqUuFL46mlfBw06tq+F99ZdhLWHuSDHb/cCmMAEJnRYSu8sPqKJ4D7wVfucJdXlXrutWcIHNx71N505JiYY3YdVwPhQ4iq/VCnOoVOchhx382Qo93D2k1OeFlEvcVcC05OpI/RFmoN//Aj4SfX9cX+P3V65ducU0VxP0tbfVM8/sWILn85twHztDStFggs8QmmpADqwfsl/jTzWnxgH2dTftVaI9r518ApWcKrIGjJLaBmokcE2U0Rsl6O8vc4hEc0++68etmbZlQknn8heHNAFzG1KN3wStc0Oix2QYAasQGLaOwgtjFtK1WCWhG8JsQzjA1SrlfweGrH8bFhlJXxdlpD+YG+b1WBBPNMzPRfLPpAe853fe3rnZhPA6XwtCXraB9rDrxwQvpjkMgXsQbnSF8Pzrs9nsw8OOWLijE2lu2vDYy0XKfxsWPWdCxESH9FY5RY/gg8BLXZjfKvUZ1Q2ehd24dbSOOsANpRDQH4au8YV3dS7XeWepDja16WqC06ZMP0FJdRaSCb8GskWZ8PvhnlzXjCB4wENsOorVPBpkrGVjLgUGXzIlE0K+/wz7FQ0DtBRX9GS73mUKK9fpzp+/eP/G9MDjrutRXn55LgqkXFX+uPtHmptPmJGShX9Akyjvw1YBh+fQ2cgL9gurhGJhGIEQENjngaVp4UT/Ab5+sgGrdmAnISfSRQgtvAhGwDsw/Pqi8n6dz3f+t3ZSo0doN9DGVGMbXpxOxyydji+6B7LpZDROQ1o+Z8p4pXlMbJg4C0k22Hg1BPCIfr5ASvkNoVJfgxEghy9rv4Jx6DcwGj8YEf8x2egF7H77HbAI7tvLkEjz1cITBxD6Yj+m/nV26EMOnzO7cvYbJ+vRU0nvE1KpVfXQSNDYadD1fZ7w3wdPzL9J6f9EpuRvkajbGu8BvdBtaBhYjHP3NDyjT0EKpv3ieTiowB41+DCA8MF4pA7zXMZ7mOnzwvkwy31415MvbR8Ruj/S6QKduS4xTXhHCXy/KEHOyqZ8ftXGTKbtI1LJy60UMAKhsKa/vKXlhHwut+qBCNgxC0YgMgSGGbB29O24Hp4l2uVwamQS0GP0Uqj0UlRX+iKMWQ/jnTCrfJWTInWPSBXue+qpp9avW7euv5Ta2mPjsQ2PHY5a60eoVPEI3HSPQz9tUDwaL8ZeqTHcNgqB+yZPHTyHRx0Iq6GYEnPgccdbfAjgWoAHixStMBp/E9fZP5VQK6Xn3TxuZ0NXxCFH8IjMHCVVGtU+FcKFRAcMzPCKdH8xGPX0YvF5IcJEc1HzjZpfNrv6Vnhy/BG3kJOj5u02P/VipeTXVUF8Hdf8P3CJ3QhP5D8VRGFNPp/fGZVuOhzY8xoXwAi5CNf5iUIMHIfrHvar2Lf7g0qA3FlzLJA/qPj7xuH8CIzBPiJlfgx61G58ZGaZw+41K7o5kMKYDKnznVG4KMqAIRuSMf/ZbPcVeF5oD/iTykBBvXk/TxSuxf3r5ZzzjvpUJ0u/YQYsXVIVFcB+ipv2hcmCwZi2hwLLZfAaWTZYGMf3xLSp+/u4meqcHtux4O3DC/AAfuswwEnw2JgKM9WgoQrGK2NCkSas5AdXrFgBXM1tmJvZjqZiMgdKvJSRU0oehTxw79nV1K/gqfFvvHfejgXmX5Dn4e8iLf4Dj42HIGJdr6NILD2uUCgcqZR3JIxULwbPBaB5PKgiUeYe0nzZBj0Tvp3Ndv0o6GDXxqHE4ofhVfQKyK2r2/JWOwIvxCX3QiXlpcgtN9Da3H6H9ETeF+Iv8NK6J51O/wvFaXSYd+BNGyw2bnxitqf6j4J96gXIXYZrXulr/nm4/vfQ3fs3MJsQB9axIJUeFus26RIMlsZGeX+wkWOPwrlwGF7OGsfu6UiPVJG8B049MyF95Duj+zzvP+igg6xPw1DP/A0Zq9K+986C5/8dbZOGtCfpZ9umhx75EBT+YpKUZl1pIzDMgKVVlZ76f8iFoEuQ0r11xzun2kClwyLwjyEOcyqA5h+786t/EybNUrTwnj8bCXl5sxMBzIw6Ev8dicvrHCxohYBLI4zG2kPjv6gitREL38dghHocubQegzHSR76aLVJ5g12xiBuPceNgdJ4Ir67nYMyh+Hcg5nxGod+fCUdI2MT0xifAIAxh/CfVynRD6n/CIOUKjVyu8x84J38Cec91RWaL5WzA5bgA1+iCwatS4Xtzv6+v+QfRvgGhxo/hnqAXazrH0y4YnrWp5mmtj1L+BFzrTbjWp6B9Iu4Nh+CwvuYPwQclbbBowkvRnqvdcgNPHQnM4SU+l8AtbSuMlsZyFklZJOWRUywWjRn79LXl/CZhwKK7rU+SN07nbZ3r8WETVcnVt+hO6RiaSfGZ1tbWW5Fyo3eMnnyYEXACgVEGLJQfvRv5ZZDMnZPMOjGDLOReBLbKtIgkISmMV5RfbPbiSe0vqhqKF2Ex+yKtGMID8C4zuNzFelX/3bM43d2Ehe3wxeqeZj2UtzARQB6WdGPqbCw8YWZM1lZU6U8gwSy8c8XkZGkembYzcVnD6Dz8Woaxap8AMF4N/obxanfb4B83r3blyfv3KVbrDynm1jrEuv5SrDcrk84TRmbbgrDbJ8loY0KRwRBCN+8FVcAR/F5RBXEbuyBh/XczLe0oriHabZQvApnSwpfXIeXFcSiS80wE/JgFI2AUAXxgLLElOOFdCTS4yQEEYG+4BGFiG6IRVc2Ohg9zYQRII/CUTKtTTXpN2IyeTjAL+S6zWUaWzR0EfD91Xx3SPreOsXYMNZzTCd885tihaP1SwIRbz7lSvwAuUCA036PhDl7wYTQtZ1p86fnnQdrI8iXah4x8rlDpr9snF0vECNSOQEkD1lNbn/gVSFEoqVw7IjzCOQTwMtaVzXddGZXg+IJD5kU2KsyYDyMwAoFdyF90uvb4HdGeqN10o6dDGu5MlNKsrAkEdsEguikIYV05FeNmBBlr0xh8xDLrVULL85oNWBVOXp3/Dn7aMyt0cfoQHE/NXiuWooPwuX/jPvEJS8WLRCzkcXxHJtP+2kiYMRNGwCACJQ1YukoewmoSk1DXIL5M2jwCu/Z8VYEdy/wG99vJYLS/eU7MgREgi0ARL1HnoBpfN1kNq1RMh04iI9P56O5XOYS7MQKlENAL0kDn0LRp02ZjLBbsbm+e9M0uyhWBMMu9U2zYW20vG1f/6mrgkL3BVfnHlLuOfHlj0ra8Az52fx0R40iTk9wN3qTfRz4ssgba5M5ssjQvacDSEBRE6nv4058sOFhb1xBA7pJP6q8qUcmd8lOzo+LFfBgBigggaf7F3bnuX1PULYhO3fnuNcjTxB+MgoDHYwYRgFdwYOONLEoSHsXIWxgYgypPo7lV9rO+GyqRmMbKegwqCeh7Ppm5Lqmnn+j594u+9w7gsqskNslonKZ879rdnobJUJi1pIdAWQOWzs8BK+3P6anMGpFBQKnOg2cc+LUo9Sl6HD4YJd7MixYCWGR+Ipvt/i4trerXBsUw/0cJ00mo65eTKdiJAOpQBDdISI/EYl155gxYS45dMhEzf6Cds1+7VErVkfC/dnbOjYCLMAmjbjngU+PqypdXjqwz7fl85z0o4PEZZwQ2ICg+erRvfnjzBwyQZpKMQCQIlDVgae5F6X0Vf/BezRsjYB0CjynPf2PUpYARWjvbOiRYIEbABQSkuCKb7070S2O5adJVgaTnvQnHi+X6cDsjUBaBekLCdLU19ze1a9eu4Ea8MfTfNXEXBYye1TJVuO/ZHf41EgF8vKdswHoKoetPj9Q5afupBvll6PyXpOk9VF8Ysj/X1tw2f2gb/2YEXEGgogErl+v8BxS5yRVlWM7EIKCEJ9+ORd/DUWuMBJCzo+bJ/BgB5xGQ4meHHHrQhc7rYVCBnp7OHrxQftsgCyZNFAGp/MAGCeWTyO20ee3atTtMTS/CnikZsPzJkyc/YAorGnRJzfeIKZGB7xUjCDm9O5h/sqjeDiWSnCqnQUh5XUdHxySnJ5OFTyQCFQ1YGhFUioo0RCuRs8BK14QAFnnf7OlZ/YeaBoXUWXpqdkikmAwjkBAE5K/SDd5bovaWdBFcX/R/FNWv1rkoO8scHwIqVUf4nCRhwDLmfTU4qzQw2nuCblyxYkXf3h3+WwoBGnnhSmkmpGID1h5gunu778LPL5TEKSGNCLE6ojDg62gr3hgBpxAY04CFSlE3I1Y275RWLCxhBOTap7c+fmlsCtJ2LY8NVmZMFAElbkg3yrP1106iGoaqVj6f3ym84pkg+kyohJkYaQQGBgbqMeAQ8C5S95qcYJ/Qcx8L1nrOFZMw20SbwDVRBk7zxQ7KMLazOd3ofRaS3WGndBFJpcT5rc2LlkXEjdkwAqEgMKYBS3PxpfxkKNyYCCNQBwIwpD6Bxd1r161bF6fL7+w6VOChjEByEJDiNzv7t7+ejVe1TbmuqiqFemdto7h3ghF4rLe3d2sQ/RE6cgDGTQky1q4xZsOipPDm2KVvPdKYxaoeyWwYSy1h/0hM6yr4MJIYgX39fuILT4cSDhBQJ7gKUv2/TCZzaHACPJIRiBaBqgxY2gsLYq2OVjTmxggMQ2BAed5rsLiLzf35xHknToVE+w2TincYAUZgNAJKrJg8ZeLZyEuT7JfC0chU1dKd6/4FAvh/UFVn7pRsBJQI/EwsFArPpQCe8UW5opMTyaunYiWFk2UMHcgl7B+hL1JwBL5fjCBFZjeX67wTBZqSHkZ3gFSpqzGpVdkFyEw+K+IsAtWfqJ73MWe1ZMGdR0AKeSGSHHfGqciOpgKhr7BxIsm8SSOgxB+e2vrEGZxnpb5ZTjem3gsKyQ5tqA/CZIyWMnBImPSp5PoxuijH64eYTeZkqiPhPxkMKihS9EhXIBRKeWzAKjH/k/abcBnnnxQntbYsurgEPNzECFiHQNUGLF0hCRf3r6zTgAUij4AS6jvdudWxeyN4SrEBi/zZxgrWh4D8BcIGz4o5zLc+FSwZjdCGXUoWXwVxHrJEJBbDQgSUqKMCoZAkPLB8P2VsUd7W1nYwpn2ChVMfTCSfc2BVBM6n421XQk9/v/3GbyjRnvimwQ9uXlGHEhaTDYb6fEtLx0uSjQFr7wICVRuwBpXxih/GX65e4sLM0pHxlobG1AdsUEd6/mwb5GAZGAE7EVCX9+RWv5HDBsObnWw2+7D01emguCM8qkyJEgJ1hYTRSE6+K59ftcnUnMoCFS+13Qj5KT+wx54pjG2iKyWt+R6OrdrAntHDERm6hxQlvdj/5tC2BP5u8oT/s3nz5tEx2idwEpOgck0GrN35h9S3kgAM6xg/AkqIv47razzLmiTQvpwbPyosASNgJQJf6sl1XwDJfCulc1io7tu670BS9zdDBdwSeWMEhiOA3C3BvY+koPBM0wYZY/cdFDEi4aW256zZBaO4MWPf8DPT1T3C73mKve/GOisnT534UfT551j9iB8/avy4iV8mriOr5zgCNRmwtK47+3Zchtdo/oLj+MTbLr4U4r8NA97JK9eu3GKLrEgUyyGEtkwGy2ELAj6eBxf35LoutUUginIgqfuvodcnKOrGOtWJQLqe9zES4VLBDXhVQC9pPff1uzsbwivPO933PFmHsbsyZmSOag81X0gdSmjMKO4EWEpckMm0n+aErCxkIhGo2YCF8JAdypMXJhItVjoqBDamfO+kzts7N0fFsEo+FL5WV6kqd2MExkQAOZrEG3ryXeyVOyZU9XeAkfCzWHt+vX5KTIEQAgXP8wLltEGISAPymh7mOhbIkWnUgOXTCLMcnGZ8GOSPz5VPeEBEOtcpz3/l+R88msutzuO+8r0qulLuIqUSP0QOwEMoK8m6uYtAOojo2ezqFahUgITu6jVBxvMYRqACAo/LlFrSmetcX6FPHIfwYiNmx8GYeTICtiGAi+EJ5XlnZAeLe9gmHV15EKb5wdaWtmkwPLyNrpasWfUIqAeChthPTE+cDReDVPW87OxZVw6wqlQi4aU2qCk+OLABo8KcdxzfcVBB+GRz//D8V5j8EYd29e24dELTxKVwVzxixKEk7U4XRXk1FH4l/gGKaLbW1taZQnlfDZObLKpvIR1DdijN9pb2dl+Ki4a27f2N3KPf6853r967X8vf1uZFZwtPvbrUmKKffj9yNm4sdYzbakMgkAFLsxgopi9qSA0sws/ptbHk3oxAWQSehuvuybnurrvL9ojpQCaTOQS37/ExsWe2jIBNCNyjPP+Unp4uo54PNilskSwKYfznj2+aeCBkOsUiuViUWBAIHhKkPG2YgSna9U0Jo/chIETH85rTf1Q82/20T2euS2iq6smXV4Ie5SYdbdTa2nGe8P1V0JPAjTLYbMFqtaS1uf29UXrae0VvKgxLy4JJXHqUkt5vcGSYAQvrzVlCqZJ8lJDj0D+QAUtI9XGsF48qLYn/idLt3ForAl6tA/b27+295REklj1v7z7/ZQTqROApqdQr4Lp7e510jAyXsoH0i40R0JgoPQSUWJFu9Jp3F/Sgp54LGukqj0g0exbeqW90QV6W0SgC9wemLj0Sz7SiSN0bGIMxBi5durQJXQ4do5szh9kDp/JUFT3aeU6LxbRRY29ldN072tPT2QnT1ZXuSR6yxFJ8CV5RLw6Zqt3kpDi5vb398FqFbFvYlsGYMsarWqlx/0oIBDZgaaJILPs7/PlxJQZ8jBGoAoFHPCUWwV1zTRV94+lSpP1lLh5QmatDCGj38S/hK9ypCFl62iG5SYqqE80+teXxs/BZ+PckFWSlqkOgHo8aSSM0rrFRrK8OrNp7bd26dTZG1fWeXDtXcyNSPocQVkTXp3FNlNFxBxwPHi1zjJvLIDBQ6LsEhx4sczgpzU2i6P2subk5kiiUAeHtxAe6teX/iTtHAy//Vb6/XCuF/+ToMRVbUn5BvKVijxIHkSP83BLN3GQAgcAhhHtlwdf49xX6/Rbsv2BvG/9lBGpA4EGvKE7s6u36Tw1jou9KqxJR9PgxR5cR2AZv27fuqYTnsh6kZF+3bl3/Mcccs2za1AN+ifQUZ5BSjpWpCgHlBQ+fUz5C41wPjJFiMwzq26oCK0An6TfMEdIPMNLOIX7KX2+nZHZIRazi5EhQtfeV/hDFWw0I9Pb2bm1rbjtXSXkzhrl+x6xB8xFdpTg6JRq+iNb3jTgS+m4+3/lfEH1ZOcILFiyY0pBq2jL0uKfUuV35rtzQtgC/d2FMAf8mDY5VQhujPo9/VT0EkGpmMq6w1w6O3f3f4/hzwJB9/hkiAnV/WdIvD0i6jXAGYewlIkR9mZRVCKh7fZFut954BcxQjWOOVdCxMIxANAj80xdeMxuvogG7Vi7aiAVPrNfhrRpGLN6ShgBy2gQOIUQ4mfPPNDyXA+tfzbmCMlzOYzREzy0I/X5qyD7/HIkA5fc8w9fKSCgp7SM65BbY/q6mpFNAXd7T2tx6asCxLgx7BgaoZ9+l8IzMZBYtrlZwT3ivQ9/dxi89SIofVjuW+9WOQN0GLM2yu7v7brwMvaN29jwiwQjcNlBszORyqx5wAQOc33NdkJNlZATCQ0Bdu7Nv+8tyuc5/hEeTKYWNgDZidee6zsYL9pfDps307EZAqf7A+Z9g9HT+mYYkvIH1r2ZmlfBnV9PPkT5GsXIEg8piSun8NVFWQRncW7MszQQdGNfX9H6o+1CCVC6lqhTS+zGqdR5c6iCFNl/KHw3VA9UIq7Zt4IPS2/eNVWI7vHd/sW+ff4SOQCgGLC1VNtulrZZfC11CJkgPASl+htDTl+tCAA4pR+lLrEOws6gxIPAMDLbn9OS636wr8cTAn1nWjoDCfH0YXw8vxtCq3N1rZ8EjLENgaz6frzWvx6AKHR0dOqxhqmX61C6O8nVYlLlNydnmiEdLWQmz3mrRahM+t3nz5jWA6ozwKVtCkT2w6pqIlWtXbkEqhXfVRYTG4OmFxuJVUAXfQOhtudzqPFT72z7NpDijpaVFV32uuDU3d+g0Sgv3dZLqes/ztu7b5x+hIxCaAUtL1pPrugSn9G9Cl5IJUkEA71BIBJ3tOgehpzrW2IkNL/vjICiZSkROgM5CxoXAbchJNw8fJK6LSwDmGxwBXeoaL9lvBAUkQeWNOAKBjTf9/TRC4zxp1ihDKSeSaaxcv9YmpifOhg4p1/UoK39KBr5flKWZsANIpfB/sNrwu5GSr2xtbr+A6vQr5V89RLdGT6TfNGS/5M+ULJ439ICnJIcPDgXEwO9QDViQzy/6A/rl+TYDsjJJtxHow8LqzTByXgo1tCHLma2vT8yGsGFfK87oz4ImAoEBaHnZITMOanUhJ10iZiSgknjJ/gXylrXgJrs+IAke5gICKnhIUEr4z3VBxbFkRDyL0UU5rqHZY8ngyvF68qW5omM9chZS7ueEq6S/78v7Kx3nY9Uh0FdoeB8cNTZX15twLym+2rag7ViKGiK9zbXQa4iThdTGqbIeZyim04jD5wzB4h4klIcnF28mEQh9UQ6X9p1I6n4aTBR3mxScabuDwOBCyvMXYWH1U3ekflZSz6PxtfpZjfgXIzAUAfk3WVQvg3H5U8uXLy8OPcK/3UQgl+u8s1BsgDu76nFTA5Z6TATq8D6CMWP2mPQd6OAVPWMGrCXHLpkICKY7AENVIiIsnA0YFZCSlBO440EwaVsjz3+F+a/20Jo1tzwhlbqo2v6E+41TaXnt0qVLm6jpqOcYl8yQaDJ1ZGtrR6acns+Z+pxX4di+MEMU/7gS+1j68mYSgdANWFpYJHV/rCjSSzB9fMM0OXsu0FbihoZG7zhUv+l1QdxSMlJ5sUE4xDehH+c0KjXJyWzbqaT63519247v7u2+K5kQ0NVa5xh8asuTi6Hht/CPX6bITXVw7yN8Sp5FAI6+zt7Oh03psW1S/xxTtOOgyx44lVH3hKRwTZRT8tGb7rppe7mD3F4bAoNVmaVYXtsogr2VOHbr0zu+QFAzhNwMDwGURb9CMnd57hAM+jHYSWeNITo48dOIAUtrns+v2ihS/on4+ZATSLCQYSOwC4vjdyMny1nId/V02MSjpafmRsvPCLfik08/8WEvLV4I6n82woGJOoMArBldReW9NJvt/gIStevwQd4IIqArFMKz7mLhydNhtMBXRd7IIKCCG7Bw/VNYrN+PufRNzaenCrNN0Y6BLqa874EY+DrDUnmKwjVREm/c+415KpZkmIDGdIOnc0A9mgBVK6oIb6OLM5n2kyt2cvBgV67rVlw3/90rOjxYX9va2jpt7/7ev83NJ8zAzfUVe/cRSniDduJ5dp9/mULAmAFLCwyvm/uwYG7Hx997TSnAdK1E4B7h+QuxOP6+ldLVKhQB13LcYDfoxWxXV9f9WNC+EvnI3sQL2lpPBBL9H8Xcvy2b6+rI5zvvIaERKzEmAj09q/+QKnovwX2ga8zO3MEJBJQ3cH9gQaWcGXisLQMNe/hLKefYomoIcmzW6T1CoEOZxCzCyrEBK+TJxYf5x4WSuupv0jfYsMRVCxYsPogYEMqX6sdDdBov/NTZQ/YHf6Zk4a34sa/4g1Q+J28fCZKhfaMGLC2zXjCnB1KtSH/GISqGJtEisgXI8u0J28a9DMbLZ8uQWiRgIFGkpJDwdtgLjM5HVhSFo7Gg/XUgTHiQawhoL6tvj+trfD7m/mr8xtTzliQEEG71EAyXL8cXwvMx+xxO4vbk+1OmTFkfXAXlvAELH2CMfhjFDXJ2cHwtGynZA2fMGVEkvBJLqolz+f6SB7ixLgR68qt/jmfpDXURoTH4wAZv4Cqogtsyna2hP6V1ejZCQarzR2iHzCzirfva8FGlO9996759/mEUAeMGLC195+2dm/sHGk7AmqnHqDZMPEYE5N+01xW8e95HL9be/STu8LoZ9bKfy+UexYL2NfiK9FqcOOzyGuPVY5S1VCuVLB6nr82Va1duMcqLiduOgN+TW32lL9MvhqCrbReW5SuLwMYV/7+9ew2Oq7zvOP48Z1eyFWwuNcQxBlt2QgrDJQUXXEuWUW0nbZhJhyQkJWFyaVImM70lTae39E06nV7yprRNO8y0kzQkaVrqdJIMJG6AgCx5pZggIBS3JQXsQBIMhIuDLVmWznn6e2SvI8RK7Gr3nD3P2e/OaLR79uxz+Txnd8/+z3PZvXtqwWcXeeKqq3as0tMrF9kliKecten+KC9QDyxWIFz8kN60aVOX9liz+F4BP5tyb8WAZZouenkm+k0l8nzTCYWegDVv7e8fmB/gCbpWPnbhjPnGqUpozi8NI9xUfdzff/Wgnn9D9bHCd5/R/eTUY+6kKpBJAMvXwM/q7yeUVVfDW1KtEYlnLeCj05964fCPr1Kvq/GsM087v5Mn+6ennU/a6S+2ApGuIu1KzMwlztgvqhz6POZWEIH79CPvLXsrI2+uVCr7C1InqtECgdHRux9bs3b1DvX9/7iSe6kFSZJEhgL6kD6w1OyWRcfXL/W1eXqdhmq8rFdxq8vmnOltdZrtSi+ySz9e2lXmLPNd2bVyrfI7NQwoy7wzyauU3mqdmZQ/x5nMBjms8d+jHX+zzt60bcu2S4sEMX9IoI2jX6/WL3Luw9X7+j8Tu/Ln5jzmbsoCmQWwfD38HDwjY8Mf1OTen9DDOOW6kXzaAs7s1kTQl6lnxx/5tk07u3akXy7PbGxHvq3Pc/EJf0/0xtrzvsTYzcr73tbnT4rZCdhHfK86vS+vqlT23JldvuQUksCuXbvikcrITTrpukg9//8tpLJ3ellr9ait18TZqBABLF3nTjWAZY3ZUK9p3vdTMG7JAc+8160V5YttXIz3xIIYM6m+VxbMtkOeqFSGb3HGfK1DqrtYNZcn1nxpcHBw+WI7hfTcmvPW7FZ5n6yWWZ0BblD9VuzctPMMtfnbq9v1ffGN2cXrqhv4n7pApgGsam38ylcminbq8VPVbfwPSuB7xiVv0wqD1xR9Imj1UCjESayGENR1AjM6uuc76pnRp35Yv6Uj8oWgjsoOL6y+QB9Vu3243G0v8b3qxKHvV24ILC7gT7o0rPA9OhnYoUAWPfUW58rHs87etdSCOJMU4sd6qadU13faUpz8jxO97sylvDaXr4nsgVyWKyeFUu/zQrwnFuCcXrNmzQ8XeI7NrRKwsV+VMPAV11uCcUk8nfxZS1LKQSL+Qp+KccucoqycOe7edWzZ9A3a9prqdhdZJm+vYmT0vy0BLF+3vXuHhsrT0RW6e09GdSWb5gWe15Xf35mcOqofyHtvbz65/KdgE1OIHlgzM+W6T/b9B7aCk/9Q7o7eqBjIX6uVjuW/pTq4hH6BDGff+7q1qy9Uu31Wq+P4xRS4IdCQgJaNvnvN2te+SVcYfRd5fvA0pJfpzveXl0X/vvQco3VLf21uXvmMPueOpFWaiWUzhbhwVfVJkogAVhWj1n9rivCeqFUzv+3gyR/hCz3P9hYIaJqGH1lj/6AFSQWfhHp8fnzrLwz6TiqFuJWTaN7cVk7nSHOGD1pzqFy2vqcWtwwF2hbA8nX0Y4c1zGXnyXk4JjOsN1k1JuDnSPlU7KYv0Apmnx4fH/fzXnXGzboiBLAO+znoGm0wv0zw3tGR3yvH0QW6QumvLhAYaRQx3f1HTGR/ZW9l+Of8ajicpKaL3Qmp+2NIwyE+4z/r1X/vj1VnemHmp+E1abv7guYrfGszQWpdhCpCb5O6L8gspfk0t0mRAljTa9eu+sFSHDrlNUXugaWe2QQvMzqQR0b3+PPkb2aUXZ6zibSo1y0aand2ngtZb9mGvj10UO+ju+bs36f7vgPO7M05x4XjKkaG/9sawDpZz8TPw6GD/RLj3FCGdSerVxfwVzj/bjruusDPczU2NtZ5K23Y8OfBcKa5uUKG9g39oDK650a9Ry/WKhtf0jFBIOvV3ztp7aHecO6fI2eu0Hty2969e25TRmpibgi0TkCf9ZPqzfdX6oW5TkfXx5Qyw/1bx9toSt5eF5DKr9cFhff7+QobTeBl+1vT+7LHIT6wzX2nvVqVbZSEb3Sqku4JLm6cwqh5pyBB3Zp10+d3qsHe2pl27FaXmLJfiY+FUYw5V0Pt/qkoR4Lm9vK9sGrd1OGs67O1nmBbugJ5CGDN1lAr2D2+d2xkuz5sP6ANzZ2gpWvWCalXe1yt14/kj+7b962nO6HSNevobBF6YLXkBEbv0e+pt88NUdm80Trz9/KaqGnGxjQEHrfW/oktuXX6Efuh4bHhB9LIhDQRmCvgh2kpkPW3Gjb+Bl1l/F09d2oy07n7cT8VgXv0w/o6H0Q8cQHp7lYN61yXSmmzTDTlH+WJC//C1anmYAXCUxQL37HhvycWqpy1BxZ6iu2tF9AKv9/X71jfe5mbcdcO9F19YxEgXnzxua+qHq+MTVj3Lb+qcxHqGFodchPAOgnndLL8efX0uPDkD2R6emR7RP2fPng/Nh1PnXfihLkDe1zN8Vb317Ienj9nU5h365zAvd7KDQ8PH9Bqor+tH1br9Zo/1d8rP9TrTYz9FhOY1NCGLzprt+v9+IaRyp6/GBkZeXaxF/AcAmkIaNj4RGVs5G/0nt+ooMq7lMdIGvmQpvmJOlTe7Gx8id7z2zVk/z+aGS443/Mtl73lNG0LfliHjsFUfzBoOfje+XbBPmYFwldrOo0OcoUNYLEC5as1f+uf1+/Ym5UqK0ALQRe+burv77+49crZprh///7jyvEL83M9Ob3K/M08zkAgbwGs2Sqrp8cL/gey7+mhDf+ovzgDi07NIjHW3aVJoN+t1ecu8lfb9+3bp5NobkmS+OBVV/ASUdKSHljzHU7MkTX8yRcOP3e+Jn6+3hlzt/bRP25NCMQnHO1Hlk91r9HQzfdVKnvuUXq4NoHKS1sj4IMpCqp8WcGVbYmJLleq/vv5cGtS79hUJvQL+lZ9B79DAcLV6mH5G5oQOJXVICfPmFxfBOXYRKn4nLIpwNQB1brou/lA9T7/XynQ19d3jrb2vPKZgmwpxamc/xVEJ61qJMdnut6jxLG35jTrSru3bdsWfGcAXVjyQyJPnYvre/u5008/zffM4tYGAd/DJLc339NDhftIX9/gp61JPqmD5e16nMugW24RFy6YhgW6f4ld6eax0aFHF96tg5+ZKcYwAtfiHljzj4iTVyZu1fZbt27dquGF0Y266vdePT53/r48rimQaGtFX4u3TiddX+7oIbs1ediYR4HR0aEHVa6PqKfqR2em3Ns0P9779Z3yVm0r5bG8OSvTlDH2Tl2e3uWi+Ct7K5VM5kzRanTr1XspZxQNFydZcWTZfzf8qsZesL6x3fO7t+ZL9OfR3BYU6FJbB/+eWLB2cRzT/gvqpPeEXzhJwdEtkSt/Tt+N/nuxk2/nxzNmWEGs7Sd/1wdpoQtLj2zt3zaqj4t+X4HE2c/v3r1b3+Xc2iGQ6wBWFWR0dOhh3b9OP443miT6qA6eD+sDwXeF59aYwKTcbjfWfmFy8sh/dtRqgo05ze6trqGvL8aJTTnV4RZzaf08WXr8+/r7w61bB/tMkrxL939Vf6v1x60q4MxRvQ/v0cPbFET++thYy+a3qebAfwQyEVCvLC0sYHb5vy1btq8t2fidzrh36oLTVm3jgtNPW+Elmeg9775S6i59VW4v/vSpbO4lyfF9pVLp57PJLZ1ckqQc3/HQHUfTSX021Ujnme9IMf1Mk56xU/dnmmFgmXVP2ydnyubdgRW7ruJamyQdufhSXTrp73RywY1rZi/sJqUd+l7058HL08+59TlYa0q6MH36UlPWd5+JY3ue/jUdUO3p6ZmYOWbePLcs3dPl/XMf13PflpK73HTpVDpRlBx/tdclrvyBKEk2+P2irvi7i+0/PT19qOSWnUrf77tyovvJxV7Dc/UL+GMquNuWLVt+pmS7P6iCf0gng8GPrU25AfTjwmqIoPnS5PEjX/NzmaScX2GS7+8b+HNr7CcCr1CsCZh72hms9HOJxVPxDhfZt+k49FeiNgZuupTiz6ju4wogD+kX/R1Hp46OtLNNllIBXoNAIwKDVw6+bro7vlZD435ZJxo79NoVjby+APv6OTzv1Rwgd9lS6c5y2XzbD8EsQL2oAgIIIIAAAggg0DaBIANYc7UU2d5sXPRrmvT9OmfMqrnPdex9aw6ZxHxdQwVu7znac2fKVysLy7y17+p/VYD0+pArqPfEwcro8OzVgrzUQxM6/mxkoms0tPGXVCbfFbeIP2yP6cP1AQWsNDTQDSU2GVb340yGCeWlnSkHAlWBiy++uHvVGau2JsbpPW+3afsm/XVVny/Ifz8U+BG95++2zt15PD5+D/NJFqRlqQYCCCCAAAII5EYg+ABWVdL38lCXwkETxer6ba/V9jXV5zrgv+/2eJ+/0mui0m2VytC4Hit2wa0Zga192/bp9Vc1k0a7X6uD4G4FsHzvh1zeZt+3MzNvMnG0VUPqNOTI9amg5+aysAsXyo+B/x+V/QFrou9oTpt7JycnH6KH1cJgPNPZAn41vGMrjm1WxGdAJyFXaaLpK/SN9bqAVGKV9xGtEHq/ccl4Sf+n4qkHCVgF1IIUFQEEEEAAAQSCFChMAGu+/on5sko7tcLeTp1o+jGoZ87fJ+DHE7rK+4DqtddEtjI9fWwPJ86tb00FsJ5Rque0PuXsUvRLvGoluxuzy7H5nAYGBs4xM+YyZ6M3KQB3qT6kLlVwSPORtf09/Kzec48r0HZA5flf9XDcr55V/9XV1fUYQ4Oab3dS6GwB9cw81yb2Cg01vlQ9qi/S8O0L9f73KxGf0UYZxdic5qywj+o791HNYfJwKbH3Lz+6/Lv0bG5jq5A1AggggAACCHSsQGEDWHNbdHYOnmPxZp0Y/6IqfKVOiq/Q834yuRBufs6qh33ASifPD0aJub+0rHQ/P5jTbTr9mFqppV9/km4u6afurPtEpTLyl+nnlH4Os3PflUobTFzaqPfCemud72V5jubYOVtBpdfqh6YPNq7UX4/+6pkoc1r7HVFQ6kW9vzQpsHtRaT2jz4gfKTDsg1VPucgcimJ3MFoWHdB77oj254YAAhkK+DNfWmsAAAu3SURBVLm04nK8LonseTYx5ysor/d+crYCXKs0qewqTS67St/pfvoAPySxnuHIvsek/171Q3qf12ufV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"})),I.createElement("image",{x:370,y:82,width:51,height:83,xlinkHref:"data:image/png;base64,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"}))),I.createElement("image",{x:342,y:60,width:51,height:83,xlinkHref:"data:image/png;base64,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The LIMIT a, b clause paginate the selection results from the 'a' th results and return at most 'b' results."),(0,o.kt)("h2",{id:"transform-function-in-aggregation-and-grouping"},"Transform Function in Aggregation and Grouping"),(0,o.kt)("p",null,"In aggregation and grouping, each column can be transformed from one or multiple columns. 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",(0,o.kt)("br",null)," Examples - ",(0,o.kt)("inlineCode",{parentName:"td"},"TIMECONVERT(time, 'MILLISECONDS', 'SECONDS')")," - This expression converts the value of column ",(0,o.kt)("inlineCode",{parentName:"td"},"time")," (taken to be in milliseconds) to the nearest seconds (i.e. the nearest seconds that is lower than the value of ",(0,o.kt)("inlineCode",{parentName:"td"},"date")," column) ",(0,o.kt)("br",null)," ",(0,o.kt)("br",null)," Takes 4 arguments, converts the value into another date time format, and buckets time based on the given time granularity. ",(0,o.kt)("br",null)," ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"DATETIMECONVERT(columnName, inputFormat, outputFormat, outputGranularity)")," where: ",(0,o.kt)("br",null),(0,o.kt)("inlineCode",{parentName:"td"},"columnName")," - column name to convert ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"inputFormat")," - format of the column columnName ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"outputFormat")," - format of the result desired after conversion ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"outputGranularity")," - the granularity in which to bucket the result")),(0,o.kt)("tr",{parentName:"tbody"},(0,o.kt)("td",{parentName:"tr",align:null},"DATETIMECONVERT"),(0,o.kt)("td",{parentName:"tr",align:null},"Format is expressed as ",(0,o.kt)("inlineCode",{parentName:"td"},"<time size>:<time unit>:<time format>:<pattern>")," ",(0,o.kt)("br",null)," where: ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"time size")," - size of the time unit eg: 1, 10 ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"time unit")," - HOURS, DAYS etc ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"time format")," - EPOCH or SIMPLE_DATE_FORMAT ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"pattern")," - this is defined in case of SIMPLE_DATE_FORMAT. eg: yyyyMMdd. A specific timezone can be passed using tz(timezone) ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"timezone")," - can be expressed as long form tz(Asia/Kolkata), or short form tz(IST) or in terms of GMT tz(GMT+0530). Default is UTC. It is recommended to use long form timezone, as short forms are ambiguous with daylight savings (eg: PDT works during daylight savings, PST otherwise) ",(0,o.kt)("br",null)," ",(0,o.kt)("br",null)," Granularity is expressed as ",(0,o.kt)("inlineCode",{parentName:"td"},"<time size>:<time unit>")," ",(0,o.kt)("br",null)," ",(0,o.kt)("strong",{parentName:"td"},"Examples")," ",(0,o.kt)("br",null)," 1. To convert column ",(0,o.kt)("inlineCode",{parentName:"td"},"Date")," from ",(0,o.kt)("inlineCode",{parentName:"td"},"hoursSinceEpoch")," to ",(0,o.kt)("inlineCode",{parentName:"td"},"daysSinceEpoch")," and bucket it to 1 day granularity ",(0,o.kt)("br",null),' 2. To simply bucket millis "Date" to 15 minutes ',(0,o.kt)("inlineCode",{parentName:"td"},"granularity dateTimeConvert(Date, '1:MILLISECONDS:EPOCH', '1:MILLISECONDS:EPOCH', '15:MINUTES')")," ",(0,o.kt)("br",null),' 3. To convert column "Date" from hoursSinceEpoch to format yyyyMdd and bucket it to 1 days granularity ',(0,o.kt)("inlineCode",{parentName:"td"},"dateTimeConvert(Date, '1:HOURS:EPOCH', '1:DAYS:SIMPLE_DATE_FORMAT:yyyyMMdd', '1:DAYS')")," ",(0,o.kt)("br",null),' 4. To convert column "Date" from format yyyy/MM/dd to weeksSinceEpoch and bucket it to 1 weeks granularity ',(0,o.kt)("inlineCode",{parentName:"td"},"dateTimeConvert(Date, '1:DAYS:SIMPLE_DATE_FORMAT:yyyy/MM/dd', '1:WEEKS:EPOCH', '1:WEEKS')")," ",(0,o.kt)("br",null),' 5. To convert column "Date" from millis to format yyyyMdd in timezone PST ',(0,o.kt)("inlineCode",{parentName:"td"},"dateTimeConvert(Date, '1:MILLISECONDS:EPOCH', '1:DAYS:SIMPLE_DATE_FORMAT:yyyyMMdd tz(America/Los_Angeles)', '1:DAYS')"))),(0,o.kt)("tr",{parentName:"tbody"},(0,o.kt)("td",{parentName:"tr",align:null},"DATETRUNC"),(0,o.kt)("td",{parentName:"tr",align:null},"(Presto) SQL compatible date truncation, equivalent to the Presto function date_trunc. Takes at least 3 and upto 5 arguments, converts the value into a specified output granularity seconds since UTC epoch that is bucketed on a unit in a specified timezone. Examples DATETRUNC('week', time_in_seconds, 'SECONDS') This expression converts the column time_in_seconds, which is a long containing seconds since UTC epoch truncated at WEEK (where a Week starts at Monday UTC midnight). The output is a long seconds since UTC epoch. ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"DATETRUNC('quarter', DIV(time_milliseconds/1000), 'SECONDS', 'America/Los_Angeles', 'HOURS')")," This expression converts the expression ",(0,o.kt)("inlineCode",{parentName:"td"},"time_in_milliseconds/1000")," (which is thus in seconds) into hours that are truncated at ",(0,o.kt)("inlineCode",{parentName:"td"},"QUARTER")," at the Los Angeles time zone (where a Quarter begins on 1/1, 4/1, 7/1, 10/1 in Los Angeles timezone). The output is expressed as hours since UTC epoch (note that the output is not Los Angeles timezone)")),(0,o.kt)("tr",{parentName:"tbody"},(0,o.kt)("td",{parentName:"tr",align:null},"VALUEIN"),(0,o.kt)("td",{parentName:"tr",align:null},"Takes at least 2 arguments, where the first argument is a multi-valued column, and the following arguments are constant values. The transform function will filter the value from the multi-valued column with the given constant values. The ",(0,o.kt)("inlineCode",{parentName:"td"},"VALUEIN")," transform function is especially useful when the same multi-valued column is both filtering column and grouping column. ",(0,o.kt)("br",null),(0,o.kt)("br",null)," Examples ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"VALUEIN(mvColumn, 3, 5, 15)"))))),(0,o.kt)("h2",{id:"differences-with-sql"},"Differences with SQL"),(0,o.kt)(l.Z,{type:"info",mdxType:"Alert"}," These differences only apply to the PQL endpoint. They do not hold true for the standard-SQL endpoint, which is the recommended endpoint. ",(0,o.kt)("br",null),"More information about the two types of endpoints in Querying Pinot.. "),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"TOP works like LIMIT for truncation in group by queries"),(0,o.kt)("li",{parentName:"ul"},"No need to select the columns to group with.\nThe following two queries are both supported in PQL, where the non-aggregation columns are ignored.")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-sql"},"SELECT MIN(foo), MAX(foo), SUM(foo), AVG(foo) FROM mytable\n GROUP BY bar, baz\n TOP 50\n\nSELECT bar, baz, MIN(foo), MAX(foo), SUM(foo), AVG(foo) FROM mytable\n GROUP BY bar, baz\n TOP 50\n")),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"The results will always order by the aggregated value (descending).\nThe results for query")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-sql"},"SELECT MIN(foo), MAX(foo) FROM myTable\n GROUP BY bar\n TOP 50\n")),(0,o.kt)("p",null,"will be the same as the combining results from the following queries"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-sql"},"SELECT MIN(foo) FROM myTable\n GROUP BY bar\n TOP 50\nSELECT MAX(foo) FROM myTable\n GROUP BY bar\n TOP 50\n")),(0,o.kt)("p",null,"where we don't put the results for the same group together."),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"No support for ",(0,o.kt)("strong",{parentName:"li"},"ORDER BY")," in aggregation group by. However, ORDER BY support was added recently and is available in the standard-SQL endpoint. It can be used in the PQL endpoint by passing ",(0,o.kt)("inlineCode",{parentName:"li"},"queryOptions")," into the payload as follows")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-sql"},'{\n "pql" : "SELECT SUM(foo), SUM(bar) from myTable GROUP BY moo ORDER BY SUM(bar) ASC, moo DESC TOP 10",\n "queryOptions" : "groupByMode=sql;responseFormat=sql"\n}\n')),(0,o.kt)("p",null,"where:"),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("inlineCode",{parentName:"li"},"groupByMode=sql")," - standard sql way of execution group by, hence accepting order by"),(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("inlineCode",{parentName:"li"},"responseFormat=sql")," - standard sql way of displaying results, in a tabular manner")))}c.isMDXComponent=!0},4184:function(e,t){var n;!function(){"use strict";var a={}.hasOwnProperty;function r(){for(var e=[],t=0;t<arguments.length;t++){var n=arguments[t];if(n){var o=typeof n;if("string"===o||"number"===o)e.push(n);else if(Array.isArray(n)){if(n.length){var l=r.apply(null,n);l&&e.push(l)}}else if("object"===o)if(n.toString===Object.prototype.toString)for(var i in n)a.call(n,i)&&n[i]&&e.push(i);else e.push(n.toString())}}return e.join(" ")}e.exports?(r.default=r,e.exports=r):void 0===(n=function(){return r}.apply(t,[]))||(e.exports=n)}()}}]);
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Injecting functions is not allowed yet. The example below demonstrate the use of UDFs. More examples in Transform Function in Aggregation Grouping"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-sql"},"SELECT count(*) FROM myTable\n GROUP BY timeConvert(timeColumnName, 'SECONDS', 'DAYS')\n")),(0,o.kt)("h3",{id:"bytes-column"},"BYTES column"),(0,o.kt)("p",null,"Pinot supports queries on BYTES column using HEX string. 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",(0,o.kt)("br",null)," ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"DATETIMECONVERT(columnName, inputFormat, outputFormat, outputGranularity)")," where: ",(0,o.kt)("br",null),(0,o.kt)("inlineCode",{parentName:"td"},"columnName")," - column name to convert ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"inputFormat")," - format of the column columnName ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"outputFormat")," - format of the result desired after conversion ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"outputGranularity")," - the granularity in which to bucket the result")),(0,o.kt)("tr",{parentName:"tbody"},(0,o.kt)("td",{parentName:"tr",align:null},"DATETIMECONVERT"),(0,o.kt)("td",{parentName:"tr",align:null},"Format is expressed as ",(0,o.kt)("inlineCode",{parentName:"td"},"<time size>:<time unit>:<time format>:<pattern>")," ",(0,o.kt)("br",null)," where: ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"time size")," - size of the time unit eg: 1, 10 ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"time unit")," - HOURS, DAYS etc ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"time format")," - EPOCH or SIMPLE_DATE_FORMAT ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"pattern")," - this is defined in case of SIMPLE_DATE_FORMAT. eg: yyyyMMdd. 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To convert column "Date" from millis to format yyyyMdd in timezone PST ',(0,o.kt)("inlineCode",{parentName:"td"},"dateTimeConvert(Date, '1:MILLISECONDS:EPOCH', '1:DAYS:SIMPLE_DATE_FORMAT:yyyyMMdd tz(America/Los_Angeles)', '1:DAYS')"))),(0,o.kt)("tr",{parentName:"tbody"},(0,o.kt)("td",{parentName:"tr",align:null},"DATETRUNC"),(0,o.kt)("td",{parentName:"tr",align:null},"(Presto) SQL compatible date truncation, equivalent to the Presto function date_trunc. Takes at least 3 and upto 5 arguments, converts the value into a specified output granularity seconds since UTC epoch that is bucketed on a unit in a specified timezone. Examples DATETRUNC('week', time_in_seconds, 'SECONDS') This expression converts the column time_in_seconds, which is a long containing seconds since UTC epoch truncated at WEEK (where a Week starts at Monday UTC midnight). The output is a long seconds since UTC epoch. ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"DATETRUNC('quarter', DIV(time_milliseconds/1000), 'SECONDS', 'America/Los_Angeles', 'HOURS')")," This expression converts the expression ",(0,o.kt)("inlineCode",{parentName:"td"},"time_in_milliseconds/1000")," (which is thus in seconds) into hours that are truncated at ",(0,o.kt)("inlineCode",{parentName:"td"},"QUARTER")," at the Los Angeles time zone (where a Quarter begins on 1/1, 4/1, 7/1, 10/1 in Los Angeles timezone). The output is expressed as hours since UTC epoch (note that the output is not Los Angeles timezone)")),(0,o.kt)("tr",{parentName:"tbody"},(0,o.kt)("td",{parentName:"tr",align:null},"VALUEIN"),(0,o.kt)("td",{parentName:"tr",align:null},"Takes at least 2 arguments, where the first argument is a multi-valued column, and the following arguments are constant values. The transform function will filter the value from the multi-valued column with the given constant values. The ",(0,o.kt)("inlineCode",{parentName:"td"},"VALUEIN")," transform function is especially useful when the same multi-valued column is both filtering column and grouping column. ",(0,o.kt)("br",null),(0,o.kt)("br",null)," Examples ",(0,o.kt)("br",null)," ",(0,o.kt)("inlineCode",{parentName:"td"},"VALUEIN(mvColumn, 3, 5, 15)"))))),(0,o.kt)("h2",{id:"differences-with-sql"},"Differences with SQL"),(0,o.kt)(l.Z,{type:"info",mdxType:"Alert"}," These differences only apply to the PQL endpoint. They do not hold true for the standard-SQL endpoint, which is the recommended endpoint. ",(0,o.kt)("br",null),"More information about the two types of endpoints in Querying Pinot.. "),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"TOP works like LIMIT for truncation in group by queries"),(0,o.kt)("li",{parentName:"ul"},"No need to select the columns to group with.\nThe following two queries are both supported in PQL, where the non-aggregation columns are ignored.")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-sql"},"SELECT MIN(foo), MAX(foo), SUM(foo), AVG(foo) FROM mytable\n GROUP BY bar, baz\n TOP 50\n\nSELECT bar, baz, MIN(foo), MAX(foo), SUM(foo), AVG(foo) FROM mytable\n GROUP BY bar, baz\n TOP 50\n")),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"The results will always order by the aggregated value (descending).\nThe results for query")),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-sql"},"SELECT MIN(foo), MAX(foo) FROM myTable\n GROUP BY bar\n TOP 50\n")),(0,o.kt)("p",null,"will be the same as the combining results from the following queries"),(0,o.kt)("pre",null,(0,o.kt)("code",{parentName:"pre",className:"language-sql"},"SELECT MIN(foo) FROM myTable\n GROUP BY bar\n TOP 50\nSELECT MAX(foo) FROM myTable\n GROUP BY bar\n TOP 50\n")),(0,o.kt)("p",null,"where we don't put the results for the same group together."),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},"No support for ",(0,o.kt)("strong",{parentName:"li"},"ORDER BY")," in aggregation group by. 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")),(0,i.kt)("h2",{id:"setup-a-pinot-cluster-for-demo"},"Setup a Pinot cluster for demo"),(0,i.kt)("h3",{id:"update-helm-dependency"},"Update helm dependency"),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"helm dependency update\n")),(0,i.kt)("h3",{id:"start-pinot-with-helm"},"Start Pinot with Helm"),(0,i.kt)("ul",null,(0,i.kt)("li",{parentName:"ul"},"For Helm v2.12.1")),(0,i.kt)("p",null,"If cluster is just initialized, ensure helm is initialized by running:"),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"helm init --service-account tiller\n")),(0,i.kt)("p",null,"Then deploy pinot cluster by:"),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},'helm install --namespace "pinot-quickstart" --name "pinot" .\n')),(0,i.kt)("ul",null,(0,i.kt)("li",{parentName:"ul"},"For Helm v3.0.0")),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"kubectl create ns 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"system:serviceaccount:kube-system:default" cannot get resource "namespaces" in API group "" in the namespace "pinot-quickstart"\n')),(0,i.kt)("ul",null,(0,i.kt)("li",{parentName:"ul"},"Resolution:")),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"kubectl apply -f helm-rbac.yaml\n")),(0,i.kt)("ul",null,(0,i.kt)("li",{parentName:"ul"},"Check deployment status")),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"kubectl get all -n pinot-quickstart\n")),(0,i.kt)("h2",{id:"load-data-into-pinot-through-kafka"},"Load data into Pinot through Kafka"),(0,i.kt)("h3",{id:"bring-up-a-kafka-cluster-for-realtime-data-ingestion"},"Bring up a Kafka Cluster for realtime data ingestion"),(0,i.kt)("ul",null,(0,i.kt)("li",{parentName:"ul"},"For helm v2.12.1")),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},'helm repo add incubator https://charts.helm.sh/incubator\nhelm install --namespace "pinot-quickstart" --name kafka incubator/kafka\n')),(0,i.kt)("ul",null,(0,i.kt)("li",{parentName:"ul"},"For helm v3.0.0")),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"helm repo add incubator https://charts.helm.sh/incubator\nhelm install -n pinot-quickstart kafka incubator/kafka --set replicas=1\n")),(0,i.kt)("h3",{id:"check-kafka-deployment-status"},"Check Kafka deployment status"),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"kubectl get all -n pinot-quickstart |grep kafka\n")),(0,i.kt)("p",null,"Ensure Kafka deployment is ready before executing the scripts in next steps:"),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"pod/kafka-0 1/1 Running 0 2m\npod/kafka-zookeeper-0 1/1 Running 0 10m\npod/kafka-zookeeper-1 1/1 Running 0 9m\npod/kafka-zookeeper-2 1/1 Running 0 8m\n")),(0,i.kt)("h3",{id:"create-kafka-topics"},"Create Kafka topics"),(0,i.kt)("p",null,"Below scripts will create two Kafka topics for data ingestion:"),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"kubectl -n pinot-quickstart exec kafka-0 -- kafka-topics --zookeeper kafka-zookeeper:2181 --topic flights-realtime --create --partitions 1 --replication-factor 1\nkubectl -n pinot-quickstart exec kafka-0 -- kafka-topics --zookeeper kafka-zookeeper:2181 --topic flights-realtime-avro --create --partitions 1 --replication-factor 1\n")),(0,i.kt)("h3",{id:"load-data-into-kafka-and-create-pinot-schematables"},"Load data into Kafka and Create Pinot Schema/Tables"),(0,i.kt)("p",null,"Below script will deploy 3 batch jobs"),(0,i.kt)("ul",null,(0,i.kt)("li",{parentName:"ul"},"Ingest 19492 Json messages to Kafka topic ",(0,i.kt)("inlineCode",{parentName:"li"},"flights-realtime")," at a speed of 1 msg/sec"),(0,i.kt)("li",{parentName:"ul"},"Ingest 19492 Avro messages to Kafka topic ",(0,i.kt)("inlineCode",{parentName:"li"},"flights-realtime-avro")," at a speed of 1 msg/sec"),(0,i.kt)("li",{parentName:"ul"},"Upload Pinot schema ",(0,i.kt)("inlineCode",{parentName:"li"},"airlineStats")),(0,i.kt)("li",{parentName:"ul"},"Create Pinot Table ",(0,i.kt)("inlineCode",{parentName:"li"},"airlineStats")," to ingest data from Json encoded Kafka topic ",(0,i.kt)("inlineCode",{parentName:"li"},"flights-realtime")),(0,i.kt)("li",{parentName:"ul"},"Create Pinot Table ",(0,i.kt)("inlineCode",{parentName:"li"},"airlineStatsAvro")," to ingest data from Avro encoded Kafka topic ",(0,i.kt)("inlineCode",{parentName:"li"},"flights-realtime-avro"))),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"kubectl apply -f pinot-realtime-quickstart.yml\n")),(0,i.kt)("h2",{id:"how-to-query-pinot-data"},"How to query pinot data"),(0,i.kt)("h3",{id:"pinot-query-console"},"Pinot Query Console"),(0,i.kt)("p",null,"Please use below script to do local port-forwarding and open Pinot query console on your web 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init'\n")),(0,i.kt)("h3",{id:"load-demo-data-source"},"Load Demo Data source"),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"kubectl exec -it pod/superset-0 -n pinot-quickstart -- bash -c 'superset import_datasources -p /etc/superset/pinot_example_datasource.yaml'\nkubectl exec -it pod/superset-0 -n pinot-quickstart -- bash -c 'superset import_dashboards -p /etc/superset/pinot_example_dashboard.json'\n")),(0,i.kt)("h3",{id:"access-superset-ui"},"Access Superset UI"),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"./open-superset-ui.sh\n")),(0,i.kt)("p",null,"You can open the imported dashboard by click Dashboards banner then click on AirlineStats."),(0,i.kt)("h2",{id:"access-pinot-using-presto"},"Access Pinot Using Presto"),(0,i.kt)("h3",{id:"deploy-presto-with-pinot-plugin"},"Deploy Presto with Pinot Plugin"),(0,i.kt)("p",null,"You can run below command to deploy a customized Presto with Pinot 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(100.00%)\n0:02 [80 rows, 6.06KB] [35 rows/s, 2.66KB/s]\n")),(0,i.kt)("ul",null,(0,i.kt)("li",{parentName:"ul"},"Count total documents")),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-SQL"},"presto:default> select count(*) as cnt from pinot.dontcare.airlinestats limit 10;\n")),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"}," cnt\n------\n 9745\n(1 row)\n\nQuery 20191112_051114_00006_xkm4g, FINISHED, 1 node\nSplits: 17 total, 17 done (100.00%)\n0:00 [1 rows, 8B] [2 rows/s, 19B/s]\n")),(0,i.kt)("h3",{id:"how-to-clean-up-pinot-deployment"},"How to clean up Pinot deployment"),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre",className:"language-bash"},"kubectl delete ns pinot-quickstart\n")),(0,i.kt)(o.Z,{to:"/docs/administration/",mdxType:"Jump"},"Administration"))}m.isMDXComponent=!0},4184:function(e,t){var n;!function(){"use strict";var a={}.hasOwnProperty;function r(){for(var e=[],t=0;t<arguments.length;t++){var 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><article><header><h1 class="blogPostTitle_GeHD">A Brief History of Scaling LinkedIn</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z">May 16, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col margin-top--sm"><a href="https://github.com/apache/pinot-site/edit/dev/website/blog/2015-05-16-LinkedIn-Scaling.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Blog post page navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/blog/2015/06/10/Open-Sourcing-Pinot"><div class="pagination-nav__sublabel">Newer Post</div><div class="pagination-nav__label">« Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</div></a></div><div class="pagination-nav__item 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="blogPostTitle_GeHD" itemprop="headline">A Brief History of Scaling LinkedIn</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z" itemprop="datePublished">May 16, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li 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Scaling the Wall of Real-Time Analytics</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z">June 10, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer">Kishore Gopalakrishna</a></div><small class="avatar__subtitle">Apache Pinot Team</small></div></div></header><div class="markdown"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/a-b-testing">A/B Testing</a><a class="margin-horiz--sm" href="/blog/tags/infrastructure">Infrastructure</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col margin-top--sm"><a href="https://github.com/apache/pinot-site/edit/dev/website/blog/2015-06-10-Open-Sourcing-Pinot.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" 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Scaling the Wall of Real-Time Analytics</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z" itemprop="datePublished">June 10, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kishore Gopalakrishna</span></a></div><small class="avatar__subtitle" itemprop="description">Apache Pinot Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/a-b-testing">A/B Testing</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/infrastructure">Infrastructure</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col margin-top--sm"><a 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UberEATS Analytics Dashboard</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z">September 17, 2017</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber-data">Uber Data</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col margin-top--sm"><a href="https://github.com/apache/pinot-site/edit/dev/website/blog/2017-09-17-Restaurant-Manager.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Blog post page navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><div class="pagination-nav__sublabel">Newer Post</div><div class="pagination-nav__label">« Introducing ThirdEye - 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UberEATS Analytics Dashboard</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z" itemprop="datePublished">September 17, 2017</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber-data">Uber Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data 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LinkedIn’s Business-Wide Monitoring Platform</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z">January 9, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
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LinkedIn’s Business-Wide Monitoring Platform</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z" itemprop="datePublished">January 9, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
LinkedIn relies on ThirdEye to monitor site performance, track member growth, understand adoption of new features,
-flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" 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+flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" 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Powering fast aggregations on Pinot</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z">June 14, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
-while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col margin-top--sm"><a href="https://github.com/apache/pinot-site/edit/dev/website/blog/2019-06-14-LinkedIn-StarTree.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Blog post page navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/blog/2019/07/11/LinkedIn-AutoTune"><div class="pagination-nav__sublabel">Newer Post</div><div class="pagination-nav__label">« Auto-tuning Pinot real-time consumption</div></a></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><div class="pagination-nav__sublabel">Older Post</div><div class="pagination-nav__label">Introducing ThirdEye - 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="blogPostTitle_GeHD" itemprop="headline">Star-tree index - Powering fast aggregations on Pinot</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z" itemprop="datePublished">June 14, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
+while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li 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diff --git a/content/blog/2019/07/11/LinkedIn-AutoTune/index.html b/content/blog/2019/07/11/LinkedIn-AutoTune/index.html
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class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="blogPostTitle_GeHD" itemprop="headline">Auto-tuning Pinot real-time consumption</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z" itemprop="datePublished">July 11, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" 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This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" 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This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a 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-and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="blogPostTitle_GeHD" itemprop="headline">Analyzing anomalies with ThirdEye</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z" itemprop="datePublished">February 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
+and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><article><header><h1 class="blogPostTitle_GeHD">Using Apache Pinot and Kafka to Analyze GitHub Events</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z">April 10, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data 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For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp 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rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a 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-but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a 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+but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><article><header><h1 class="blogPostTitle_GeHD">Building a culture around metrics and anomaly detection</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" 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Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" 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As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" 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As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" 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diff --git a/content/blog/2020/08/08/DevBlog-IngestPlugins/index.html b/content/blog/2020/08/08/DevBlog-IngestPlugins/index.html
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<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,14 +11,14 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
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The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="blogPostTitle_GeHD" itemprop="headline">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" 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When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" 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When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a 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noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" 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class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="blogPostTitle_GeHD" itemprop="headline">Achieving 99th percentile latency SLA using Apache Pinot</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at 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You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a 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You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a 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The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" 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The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" 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Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a 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Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data 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target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" 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Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="blogPostTitle_GeHD" itemprop="headline">Change Data Analysis with Debezium and Apache Pinot</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at 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In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col margin-top--sm"><a href="https://github.com/apache/pinot-site/edit/dev/website/blog/2021-02-02-DevBlog-PrestoPinot.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 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In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li 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Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/upsert">Upsert</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" 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Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" 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Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="blogPostTitle_GeHD" itemprop="headline">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z" itemprop="datePublished">April 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" 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Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="blogPostTitle_GeHD" itemprop="headline">Deploying Apache Pinot at a Large Retail Chain</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z" itemprop="datePublished">April 27, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><article><header><h1 class="blogPostTitle_GeHD">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z">April 29, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing 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Charon</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z" itemprop="datePublished">April 29, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" 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Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/h-3">H3</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col margin-top--sm"><a href="https://github.com/apache/pinot-site/edit/dev/website/blog/2021-06-13-DevBlog-Geospatial.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Blog post page navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><div class="pagination-nav__sublabel">Newer Post</div><div class="pagination-nav__label">« Text analytics on LinkedIn Talent Insights using Apache Pinot</div></a></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/blog/2021/04/29/Uber-Charon"><div class="pagination-nav__sublabel">Older Post</div><div class="pagination-nav__label">Automating Merchant Live Monitoring with Real-Time Analytics - 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="blogPostTitle_GeHD" itemprop="headline">Introduction to Geospatial Queries in Apache Pinot</h1><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z" itemprop="datePublished">June 13, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" 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diff --git a/content/blog/2021/06/16/LinkedIn-TextAnalytics/index.html b/content/blog/2021/06/16/LinkedIn-TextAnalytics/index.html
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Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a 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Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg blogPostDetailsFull_3kfx"><div class="col"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col margin-top--sm"><a href="https://github.com/apache/pinot-site/edit/dev/website/blog/2021-06-16-LinkedIn-TextAnalytics.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Blog post page navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/blog/2021/06/13/DevBlog-Geospatial"><div class="pagination-nav__sublabel">Older Post</div><div class="pagination-nav__label">Introduction to Geospatial Queries in Apache Pinot »</div></a></div></nav></main><div class="col col--2"><div class="tableOfContents_35-E thin-scrollbar"></div></div></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener noreferrer" class="footer__link-item">Getting Started</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Pinot Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/users" target="_blank" rel="noopener noreferrer" class="footer__link-item">User Guide</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Administration</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Community</h4><ul class="footer__items"><li class="footer__item"><a href="https://join.slack.com/t/apache-pinot/shared_invite/zt-5z7pav2f-yYtjZdVA~EDmrGkho87Vzw" target="_blank" rel="noopener noreferrer" class="footer__link-item">Slack</a></li><li class="footer__item"><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Github</a></li><li class="footer__item"><a href="https://twitter.com/ApachePinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Twitter</a></li><li class="footer__item"><a href="mailto:dev-subscribe@pinot.apache.org?Subject=SubscribeToPinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Mailing List</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Apache</h4><ul class="footer__items"><li class="footer__item"><a href="https://www.apache.org/events/current-event" target="_blank" rel="noopener noreferrer" class="footer__link-item">Events</a></li><li class="footer__item"><a href="https://www.apache.org/foundation/thanks.html" target="_blank" rel="noopener noreferrer" class="footer__link-item">Thanks</a></li><li class="footer__item"><a href="https://www.apache.org/licenses" target="_blank" rel="noopener noreferrer" class="footer__link-item">License</a></li><li class="footer__item"><a href="https://www.apache.org/security" target="_blank" rel="noopener noreferrer" class="footer__link-item">Security</a></li><li class="footer__item"><a href="https://www.apache.org/foundation/sponsorship.html" target="_blank" rel="noopener noreferrer" class="footer__link-item">Sponsorship</a></li><li class="footer__item"><a href="https://www.apache.org" target="_blank" rel="noopener noreferrer" class="footer__link-item">Foundation</a></li></ul></div></div><div class="footer__bottom text--center"><div class="margin-bottom--sm"><a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footerLogoLink_qW4Z"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
+<script src="/assets/js/runtime~main.664acf57.js"></script>
+<script src="/assets/js/main.a1de4389.js"></script>
</body>
</html>
\ No newline at end of file
diff --git a/content/blog/atom.xml b/content/blog/atom.xml
index 5932de0..546c884 100644
--- a/content/blog/atom.xml
+++ b/content/blog/atom.xml
@@ -13,6 +13,10 @@
<link href="https://pinot.apache.org/blog/2021/06/16/LinkedIn-TextAnalytics"/>
<updated>2021-06-16T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Introduction LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Introduction to Geospatial Queries in Apache Pinot]]></title>
@@ -20,6 +24,10 @@
<link href="https://pinot.apache.org/blog/2021/06/13/DevBlog-Geospatial"/>
<updated>2021-06-13T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.]]></summary>
+ <author>
+ <name>Kenny Bastani</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Automating Merchant Live Monitoring with Real-Time Analytics - Charon]]></title>
@@ -27,6 +35,10 @@
<link href="https://pinot.apache.org/blog/2021/04/29/Uber-Charon"/>
<updated>2021-04-29T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Focus on Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.]]></summary>
+ <author>
+ <name>Uber</name>
+ <uri>https://eng.uber.com/category/articles/uberdata/</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Deploying Apache Pinot at a Large Retail Chain]]></title>
@@ -34,6 +46,10 @@
<link href="https://pinot.apache.org/blog/2021/04/27/DevBlog-PinotInRetailChain"/>
<updated>2021-04-27T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain]]></summary>
+ <author>
+ <name>PinotDev</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches]]></title>
@@ -41,6 +57,10 @@
<link href="https://pinot.apache.org/blog/2021/04/16/LinkedIn-Theta"/>
<updated>2021-04-16T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Focus on using large set intersection cardinality approximations with Apache Pinot and Theta Sketches, which allow us to efficiently figure out the unique size of a targeted audience when factoring in multiple criteria of an advertising campaign.]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Introduction to Upserts in Apache Pinot]]></title>
@@ -48,6 +68,10 @@
<link href="https://pinot.apache.org/blog/2021/04/08/DevBlog-UpsertsIntro"/>
<updated>2021-04-08T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Introduction to Pinot Upsert and explain why it’s exciting and how you can start using it.]]></summary>
+ <author>
+ <name>Kenny Bastani</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Real-time Analytics with Presto and Apache Pinot]]></title>
@@ -55,6 +79,10 @@
<link href="https://pinot.apache.org/blog/2021/02/02/DevBlog-PrestoPinot"/>
<updated>2021-02-02T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain]]></summary>
+ <author>
+ <name>PinotDev</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Change Data Analysis with Debezium and Apache Pinot]]></title>
@@ -62,6 +90,10 @@
<link href="https://pinot.apache.org/blog/2021/01/08/DevBlog-DebeziumCDC"/>
<updated>2021-01-08T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Pinot enters into a storied legacy of innovations that have emerged from one of the world’s largest online social networks. Over a few decades, the Silicon Valley tech giant has helped hundreds of millions of people around the world navigate their careers.]]></summary>
+ <author>
+ <name>Kenny Bastani</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[From Lambda to Lambda-less Lessons learned]]></title>
@@ -69,6 +101,10 @@
<link href="https://pinot.apache.org/blog/2020/12/01/LinkedIn-Lamda"/>
<updated>2020-12-01T00:00:00.000Z</updated>
<summary type="html"><![CDATA[The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Operating Apache Pinot at Uber Scale]]></title>
@@ -76,6 +112,10 @@
<link href="https://pinot.apache.org/blog/2020/10/20/Uber-Operating"/>
<updated>2020-10-20T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Present details of this platform and how it fits in Uber’s ecosystem. Explain how uber scaled from a few use cases to a multi-cluster powering hundreds of use cases for querying terabyte-scale data with millisecond latencies.]]></summary>
+ <author>
+ <name>Uber</name>
+ <uri>https://eng.uber.com/category/articles/uberdata/</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Deep Analysis of Russian Twitter Trolls]]></title>
@@ -83,6 +123,10 @@
<link href="https://pinot.apache.org/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"/>
<updated>2020-10-16T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.]]></summary>
+ <author>
+ <name>Kenny Bastani</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Leverage Plugins to Ingest Parquet Files from S3 in Pinot]]></title>
@@ -90,6 +134,10 @@
<link href="https://pinot.apache.org/blog/2020/08/08/DevBlog-IngestPlugins"/>
<updated>2020-08-08T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.]]></summary>
+ <author>
+ <name>PinotDev</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Monitoring Apache Pinot with JMX, Prometheus and Grafana]]></title>
@@ -97,6 +145,10 @@
<link href="https://pinot.apache.org/blog/2020/08/08/DevBlog-PinotMonitoring"/>
<updated>2020-08-08T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain]]></summary>
+ <author>
+ <name>PinotDev</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Achieving 99th percentile latency SLA using Apache Pinot]]></title>
@@ -104,6 +156,10 @@
<link href="https://pinot.apache.org/blog/2020/08/08/DevBlog-SLAApps"/>
<updated>2020-08-08T00:00:00.000Z</updated>
<summary type="html"><![CDATA[How users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA]]></summary>
+ <author>
+ <name>PinotDev</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Utilize UDFs to Supercharge Queries in Apache Pinot]]></title>
@@ -111,6 +167,10 @@
<link href="https://pinot.apache.org/blog/2020/08/08/DevBlog-ScalarUDFs"/>
<updated>2020-08-08T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Scalar Functions that allow users to write and add their functions as a plugin.]]></summary>
+ <author>
+ <name>PinotDev</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Building a culture around metrics and anomaly detection]]></title>
@@ -118,6 +178,10 @@
<link href="https://pinot.apache.org/blog/2020/07/28/DevBlog-AnomalyDetection"/>
<updated>2020-07-28T00:00:00.000Z</updated>
<summary type="html"><![CDATA[ThirdEye as a system is a platform that allows you to integrate your metrics (quantitative information) with events (knowledge or qualitative information) and combine the two so you can distinguish between meaningless anomalies and those ones that matter.]]></summary>
+ <author>
+ <name>Kenny Bastani</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Moving developers up the stack with Apache Pinot]]></title>
@@ -125,6 +189,10 @@
<link href="https://pinot.apache.org/blog/2020/07/28/DevBlog-DevUpStack"/>
<updated>2020-07-28T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Pinot enters into a storied legacy of innovations that have emerged from one of the world’s largest online social networks. Over a few decades, the Silicon Valley tech giant has helped hundreds of millions of people around the world navigate their careers.]]></summary>
+ <author>
+ <name>Kenny Bastani</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Bridging batch and stream processing for the Recruiter usage statistics dashboard]]></title>
@@ -132,6 +200,10 @@
<link href="https://pinot.apache.org/blog/2020/07/14/LinkedIn-BatchRealtime"/>
<updated>2020-07-14T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Focus on using large set intersection cardinality approximations with Apache Pinot and Theta Sketches, which allow us to efficiently figure out the unique size of a targeted audience when factoring in multiple criteria of an advertising campaign.]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Building LinkedIn Talent Insights to democratize data-driven decision making]]></title>
@@ -139,6 +211,10 @@
<link href="https://pinot.apache.org/blog/2020/06/29/LinkedIn-TalentInsight"/>
<updated>2020-06-29T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Focus on using large set intersection cardinality approximations with Apache Pinot and Theta Sketches, which allow us to efficiently figure out the unique size of a targeted audience when factoring in multiple criteria of an advertising campaign.]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Monitoring business performance data with ThirdEye smart alerts]]></title>
@@ -146,6 +222,10 @@
<link href="https://pinot.apache.org/blog/2020/06/25/LinkedIn-SmartAlerts"/>
<updated>2020-06-25T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Focus on using large set intersection cardinality approximations with Apache Pinot and Theta Sketches, which allow us to efficiently figure out the unique size of a targeted audience when factoring in multiple criteria of an advertising campaign.]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Using Apache Pinot and Kafka to Analyze GitHub Events]]></title>
@@ -153,6 +233,10 @@
<link href="https://pinot.apache.org/blog/2020/04/10/DevBlog-AnalyzeGitEvents"/>
<updated>2020-04-10T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API.]]></summary>
+ <author>
+ <name>Kenny Bastani</name>
+ <uri>https://medium.com/apache-pinot-developer-blog</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Analyzing anomalies with ThirdEye]]></title>
@@ -160,6 +244,10 @@
<link href="https://pinot.apache.org/blog/2020/02/20/LinkedIn-Thirdeye"/>
<updated>2020-02-20T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Focus on using large set intersection cardinality approximations with Apache Pinot and Theta Sketches, which allow us to efficiently figure out the unique size of a targeted audience when factoring in multiple criteria of an advertising campaign.]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Engineering SQL Support on Apache Pinot at Uber]]></title>
@@ -167,6 +255,10 @@
<link href="https://pinot.apache.org/blog/2020/01/15/Pinot-Presto-SQL"/>
<updated>2020-01-15T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Talks about solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore.]]></summary>
+ <author>
+ <name>Uber</name>
+ <uri>https://eng.uber.com/category/articles/uberdata/</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Auto-tuning Pinot real-time consumption]]></title>
@@ -174,6 +266,10 @@
<link href="https://pinot.apache.org/blog/2019/07/11/LinkedIn-AutoTune"/>
<updated>2019-07-11T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Focus on using large set intersection cardinality approximations with Apache Pinot and Theta Sketches, which allow us to efficiently figure out the unique size of a targeted audience when factoring in multiple criteria of an advertising campaign.]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Star-tree index - Powering fast aggregations on Pinot]]></title>
@@ -181,6 +277,10 @@
<link href="https://pinot.apache.org/blog/2019/06/14/LinkedIn-StarTree"/>
<updated>2019-06-14T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies, while using the storage space efficiently.]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform]]></title>
@@ -188,6 +288,10 @@
<link href="https://pinot.apache.org/blog/2019/01/09/LinkedIn-IntroThirdEye"/>
<updated>2019-01-09T00:00:00.000Z</updated>
<summary type="html"><![CDATA[ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Engineering Restaurant Manager - UberEATS Analytics Dashboard]]></title>
@@ -195,6 +299,10 @@
<link href="https://pinot.apache.org/blog/2017/09/17/Restaurant-Manager"/>
<updated>2017-09-17T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Restaurant Manager is a comprehensive analytics dashboard and pipeline for our restaurant partners. In this article, we discuss how we architected this analytics platform and its robust data pipeline.]]></summary>
+ <author>
+ <name>Uber</name>
+ <uri>https://eng.uber.com/category/articles/uberdata/</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics]]></title>
@@ -202,6 +310,10 @@
<link href="https://pinot.apache.org/blog/2015/06/10/Open-Sourcing-Pinot"/>
<updated>2015-06-10T00:00:00.000Z</updated>
<summary type="html"><![CDATA[Introducing Pinot which allow to slice and dice across billions of rows in real-time across a wide variety of products]]></summary>
+ <author>
+ <name>Kishore Gopalakrishna</name>
+ <uri>https://github.com/kishoreg</uri>
+ </author>
</entry>
<entry>
<title type="html"><![CDATA[A Brief History of Scaling LinkedIn]]></title>
@@ -209,5 +321,9 @@
<link href="https://pinot.apache.org/blog/2015/05/16/LinkedIn-Scaling"/>
<updated>2015-05-16T00:00:00.000Z</updated>
<summary type="html"><![CDATA[LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.]]></summary>
+ <author>
+ <name>LinkedIn</name>
+ <uri>https://engineering.linkedin.com/blog/topic/pinot</uri>
+ </author>
</entry>
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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z">June 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z">June 13, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/h-3">H3</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z">April 29, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z">April 27, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z">April 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z">April 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/upsert">Upsert</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z">February 2, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z">January 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/debezium">Debezium</a><a class="margin-horiz--sm" href="/blog/tags/cdc">CDC</a><a class="margin-horiz--sm" href="/blog/tags/change-data-analysis">Change Data Analysis</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z">December 1, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z">October 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div></footer></article><nav class="pagination-nav" aria-label="Blog list page navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/blog/page/2"><div class="pagination-nav__label">Older Entries »</div></a></div></nav></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z" itemprop="datePublished">June 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z" itemprop="datePublished">June 13, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/h-3">H3</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z" itemprop="datePublished">April 29, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z" itemprop="datePublished">April 27, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z" itemprop="datePublished">April 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z" itemprop="datePublished">April 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/upsert">Upsert</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/trino">Trino</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto-sql">PrestoSQL</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/debezium">Debezium</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/cdc">CDC</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/change-data-analysis">Change Data Analysis</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z" itemprop="datePublished">December 1, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z" itemprop="datePublished">October 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div></footer></article><nav class="pagination-nav" aria-label="Blog list page navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/blog/page/2"><div class="pagination-nav__label">Older Entries »</div></a></div></nav></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener 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-<link rel="stylesheet" href="https://at-ui.github.io/feather-font/css/iconfont.css"><title data-react-helmet="true">Blog - Apache Pinot: User-Facing Analytics | Apache Pinot™</title><meta data-react-helmet="true" property="og:title" content="Blog - Apache Pinot: User-Facing Analytics | Apache Pinot™"><meta data-react-helmet="true" property="og:description" content="Blog"><meta data-react-helmet="true" property="og:url" content="https://pinot.apache.org/blog/page/2"><meta data-react-helmet="true" name="docsearch:language" content="en"><meta data-react-helmet="true" name="docsearch:docusaurus_tag" content="blog_posts_list"><meta data-react-helmet="true" name="description" content="Apache Pinot"><meta data-react-helmet="true" name="description" content="Real-time Analytics"><meta data-react-helmet="true" name="description" content="User-facing Analytics"><meta data-react-helmet="true" name="description" content="user facing analytics"><meta data-react-helmet="true" name="description" content="Olap"><meta data-react-helmet="true" name="description" content="Consumer-facing facing analytics"><meta data-react-helmet="true" name="description" content="Fast Analytics"><meta data-react-helmet="true" name="description" content="Who uses Apache Pinot?"><meta data-react-helmet="true" name="keywords" content="Pinot,LinkedIn,User-Facing Analytics,Smart alerts,Automated User facing dashboards,Real-time data platform"><link data-react-helmet="true" rel="shortcut icon" href="/img/favicon.ico"><link data-react-helmet="true" rel="canonical" href="https://pinot.apache.org/blog/page/2"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/blog/page/2" hreflang="en"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/blog/page/2" hreflang="x-default"><link data-react-helmet="true" rel="preconnect" href="https://BH4D9OD16A-dsn.algolia.net" crossorigin="anonymous"><link rel="stylesheet" href="/assets/css/styles.f8c6b66d.css">
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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z">October 16, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z">July 14, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Batch and streaming computations are often combined together in the Lambda architecture,
-but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" 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Team</small></div></div></header><div class="markdown"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z">June 25, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z" itemprop="datePublished">October 16, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/prometheus">Prometheus</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/grafana">Grafana</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z" itemprop="datePublished">July 14, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Batch and streaming computations are often combined together in the Lambda architecture,
+but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z" itemprop="datePublished">June 29, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z" itemprop="datePublished">June 25, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><nav class="pagination-nav" aria-label="Blog list page navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/blog"><div class="pagination-nav__label">« Newer Entries</div></a></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/blog/page/3"><div class="pagination-nav__label">Older Entries »</div></a></div></nav></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener 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<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,18 +11,18 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
<link rel="search" type="application/opensearchdescription+xml" title="Apache Pinot™" href="/opensearch.xml">
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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z">April 10, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z">February 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
-and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z">January 15, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/sql">SQL</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z">July 11, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z">June 14, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
-while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z">January 9, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a aria-current="page" class="navbar__item navbar__link navbar__link--active" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper blog-wrapper blog-list-page"><div class="container margin-vert--lg"><div class="row"><aside class="col col--3"><nav class="sidebar_2ahu thin-scrollbar" aria-label="Blog recent posts navigation"><div class="sidebarItemTitle_2hhb margin-bottom--md">All our posts</div><ul class="sidebarItemList_2xAf"><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z" itemprop="datePublished">April 10, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z" itemprop="datePublished">February 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
+and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z" itemprop="datePublished">January 15, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sql">SQL</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z" itemprop="datePublished">July 11, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z" itemprop="datePublished">June 14, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
+while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z" itemprop="datePublished">January 9, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
LinkedIn relies on ThirdEye to monitor site performance, track member growth, understand adoption of new features,
-flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z">September 17, 2017</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber-data">Uber Data</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z">June 10, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer">Kishore Gopalakrishna</a></div><small class="avatar__subtitle">Apache Pinot Team</small></div></div></header><div class="markdown"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/a-b-testing">A/B Testing</a><a class="margin-horiz--sm" href="/blog/tags/infrastructure">Infrastructure</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z">May 16, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div></footer></article><nav class="pagination-nav" aria-label="Blog list page navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/blog/page/2"><div class="pagination-nav__label">« Newer Entries</div></a></div><div class="pagination-nav__item pagination-nav__item--next"></div></nav></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" 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+flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z" itemprop="datePublished">September 17, 2017</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber-data">Uber Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z" itemprop="datePublished">June 10, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kishore Gopalakrishna</span></a></div><small class="avatar__subtitle" itemprop="description">Apache Pinot Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/a-b-testing">A/B Testing</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/infrastructure">Infrastructure</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z" itemprop="datePublished">May 16, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a 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Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z">June 10, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer">Kishore Gopalakrishna</a></div><small class="avatar__subtitle">Apache Pinot Team</small></div></div></header><div class="markdown"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/a-b-testing">A/B Testing</a><a class="margin-horiz--sm" href="/blog/tags/infrastructure">Infrastructure</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics" href="/blog/2015/06/10/Open-Sourcing-Pinot"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "A/B Testing"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z" itemprop="datePublished">June 10, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kishore Gopalakrishna</span></a></div><small class="avatar__subtitle" itemprop="description">Apache Pinot Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/a-b-testing">A/B Testing</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/infrastructure">Infrastructure</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics" href="/blog/2015/06/10/Open-Sourcing-Pinot"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>29 posts tagged with "analytics"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z">June 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z">June 13, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/h-3">H3</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z">April 29, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z">April 27, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z">April 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z">April 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/upsert">Upsert</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z">February 2, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z">January 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/debezium">Debezium</a><a class="margin-horiz--sm" href="/blog/tags/cdc">CDC</a><a class="margin-horiz--sm" href="/blog/tags/change-data-analysis">Change Data Analysis</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z">December 1, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z">October 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z">October 16, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z">July 14, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Batch and streaming computations are often combined together in the Lambda architecture,
-but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z">June 29, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z">June 25, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z">April 10, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z">February 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
-and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z">January 15, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/sql">SQL</a></div><div class="col text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z">July 11, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z">June 14, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
-while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z">January 9, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a aria-current="page" class="navbar__item navbar__link navbar__link--active" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper blog-wrapper blog-tags-post-list-page"><div class="container margin-vert--lg"><div class="row"><aside class="col col--3"><nav class="sidebar_2ahu thin-scrollbar" aria-label="Blog recent posts navigation"><div class="sidebarItemTitle_2hhb margin-bottom--md">All our posts</div><ul class="sidebarItemList_2xAf"><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>29 posts tagged with "Analytics"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z" itemprop="datePublished">June 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z" itemprop="datePublished">June 13, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/h-3">H3</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z" itemprop="datePublished">April 29, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z" itemprop="datePublished">April 27, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z" itemprop="datePublished">April 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z" itemprop="datePublished">April 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/upsert">Upsert</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/trino">Trino</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto-sql">PrestoSQL</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/debezium">Debezium</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/cdc">CDC</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/change-data-analysis">Change Data Analysis</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z" itemprop="datePublished">December 1, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z" itemprop="datePublished">October 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z" itemprop="datePublished">October 16, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/prometheus">Prometheus</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/grafana">Grafana</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z" itemprop="datePublished">July 14, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Batch and streaming computations are often combined together in the Lambda architecture,
+but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z" itemprop="datePublished">June 29, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z" itemprop="datePublished">June 25, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z" itemprop="datePublished">April 10, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z" itemprop="datePublished">February 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
+and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z" itemprop="datePublished">January 15, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sql">SQL</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z" itemprop="datePublished">July 11, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z" itemprop="datePublished">June 14, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
+while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z" itemprop="datePublished">January 9, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
LinkedIn relies on ThirdEye to monitor site performance, track member growth, understand adoption of new features,
-flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z">September 17, 2017</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber-data">Uber Data</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z">June 10, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer">Kishore Gopalakrishna</a></div><small class="avatar__subtitle">Apache Pinot Team</small></div></div></header><div class="markdown"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/a-b-testing">A/B Testing</a><a class="margin-horiz--sm" href="/blog/tags/infrastructure">Infrastructure</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics" href="/blog/2015/06/10/Open-Sourcing-Pinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z">May 16, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a 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+flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z" itemprop="datePublished">September 17, 2017</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber-data">Uber Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z" itemprop="datePublished">June 10, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kishore Gopalakrishna</span></a></div><small class="avatar__subtitle" itemprop="description">Apache Pinot Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/a-b-testing">A/B Testing</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/infrastructure">Infrastructure</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics" href="/blog/2015/06/10/Open-Sourcing-Pinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z" itemprop="datePublished">May 16, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a 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<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
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class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "CDC"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/debezium">Debezium</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/cdc">CDC</a></li><li class="tag_11ep"><a class="tag_1Okp 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class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>One post tagged with "change data analysis"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z">January 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache 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href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "Change Data Analysis"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/debezium">Debezium</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/cdc">CDC</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/change-data-analysis">Change Data Analysis</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>One post tagged with "data"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z">June 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "Data"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z" itemprop="datePublished">June 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read 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href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>One post tagged with "debezium"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z">January 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/debezium">Debezium</a><a class="margin-horiz--sm" href="/blog/tags/cdc">CDC</a><a class="margin-horiz--sm" href="/blog/tags/change-data-analysis">Change Data Analysis</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article></main></div></div></div><footer 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href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "Debezium"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/debezium">Debezium</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/cdc">CDC</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/change-data-analysis">Change Data Analysis</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>13 posts tagged with "devblog"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z">June 13, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/h-3">H3</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z">April 27, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z">April 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/upsert">Upsert</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z">February 2, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z">January 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/debezium">Debezium</a><a class="margin-horiz--sm" href="/blog/tags/cdc">CDC</a><a class="margin-horiz--sm" href="/blog/tags/change-data-analysis">Change Data Analysis</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z">October 16, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z">April 10, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>13 posts tagged with "DevBlog"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z" itemprop="datePublished">June 13, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/h-3">H3</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z" itemprop="datePublished">April 27, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z" itemprop="datePublished">April 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/upsert">Upsert</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/trino">Trino</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto-sql">PrestoSQL</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/debezium">Debezium</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/cdc">CDC</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/change-data-analysis">Change Data Analysis</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z" itemprop="datePublished">October 16, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/prometheus">Prometheus</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/grafana">Grafana</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z" itemprop="datePublished">April 10, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>2 posts tagged with "financial intelligence"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z">October 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z">September 17, 2017</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber-data">Uber Data</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener noreferrer" class="footer__link-item">Getting Started</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Pinot Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/users" target="_blank" rel="noopener noreferrer" class="footer__link-item">User Guide</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Administration</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Community</h4><ul class="footer__items"><li class="footer__item"><a href="https://join.slack.com/t/apache-pinot/shared_invite/zt-5z7pav2f-yYtjZdVA~EDmrGkho87Vzw" target="_blank" rel="noopener noreferrer" class="footer__link-item">Slack</a></li><li class="footer__item"><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Github</a></li><li class="footer__item"><a href="https://twitter.com/ApachePinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Twitter</a></li><li class="footer__item"><a href="mailto:dev-subscribe@pinot.apache.org?Subject=SubscribeToPinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Mailing List</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Apache</h4><ul class="footer__items"><li class="footer__item"><a href="https://www.apache.org/events/current-event" target="_blank" rel="noopener noreferrer" class="footer__link-item">Events</a></li><li class="footer__item"><a href="https://www.apache.org/foundation/thanks.html" target="_blank" rel="noopener noreferrer" class="footer__link-item">Thanks</a></li><li class="footer__item"><a href="https://www.apache.org/licenses" target="_blank" rel="noopener noreferrer" class="footer__link-item">License</a></li><li class="footer__item"><a href="https://www.apache.org/security" target="_blank" rel="noopener noreferrer" class="footer__link-item">Security</a></li><li class="footer__item"><a href="https://www.apache.org/foundation/sponsorship.html" target="_blank" rel="noopener noreferrer" class="footer__link-item">Sponsorship</a></li><li class="footer__item"><a href="https://www.apache.org" target="_blank" rel="noopener noreferrer" class="footer__link-item">Foundation</a></li></ul></div></div><div class="footer__bottom text--center"><div class="margin-bottom--sm"><a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footerLogoLink_qW4Z"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>2 posts tagged with "financial intelligence"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z" itemprop="datePublished">October 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z" itemprop="datePublished">September 17, 2017</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber-data">Uber Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener 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When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "Grafana"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp 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Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/h-3">H3</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "H3"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z" itemprop="datePublished">June 13, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" 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href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a 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class="padding-right--md" href="/blog/tags/financial-intelligence">financial intelligence (2)</a><hr></article><article><h2>G</h2><a class="padding-right--md" href="/blog/tags/grafana">grafana (1)</a><hr></article><article><h2>H</h2><a class="padding-right--md" href="/blog/tags/h-3">h3 (1)</a><hr></article><article><h2>I</h2><a class="padding-right--md" href="/blog/tags/infrastructure">infrastructure (1)</a><hr></article><article><h2>J</h2><a class="padding-right--md" href="/blog/tags/jmx">jmx (1)</a><hr></article><article><h2>L</h2><a class="padding-right--md" href="/blog/tags/linked-in">linkedin (11)</a><hr></article><article><h2>M</h2><a class="padding-right--md" href="/blog/tags/monitoring">monitoring (1)</a><hr></article><article><h2>P</h2><a class="padding-right--md" href="/blog/tags/pinot">pinot (29)</a><a class="padding-right--md" href="/blog/tags/presto">presto (2)</a><a class="padding-right--md" href="/blog/tags/presto-sql">prestosql (1)</a><a class="padding-right--md" href="/blog/tags/prometheus">prometheus (1)</a><hr></article><article><h2>R</h2><a class="padding-right--md" href="/blog/tags/real-time-data-platform">real-time data platform (28)</a><a class="padding-right--md" href="/blog/tags/realtime">realtime (28)</a><hr></article><article><h2>S</h2><a class="padding-right--md" href="/blog/tags/sla">sla (3)</a><a class="padding-right--md" href="/blog/tags/sql">sql (1)</a><hr></article><article><h2>T</h2><a class="padding-right--md" href="/blog/tags/text-analytics">text analytics (1)</a><a class="padding-right--md" href="/blog/tags/third-eye">thirdeye (12)</a><a class="padding-right--md" href="/blog/tags/trino">trino (1)</a><hr></article><article><h2>U</h2><a class="padding-right--md" href="/blog/tags/user-facing-analytics">user-facing analytics (29)</a><a class="padding-right--md" href="/blog/tags/uber">uber (3)</a><a class="padding-right--md" href="/blog/tags/upsert">upsert (1)</a><a class="padding-right--md" href="/blog/tags/uber-data">uber data 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Analysis<span>1</span></a></li></ul><hr></article><article><h2>D</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/data">Data<span>1</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/debezium">Debezium<span>1</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/dev-blog">DevBlog<span>13</span></a></li></ul><hr></article><article><h2>F</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/financial-intelligence">financial intelligence<span>2</span></a></li></ul><hr></article><article><h2>G</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/grafana">Grafana<span>1</span></a></li></ul><hr></article><article><h2>H</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/h-3">H3<span>1</span></a></li></ul><hr></article><article><h2>I</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/infrastructure">Infrastructure<span>1</span></a></li></ul><hr></article><article><h2>J</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/jmx">JMX<span>1</span></a></li></ul><hr></article><article><h2>L</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/linked-in">LinkedIn<span>11</span></a></li></ul><hr></article><article><h2>M</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/monitoring">Monitoring<span>1</span></a></li></ul><hr></article><article><h2>P</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/pinot">Pinot<span>29</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/presto">Presto<span>2</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/presto-sql">PrestoSQL<span>1</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/prometheus">Prometheus<span>1</span></a></li></ul><hr></article><article><h2>R</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/real-time-data-platform">real-time data platform<span>28</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/realtime">Realtime<span>28</span></a></li></ul><hr></article><article><h2>S</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/sla">SLA<span>3</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/sql">SQL<span>1</span></a></li></ul><hr></article><article><h2>T</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/text-analytics">Text analytics<span>1</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/third-eye">ThirdEye<span>12</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/trino">Trino<span>1</span></a></li></ul><hr></article><article><h2>U</h2><ul class="padding--none"><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/uber">Uber<span>3</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/uber-data">Uber Data<span>1</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/upsert">Upsert<span>1</span></a></li><li class="tag_21yA"><a class="tag_1Okp tagWithCount_1HU1" href="/blog/tags/user-facing-analytics">User-Facing Analytics<span>29</span></a></li></ul><hr></article></section></main></div></div></div><footer class="footer"><div 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>One post tagged with "infrastructure"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z">June 10, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer">Kishore Gopalakrishna</a></div><small class="avatar__subtitle">Apache Pinot Team</small></div></div></header><div class="markdown"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/a-b-testing">A/B Testing</a><a class="margin-horiz--sm" href="/blog/tags/infrastructure">Infrastructure</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics" href="/blog/2015/06/10/Open-Sourcing-Pinot"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "Infrastructure"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z" itemprop="datePublished">June 10, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kishore Gopalakrishna</span></a></div><small class="avatar__subtitle" itemprop="description">Apache Pinot Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/a-b-testing">A/B Testing</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/infrastructure">Infrastructure</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics" href="/blog/2015/06/10/Open-Sourcing-Pinot"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>One post tagged with "jmx"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "JMX"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>11 posts tagged with "linkedin"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z">June 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z">April 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z">December 1, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z">July 14, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Batch and streaming computations are often combined together in the Lambda architecture,
-but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z">June 29, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z">June 25, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z">February 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
-and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z">July 11, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z">June 14, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
-while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z">January 9, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a aria-current="page" class="navbar__item navbar__link navbar__link--active" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper blog-wrapper blog-tags-post-list-page"><div class="container margin-vert--lg"><div class="row"><aside class="col col--3"><nav class="sidebar_2ahu thin-scrollbar" aria-label="Blog recent posts navigation"><div class="sidebarItemTitle_2hhb margin-bottom--md">All our posts</div><ul class="sidebarItemList_2xAf"><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>11 posts tagged with "LinkedIn"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z" itemprop="datePublished">June 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z" itemprop="datePublished">April 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z" itemprop="datePublished">December 1, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z" itemprop="datePublished">July 14, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Batch and streaming computations are often combined together in the Lambda architecture,
+but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z" itemprop="datePublished">June 29, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z" itemprop="datePublished">June 25, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z" itemprop="datePublished">February 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
+and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z" itemprop="datePublished">July 11, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z" itemprop="datePublished">June 14, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
+while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z" itemprop="datePublished">January 9, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
LinkedIn relies on ThirdEye to monitor site performance, track member growth, understand adoption of new features,
-flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z">May 16, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a 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+flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z" itemprop="datePublished">May 16, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a 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When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a 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When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/prometheus">Prometheus</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/grafana">Grafana</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>29 posts tagged with "pinot"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z">June 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z">June 13, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/h-3">H3</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z">April 29, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z">April 27, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z">April 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z">April 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/upsert">Upsert</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z">February 2, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z">January 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/debezium">Debezium</a><a class="margin-horiz--sm" href="/blog/tags/cdc">CDC</a><a class="margin-horiz--sm" href="/blog/tags/change-data-analysis">Change Data Analysis</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z">December 1, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z">October 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z">October 16, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z">July 14, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Batch and streaming computations are often combined together in the Lambda architecture,
-but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z">June 29, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z">June 25, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z">April 10, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z">February 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
-and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z">January 15, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/sql">SQL</a></div><div class="col text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z">July 11, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z">June 14, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
-while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z">January 9, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a aria-current="page" class="navbar__item navbar__link navbar__link--active" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper blog-wrapper blog-tags-post-list-page"><div class="container margin-vert--lg"><div class="row"><aside class="col col--3"><nav class="sidebar_2ahu thin-scrollbar" aria-label="Blog recent posts navigation"><div class="sidebarItemTitle_2hhb margin-bottom--md">All our posts</div><ul class="sidebarItemList_2xAf"><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>29 posts tagged with "Pinot"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z" itemprop="datePublished">June 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z" itemprop="datePublished">June 13, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/h-3">H3</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z" itemprop="datePublished">April 29, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z" itemprop="datePublished">April 27, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z" itemprop="datePublished">April 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z" itemprop="datePublished">April 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/upsert">Upsert</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/trino">Trino</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto-sql">PrestoSQL</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/debezium">Debezium</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/cdc">CDC</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/change-data-analysis">Change Data Analysis</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z" itemprop="datePublished">December 1, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z" itemprop="datePublished">October 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z" itemprop="datePublished">October 16, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/prometheus">Prometheus</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/grafana">Grafana</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z" itemprop="datePublished">July 14, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Batch and streaming computations are often combined together in the Lambda architecture,
+but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z" itemprop="datePublished">June 29, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z" itemprop="datePublished">June 25, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z" itemprop="datePublished">April 10, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z" itemprop="datePublished">February 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
+and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z" itemprop="datePublished">January 15, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sql">SQL</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z" itemprop="datePublished">July 11, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z" itemprop="datePublished">June 14, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
+while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z" itemprop="datePublished">January 9, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
LinkedIn relies on ThirdEye to monitor site performance, track member growth, understand adoption of new features,
-flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z">September 17, 2017</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber-data">Uber Data</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z">June 10, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer">Kishore Gopalakrishna</a></div><small class="avatar__subtitle">Apache Pinot Team</small></div></div></header><div class="markdown"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/a-b-testing">A/B Testing</a><a class="margin-horiz--sm" href="/blog/tags/infrastructure">Infrastructure</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics" href="/blog/2015/06/10/Open-Sourcing-Pinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z">May 16, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a 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+flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z" itemprop="datePublished">September 17, 2017</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber-data">Uber Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z" itemprop="datePublished">June 10, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kishore Gopalakrishna</span></a></div><small class="avatar__subtitle" itemprop="description">Apache Pinot Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/a-b-testing">A/B Testing</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/infrastructure">Infrastructure</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics" href="/blog/2015/06/10/Open-Sourcing-Pinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z" itemprop="datePublished">May 16, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a 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<meta name="viewport" content="width=device-width,initial-scale=1">
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<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
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<script async src="https://www.google-analytics.com/analytics.js"></script>
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In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "PrestoSQL"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>2 posts tagged with "presto"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z">February 2, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z">January 15, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/sql">SQL</a></div><div class="col text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>2 posts tagged with "Presto"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/trino">Trino</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto-sql">PrestoSQL</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z" itemprop="datePublished">January 15, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sql">SQL</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>One post tagged with "prometheus"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "Prometheus"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>28 posts tagged with "real-time data platform"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z">June 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z">June 13, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/h-3">H3</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z">April 29, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z">April 27, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z">April 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z">April 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/upsert">Upsert</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z">February 2, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z">January 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/debezium">Debezium</a><a class="margin-horiz--sm" href="/blog/tags/cdc">CDC</a><a class="margin-horiz--sm" href="/blog/tags/change-data-analysis">Change Data Analysis</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z">December 1, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z">October 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z">October 16, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z">July 14, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Batch and streaming computations are often combined together in the Lambda architecture,
-but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z">June 29, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z">June 25, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z">April 10, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z">February 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
-and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z">January 15, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/sql">SQL</a></div><div class="col text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z">July 11, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z">June 14, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
-while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z">January 9, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a aria-current="page" class="navbar__item navbar__link navbar__link--active" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper blog-wrapper blog-tags-post-list-page"><div class="container margin-vert--lg"><div class="row"><aside class="col col--3"><nav class="sidebar_2ahu thin-scrollbar" aria-label="Blog recent posts navigation"><div class="sidebarItemTitle_2hhb margin-bottom--md">All our posts</div><ul class="sidebarItemList_2xAf"><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>28 posts tagged with "real-time data platform"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z" itemprop="datePublished">June 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z" itemprop="datePublished">June 13, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/h-3">H3</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z" itemprop="datePublished">April 29, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z" itemprop="datePublished">April 27, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z" itemprop="datePublished">April 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z" itemprop="datePublished">April 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/upsert">Upsert</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/trino">Trino</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto-sql">PrestoSQL</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/debezium">Debezium</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/cdc">CDC</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/change-data-analysis">Change Data Analysis</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z" itemprop="datePublished">December 1, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z" itemprop="datePublished">October 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z" itemprop="datePublished">October 16, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/prometheus">Prometheus</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/grafana">Grafana</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z" itemprop="datePublished">July 14, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Batch and streaming computations are often combined together in the Lambda architecture,
+but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z" itemprop="datePublished">June 29, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z" itemprop="datePublished">June 25, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z" itemprop="datePublished">April 10, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z" itemprop="datePublished">February 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
+and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z" itemprop="datePublished">January 15, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sql">SQL</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z" itemprop="datePublished">July 11, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z" itemprop="datePublished">June 14, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
+while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z" itemprop="datePublished">January 9, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
LinkedIn relies on ThirdEye to monitor site performance, track member growth, understand adoption of new features,
-flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z">September 17, 2017</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber-data">Uber Data</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z">May 16, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a 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and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
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+flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z" itemprop="datePublished">September 17, 2017</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber-data">Uber Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z" itemprop="datePublished">May 16, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener noreferrer" class="footer__link-item">Getting Started</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Pinot Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/users" target="_blank" rel="noopener noreferrer" class="footer__link-item">User Guide</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Administration</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Community</h4><ul class="footer__items"><li class="footer__item"><a href="https://join.slack.com/t/apache-pinot/shared_invite/zt-5z7pav2f-yYtjZdVA~EDmrGkho87Vzw" target="_blank" rel="noopener noreferrer" class="footer__link-item">Slack</a></li><li class="footer__item"><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Github</a></li><li class="footer__item"><a href="https://twitter.com/ApachePinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Twitter</a></li><li class="footer__item"><a href="mailto:dev-subscribe@pinot.apache.org?Subject=SubscribeToPinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Mailing List</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Apache</h4><ul class="footer__items"><li class="footer__item"><a href="https://www.apache.org/events/current-event" target="_blank" rel="noopener noreferrer" class="footer__link-item">Events</a></li><li class="footer__item"><a href="https://www.apache.org/foundation/thanks.html" target="_blank" rel="noopener noreferrer" class="footer__link-item">Thanks</a></li><li class="footer__item"><a href="https://www.apache.org/licenses" target="_blank" rel="noopener noreferrer" class="footer__link-item">License</a></li><li class="footer__item"><a href="https://www.apache.org/security" target="_blank" rel="noopener noreferrer" class="footer__link-item">Security</a></li><li class="footer__item"><a href="https://www.apache.org/foundation/sponsorship.html" target="_blank" rel="noopener noreferrer" class="footer__link-item">Sponsorship</a></li><li class="footer__item"><a href="https://www.apache.org" target="_blank" rel="noopener noreferrer" class="footer__link-item">Foundation</a></li></ul></div></div><div class="footer__bottom text--center"><div class="margin-bottom--sm"><a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footerLogoLink_qW4Z"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>28 posts tagged with "realtime"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z">June 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z">June 13, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/h-3">H3</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z">April 29, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z">April 27, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z">April 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z">April 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/upsert">Upsert</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z">February 2, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z">January 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/debezium">Debezium</a><a class="margin-horiz--sm" href="/blog/tags/cdc">CDC</a><a class="margin-horiz--sm" href="/blog/tags/change-data-analysis">Change Data Analysis</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z">December 1, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z">October 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z">October 16, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z">July 14, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Batch and streaming computations are often combined together in the Lambda architecture,
-but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z">June 29, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z">June 25, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z">April 10, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z">February 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
-and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z">January 15, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/sql">SQL</a></div><div class="col text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z">July 11, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z">June 14, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
-while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z">January 9, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a aria-current="page" class="navbar__item navbar__link navbar__link--active" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper blog-wrapper blog-tags-post-list-page"><div class="container margin-vert--lg"><div class="row"><aside class="col col--3"><nav class="sidebar_2ahu thin-scrollbar" aria-label="Blog recent posts navigation"><div class="sidebarItemTitle_2hhb margin-bottom--md">All our posts</div><ul class="sidebarItemList_2xAf"><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>28 posts tagged with "Realtime"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z" itemprop="datePublished">June 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z" itemprop="datePublished">June 13, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/h-3">H3</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z" itemprop="datePublished">April 29, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z" itemprop="datePublished">April 27, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z" itemprop="datePublished">April 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z" itemprop="datePublished">April 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/upsert">Upsert</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/trino">Trino</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto-sql">PrestoSQL</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/debezium">Debezium</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/cdc">CDC</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/change-data-analysis">Change Data Analysis</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z" itemprop="datePublished">December 1, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z" itemprop="datePublished">October 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z" itemprop="datePublished">October 16, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/prometheus">Prometheus</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/grafana">Grafana</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z" itemprop="datePublished">July 14, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Batch and streaming computations are often combined together in the Lambda architecture,
+but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z" itemprop="datePublished">June 29, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z" itemprop="datePublished">June 25, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z" itemprop="datePublished">April 10, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z" itemprop="datePublished">February 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
+and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z" itemprop="datePublished">January 15, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sql">SQL</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z" itemprop="datePublished">July 11, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z" itemprop="datePublished">June 14, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
+while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z" itemprop="datePublished">January 9, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
LinkedIn relies on ThirdEye to monitor site performance, track member growth, understand adoption of new features,
-flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z">September 17, 2017</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber-data">Uber Data</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z">May 16, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener 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+flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z" itemprop="datePublished">September 17, 2017</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber-data">Uber Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z" itemprop="datePublished">May 16, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a 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diff --git a/content/blog/tags/sla/index.html b/content/blog/tags/sla/index.html
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<meta name="viewport" content="width=device-width,initial-scale=1">
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<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
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-<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a aria-current="page" class="navbar__item navbar__link navbar__link--active" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper blog-wrapper blog-tags-post-page"><div class="container margin-vert--lg"><div class="row"><aside class="col col--3"><nav class="sidebar_2ahu thin-scrollbar" aria-label="Blog recent posts navigation"><div class="sidebarItemTitle_2hhb margin-bottom--md">All our posts</div><ul class="sidebarItemList_2xAf"><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>3 posts tagged with "sla"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>3 posts tagged with "SLA"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a 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This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "SQL"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z" itemprop="datePublished">January 15, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sql">SQL</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>One post tagged with "text analytics"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z">June 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a class="margin-horiz--sm" 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Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>12 posts tagged with "thirdeye"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z">June 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z">April 27, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z">February 2, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z">October 16, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z">April 10, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z">January 9, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
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Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z" itemprop="datePublished">April 27, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/trino">Trino</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto-sql">PrestoSQL</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z" itemprop="datePublished">October 16, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/prometheus">Prometheus</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/grafana">Grafana</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z" itemprop="datePublished">April 10, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z" itemprop="datePublished">January 9, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
LinkedIn relies on ThirdEye to monitor site performance, track member growth, understand adoption of new features,
-flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener noreferrer" class="footer__link-item">Getting Started</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Pinot Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/users" target="_blank" rel="noopener noreferrer" class="footer__link-item">User Guide</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Administration</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Community</h4><ul class="footer__items"><li class="footer__item"><a href="https://join.slack.com/t/apache-pinot/shared_invite/zt-5z7pav2f-yYtjZdVA~EDmrGkho87Vzw" target="_blank" rel="noopener noreferrer" class="footer__link-item">Slack</a></li><li class="footer__item"><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Github</a></li><li class="footer__item"><a href="https://twitter.com/ApachePinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Twitter</a></li><li class="footer__item"><a href="mailto:dev-subscribe@pinot.apache.org?Subject=SubscribeToPinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Mailing List</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Apache</h4><ul class="footer__items"><li class="footer__item"><a href="https://www.apache.org/events/current-event" target="_blank" rel="noopener noreferrer" class="footer__link-item">Events</a></li><li class="footer__item"><a href="https://www.apache.org/foundation/thanks.html" target="_blank" rel="noopener noreferrer" class="footer__link-item">Thanks</a></li><li class="footer__item"><a href="https://www.apache.org/licenses" target="_blank" rel="noopener noreferrer" class="footer__link-item">License</a></li><li class="footer__item"><a href="https://www.apache.org/security" target="_blank" rel="noopener noreferrer" class="footer__link-item">Security</a></li><li class="footer__item"><a href="https://www.apache.org/foundation/sponsorship.html" target="_blank" rel="noopener noreferrer" class="footer__link-item">Sponsorship</a></li><li class="footer__item"><a href="https://www.apache.org" target="_blank" rel="noopener noreferrer" class="footer__link-item">Foundation</a></li></ul></div></div><div class="footer__bottom text--center"><div class="margin-bottom--sm"><a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footerLogoLink_qW4Z"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
-<script src="/assets/js/runtime~main.59053854.js"></script>
-<script src="/assets/js/main.5e591844.js"></script>
+flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener noreferrer" class="footer__link-item">Getting Started</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Pinot Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/users" target="_blank" rel="noopener noreferrer" class="footer__link-item">User Guide</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Administration</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Community</h4><ul class="footer__items"><li class="footer__item"><a href="https://join.slack.com/t/apache-pinot/shared_invite/zt-5z7pav2f-yYtjZdVA~EDmrGkho87Vzw" target="_blank" rel="noopener noreferrer" class="footer__link-item">Slack</a></li><li class="footer__item"><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Github</a></li><li class="footer__item"><a href="https://twitter.com/ApachePinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Twitter</a></li><li class="footer__item"><a href="mailto:dev-subscribe@pinot.apache.org?Subject=SubscribeToPinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Mailing List</a></li></ul></div><div class="col footer__col"><h4 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class="footer__link-item">Foundation</a></li></ul></div></div><div class="footer__bottom text--center"><div class="margin-bottom--sm"><a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footerLogoLink_qW4Z"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
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<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
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+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
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-<link rel="stylesheet" href="https://at-ui.github.io/feather-font/css/iconfont.css"><title data-react-helmet="true">One post tagged with "trino" | Apache Pinot™</title><meta data-react-helmet="true" property="og:title" content="One post tagged with "trino" | Apache Pinot™"><meta data-react-helmet="true" property="og:url" content="https://pinot.apache.org/blog/tags/trino"><meta data-react-helmet="true" name="docsearch:language" content="en"><meta data-react-helmet="true" name="docsearch:docusaurus_tag" content="blog_tags_posts"><meta data-react-helmet="true" name="description" content="Apache Pinot"><meta data-react-helmet="true" name="description" content="Real-time Analytics"><meta data-react-helmet="true" name="description" content="User-facing Analytics"><meta data-react-helmet="true" name="description" content="user facing analytics"><meta data-react-helmet="true" name="description" content="Olap"><meta data-react-helmet="true" name="description" content="Consumer-facing facing analytics"><meta data-react-helmet="true" name="description" content="Fast Analytics"><meta data-react-helmet="true" name="description" content="Who uses Apache Pinot?"><meta data-react-helmet="true" name="keywords" content="Pinot,LinkedIn,Trino,Presto,User-Facing Analytics,Real-time data platform"><link data-react-helmet="true" rel="shortcut icon" href="/img/favicon.ico"><link data-react-helmet="true" rel="canonical" href="https://pinot.apache.org/blog/tags/trino"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/blog/tags/trino" hreflang="en"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/blog/tags/trino" hreflang="x-default"><link data-react-helmet="true" rel="preconnect" href="https://BH4D9OD16A-dsn.algolia.net" crossorigin="anonymous"><link rel="stylesheet" href="/assets/css/styles.f8c6b66d.css">
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In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "Trino"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a 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UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z">September 17, 2017</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber-data">Uber Data</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Engineering Restaurant Manager - 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UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z" itemprop="datePublished">September 17, 2017</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber-data">Uber Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener 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-<link rel="stylesheet" href="https://at-ui.github.io/feather-font/css/iconfont.css"><title data-react-helmet="true">3 posts tagged with "uber" | Apache Pinot™</title><meta data-react-helmet="true" property="og:title" content="3 posts tagged with "uber" | Apache Pinot™"><meta data-react-helmet="true" property="og:url" content="https://pinot.apache.org/blog/tags/uber"><meta data-react-helmet="true" name="docsearch:language" content="en"><meta data-react-helmet="true" name="docsearch:docusaurus_tag" content="blog_tags_posts"><meta data-react-helmet="true" name="description" content="Apache Pinot"><meta data-react-helmet="true" name="description" content="Real-time Analytics"><meta data-react-helmet="true" name="description" content="User-facing Analytics"><meta data-react-helmet="true" name="description" content="user facing analytics"><meta data-react-helmet="true" name="description" content="Olap"><meta data-react-helmet="true" name="description" content="Consumer-facing facing analytics"><meta data-react-helmet="true" name="description" content="Fast Analytics"><meta data-react-helmet="true" name="description" content="Who uses Apache Pinot?"><meta data-react-helmet="true" name="keywords" content="Pinot,Pinot SQL,Pinot Presto,User-Facing Analytics,Real-time data platform"><link data-react-helmet="true" rel="shortcut icon" href="/img/favicon.ico"><link data-react-helmet="true" rel="canonical" href="https://pinot.apache.org/blog/tags/uber"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/blog/tags/uber" hreflang="en"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/blog/tags/uber" hreflang="x-default"><link data-react-helmet="true" rel="preconnect" href="https://BH4D9OD16A-dsn.algolia.net" crossorigin="anonymous"><link rel="stylesheet" href="/assets/css/styles.f8c6b66d.css">
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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>3 posts tagged with "uber"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z">April 29, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z">October 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z">January 15, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/sql">SQL</a></div><div class="col text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" 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Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z" itemprop="datePublished">April 29, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z" itemprop="datePublished">October 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z" itemprop="datePublished">January 15, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sql">SQL</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" 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Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/upsert">Upsert</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "Upsert"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z" itemprop="datePublished">April 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/upsert">Upsert</a></li><li 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Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7"><header class="margin-bottom--xl"><h1>29 posts tagged with "user-facing analytics"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z">June 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/data">Data</a><a class="margin-horiz--sm" href="/blog/tags/text-analytics">Text analytics</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z">June 13, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/h-3">H3</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z">April 29, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z">April 27, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z">April 16, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z">April 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/upsert">Upsert</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z">February 2, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/trino">Trino</a><a class="margin-horiz--sm" href="/blog/tags/presto-sql">PrestoSQL</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z">January 8, 2021</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/debezium">Debezium</a><a class="margin-horiz--sm" href="/blog/tags/cdc">CDC</a><a class="margin-horiz--sm" href="/blog/tags/change-data-analysis">Change Data Analysis</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z">December 1, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z">October 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z">October 16, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/monitoring">Monitoring</a><a class="margin-horiz--sm" href="/blog/tags/jmx">JMX</a><a class="margin-horiz--sm" href="/blog/tags/prometheus">Prometheus</a><a class="margin-horiz--sm" href="/blog/tags/grafana">Grafana</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z">August 8, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">PinotDev</a></div><small class="avatar__subtitle">Pinot Editorial Team</small></div></div></header><div class="markdown"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/sla">SLA</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z">July 28, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z">July 14, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Batch and streaming computations are often combined together in the Lambda architecture,
-but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z">June 29, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z">June 25, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z">April 10, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer">Kenny Bastani</a></div><small class="avatar__subtitle">Kenny Bastani</small></div></div></header><div class="markdown"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/dev-blog">DevBlog</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z">February 20, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
-and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z">January 15, 2020</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber">Uber</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/presto">Presto</a><a class="margin-horiz--sm" href="/blog/tags/sql">SQL</a></div><div class="col text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z">July 11, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z">June 14, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
-while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z">January 9, 2019</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a aria-current="page" class="navbar__item navbar__link navbar__link--active" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper blog-wrapper blog-tags-post-list-page"><div class="container margin-vert--lg"><div class="row"><aside class="col col--3"><nav class="sidebar_2ahu thin-scrollbar" aria-label="Blog recent posts navigation"><div class="sidebarItemTitle_2hhb margin-bottom--md">All our posts</div><ul class="sidebarItemList_2xAf"><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></li><li class="sidebarItem_2UVv"><a class="sidebarItemLink_1RT6" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>29 posts tagged with "User-Facing Analytics"</h1><a href="/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/16/LinkedIn-TextAnalytics">Text analytics on LinkedIn Talent Insights using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-16T00:00:00.000Z" itemprop="datePublished">June 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn Talent Insights (LTI) is a platform that helps organizations understand the external labor market and their internal workforce, and enables the long term success of their employees. Users of LTI have the flexibility to construct searches using the various facets of the LinkedIn Economic Graph (skills, titles, location, company, etc.).</p><p><a href="https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2021/text-analytics-on-linkedin-talent-insights-using-apache-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/06/ltipinot6.png" alt="Text analytics on LinkedIn Talent Insights using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/data">Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/text-analytics">Text analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Text analytics on LinkedIn Talent Insights using Apache Pinot" href="/blog/2021/06/16/LinkedIn-TextAnalytics"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/06/13/DevBlog-Geospatial">Introduction to Geospatial Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-06-13T00:00:00.000Z" itemprop="datePublished">June 13, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Geospatial data has been widely used across the industry, spanning multiple verticals, such as ride-sharing and delivery, transportation infrastructure, defense and intel, public health. Deriving insights from timely and accurate geospatial data could enable mission-critical use cases in the organizations and fuel a vibrant marketplace across the industry. In the design document for this new Pinot feature, we discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9</a></p><p><img src="https://miro.medium.com/max/1400/0*1xrDSs9lLZ5dD3zK" alt="Introduction to Geospatial Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/h-3">H3</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Geospatial Queries in Apache Pinot" href="/blog/2021/06/13/DevBlog-Geospatial"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/29/Uber-Charon">Automating Merchant Live Monitoring with Real-Time Analytics - Charon</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-29T00:00:00.000Z" itemprop="datePublished">April 29, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, live monitoring and automation of Ops is critical to preserve marketplace health, maintain reliability, and gain efficiency in markets. By the virtue of the word “live”, this monitoring needs to show what is happening now, with prompt access to fresh data, and the ability to recommend appropriate actions based on that data. Uber’s data platform provides the self-serve tools which empower the Ops teams to build their own live monitoring tools, and support their regional teams by building rich solutions.</p><p>For this project, the requirement was to provide merchant level monitoring and handle the edge cases which remain unaddressed by the sophisticated internal marketplace management tools. We used a variety of Uber’s real-time data platform components to build a tool called Charon to reduce impact of poor marketplace reliability on the merchants.</p><p>Read More at <a href="https://eng.uber.com/charon/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/charon/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2021/04/deliverDoor@3x-768x263.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Automating Merchant Live Monitoring with Real-Time Analytics - Charon" href="/blog/2021/04/29/Uber-Charon"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/27/DevBlog-PinotInRetailChain">Deploying Apache Pinot at a Large Retail Chain</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-27T00:00:00.000Z" itemprop="datePublished">April 27, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Blog gives an overview of our use of Apache Pinot to solve some of biggest challenges around Data Analytics in Large Retail Chain</p><p><a href="https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/deploying-apache-pinot-at-a-large-retail-chain-42aed2921a38</a></p><p><img src="https://miro.medium.com/max/1400/1*EtqD0vTPEe569jybXCt69w.png" alt="Deploying Apache Pinot at a Large Retail Chain"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deploying Apache Pinot at a Large Retail Chain" href="/blog/2021/04/27/DevBlog-PinotInRetailChain"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/16/LinkedIn-Theta">Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-16T00:00:00.000Z" itemprop="datePublished">April 16, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2021/pinot-and-theta-sketches</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2021/04/thetasketches2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Solving for the cardinality of set intersection at scale with Pinot and Theta Sketches" href="/blog/2021/04/16/LinkedIn-Theta"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/04/08/DevBlog-UpsertsIntro">Introduction to Upserts in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-04-08T00:00:00.000Z" itemprop="datePublished">April 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Since the 0.6.0 release of Apache Pinot, a new feature was made available for stream ingestion that allows you to upsert events from an immutable log. Typically, upsert is a term used to describe inserting a record into a database if it does not already exist or update it if it does exist. In Apache Pinot’s case, upsert isn’t precisely the same concept, and I wanted to write this blog post to explain why it’s exciting and how you can start using it.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/introduction-to-upserts-in-apache-pinot-987c12149d93</a></p><p><img src="https://miro.medium.com/max/1400/0*So3GjHjLY7DJAiaP" alt="Introduction to Upserts in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/upsert">Upsert</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introduction to Upserts in Apache Pinot" href="/blog/2021/04/08/DevBlog-UpsertsIntro"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/02/02/DevBlog-PrestoPinot">Real-time Analytics with Presto and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-02-02T00:00:00.000Z" itemprop="datePublished">February 2, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this world, most analytics products either focus on ad-hoc analytics, which requires query flexibility without guaranteed latency, or low latency analytics with limited query capability. In this blog, we will explore how to get the best of both worlds using Apache Pinot and Presto.</p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307" target="_blank" rel="noopener noreferrer">Read Part 1 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-i-cc672caea307</a></p><p><a href="https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713" target="_blank" rel="noopener noreferrer">Read Part 2 at https://medium.com/apache-pinot-developer-blog/real-time-analytics-with-presto-and-apache-pinot-part-ii-3d09ff937713</a></p><p><img src="https://miro.medium.com/max/1400/0*hJc6aV9aBJaKyXcx" alt="Real-time Analytics with Presto and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/trino">Trino</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto-sql">PrestoSQL</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Real-time Analytics with Presto and Apache Pinot" href="/blog/2021/02/02/DevBlog-PrestoPinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2021/01/08/DevBlog-DebeziumCDC">Change Data Analysis with Debezium and Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2021-01-08T00:00:00.000Z" itemprop="datePublished">January 8, 2021</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’re going to explore an exciting new world of real-time analytics based on combining the popular CDC tool, Debezium, with the real-time OLAP datastore, Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7" target="_blank" rel="noopener noreferrer">Read More at https://medium.com/apache-pinot-developer-blog/change-data-analysis-with-debezium-and-apache-pinot-b4093dc178a7</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Change Data Analysis with Debezium and Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/debezium">Debezium</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/cdc">CDC</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/change-data-analysis">Change Data Analysis</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Change Data Analysis with Debezium and Apache Pinot" href="/blog/2021/01/08/DevBlog-DebeziumCDC"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/12/01/LinkedIn-Lamda">From Lambda to Lambda-less Lessons learned</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-12-01T00:00:00.000Z" itemprop="datePublished">December 1, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/lambda-to-lambda-less-architecture</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/03/pinotincubator2.png" alt="From Lambda to Lambda-less Lessons learned"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about From Lambda to Lambda-less Lessons learned" href="/blog/2020/12/01/LinkedIn-Lamda"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/20/Uber-Operating">Operating Apache Pinot at Uber Scale</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-20T00:00:00.000Z" itemprop="datePublished">October 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making. For instance, identifying delayed Uber Eats orders or abandoned carts helps to enable our community operations team to take corrective action. Having a real-time dashboard of different events such as consumer demand, driver availability, or trips happening in a city is crucial for day-to-day operation, incident triaging, and financial intelligence.</p><p>Read More at <a href="https://eng.uber.com/operating-apache-pinot/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/operating-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/10/1224-5.png" alt="Operating Apache Pinot at Uber Scale"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Operating Apache Pinot at Uber Scale" href="/blog/2020/10/20/Uber-Operating"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis">Deep Analysis of Russian Twitter Trolls</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-10-16T00:00:00.000Z" itemprop="datePublished">October 16, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>The history behind Russian disinformation is a dense and continuously evolving subject. The world’s best research hasn’t seemed to hit the mainstream yet, which made this an excellent opportunity to see if I could use some open source tooling to surface new analytical evidence.</p><p>In this blog post, I’ll show you how to use Apache Pinot and Superset to analyze 3 million tweets by the Internet Research Agency (IRA) open-sourced by FiveThirtyEight.</p><p><a href="https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843" target="_blank" rel="noopener noreferrer">Read More at https://towardsdatascience.com/a-deep-analysis-of-russian-trolls-with-apache-pinot-and-superset-590c8c4d1843</a></p><p><img src="https://miro.medium.com/max/4320/0*iqUTy0GkLFTcSYlR.png" alt="Deep Analysis of Russian Twitter Trolls"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Deep Analysis of Russian Twitter Trolls" href="/blog/2020/10/16/DevBlog-TwitterTrollAnalysis"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-IngestPlugins">Leverage Plugins to Ingest Parquet Files from S3 in Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>One of the primary advantages of using Pinot is its pluggable architecture. The plugins make it easy to add support for any third-party system which can be an execution framework, a filesystem, or input format.</p><p>In this tutorial, we will use three such plugins to easily ingest data and push it to our Pinot cluster. The plugins we will be using are -</p><ul><li>pinot-batch-ingestion-spark</li><li>pinot-s3</li><li>pinot-parquet</li></ul><p><a href="https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/leverage-plugins-to-ingest-parquet-files-from-s3-in-pinot-decb12e4d09d</a></p><p><img src="https://miro.medium.com/max/6000/0*afbs7azGt-GpSVeP" alt="Leverage Plugins to Ingest Parquet Files from S3 in Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Leverage Plugins to Ingest Parquet Files from S3 in Pinot" href="/blog/2020/08/08/DevBlog-IngestPlugins"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-PinotMonitoring">Monitoring Apache Pinot with JMX, Prometheus and Grafana</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>I may be kicking open doors here, but a simple question has always helped me start from somewhere. When it comes to investigating degraded user experience caused by latency, can I observe high resource usage on all or some nodes of the system?</p><p><a href="https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/monitoring-apache-pinot-99034050c1a5</a></p><p><img src="https://miro.medium.com/max/1400/1*5kWginewoWzzQHQoZdPAGQ.png" alt="Monitoring Apache Pinot with JMX, Prometheus and Grafana"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/monitoring">Monitoring</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/jmx">JMX</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/prometheus">Prometheus</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/grafana">Grafana</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring Apache Pinot with JMX, Prometheus and Grafana" href="/blog/2020/08/08/DevBlog-PinotMonitoring"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-SLAApps">Achieving 99th percentile latency SLA using Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this article, we talk about how users can build critical site-facing analytical applications requiring high throughput and strict p99th query latency SLA using Apache Pinot.</p><p><a href="https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/achieving-99th-percentile-latency-sla-using-apache-pinot-2ba4ce1d9eff</a></p><p><img src="https://miro.medium.com/max/1140/0*VCPyrmNB2PteCmnC" alt="Achieving 99th percentile latency SLA using Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Achieving 99th percentile latency SLA using Apache Pinot" href="/blog/2020/08/08/DevBlog-SLAApps"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/08/08/DevBlog-ScalarUDFs">Utilize UDFs to Supercharge Queries in Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-08-08T00:00:00.000Z" itemprop="datePublished">August 8, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="PinotDev"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">PinotDev</span></a></div><small class="avatar__subtitle" itemprop="description">Pinot Editorial Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Apache Pinot is a realtime distributed OLAP datastore that can answer hundreds of thousands of queries with millisecond latencies. You can head over to <a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer">https://pinot.apache.org/</a> to get started with Apache Pinot.</p><p>While using any database, we can come across a scenario where a function required for the query is not supported out of the box. In such time, we have to resort to raising a pull request for a new function or finding a tedious workaround.</p><p>Scalar Functions that allow users to write and add their functions as a plugin.</p><p><a href="https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1" target="_blank" rel="noopener noreferrer">Read more at https://medium.com/apache-pinot-developer-blog/utilize-udfs-to-supercharge-queries-in-apache-pinot-e488a0f164f1</a></p><p><img src="https://miro.medium.com/max/10368/0*VtswFI-HcaXyyjhK" alt="Utilize UDFs to Supercharge Queries in Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sla">SLA</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Utilize UDFs to Supercharge Queries in Apache Pinot" href="/blog/2020/08/08/DevBlog-ScalarUDFs"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-AnomalyDetection">Building a culture around metrics and anomaly detection</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Anomaly detection is a very broad term. Usually it means that you want to see if things are running as usual. This could go from your business metrics down to the lowest level of how your systems are running. Anomaly detection is an entire process. It’s not just a tool that you get out of the box that measures time series data. Similar to DevOps, anomaly detection is a culture of different roles engaging in a process that combines tooling with human analysis.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/building-a-culture-around-metrics-and-anomaly-detection-da740960fcc2</a></p><p><img src="https://miro.medium.com/max/1400/0*xYm2ZURZVpyJ1JQ5" alt="Building a culture around metrics and anomaly detection"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building a culture around metrics and anomaly detection" href="/blog/2020/07/28/DevBlog-AnomalyDetection"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/28/DevBlog-DevUpStack">Moving developers up the stack with Apache Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-28T00:00:00.000Z" itemprop="datePublished">July 28, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Once upon a time, an internet company named LinkedIn faced the challenge of having petabytes of connected data with no way to analyze it in real-time. As this was a problem that was the first of its kind, there was only one solution. The company put together a talented team of engineers and tasked them with building the right tool for the job. Today, that tool goes by the name of Apache Pinot.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/moving-developers-up-the-stack-with-apache-pinot-29d36717a3f4</a></p><p><img src="https://miro.medium.com/max/1400/1*dnSikeGxTrfrF95niX16PA.png" alt="Moving developers up the stack with Apache Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Moving developers up the stack with Apache Pinot" href="/blog/2020/07/28/DevBlog-DevUpStack"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/07/14/LinkedIn-BatchRealtime">Bridging batch and stream processing for the Recruiter usage statistics dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-07-14T00:00:00.000Z" itemprop="datePublished">July 14, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Batch and streaming computations are often combined together in the Lambda architecture,
+but carry the cost of maintaining two different code bases for the same logic.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Bridging batch and stream processing for the Recruiter usage statistics dashboard" href="/blog/2020/07/14/LinkedIn-BatchRealtime"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/29/LinkedIn-TalentInsight">Building LinkedIn Talent Insights to democratize data-driven decision making</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-29T00:00:00.000Z" itemprop="datePublished">June 29, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/building-linkedin-talent-insights</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/lti-1.png" alt="Building LinkedIn Talent Insights to democratize data-driven decision making"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Building LinkedIn Talent Insights to democratize data-driven decision making" href="/blog/2020/06/29/LinkedIn-TalentInsight"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/06/25/LinkedIn-SmartAlerts">Monitoring business performance data with ThirdEye smart alerts</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-06-25T00:00:00.000Z" itemprop="datePublished">June 25, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Explain how ThirdEye smart alerts and automated dashboards helped the LinkedIn Premium business operations team monitor key metrics—such as new free trial signups—for the timely detection of outliers in business performance data.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/monitoring-business-performance-data-with-thirdeye-smart-alerts</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/06/thirdeye_business_performance-3.png" alt="Monitoring business performance data with ThirdEye smart alerts"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Monitoring business performance data with ThirdEye smart alerts" href="/blog/2020/06/25/LinkedIn-SmartAlerts"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents">Using Apache Pinot and Kafka to Analyze GitHub Events</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-04-10T00:00:00.000Z" itemprop="datePublished">April 10, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1400521020973400069/5y2UMi4r_400x400.jpg" alt="Kenny Bastani"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://medium.com/apache-pinot-developer-blog" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kenny Bastani</span></a></div><small class="avatar__subtitle" itemprop="description">Kenny Bastani</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>In this blog post, we’ll show you how Pinot and Kafka can be used together to ingest, query, and visualize event streams sourced from the public GitHub API. For the step-by-step instructions, please visit our documentation, which will guide you through the specifics of running this example in your development environment.</p><p>Read More at <a href="https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7" target="_blank" rel="noopener noreferrer">https://medium.com/apache-pinot-developer-blog/using-apache-pinot-and-kafka-to-analyze-github-events-93cdcb57d5f7</a></p><p><img src="https://miro.medium.com/max/4728/1*eR64jBH1ZvC3uNfPP56p5g.png" alt="Using Apache Pinot and Kafka to Analyze GitHub Events"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/dev-blog">DevBlog</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Using Apache Pinot and Kafka to Analyze GitHub Events" href="/blog/2020/04/10/DevBlog-AnalyzeGitEvents"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/02/20/LinkedIn-Thirdeye">Analyzing anomalies with ThirdEye</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-02-20T00:00:00.000Z" itemprop="datePublished">February 20, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on the behind-the-scenes functionalities of ThirdEye that analyze the multi-dimensional time series data
+and help our engineers understand why these anomalies happened through a dimension heatmap</p><p><a href="https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye" target="_blank" rel="noopener noreferrer">Read More at https://engineering.linkedin.com/blog/2020/analyzing-anomalies-with-thirdeye</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/02/datacube-1.png" alt="Analyzing anomalies with ThirdEye"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Analyzing anomalies with ThirdEye" href="/blog/2020/02/20/LinkedIn-Thirdeye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2020/01/15/Pinot-Presto-SQL">Engineering SQL Support on Apache Pinot at Uber</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2020-01-15T00:00:00.000Z" itemprop="datePublished">January 15, 2020</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform.</p><p>To resolve these issues, we built a solution that linked Presto, a query engine that supports full ANSI SQL, and Pinot, a real-time OLAP (online analytical processing) datastore. This married solution allows users to write ad-hoc SQL queries, empowering teams to unlock significant analysis capabilities.</p><p><a href="https://eng.uber.com/engineering-sql-support-on-apache-pinot/" target="_blank" rel="noopener noreferrer">Read More at https://eng.uber.com/engineering-sql-support-on-apache-pinot/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2020/01/Header-SQL-768x329.png" alt="SQL Support on Apache Pinot at Uber"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber">Uber</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/presto">Presto</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/sql">SQL</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering SQL Support on Apache Pinot at Uber" href="/blog/2020/01/15/Pinot-Presto-SQL"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/07/11/LinkedIn-AutoTune">Auto-tuning Pinot real-time consumption</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-07-11T00:00:00.000Z" itemprop="datePublished">July 11, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Focus on Auto tuning Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2020/bridging-batch-and-stream-processing</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2020/07/bridging-1.png" alt="Bridging batch and stream processing for the Recruiter usage statistics dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Auto-tuning Pinot real-time consumption" href="/blog/2019/07/11/LinkedIn-AutoTune"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/06/14/LinkedIn-StarTree">Star-tree index - Powering fast aggregations on Pinot</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-06-14T00:00:00.000Z" itemprop="datePublished">June 14, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Introduced Star-Tree index to utilize the pre-aggregated documents in a smart way that achieves low query latencies,
+while using the storage space efficiently.</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/06/star-tree-index--powering-fast-aggregations-on-pinot</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Star-tree index - Powering fast aggregations on Pinot" href="/blog/2019/06/14/LinkedIn-StarTree"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2019/01/09/LinkedIn-IntroThirdEye">Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2019-01-09T00:00:00.000Z" itemprop="datePublished">January 9, 2019</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>ThirdEye is a comprehensive platform for real-time monitoring of metrics that covers a wide variety of use-cases.
LinkedIn relies on ThirdEye to monitor site performance, track member growth, understand adoption of new features,
-flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/third-eye">ThirdEye</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z">September 17, 2017</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer">Uber</a></div><small class="avatar__subtitle">Uber Data Team</small></div></div></header><div class="markdown"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/uber-data">Uber Data</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a><a class="margin-horiz--sm" href="/blog/tags/financial-intelligence">financial intelligence</a></div><div class="col text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z">June 10, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer">Kishore Gopalakrishna</a></div><small class="avatar__subtitle">Apache Pinot Team</small></div></div></header><div class="markdown"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/a-b-testing">A/B Testing</a><a class="margin-horiz--sm" href="/blog/tags/infrastructure">Infrastructure</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics" href="/blog/2015/06/10/Open-Sourcing-Pinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl"><header><h2 class="blogPostTitle_GeHD"><a href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z">May 16, 2015</time> · One min read</div><div class="avatar margin-vert--md"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer">LinkedIn</a></div><small class="avatar__subtitle">LinkedIn Engineering Team</small></div></div></header><div class="markdown"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><a class="margin-horiz--sm" href="/blog/tags/pinot">Pinot</a><a class="margin-horiz--sm" href="/blog/tags/linked-in">LinkedIn</a><a class="margin-horiz--sm" href="/blog/tags/real-time-data-platform">real-time data platform</a><a class="margin-horiz--sm" href="/blog/tags/realtime">Realtime</a><a class="margin-horiz--sm" href="/blog/tags/analytics">Analytics</a><a class="margin-horiz--sm" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></div><div class="col text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a 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+flag sustained attempts to circumvent system security, and many other areas</p><p>Read More at <a href="https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/blog/2019/01/introducing-thirdeye--linkedins-business-wide-monitoring-platfor</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/site-assets/images/blog/posts/2019/06/startree3.png" alt="Star-tree index - Powering fast aggregations on Pinot"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/third-eye">ThirdEye</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Introducing ThirdEye - LinkedIn’s Business-Wide Monitoring Platform" href="/blog/2019/01/09/LinkedIn-IntroThirdEye"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2017/09/17/Restaurant-Manager">Engineering Restaurant Manager - UberEATS Analytics Dashboard</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2017-09-17T00:00:00.000Z" itemprop="datePublished">September 17, 2017</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://pbs.twimg.com/profile_images/1192909783856103427/6A4s8gW2_400x400.png" alt="Uber"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://eng.uber.com/category/articles/uberdata/" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Uber</span></a></div><small class="avatar__subtitle" itemprop="description">Uber Data Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>At Uber, we use data analytics to architect more magical user experiences across our products. Whenever possible, we harness these data engineering capabilities to empower our partners to better serve their customers. For instance, in late 2016, the UberEATS engineering team built a comprehensive analytics dashboard that provides restaurant partners with additional insights about the health of their business.</p><p>Read More at <a href="https://eng.uber.com/restaurant-manager/" target="_blank" rel="noopener noreferrer">https://eng.uber.com/restaurant-manager/</a></p><p><img src="https://1fykyq3mdn5r21tpna3wkdyi-wpengine.netdna-ssl.com/wp-content/uploads/2017/09/image4-2.png" alt="Engineering Restaurant Manager - UberEATS Analytics Dashboard"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/uber-data">Uber Data</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/financial-intelligence">financial intelligence</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Engineering Restaurant Manager - UberEATS Analytics Dashboard" href="/blog/2017/09/17/Restaurant-Manager"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/06/10/Open-Sourcing-Pinot">Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-06-10T00:00:00.000Z" itemprop="datePublished">June 10, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://avatars.githubusercontent.com/kishoreg" alt="Kishore Gopalakrishna"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/kishoreg" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Kishore Gopalakrishna</span></a></div><small class="avatar__subtitle" itemprop="description">Apache Pinot Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Read More at (<a href="https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/pinot/open-sourcing-pinot-scaling-wall-real-time-analytics</a>)</p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/a-b-testing">A/B Testing</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/infrastructure">Infrastructure</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about Open Sourcing Pinot - Scaling the Wall of Real-Time Analytics" href="/blog/2015/06/10/Open-Sourcing-Pinot"><b>Read More</b></a></div></footer></article><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="blogPostTitle_GeHD" itemprop="headline"><a itemprop="url" href="/blog/2015/05/16/LinkedIn-Scaling">A Brief History of Scaling LinkedIn</a></h2><div class="blogPostData_291c margin-vert--md"><time datetime="2015-05-16T00:00:00.000Z" itemprop="datePublished">May 16, 2015</time> · One min read</div><div class="row margin-top--md margin-bottom--sm"><div class="col col--6 authorCol_1R69"><div class="avatar margin-bottom--sm"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" class="avatar__photo-link avatar__photo"><img class="image_1yU8" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Linkedin_icon.svg/512px-Linkedin_icon.svg.png" alt="LinkedIn"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://engineering.linkedin.com/blog/topic/pinot" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">LinkedIn</span></a></div><small class="avatar__subtitle" itemprop="description">LinkedIn Engineering Team</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn’s product portfolio, member base, and server load has grown tremendously.</p><p>Today, LinkedIn operates globally with more than 350 million members. We serve tens of thousands of web pages every second of every day. We've hit our mobile moment where mobile accounts for more than 50 percent of all global traffic. All those requests are fetching data from our backend systems, which in turn handle millions of queries per second.</p><p>Read More at <a href="https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin" target="_blank" rel="noopener noreferrer">https://engineering.linkedin.com/architecture/brief-history-scaling-linkedin</a></p><p><img src="https://content.linkedin.com/content/dam/engineering/en-us/blog/migrated/data_centers_pops_0.png" alt="A Brief History of Scaling LinkedIn"></p></div><footer class="row docusaurus-mt-lg"><div class="col col--9"><b>Tags:</b><ul class="tags_2ga9 padding--none margin-left--sm"><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/pinot">Pinot</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/linked-in">LinkedIn</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/real-time-data-platform">real-time data platform</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/realtime">Realtime</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/analytics">Analytics</a></li><li class="tag_11ep"><a class="tag_1Okp tagRegular_3MiF" href="/blog/tags/user-facing-analytics">User-Facing Analytics</a></li></ul></div><div class="col col--3 text--right"><a aria-label="Read more about A Brief History of Scaling LinkedIn" href="/blog/2015/05/16/LinkedIn-Scaling"><b>Read More</b></a></div></footer></article></main></div></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a 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class="h1Heading_27L5">Features of Pinot</h1></header><ul><li>A column-oriented database with various compression schemes such as Run Length, Fixed Bit Length</li><li>Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index</li><li>Ability to optimize query/execution plan based on query and segment metadata .</li><li>Near real time ingestion from streams and batch ingestion from Hadoop</li><li>SQL like language that supports selection, aggregation, filtering, group by, order by, distinct queries on data.</li><li>Support for multivalued fields</li><li>Horizontally scalable and fault tolerant</li></ul><p>Because of the design choices we made to achieve these goals, there are certain limitations in Pinot:</p><p>Pinot is not a replacement for database i.e it cannot be used as source of truth store, cannot mutate data
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img 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stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><aside class="docSidebarContainer_3Kbt"><div class="sidebar_15mo sidebarWithHideableNavbar_267A"><a tabindex="-1" class="sidebarLogo_3h0W" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m"></a><nav class="menu thin-scrollbar menu_Bmed menuWithAnnouncementBar_2WvA"><ul class="menu__list"><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">About</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/about/what_is_pinot">What is Pinot</a></li><li class="menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/docs/about/features_of_pinot">Features of Pinot</a></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Administration</a></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Components</a></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="markdown"><header><h1>Features of Pinot</h1></header><ul><li>A column-oriented database with various compression schemes such as Run Length, Fixed Bit Length</li><li>Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index</li><li>Ability to optimize query/execution plan based on query and segment metadata .</li><li>Near real time ingestion from streams and batch ingestion from Hadoop</li><li>SQL like language that supports selection, aggregation, filtering, group by, order by, distinct queries on data.</li><li>Support for multivalued fields</li><li>Horizontally scalable and fault tolerant</li></ul><p>Because of the design choices we made to achieve these goals, there are certain limitations in Pinot:</p><p>Pinot is not a replacement for database i.e it cannot be used as source of truth store, cannot mutate data
Not a replacement for search engine i.e Full text search, relevance not supported
Query cannot span across multiple tables.
-Pinot works very well for querying time series data with lots of Dimensions and Metrics. <br></p><p>For example:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">SELECT sum(clicks), sum(impressions) FROM AdAnalyticsTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> WHERE ((daysSinceEpoch >= 17849 AND daysSinceEpoch <= 17856)) AND accountId IN (123456789)</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> GROUP BY daysSinceEpoch TOP 100</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">SELECT sum(impressions) FROM AdAnalyticsTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> WHERE (daysSinceEpoch >= 17824 and daysSinceEpoch <= 17854) AND adveriserId = '1234356789'</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> GROUP BY daysSinceEpoch,advertiserId TOP 100</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">SELECT sum(cost) FROM AdAnalyticsTable GROUP BY advertiserId TOP 50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/about/features_of_pinot.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_3DPF"></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" 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footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
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+Pinot works very well for querying time series data with lots of Dimensions and Metrics. <br></p><p>For example:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">SELECT sum(clicks), sum(impressions) FROM AdAnalyticsTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> WHERE ((daysSinceEpoch >= 17849 AND daysSinceEpoch <= 17856)) AND accountId IN (123456789)</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> GROUP BY daysSinceEpoch TOP 100</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">SELECT sum(impressions) FROM AdAnalyticsTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> WHERE (daysSinceEpoch >= 17824 and daysSinceEpoch <= 17854) AND adveriserId = '1234356789'</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> GROUP BY daysSinceEpoch,advertiserId TOP 100</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">SELECT sum(cost) FROM AdAnalyticsTable GROUP BY advertiserId TOP 50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/about/features_of_pinot.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_13-_"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" 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rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener 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class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
+<script src="/assets/js/runtime~main.664acf57.js"></script>
+<script src="/assets/js/main.a1de4389.js"></script>
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diff --git a/content/docs/about/index.html b/content/docs/about/index.html
index 2691799..3433c6d 100644
--- a/content/docs/about/index.html
+++ b/content/docs/about/index.html
@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,14 +11,14 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
<link rel="search" type="application/opensearchdescription+xml" title="Apache Pinot™" href="/opensearch.xml">
<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Ubuntu|Roboto|Source+Code+Pro">
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class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener noreferrer" class="footer__link-item">Getting Started</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Pinot Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/users" target="_blank" rel="noopener noreferrer" class="footer__link-item">User Guide</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Administration</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Community</h4><ul class="footer__items"><li class="footer__item"><a 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class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
-<script src="/assets/js/runtime~main.59053854.js"></script>
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src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="markdown"><header><h1>About</h1></header><p>Provide basic foundation of Pinot.</p><a class="jump-to jump-to--undefined" href="/docs/about/what_is_pinot/"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">What is Pinot?</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a><a class="jump-to jump-to--undefined" href="/docs/about/features_of_pinot/"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Features of Pinot</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a><a class="jump-to jump-to--undefined" href="/docs/about/guarantees/"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Who is using Pinot?</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/about.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_13-_"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"></div></nav></div></div></div></div></main></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener noreferrer" class="footer__link-item">Getting Started</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Pinot Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/users" target="_blank" rel="noopener noreferrer" class="footer__link-item">User Guide</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Administration</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Community</h4><ul class="footer__items"><li class="footer__item"><a 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href="https://www.apache.org/foundation/thanks.html" target="_blank" rel="noopener noreferrer" class="footer__link-item">Thanks</a></li><li class="footer__item"><a href="https://www.apache.org/licenses" target="_blank" rel="noopener noreferrer" class="footer__link-item">License</a></li><li class="footer__item"><a href="https://www.apache.org/security" target="_blank" rel="noopener noreferrer" class="footer__link-item">Security</a></li><li class="footer__item"><a href="https://www.apache.org/foundation/sponsorship.html" target="_blank" rel="noopener noreferrer" class="footer__link-item">Sponsorship</a></li><li class="footer__item"><a href="https://www.apache.org" target="_blank" rel="noopener noreferrer" class="footer__link-item">Foundation</a></li></ul></div></div><div class="footer__bottom text--center"><div class="margin-bottom--sm"><a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footerLogoLink_qW4Z"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
+<script src="/assets/js/runtime~main.664acf57.js"></script>
+<script src="/assets/js/main.a1de4389.js"></script>
</body>
</html>
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diff --git a/content/docs/about/what_is_pinot/index.html b/content/docs/about/what_is_pinot/index.html
index cd4aa16..e8d37d7 100644
--- a/content/docs/about/what_is_pinot/index.html
+++ b/content/docs/about/what_is_pinot/index.html
@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,16 +11,16 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
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type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1 class="h1Heading_27L5">What is Pinot</h1></header><p>Apache Pinot is a realtime distributed OLAP datastore, which is used to deliver scalable real time analytics with low latency. It can ingest data from batch data sources (such as HDFS, S3, Azure Data Lake, Google Cloud Storage) as well as streaming sources (such as Kafka). Pinot is designed to scale horizontally, so that it can scale to larger data sets and higher query rates as needed.</p><p><img alt="Pinot" src="/assets/images/pinot-overview-f1b5a17c2e53228461f1510ea2fe0e9b.png"></p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="when-should-i-use-it"></a>When should I use it?<a class="hash-link" href="#when-should-i-use-it" title="Direct link to heading">#</a></h2><p>Pinot is designed to answer OLAP queries with low latency. It is suited in contexts where fast analytics, such as aggregations, are needed on immutable data, possibly, with real-time data ingestion.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="when-should-i-not-use-it"></a>When should I not use it?<a class="hash-link" href="#when-should-i-not-use-it" title="Direct link to heading">#</a></h2><p>Pinot is not a replacement for your database, nor a search engine. It addresses fast analytics on immutable data and it is not thought by design, to handle data updates or deletions. Joins are currently not supported, but this problem can be overcome by using <a href="/docs/about/(https://prestodb.io/)">PrestoDB</a> for querying Pinot.</p><p>For more information about PrestoDB connector for Pinot see the <a href="https://github.com/apache/pinot/tree/master/kubernetes/examples/helm#access-pinot-using-presto" target="_blank" rel="noopener noreferrer">Helm Chart of Pinot with Presto</a>
-Pinot-Presto connector is avilable with version <a href="https://github.com/prestodb/presto/pull/13504" target="_blank" rel="noopener noreferrer">0.229</a></p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="quick-example"></a>Quick example<a class="hash-link" href="#quick-example" title="Direct link to heading">#</a></h2><p>Pinot works very well for querying time series data with lots of Dimensions and Metrics.
-Filters and aggregations are easy and fast.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">SELECT sum(clicks), sum(impressions) FROM AdAnalyticsTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> WHERE ((daysSinceEpoch >= 17849 AND daysSinceEpoch <= 17856)) AND accountId IN (123456789)</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> GROUP BY daysSinceEpoch TOP 100</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="who-uses-pinot"></a>Who uses Pinot?<a class="hash-link" href="#who-uses-pinot" title="Direct link to heading">#</a></h2><p>Pinot powers several big players, including LinkedIn, Uber, Factual, Weibo, Slack and more..</p></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/about/what_is_pinot.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_3DPF"></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/docs/about/features_of_pinot"><div class="pagination-nav__sublabel">Next</div><div 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class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">About</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/docs/about/what_is_pinot">What is Pinot</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/about/features_of_pinot">Features of Pinot</a></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Administration</a></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Components</a></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>What is Pinot</h1></header><p>Apache Pinot is a realtime distributed OLAP datastore, which is used to deliver scalable real time analytics with low latency. It can ingest data from batch data sources (such as HDFS, S3, Azure Data Lake, Google Cloud Storage) as well as streaming sources (such as Kafka). Pinot is designed to scale horizontally, so that it can scale to larger data sets and higher query rates as needed.</p><p><img alt="Pinot" src="/assets/images/pinot-overview-f1b5a17c2e53228461f1510ea2fe0e9b.png"></p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="when-should-i-use-it"></a>When should I use it?<a class="hash-link" href="#when-should-i-use-it" title="Direct link to heading">#</a></h2><p>Pinot is designed to answer OLAP queries with low latency. It is suited in contexts where fast analytics, such as aggregations, are needed on immutable data, possibly, with real-time data ingestion.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="when-should-i-not-use-it"></a>When should I not use it?<a class="hash-link" href="#when-should-i-not-use-it" title="Direct link to heading">#</a></h2><p>Pinot is not a replacement for your database, nor a search engine. It addresses fast analytics on immutable data and it is not thought by design, to handle data updates or deletions. Joins are currently not supported, but this problem can be overcome by using <a href="/docs/about/(https://prestodb.io/)">PrestoDB</a> for querying Pinot.</p><p>For more information about PrestoDB connector for Pinot see the <a href="https://github.com/apache/pinot/tree/master/kubernetes/examples/helm#access-pinot-using-presto" target="_blank" rel="noopener noreferrer">Helm Chart of Pinot with Presto</a>
+Pinot-Presto connector is avilable with version <a href="https://github.com/prestodb/presto/pull/13504" target="_blank" rel="noopener noreferrer">0.229</a></p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="quick-example"></a>Quick example<a class="hash-link" href="#quick-example" title="Direct link to heading">#</a></h2><p>Pinot works very well for querying time series data with lots of Dimensions and Metrics.
+Filters and aggregations are easy and fast.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">SELECT sum(clicks), sum(impressions) FROM AdAnalyticsTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> WHERE ((daysSinceEpoch >= 17849 AND daysSinceEpoch <= 17856)) AND accountId IN (123456789)</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> GROUP BY daysSinceEpoch TOP 100</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="who-uses-pinot"></a>Who uses Pinot?<a class="hash-link" href="#who-uses-pinot" title="Direct link to heading">#</a></h2><p>Pinot powers several big players, including LinkedIn, Uber, Factual, Weibo, Slack and more..</p></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/about/what_is_pinot.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_13-_"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/docs/about/features_of_pinot"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Features of Pinot »</div></a></div></nav></div></div><div class="col col--3"><div class="tableOfContents_35-E thin-scrollbar"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#when-should-i-use-it" class="table-of-contents__link">When should I use it?</a></li><li><a href="#when-should-i-not-use-it" class="table-of-contents__link">When should I not use it?</a></li><li><a href="#quick-example" class="table-of-contents__link">Quick example</a></li><li><a href="#who-uses-pinot" class="table-of-contents__link">Who uses Pinot?</a></li></ul></div></div></div></div></main></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li 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href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Administration</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Community</h4><ul class="footer__items"><li class="footer__item"><a href="https://join.slack.com/t/apache-pinot/shared_invite/zt-5z7pav2f-yYtjZdVA~EDmrGkho87Vzw" target="_blank" rel="noopener noreferrer" class="footer__link-item">Slack</a></li><li class="footer__item"><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Github</a></li><li class="footer__item"><a href="https://twitter.com/ApachePinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Twitter</a></li><li class="footer__item"><a href="mailto:dev-subscribe@pinot.apache.org?Subject=SubscribeToPinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Mailing List</a></li></ul></div><div class="col footer__col"><h4 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+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
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Pinot also serves as the backend for to visualize and monitor 10,000+ business metrics.</li><li>Pinot runs on 1000+ nodes serving 100k+ queries while ingesting 1.5M+ events per second.</li></ul><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="uber"></a>Uber<a class="hash-link" href="#uber" title="Direct link to heading">#</a></h3><ul><li>Pinot powers both internal and external site facing analytics applications like Uber Eats Restaurant Analytics.</li></ul></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/about/who_use_pinot.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col 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Pinot also serves as the backend for to visualize and monitor 10,000+ business metrics.</li><li>Pinot runs on 1000+ nodes serving 100k+ queries while ingesting 1.5M+ events per second.</li></ul><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="uber"></a>Uber<a class="hash-link" href="#uber" title="Direct link to heading">#</a></h3><ul><li>Pinot powers both internal and external site facing analytics applications like Uber Eats Restaurant Analytics.</li></ul></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/about/who_use_pinot.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 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diff --git a/content/docs/administration/index.html b/content/docs/administration/index.html
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--- a/content/docs/administration/index.html
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@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,14 +11,14 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
<link rel="search" type="application/opensearchdescription+xml" title="Apache Pinot™" href="/opensearch.xml">
<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Ubuntu|Roboto|Source+Code+Pro">
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+<link rel="preload" href="/assets/js/main.a1de4389.js" as="script">
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class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/on-premise">Kubernetes</a></li><li class="menu__list-item"><a aria-current="page" class="menu__link menu__link--active active" tabindex="0" href="/docs/administration/installation/cloud/aws">AWS</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/gcp">GCP</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/azure">Azure</a></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Operating Systems</a></li></ul></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Components</a></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1 class="h1Heading_27L5">AWS Quickstart</h1></header><p>This document provides the basic instruction to set up a Kubernetes Cluster on <a href="https://aws.amazon.com/eks/" target="_blank" rel="noopener noreferrer">Amazon Elastic Kubernetes Service (Amazon EKS)</a></p><div class="alert alert--info alert--icon" role="alert"><i class="feather icon-info"></i> Because Pinot must be manually updated on Nix, new Pinot releases will be delayed. Generally new Pinot releases are made available within a few days.</div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="tooling-installation"></a>Tooling Installation<a class="hash-link" href="#tooling-installation" title="Direct link to heading">#</a></h2><ol><li><p>Install Pinot</p><p>Please follow this link (<a href="https://kubernetes.io/docs/tasks/tools/install-kubectl" target="_blank" rel="noopener noreferrer">https://kubernetes.io/docs/tasks/tools/install-kubectl</a>) to install kubectl.</p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-cli</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check kubectl version after installation:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info" role="alert">QuickStart scripts are tested under kubectl client version v1.16.3 and server version v1.13.12</div></li><li><p>Install Helm</p><p>Please follow this link (<a href="https://helm.sh/docs/using_helm/#installing-helm" target="_blank" rel="noopener noreferrer">https://helm.sh/docs/using_helm/#installing-helm</a>) to install helm.</p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-helm</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check helm version after installation.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info" role="alert"><ul><li>This QuickStart provides helm supports for helm v3.0.0 and v2.12.1.</li><li>Please pick the script based on your helm version.</li></ul></div></li><li><p>Install AWS CLI</p><p><a href="/docs/administration/installation/cloud/(https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-install.html#install-tool-bundled)">Install AWS CLI</a></p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">curl</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"https://d1vvhvl2y92vvt.cloudfront.net/awscli-exe-macos.zip"</span><span class="token plain"> -o </span><span class="token string" style="color:rgb(255, 121, 198)">"awscliv2.zip"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">unzip</span><span class="token plain"> awscliv2.zip</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">sudo</span><span class="token plain"> ./aws/install</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></li><li><p>Install Eksctl</p><p>Install <a href="https://docs.aws.amazon.com/eks/latest/userguide/eksctl.html#installing-eksctl" target="_blank" rel="noopener noreferrer">AWS CLI</a></p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew tap weaveworks/tap</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> weaveworks/tap/eksctl</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></li></ol><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="optional-login-to-your-aws-account"></a>(Optional) Login to your AWS account<a class="hash-link" href="#optional-login-to-your-aws-account" title="Direct link to heading">#</a></h2><p>For first time AWS user, please register your <a href="https://aws.amazon.com/" target="_blank" rel="noopener noreferrer">aws account</a></p><p>Once created the account, you can go to <a href="https://console.aws.amazon.com/iam/home#/home" target="_blank" rel="noopener noreferrer">AWS Identity and Access Management (IAM)</a> to create a user and create access keys under Security Credential tab.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">aws configure</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info alert--icon" role="alert"><i class="feather icon-info"></i> Environment variables AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY will override AWS configuration stored in file ~/.aws/credentials</div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="optional-create-a-kubernetes-clustereks-in-aws"></a>(Optional) Create a Kubernetes cluster(EKS) in AWS<a class="hash-link" href="#optional-create-a-kubernetes-clustereks-in-aws" title="Direct link to heading">#</a></h3><p>Below script will create a 3 nodes cluster named pinot-quickstart in us-west-2 with t3.small machines for demo purposes.
-Please modify the parameters in the example command below:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">EKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">eksctl create cluster </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${EKS_CLUSTER_NAME}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --version </span><span class="token number">1.14</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --region us-west-2 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --nodegroup-name standard-workers </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --node-type t3.small </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --nodes </span><span class="token number">3</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --nodes-min </span><span class="token number">3</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --nodes-max </span><span class="token number">4</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --node-ami auto</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can monitor cluster status by command:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">EKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">aws eks describe-cluster --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${EKS_CLUSTER_NAME}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Once the cluster is in ACTIVE status, it's ready to be used.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="connect-to-an-existing-cluster"></a>Connect to an existing cluster<a class="hash-link" href="#connect-to-an-existing-cluster" title="Direct link to heading">#</a></h2><p>Simply run below command to get the credential for the cluster pinot-quickstart that you just created or your existing cluster.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">EKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">aws eks update-kubeconfig --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${EKS_CLUSTER_NAME}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>To verify the connection, you can run:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl get nodes</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="pinot-quickstart"></a>Pinot Quickstart<a class="hash-link" href="#pinot-quickstart" title="Direct link to heading">#</a></h2><p>Please follow this <a href="/docs/administration/installation/cloud/on-premises">Kubernetes QuickStart</a> to deploy your Pinot Demo.</p><a class="jump-to jump-to--undefined" href="/docs/administration/installation/cloud/on-premises"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Kubernetes Quickstart</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="delete-a-kubernetes-cluster"></a>Delete a Kubernetes Cluster<a class="hash-link" href="#delete-a-kubernetes-cluster" title="Direct link to heading">#</a></h2><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">EKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">aws eks delete-cluster --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${EKS_CLUSTER_NAME}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/administration/installation/cloud/aws.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 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menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">About</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">Administration</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/running_locally">Running Pinot locally</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#" tabindex="0">Installation</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Containers</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#" tabindex="0">Cloud</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/on-premise">Kubernetes</a></li><li class="menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/docs/administration/installation/cloud/aws">AWS</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/gcp">GCP</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/azure">Azure</a></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Operating Systems</a></li></ul></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Components</a></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>AWS Quickstart</h1></header><p>This document provides the basic instruction to set up a Kubernetes Cluster on <a href="https://aws.amazon.com/eks/" target="_blank" rel="noopener noreferrer">Amazon Elastic Kubernetes Service (Amazon EKS)</a></p><div class="alert alert--info alert--icon" role="alert"><i class="feather icon-info"></i> Because Pinot must be manually updated on Nix, new Pinot releases will be delayed. Generally new Pinot releases are made available within a few days.</div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="tooling-installation"></a>Tooling Installation<a class="hash-link" href="#tooling-installation" title="Direct link to heading">#</a></h2><ol><li><p>Install Pinot</p><p>Please follow this link (<a href="https://kubernetes.io/docs/tasks/tools/install-kubectl" target="_blank" rel="noopener noreferrer">https://kubernetes.io/docs/tasks/tools/install-kubectl</a>) to install kubectl.</p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-cli</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check kubectl version after installation:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info" role="alert">QuickStart scripts are tested under kubectl client version v1.16.3 and server version v1.13.12</div></li><li><p>Install Helm</p><p>Please follow this link (<a href="https://helm.sh/docs/using_helm/#installing-helm" target="_blank" rel="noopener noreferrer">https://helm.sh/docs/using_helm/#installing-helm</a>) to install helm.</p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-helm</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check helm version after installation.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info" role="alert"><ul><li>This QuickStart provides helm supports for helm v3.0.0 and v2.12.1.</li><li>Please pick the script based on your helm version.</li></ul></div></li><li><p>Install AWS CLI</p><p><a href="/docs/administration/installation/cloud/(https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-install.html#install-tool-bundled)">Install AWS CLI</a></p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">curl</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"https://d1vvhvl2y92vvt.cloudfront.net/awscli-exe-macos.zip"</span><span class="token plain"> -o </span><span class="token string" style="color:rgb(255, 121, 198)">"awscliv2.zip"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">unzip</span><span class="token plain"> awscliv2.zip</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">sudo</span><span class="token plain"> ./aws/install</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></li><li><p>Install Eksctl</p><p>Install <a href="https://docs.aws.amazon.com/eks/latest/userguide/eksctl.html#installing-eksctl" target="_blank" rel="noopener noreferrer">AWS CLI</a></p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew tap weaveworks/tap</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> weaveworks/tap/eksctl</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></li></ol><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="optional-login-to-your-aws-account"></a>(Optional) Login to your AWS account<a class="hash-link" href="#optional-login-to-your-aws-account" title="Direct link to heading">#</a></h2><p>For first time AWS user, please register your <a href="https://aws.amazon.com/" target="_blank" rel="noopener noreferrer">aws account</a></p><p>Once created the account, you can go to <a href="https://console.aws.amazon.com/iam/home#/home" target="_blank" rel="noopener noreferrer">AWS Identity and Access Management (IAM)</a> to create a user and create access keys under Security Credential tab.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">aws configure</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info alert--icon" role="alert"><i class="feather icon-info"></i> Environment variables AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY will override AWS configuration stored in file ~/.aws/credentials</div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="optional-create-a-kubernetes-clustereks-in-aws"></a>(Optional) Create a Kubernetes cluster(EKS) in AWS<a class="hash-link" href="#optional-create-a-kubernetes-clustereks-in-aws" title="Direct link to heading">#</a></h3><p>Below script will create a 3 nodes cluster named pinot-quickstart in us-west-2 with t3.small machines for demo purposes.
+Please modify the parameters in the example command below:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">EKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">eksctl create cluster </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${EKS_CLUSTER_NAME}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --version </span><span class="token number">1.14</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --region us-west-2 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --nodegroup-name standard-workers </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --node-type t3.small </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --nodes </span><span class="token number">3</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --nodes-min </span><span class="token number">3</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --nodes-max </span><span class="token number">4</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --node-ami auto</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can monitor cluster status by command:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">EKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">aws eks describe-cluster --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${EKS_CLUSTER_NAME}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Once the cluster is in ACTIVE status, it's ready to be used.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="connect-to-an-existing-cluster"></a>Connect to an existing cluster<a class="hash-link" href="#connect-to-an-existing-cluster" title="Direct link to heading">#</a></h2><p>Simply run below command to get the credential for the cluster pinot-quickstart that you just created or your existing cluster.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">EKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">aws eks update-kubeconfig --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${EKS_CLUSTER_NAME}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>To verify the connection, you can run:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl get nodes</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="pinot-quickstart"></a>Pinot Quickstart<a class="hash-link" href="#pinot-quickstart" title="Direct link to heading">#</a></h2><p>Please follow this <a href="/docs/administration/installation/cloud/on-premises">Kubernetes QuickStart</a> to deploy your Pinot Demo.</p><a class="jump-to jump-to--undefined" href="/docs/administration/installation/cloud/on-premises"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Kubernetes Quickstart</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="delete-a-kubernetes-cluster"></a>Delete a Kubernetes Cluster<a class="hash-link" href="#delete-a-kubernetes-cluster" title="Direct link to heading">#</a></h2><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">EKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">aws eks delete-cluster --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${EKS_CLUSTER_NAME}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/administration/installation/cloud/aws.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" 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class="table-of-contents table-of-contents__left-border"><li><a href="#tooling-installation" class="table-of-contents__link">Tooling Installation</a></li><li><a href="#optional-login-to-your-aws-account" class="table-of-contents__link">(Optional) Login to your AWS account</a><ul><li><a href="#optional-create-a-kubernetes-clustereks-in-aws" class="table-of-contents__link">(Optional) Create a Kubernetes cluster(EKS) in AWS</a></li></ul></li><li><a href="#connect-to-an-existing-cluster" class="table-of-contents__link">Connect to an existing cluster</a></li><li><a href="#pinot-quickstart" class="table-of-contents__link">Pinot Quickstart</a></li><li><a href="#delete-a-kubernetes-cluster" class="table-of-contents__link">Delete a Kubernetes Cluster</a></li></ul></div></div></div></div></main></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li 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<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
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class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1 class="h1Heading_27L5">Azure Quickstart</h1></header><p>To set up a Kubernetes Cluster on <a href="https://azure.microsoft.com/en-us/services/kubernetes-service/" target="_blank" rel="noopener noreferrer">Azure Kubernetes Service (AKS)</a></p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="install-kubectl"></a>Install Kubectl<a class="hash-link" href="#install-kubectl" title="Direct link to heading">#</a></h2><p>Please follow this link (<a href="https://kubernetes.io/docs/tasks/tools/install-kubectl" target="_blank" rel="noopener noreferrer">https://kubernetes.io/docs/tasks/tools/install-kubectl</a>) to install kubectl.</p><ul><li>For Mac User</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-cli</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check kubectl version after installation.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info" role="alert">QuickStart scripts are tested under kubectl client version v1.16.3 and server version v1.13.12</div><ul><li>Install Helm</li></ul><p>Please follow this link (<a href="https://helm.sh/docs/using_helm/#installing-helm" target="_blank" rel="noopener noreferrer">https://helm.sh/docs/using_helm/#installing-helm</a>) to install helm.</p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-helm</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check helm version after installation.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info" role="alert">This QuickStart provides helm supports for helm v3.0.0 and v2.12.1. Please pick the script based on your helm version.</div><ul><li>Install Azure CLI</li></ul><p>Please follow this link to <a href="https://docs.microsoft.com/en-us/cli/azure/install-azure-cli?view=azure-cli-latest" target="_blank" rel="noopener noreferrer">install Azure CLI</a></p><ul><li>For Mac User</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew update </span><span class="token operator">&&</span><span class="token plain"> brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> azure-cli</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="optional-login-to-your-azure-account"></a>(Optional) Login to your Azure account<a class="hash-link" href="#optional-login-to-your-azure-account" title="Direct link to heading">#</a></h2><p>Below script will open default browser to sign-in to <strong>your Azure Account</strong>.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">az login</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="optional-create-a-resource-group"></a>(Optional) Create a Resource Group<a class="hash-link" href="#optional-create-a-resource-group" title="Direct link to heading">#</a></h2><p>Below script will create a resource group in location <code>eastus</code>.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_RESOURCE_GROUP</span><span class="token operator">=</span><span class="token plain">pinot-demo</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_RESOURCE_GROUP_LOCATION</span><span class="token operator">=</span><span class="token plain">eastus</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">az group create --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_RESOURCE_GROUP}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --location </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_RESOURCE_GROUP_LOCATION}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="optional-create-a-kubernetes-clusteraks-in-azure"></a>(Optional) Create a Kubernetes cluster(AKS) in Azure<a class="hash-link" href="#optional-create-a-kubernetes-clusteraks-in-azure" title="Direct link to heading">#</a></h2><p>Below script will create a <strong>3 nodes</strong> cluster named <strong>pinot-quickstart</strong> for demo purposes.
-Please modify the parameters in the example command below:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_RESOURCE_GROUP</span><span class="token operator">=</span><span class="token plain">pinot-demo</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">az aks create --resource-group </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_RESOURCE_GROUP}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_CLUSTER_NAME}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --node-count </span><span class="token number">3</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Once the command is succeed, it's ready to be used.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="connect-to-an-existing-cluster"></a>Connect to an existing cluster<a class="hash-link" href="#connect-to-an-existing-cluster" title="Direct link to heading">#</a></h2><p>Simply run below command to get the credential for the cluster <strong>pinot-quickstart</strong> that you just created or your existing cluster.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_RESOURCE_GROUP</span><span class="token operator">=</span><span class="token plain">pinot-demo</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">az aks get-credentials --resource-group </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_RESOURCE_GROUP}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_CLUSTER_NAME}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>To verify the connection, you can run:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl get nodes</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="pinot-quickstart"></a>Pinot Quickstart<a class="hash-link" href="#pinot-quickstart" title="Direct link to heading">#</a></h2><p>Please follow this <a href="/docs/administration/installation/cloud/on-premises">Kubernetes QuickStart</a> to deploy your Pinot Demo.</p><a class="jump-to jump-to--undefined" href="/docs/administration/installation/cloud/on-premises"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Kubernetes Quickstart</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="delete-a-kubernetes-cluster"></a>Delete a Kubernetes Cluster<a class="hash-link" href="#delete-a-kubernetes-cluster" title="Direct link to heading">#</a></h2><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_RESOURCE_GROUP</span><span class="token operator">=</span><span class="token plain">pinot-demo</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">az aks delete --resource-group </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_RESOURCE_GROUP}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_CLUSTER_NAME}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/administration/installation/cloud/azure.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 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class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/on-premise">Kubernetes</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/aws">AWS</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/gcp">GCP</a></li><li class="menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/docs/administration/installation/cloud/azure">Azure</a></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Operating Systems</a></li></ul></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Components</a></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>Azure Quickstart</h1></header><p>To set up a Kubernetes Cluster on <a href="https://azure.microsoft.com/en-us/services/kubernetes-service/" target="_blank" rel="noopener noreferrer">Azure Kubernetes Service (AKS)</a></p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="install-kubectl"></a>Install Kubectl<a class="hash-link" href="#install-kubectl" title="Direct link to heading">#</a></h2><p>Please follow this link (<a href="https://kubernetes.io/docs/tasks/tools/install-kubectl" target="_blank" rel="noopener noreferrer">https://kubernetes.io/docs/tasks/tools/install-kubectl</a>) to install kubectl.</p><ul><li>For Mac User</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-cli</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check kubectl version after installation.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info" role="alert">QuickStart scripts are tested under kubectl client version v1.16.3 and server version v1.13.12</div><ul><li>Install Helm</li></ul><p>Please follow this link (<a href="https://helm.sh/docs/using_helm/#installing-helm" target="_blank" rel="noopener noreferrer">https://helm.sh/docs/using_helm/#installing-helm</a>) to install helm.</p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-helm</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check helm version after installation.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info" role="alert">This QuickStart provides helm supports for helm v3.0.0 and v2.12.1. Please pick the script based on your helm version.</div><ul><li>Install Azure CLI</li></ul><p>Please follow this link to <a href="https://docs.microsoft.com/en-us/cli/azure/install-azure-cli?view=azure-cli-latest" target="_blank" rel="noopener noreferrer">install Azure CLI</a></p><ul><li>For Mac User</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew update </span><span class="token operator">&&</span><span class="token plain"> brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> azure-cli</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="optional-login-to-your-azure-account"></a>(Optional) Login to your Azure account<a class="hash-link" href="#optional-login-to-your-azure-account" title="Direct link to heading">#</a></h2><p>Below script will open default browser to sign-in to <strong>your Azure Account</strong>.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">az login</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="optional-create-a-resource-group"></a>(Optional) Create a Resource Group<a class="hash-link" href="#optional-create-a-resource-group" title="Direct link to heading">#</a></h2><p>Below script will create a resource group in location <code>eastus</code>.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_RESOURCE_GROUP</span><span class="token operator">=</span><span class="token plain">pinot-demo</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_RESOURCE_GROUP_LOCATION</span><span class="token operator">=</span><span class="token plain">eastus</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">az group create --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_RESOURCE_GROUP}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --location </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_RESOURCE_GROUP_LOCATION}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="optional-create-a-kubernetes-clusteraks-in-azure"></a>(Optional) Create a Kubernetes cluster(AKS) in Azure<a class="hash-link" href="#optional-create-a-kubernetes-clusteraks-in-azure" title="Direct link to heading">#</a></h2><p>Below script will create a <strong>3 nodes</strong> cluster named <strong>pinot-quickstart</strong> for demo purposes.
+Please modify the parameters in the example command below:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_RESOURCE_GROUP</span><span class="token operator">=</span><span class="token plain">pinot-demo</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">az aks create --resource-group </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_RESOURCE_GROUP}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_CLUSTER_NAME}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --node-count </span><span class="token number">3</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Once the command is succeed, it's ready to be used.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="connect-to-an-existing-cluster"></a>Connect to an existing cluster<a class="hash-link" href="#connect-to-an-existing-cluster" title="Direct link to heading">#</a></h2><p>Simply run below command to get the credential for the cluster <strong>pinot-quickstart</strong> that you just created or your existing cluster.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_RESOURCE_GROUP</span><span class="token operator">=</span><span class="token plain">pinot-demo</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">az aks get-credentials --resource-group </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_RESOURCE_GROUP}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_CLUSTER_NAME}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>To verify the connection, you can run:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl get nodes</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="pinot-quickstart"></a>Pinot Quickstart<a class="hash-link" href="#pinot-quickstart" title="Direct link to heading">#</a></h2><p>Please follow this <a href="/docs/administration/installation/cloud/on-premises">Kubernetes QuickStart</a> to deploy your Pinot Demo.</p><a class="jump-to jump-to--undefined" href="/docs/administration/installation/cloud/on-premises"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Kubernetes Quickstart</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="delete-a-kubernetes-cluster"></a>Delete a Kubernetes Cluster<a class="hash-link" href="#delete-a-kubernetes-cluster" title="Direct link to heading">#</a></h2><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_RESOURCE_GROUP</span><span class="token operator">=</span><span class="token plain">pinot-demo</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">AKS_CLUSTER_NAME</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">az aks delete --resource-group </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_RESOURCE_GROUP}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${AKS_CLUSTER_NAME}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a 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@@ -3,7 +3,7 @@
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class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1 class="h1Heading_27L5">GCP Quickstart</h1></header><p>To have basic set with <a href="https://cloud.google.com/kubernetes-engine" target="_blank" rel="noopener noreferrer">Google Kubernetes Engine(GKE)</a> on GCP:</p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="tooling-installation"></a>Tooling Installation<a class="hash-link" href="#tooling-installation" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="install-kubectl"></a>Install Kubectl<a class="hash-link" href="#install-kubectl" title="Direct link to heading">#</a></h3><p>Please follow this link (<a href="https://kubernetes.io/docs/tasks/tools/install-kubectl" target="_blank" rel="noopener noreferrer">https://kubernetes.io/docs/tasks/tools/install-kubectl</a>) to install kubectl.</p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-cli</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check kubectl version after installation.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>QuickStart scripts are tested under kubectl client version v1.16.3 and server version v1.13.12</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="install-helm"></a>Install Helm<a class="hash-link" href="#install-helm" title="Direct link to heading">#</a></h3><p>Please follow this <a href="https://helm.sh/docs/using_helm/#installing-helm" target="_blank" rel="noopener noreferrer">link to install helm</a></p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-helm</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check helm version after installation.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info" role="alert">This QuickStart provides helm supports for helm v3.0.0 and v2.12.1. Please pick the script based on your helm version.</div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="install-google-cloud-sdk"></a>Install Google Cloud SDK<a class="hash-link" href="#install-google-cloud-sdk" title="Direct link to heading">#</a></h2><p>Please follow this link to <a href="https://cloud.google.com/sdk/install" target="_blank" rel="noopener noreferrer">install Google Cloud SDK</a></p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="for-mac-user"></a>For Mac User<a class="hash-link" href="#for-mac-user" title="Direct link to heading">#</a></h3><ul><li>Install Google Cloud SDK</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">curl</span><span class="token plain"> https://sdk.cloud.google.com </span><span class="token operator">|</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Restart your shell</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -l </span><span class="token environment constant" style="color:rgb(189, 147, 249)">$SHELL</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="optional-initialize-google-cloud-environment"></a>(Optional) Initialize Google Cloud Environment<a class="hash-link" href="#optional-initialize-google-cloud-environment" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">gcloud init</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="optional-create-a-kubernetes-clustergke-in-google-cloud"></a>(Optional) Create a Kubernetes cluster(GKE) in Google Cloud<a class="hash-link" href="#optional-create-a-kubernetes-clustergke-in-google-cloud" title="Direct link to heading">#</a></h3><p>Below script will create a 3 nodes cluster named pinot-quickstart in <code>us-west1-b</code> with <code>n1-standard-2</code> machines for demo purposes.</p><p>Please modify the parameters in the example command below:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_PROJECT</span><span class="token operator">=</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">your gcloud project name</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_ZONE</span><span class="token operator">=</span><span class="token plain">us-west1-b</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_CLUSTER</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_MACHINE_TYPE</span><span class="token operator">=</span><span class="token plain">n1-standard-2</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_NUM_NODES</span><span class="token operator">=</span><span class="token number">3</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">gcloud container clusters create </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_CLUSTER}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --num-nodes</span><span class="token operator">=</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_NUM_NODES}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --machine-type</span><span class="token operator">=</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_MACHINE_TYPE}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --zone</span><span class="token operator">=</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_ZONE}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --project</span><span class="token operator">=</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_PROJECT}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can monitor cluster status by command:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">gcloud compute instances list</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Once the cluster is in RUNNING status, it's ready to be used.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="connect-to-an-existing-cluster"></a>Connect to an existing cluster<a class="hash-link" href="#connect-to-an-existing-cluster" title="Direct link to heading">#</a></h3><p>Simply run below command to get the credential for the cluster pinot-quickstart that you just created or your existing cluster.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_PROJECT</span><span class="token operator">=</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">your gcloud project name</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_ZONE</span><span class="token operator">=</span><span class="token plain">us-west1-b</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_CLUSTER</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">gcloud container clusters get-credentials </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_CLUSTER}</span><span class="token plain"> --zone </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_ZONE}</span><span class="token plain"> --project </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_PROJECT}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>To verify the connection, you can run:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl get nodes</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="pinot-quickstart"></a>Pinot Quickstart<a class="hash-link" href="#pinot-quickstart" title="Direct link to heading">#</a></h3><p>Please follow this <a href="/docs/administration/installation/cloud/on-premises">Kubernetes QuickStart</a> to deploy your Pinot Demo.</p><a class="jump-to jump-to--undefined" href="/docs/administration/installation/cloud/on-premises"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Kubernetes Quickstart</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="delete-a-kubernetes-cluster"></a>Delete a Kubernetes Cluster<a class="hash-link" href="#delete-a-kubernetes-cluster" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_ZONE</span><span class="token operator">=</span><span class="token plain">us-west1-b</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">gcloud container clusters delete pinot-quickstart --zone</span><span class="token operator">=</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_ZONE}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/administration/installation/cloud/gcp.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_3DPF"></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" 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menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">About</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">Administration</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/running_locally">Running Pinot locally</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#" tabindex="0">Installation</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Containers</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#" tabindex="0">Cloud</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a 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docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>GCP Quickstart</h1></header><p>To have basic set with <a href="https://cloud.google.com/kubernetes-engine" target="_blank" rel="noopener noreferrer">Google Kubernetes Engine(GKE)</a> on GCP:</p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="tooling-installation"></a>Tooling Installation<a class="hash-link" href="#tooling-installation" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="install-kubectl"></a>Install Kubectl<a class="hash-link" href="#install-kubectl" title="Direct link to heading">#</a></h3><p>Please follow this link (<a href="https://kubernetes.io/docs/tasks/tools/install-kubectl" target="_blank" rel="noopener noreferrer">https://kubernetes.io/docs/tasks/tools/install-kubectl</a>) to install kubectl.</p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-cli</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check kubectl version after installation.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>QuickStart scripts are tested under kubectl client version v1.16.3 and server version v1.13.12</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="install-helm"></a>Install Helm<a class="hash-link" href="#install-helm" title="Direct link to heading">#</a></h3><p>Please follow this <a href="https://helm.sh/docs/using_helm/#installing-helm" target="_blank" rel="noopener noreferrer">link to install helm</a></p><p>For Mac User</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">brew </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> kubernetes-helm</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Please check helm version after installation.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm version</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="alert alert--info" role="alert">This QuickStart provides helm supports for helm v3.0.0 and v2.12.1. Please pick the script based on your helm version.</div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="install-google-cloud-sdk"></a>Install Google Cloud SDK<a class="hash-link" href="#install-google-cloud-sdk" title="Direct link to heading">#</a></h2><p>Please follow this link to <a href="https://cloud.google.com/sdk/install" target="_blank" rel="noopener noreferrer">install Google Cloud SDK</a></p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="for-mac-user"></a>For Mac User<a class="hash-link" href="#for-mac-user" title="Direct link to heading">#</a></h3><ul><li>Install Google Cloud SDK</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">curl</span><span class="token plain"> https://sdk.cloud.google.com </span><span class="token operator">|</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Restart your shell</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -l </span><span class="token environment constant" style="color:rgb(189, 147, 249)">$SHELL</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="optional-initialize-google-cloud-environment"></a>(Optional) Initialize Google Cloud Environment<a class="hash-link" href="#optional-initialize-google-cloud-environment" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">gcloud init</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="optional-create-a-kubernetes-clustergke-in-google-cloud"></a>(Optional) Create a Kubernetes cluster(GKE) in Google Cloud<a class="hash-link" href="#optional-create-a-kubernetes-clustergke-in-google-cloud" title="Direct link to heading">#</a></h3><p>Below script will create a 3 nodes cluster named pinot-quickstart in <code>us-west1-b</code> with <code>n1-standard-2</code> machines for demo purposes.</p><p>Please modify the parameters in the example command below:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_PROJECT</span><span class="token operator">=</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">your gcloud project name</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_ZONE</span><span class="token operator">=</span><span class="token plain">us-west1-b</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_CLUSTER</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_MACHINE_TYPE</span><span class="token operator">=</span><span class="token plain">n1-standard-2</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_NUM_NODES</span><span class="token operator">=</span><span class="token number">3</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">gcloud container clusters create </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_CLUSTER}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --num-nodes</span><span class="token operator">=</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_NUM_NODES}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --machine-type</span><span class="token operator">=</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_MACHINE_TYPE}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --zone</span><span class="token operator">=</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_ZONE}</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --project</span><span class="token operator">=</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_PROJECT}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can monitor cluster status by command:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">gcloud compute instances list</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Once the cluster is in RUNNING status, it's ready to be used.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="connect-to-an-existing-cluster"></a>Connect to an existing cluster<a class="hash-link" href="#connect-to-an-existing-cluster" title="Direct link to heading">#</a></h3><p>Simply run below command to get the credential for the cluster pinot-quickstart that you just created or your existing cluster.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_PROJECT</span><span class="token operator">=</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">your gcloud project name</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_ZONE</span><span class="token operator">=</span><span class="token plain">us-west1-b</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_CLUSTER</span><span class="token operator">=</span><span class="token plain">pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">gcloud container clusters get-credentials </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_CLUSTER}</span><span class="token plain"> --zone </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_ZONE}</span><span class="token plain"> --project </span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_PROJECT}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>To verify the connection, you can run:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl get nodes</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="pinot-quickstart"></a>Pinot Quickstart<a class="hash-link" href="#pinot-quickstart" title="Direct link to heading">#</a></h3><p>Please follow this <a href="/docs/administration/installation/cloud/on-premises">Kubernetes QuickStart</a> to deploy your Pinot Demo.</p><a class="jump-to jump-to--undefined" href="/docs/administration/installation/cloud/on-premises"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Kubernetes Quickstart</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="delete-a-kubernetes-cluster"></a>Delete a Kubernetes Cluster<a class="hash-link" href="#delete-a-kubernetes-cluster" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">GCLOUD_ZONE</span><span class="token operator">=</span><span class="token plain">us-west1-b</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">gcloud container clusters delete pinot-quickstart --zone</span><span class="token operator">=</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${GCLOUD_ZONE}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/administration/installation/cloud/gcp.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 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class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1 class="h1Heading_27L5">Running Pinot in Kubernetes</h1></header><p>This QuickStart assumes the existence of Kubernetes Cluster. Please follow below links to setup your Kubernetes cluster in local or major cloud vendors.</p><blockquote><b>Prerequisites:</b> <br><p> <a href="https://docs.docker.com/docker-for-mac/kubernetes/" target="_blank" rel="noopener noreferrer">Enable Kubernetes on Docker-Desktop</a><br> <a href="https://kubernetes.io/docs/tasks/tools/install-minikube/" target="_blank" rel="noopener noreferrer">Setup a Kubernetes Cluster using Amazon Elastic Kubernetes Service (Amazon EKS)</a> <br> <a href="https://kubernetes.io/docs/tasks/tools/install-minikube/" target="_blank" rel="noopener noreferrer">Setup a Kubernetes Cluster using Google Kubernetes Engine(GKE)</a> <br> <a href="https://kubernetes.io/docs/tasks/tools/install-minikube/" target="_blank" rel="noopener noreferrer">Setup a Kubernetes Cluster using Azure Kubernetes Service (AKS)</a> <br> </p></blockquote><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="setup-a-pinot-cluster-for-demo"></a>Setup a Pinot cluster for demo<a class="hash-link" href="#setup-a-pinot-cluster-for-demo" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="update-helm-dependency"></a>Update helm dependency<a class="hash-link" href="#update-helm-dependency" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm dependency update</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="start-pinot-with-helm"></a>Start Pinot with Helm<a class="hash-link" href="#start-pinot-with-helm" title="Direct link to heading">#</a></h3><ul><li>For Helm v2.12.1</li></ul><p>If cluster is just initialized, ensure helm is initialized by running:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm init --service-account tiller</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Then deploy pinot cluster by:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> --namespace </span><span class="token string" style="color:rgb(255, 121, 198)">"pinot-quickstart"</span><span class="token plain"> --name </span><span class="token string" style="color:rgb(255, 121, 198)">"pinot"</span><span class="token plain"> </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">.</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>For Helm v3.0.0</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl create ns pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> -n pinot-quickstart pinot </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">.</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="troubleshooting-for-helm-v2121"></a>Troubleshooting (For helm v2.12.1)<a class="hash-link" href="#troubleshooting-for-helm-v2121" title="Direct link to heading">#</a></h2><ul><li>Error: Please run below command if encountering issue:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">Error: could not </span><span class="token function" style="color:rgb(80, 250, 123)">find</span><span class="token plain"> tiller".</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Resolution:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl -n kube-system delete deployment tiller-deploy</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl -n kube-system delete service/tiller-deploy</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm init --service-account tiller</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Error: Please run below command if encountering permission issue:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">Error: release pinot failed: namespaces </span><span class="token string" style="color:rgb(255, 121, 198)">"pinot-quickstart"</span><span class="token plain"> is forbidden: User </span><span class="token string" style="color:rgb(255, 121, 198)">"system:serviceaccount:kube-system:default"</span><span class="token plain"> cannot get resource </span><span class="token string" style="color:rgb(255, 121, 198)">"namespaces"</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">in</span><span class="token plain"> API group </span><span class="token string" style="color:rgb(255, 121, 198)">""</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">in</span><span class="token plain"> the namespace </span><span class="token string" style="color:rgb(255, 121, 198)">"pinot-quickstart"</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Resolution:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl apply -f helm-rbac.yaml</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Check deployment status</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl get all -n pinot-quickstart</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="load-data-into-pinot-through-kafka"></a>Load data into Pinot through Kafka<a class="hash-link" href="#load-data-into-pinot-through-kafka" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="bring-up-a-kafka-cluster-for-realtime-data-ingestion"></a>Bring up a Kafka Cluster for realtime data ingestion<a class="hash-link" href="#bring-up-a-kafka-cluster-for-realtime-data-ingestion" title="Direct link to heading">#</a></h3><ul><li>For helm v2.12.1</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm repo </span><span class="token function" style="color:rgb(80, 250, 123)">add</span><span class="token plain"> incubator https://charts.helm.sh/incubator</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> --namespace </span><span class="token string" style="color:rgb(255, 121, 198)">"pinot-quickstart"</span><span class="token plain"> --name kafka incubator/kafka</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>For helm v3.0.0</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm repo </span><span class="token function" style="color:rgb(80, 250, 123)">add</span><span class="token plain"> incubator https://charts.helm.sh/incubator</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> -n pinot-quickstart kafka incubator/kafka --set </span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">replicas</span><span class="token operator">=</span><span class="token number">1</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="check-kafka-deployment-status"></a>Check Kafka deployment status<a class="hash-link" href="#check-kafka-deployment-status" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl get all -n pinot-quickstart </span><span class="token operator">|</span><span class="token function" style="color:rgb(80, 250, 123)">grep</span><span class="token plain"> kafka</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Ensure Kafka deployment is ready before executing the scripts in next steps:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">pod/kafka-0 </span><span class="token number">1</span><span class="token plain">/1 Running </span><span class="token number">0</span><span class="token plain"> 2m</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">pod/kafka-zookeeper-0 </span><span class="token number">1</span><span class="token plain">/1 Running </span><span class="token number">0</span><span class="token plain"> 10m</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">pod/kafka-zookeeper-1 </span><span class="token number">1</span><span class="token plain">/1 Running </span><span class="token number">0</span><span class="token plain"> 9m</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">pod/kafka-zookeeper-2 </span><span class="token number">1</span><span class="token plain">/1 Running </span><span class="token number">0</span><span class="token plain"> 8m</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="create-kafka-topics"></a>Create Kafka topics<a class="hash-link" href="#create-kafka-topics" title="Direct link to heading">#</a></h3><p>Below scripts will create two Kafka topics for data ingestion:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl -n pinot-quickstart </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> kafka-0 -- kafka-topics --zookeeper kafka-zookeeper:2181 --topic flights-realtime --create --partitions </span><span class="token number">1</span><span class="token plain"> --replication-factor </span><span class="token number">1</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl -n pinot-quickstart </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> kafka-0 -- kafka-topics --zookeeper kafka-zookeeper:2181 --topic flights-realtime-avro --create --partitions </span><span class="token number">1</span><span class="token plain"> --replication-factor </span><span class="token number">1</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="load-data-into-kafka-and-create-pinot-schematables"></a>Load data into Kafka and Create Pinot Schema/Tables<a class="hash-link" href="#load-data-into-kafka-and-create-pinot-schematables" title="Direct link to heading">#</a></h3><p>Below script will deploy 3 batch jobs</p><ul><li>Ingest 19492 Json messages to Kafka topic <code>flights-realtime</code> at a speed of 1 msg/sec</li><li>Ingest 19492 Avro messages to Kafka topic <code>flights-realtime-avro</code> at a speed of 1 msg/sec</li><li>Upload Pinot schema <code>airlineStats</code></li><li>Create Pinot Table <code>airlineStats</code> to ingest data from Json encoded Kafka topic <code>flights-realtime</code></li><li>Create Pinot Table <code>airlineStatsAvro</code> to ingest data from Avro encoded Kafka topic <code>flights-realtime-avro</code></li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl apply -f pinot-realtime-quickstart.yml</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="how-to-query-pinot-data"></a>How to query pinot data<a class="hash-link" href="#how-to-query-pinot-data" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="pinot-query-console"></a>Pinot Query Console<a class="hash-link" href="#pinot-query-console" title="Direct link to heading">#</a></h3><p>Please use below script to do local port-forwarding and open Pinot query console on your web browser.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./query-pinot-data.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="use-superset-to-query-pinot"></a>Use Superset to query Pinot<a class="hash-link" href="#use-superset-to-query-pinot" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="bring-up-superset"></a>Bring up Superset<a class="hash-link" href="#bring-up-superset" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl apply -f superset.yaml</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="first-time-set-up-admin-account"></a>(First time) Set up Admin account<a class="hash-link" href="#first-time-set-up-admin-account" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -it pod/superset-0 -n pinot-quickstart -- </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span><span class="token plain"> -c </span><span class="token string" style="color:rgb(255, 121, 198)">'export FLASK_APP=superset:app && flask fab create-admin'</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="first-time-init-superset"></a>(First time) Init Superset<a class="hash-link" href="#first-time-init-superset" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -it pod/superset-0 -n pinot-quickstart -- </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span><span class="token plain"> -c </span><span class="token string" style="color:rgb(255, 121, 198)">'superset db upgrade'</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -it pod/superset-0 -n pinot-quickstart -- </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span><span class="token plain"> -c </span><span class="token string" style="color:rgb(255, 121, 198)">'superset init'</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="load-demo-data-source"></a>Load Demo Data source<a class="hash-link" href="#load-demo-data-source" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -it pod/superset-0 -n pinot-quickstart -- </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span><span class="token plain"> -c </span><span class="token string" style="color:rgb(255, 121, 198)">'superset import_datasources -p /etc/superset/pinot_example_datasource.yaml'</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -it pod/superset-0 -n pinot-quickstart -- </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span><span class="token plain"> -c </span><span class="token string" style="color:rgb(255, 121, 198)">'superset import_dashboards -p /etc/superset/pinot_example_dashboard.json'</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="access-superset-ui"></a>Access Superset UI<a class="hash-link" href="#access-superset-ui" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./open-superset-ui.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can open the imported dashboard by click Dashboards banner then click on AirlineStats.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="access-pinot-using-presto"></a>Access Pinot Using Presto<a class="hash-link" href="#access-pinot-using-presto" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="deploy-presto-with-pinot-plugin"></a>Deploy Presto with Pinot Plugin<a class="hash-link" href="#deploy-presto-with-pinot-plugin" title="Direct link to heading">#</a></h3><p>You can run below command to deploy a customized Presto with Pinot plugin.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl apply -f presto-coordinator.yaml</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="query-presto-using-presto-cli"></a>Query Presto using Presto CLI<a class="hash-link" href="#query-presto-using-presto-cli" title="Direct link to heading">#</a></h3><p>Once Presto is deployed, you could run below command.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./pinot-presto-cli.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="sample-queries-to-execute"></a>Sample queries to execute<a class="hash-link" href="#sample-queries-to-execute" title="Direct link to heading">#</a></h3><ul><li>List all catalogs</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">presto:default> show catalogs;</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">Catalog</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">---------</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> pinot</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> system</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">2</span><span class="token plain"> rows</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img 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menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">About</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">Administration</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/running_locally">Running Pinot locally</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#" tabindex="0">Installation</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Containers</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#" tabindex="0">Cloud</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/docs/administration/installation/cloud/on-premise">Kubernetes</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/aws">AWS</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/gcp">GCP</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/cloud/azure">Azure</a></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Operating Systems</a></li></ul></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Components</a></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>Running Pinot in Kubernetes</h1></header><p>This QuickStart assumes the existence of Kubernetes Cluster. Please follow below links to setup your Kubernetes cluster in local or major cloud vendors.</p><blockquote><b>Prerequisites:</b> <br><p> <a href="https://docs.docker.com/docker-for-mac/kubernetes/" target="_blank" rel="noopener noreferrer">Enable Kubernetes on Docker-Desktop</a><br> <a href="https://kubernetes.io/docs/tasks/tools/install-minikube/" target="_blank" rel="noopener noreferrer">Setup a Kubernetes Cluster using Amazon Elastic Kubernetes Service (Amazon EKS)</a> <br> <a href="https://kubernetes.io/docs/tasks/tools/install-minikube/" target="_blank" rel="noopener noreferrer">Setup a Kubernetes Cluster using Google Kubernetes Engine(GKE)</a> <br> <a href="https://kubernetes.io/docs/tasks/tools/install-minikube/" target="_blank" rel="noopener noreferrer">Setup a Kubernetes Cluster using Azure Kubernetes Service (AKS)</a> <br> </p></blockquote><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="setup-a-pinot-cluster-for-demo"></a>Setup a Pinot cluster for demo<a class="hash-link" href="#setup-a-pinot-cluster-for-demo" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="update-helm-dependency"></a>Update helm dependency<a class="hash-link" href="#update-helm-dependency" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm dependency update</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="start-pinot-with-helm"></a>Start Pinot with Helm<a class="hash-link" href="#start-pinot-with-helm" title="Direct link to heading">#</a></h3><ul><li>For Helm v2.12.1</li></ul><p>If cluster is just initialized, ensure helm is initialized by running:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm init --service-account tiller</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Then deploy pinot cluster by:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> --namespace </span><span class="token string" style="color:rgb(255, 121, 198)">"pinot-quickstart"</span><span class="token plain"> --name </span><span class="token string" style="color:rgb(255, 121, 198)">"pinot"</span><span class="token plain"> </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">.</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>For Helm v3.0.0</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl create ns pinot-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> -n pinot-quickstart pinot </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">.</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="troubleshooting-for-helm-v2121"></a>Troubleshooting (For helm v2.12.1)<a class="hash-link" href="#troubleshooting-for-helm-v2121" title="Direct link to heading">#</a></h2><ul><li>Error: Please run below command if encountering issue:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">Error: could not </span><span class="token function" style="color:rgb(80, 250, 123)">find</span><span class="token plain"> tiller".</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Resolution:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl -n kube-system delete deployment tiller-deploy</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl -n kube-system delete service/tiller-deploy</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm init --service-account tiller</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Error: Please run below command if encountering permission issue:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">Error: release pinot failed: namespaces </span><span class="token string" style="color:rgb(255, 121, 198)">"pinot-quickstart"</span><span class="token plain"> is forbidden: User </span><span class="token string" style="color:rgb(255, 121, 198)">"system:serviceaccount:kube-system:default"</span><span class="token plain"> cannot get resource </span><span class="token string" style="color:rgb(255, 121, 198)">"namespaces"</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">in</span><span class="token plain"> API group </span><span class="token string" style="color:rgb(255, 121, 198)">""</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">in</span><span class="token plain"> the namespace </span><span class="token string" style="color:rgb(255, 121, 198)">"pinot-quickstart"</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Resolution:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl apply -f helm-rbac.yaml</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Check deployment status</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl get all -n pinot-quickstart</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="load-data-into-pinot-through-kafka"></a>Load data into Pinot through Kafka<a class="hash-link" href="#load-data-into-pinot-through-kafka" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="bring-up-a-kafka-cluster-for-realtime-data-ingestion"></a>Bring up a Kafka Cluster for realtime data ingestion<a class="hash-link" href="#bring-up-a-kafka-cluster-for-realtime-data-ingestion" title="Direct link to heading">#</a></h3><ul><li>For helm v2.12.1</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm repo </span><span class="token function" style="color:rgb(80, 250, 123)">add</span><span class="token plain"> incubator https://charts.helm.sh/incubator</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> --namespace </span><span class="token string" style="color:rgb(255, 121, 198)">"pinot-quickstart"</span><span class="token plain"> --name kafka incubator/kafka</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>For helm v3.0.0</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm repo </span><span class="token function" style="color:rgb(80, 250, 123)">add</span><span class="token plain"> incubator https://charts.helm.sh/incubator</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> -n pinot-quickstart kafka incubator/kafka --set </span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">replicas</span><span class="token operator">=</span><span class="token number">1</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="check-kafka-deployment-status"></a>Check Kafka deployment status<a class="hash-link" href="#check-kafka-deployment-status" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl get all -n pinot-quickstart </span><span class="token operator">|</span><span class="token function" style="color:rgb(80, 250, 123)">grep</span><span class="token plain"> kafka</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Ensure Kafka deployment is ready before executing the scripts in next steps:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">pod/kafka-0 </span><span class="token number">1</span><span class="token plain">/1 Running </span><span class="token number">0</span><span class="token plain"> 2m</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">pod/kafka-zookeeper-0 </span><span class="token number">1</span><span class="token plain">/1 Running </span><span class="token number">0</span><span class="token plain"> 10m</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">pod/kafka-zookeeper-1 </span><span class="token number">1</span><span class="token plain">/1 Running </span><span class="token number">0</span><span class="token plain"> 9m</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">pod/kafka-zookeeper-2 </span><span class="token number">1</span><span class="token plain">/1 Running </span><span class="token number">0</span><span class="token plain"> 8m</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="create-kafka-topics"></a>Create Kafka topics<a class="hash-link" href="#create-kafka-topics" title="Direct link to heading">#</a></h3><p>Below scripts will create two Kafka topics for data ingestion:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl -n pinot-quickstart </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> kafka-0 -- kafka-topics --zookeeper kafka-zookeeper:2181 --topic flights-realtime --create --partitions </span><span class="token number">1</span><span class="token plain"> --replication-factor </span><span class="token number">1</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl -n pinot-quickstart </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> kafka-0 -- kafka-topics --zookeeper kafka-zookeeper:2181 --topic flights-realtime-avro --create --partitions </span><span class="token number">1</span><span class="token plain"> --replication-factor </span><span class="token number">1</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="load-data-into-kafka-and-create-pinot-schematables"></a>Load data into Kafka and Create Pinot Schema/Tables<a class="hash-link" href="#load-data-into-kafka-and-create-pinot-schematables" title="Direct link to heading">#</a></h3><p>Below script will deploy 3 batch jobs</p><ul><li>Ingest 19492 Json messages to Kafka topic <code>flights-realtime</code> at a speed of 1 msg/sec</li><li>Ingest 19492 Avro messages to Kafka topic <code>flights-realtime-avro</code> at a speed of 1 msg/sec</li><li>Upload Pinot schema <code>airlineStats</code></li><li>Create Pinot Table <code>airlineStats</code> to ingest data from Json encoded Kafka topic <code>flights-realtime</code></li><li>Create Pinot Table <code>airlineStatsAvro</code> to ingest data from Avro encoded Kafka topic <code>flights-realtime-avro</code></li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl apply -f pinot-realtime-quickstart.yml</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="how-to-query-pinot-data"></a>How to query pinot data<a class="hash-link" href="#how-to-query-pinot-data" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="pinot-query-console"></a>Pinot Query Console<a class="hash-link" href="#pinot-query-console" title="Direct link to heading">#</a></h3><p>Please use below script to do local port-forwarding and open Pinot query console on your web browser.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./query-pinot-data.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="use-superset-to-query-pinot"></a>Use Superset to query Pinot<a class="hash-link" href="#use-superset-to-query-pinot" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="bring-up-superset"></a>Bring up Superset<a class="hash-link" href="#bring-up-superset" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl apply -f superset.yaml</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="first-time-set-up-admin-account"></a>(First time) Set up Admin account<a class="hash-link" href="#first-time-set-up-admin-account" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -it pod/superset-0 -n pinot-quickstart -- </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span><span class="token plain"> -c </span><span class="token string" style="color:rgb(255, 121, 198)">'export FLASK_APP=superset:app && flask fab create-admin'</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="first-time-init-superset"></a>(First time) Init Superset<a class="hash-link" href="#first-time-init-superset" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -it pod/superset-0 -n pinot-quickstart -- </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span><span class="token plain"> -c </span><span class="token string" style="color:rgb(255, 121, 198)">'superset db upgrade'</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -it pod/superset-0 -n pinot-quickstart -- </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span><span class="token plain"> -c </span><span class="token string" style="color:rgb(255, 121, 198)">'superset init'</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="load-demo-data-source"></a>Load Demo Data source<a class="hash-link" href="#load-demo-data-source" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -it pod/superset-0 -n pinot-quickstart -- </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span><span class="token plain"> -c </span><span class="token string" style="color:rgb(255, 121, 198)">'superset import_datasources -p /etc/superset/pinot_example_datasource.yaml'</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">exec</span><span class="token plain"> -it pod/superset-0 -n pinot-quickstart -- </span><span class="token function" style="color:rgb(80, 250, 123)">bash</span><span class="token plain"> -c </span><span class="token string" style="color:rgb(255, 121, 198)">'superset import_dashboards -p /etc/superset/pinot_example_dashboard.json'</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="access-superset-ui"></a>Access Superset UI<a class="hash-link" href="#access-superset-ui" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./open-superset-ui.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can open the imported dashboard by click Dashboards banner then click on AirlineStats.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="access-pinot-using-presto"></a>Access Pinot Using Presto<a class="hash-link" href="#access-pinot-using-presto" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="deploy-presto-with-pinot-plugin"></a>Deploy Presto with Pinot Plugin<a class="hash-link" href="#deploy-presto-with-pinot-plugin" title="Direct link to heading">#</a></h3><p>You can run below command to deploy a customized Presto with Pinot plugin.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl apply -f presto-coordinator.yaml</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="query-presto-using-presto-cli"></a>Query Presto using Presto CLI<a class="hash-link" href="#query-presto-using-presto-cli" title="Direct link to heading">#</a></h3><p>Once Presto is deployed, you could run below command.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./pinot-presto-cli.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="sample-queries-to-execute"></a>Sample queries to execute<a class="hash-link" href="#sample-queries-to-execute" title="Direct link to heading">#</a></h3><ul><li>List all catalogs</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">presto:default> show catalogs;</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">Catalog</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">---------</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> pinot</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> system</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">2</span><span class="token plain"> rows</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">Query 20191112_050827_00003_xkm4g, FINISHED, </span><span class="token number">1</span><span class="token plain"> node</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">Splits: </span><span class="token number">19</span><span class="token plain"> total, </span><span class="token number">19</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">done</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">100.00</span><span class="token plain">%</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token number">0</span><span class="token plain">:01 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">0</span><span class="token plain"> rows, 0B</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">0</span><span class="token plain"> rows/s, 0B/s</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>List All tables</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">presto:default> show tables;</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain"> Table</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">--------------</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> airlinestats</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">1</span><span class="token plain"> row</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">Query 20191112_050907_00004_xkm4g, FINISHED, </span><span class="token number">1</span><span class="token plain"> node</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">Splits: </span><span class="token number">19</span><span class="token plain"> total, </span><span class="token number">19</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">done</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">100.00</span><span class="token plain">%</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token number">0</span><span class="token plain">:01 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">1</span><span class="token plain"> rows, 29B</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">1</span><span class="token plain"> rows/s, 41B/s</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Show schema</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">presto:</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">default</span><span class="token operator">></span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">DESCRIBE</span><span class="token plain"> pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">dontcare</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">airlinestats</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain"> Column </span><span class="token operator">|</span><span class="token plain"> Type </span><span class="token operator">|</span><span class="token plain"> Extra </span><span class="token operator">|</span><span class="token plain"> Comment</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">----------------------+---------+-------+---------</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> flightnum </span><span class="token operator">|</span><span class="token plain"> integer </span><span class="token operator">|</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> origin </span><span class="token operator">|</span><span class="token plain"> varchar </span><span class="token operator">|</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> quarter </span><span class="token operator">|</span><span class="token plain"> integer </span><span class="token operator">|</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> lateaircraftdelay </span><span class="token operator">|</span><span class="token plain"> integer </span><span class="token operator">|</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> divactualelapsedtime </span><span class="token operator">|</span><span class="token plain"> integer </span><span class="token operator">|</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">..</span><span class="token punctuation" style="color:rgb(248, 248, 242)">..</span><span class="token punctuation" style="color:rgb(248, 248, 242)">..</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">Query 20191112_051021_00005_xkm4g, FINISHED, </span><span class="token number">1</span><span class="token plain"> node</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">Splits: </span><span class="token number">19</span><span class="token plain"> total, </span><span class="token number">19</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">done</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">100.00</span><span class="token plain">%</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token number">0</span><span class="token plain">:02 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">80</span><span class="token plain"> rows, </span><span class="token number">6</span><span class="token plain">.06KB</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">35</span><span class="token plain"> rows/s, </span><span class="token number">2</span><span class="token plain">.66KB/s</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Count total documents</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly SQL"><pre tabindex="0" class="prism-code language-SQL codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">presto:default> select count(*) as cnt from pinot.dontcare.airlinestats limit 10;</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain"> cnt</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">------</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">9745</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">1</span><span class="token plain"> row</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
-</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">Query 20191112_051114_00006_xkm4g, FINISHED, </span><span class="token number">1</span><span class="token plain"> node</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">Splits: </span><span class="token number">17</span><span class="token plain"> total, </span><span class="token number">17</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">done</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">100.00</span><span class="token plain">%</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token number">0</span><span class="token plain">:00 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">1</span><span class="token plain"> rows, 8B</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">2</span><span class="token plain"> rows/s, 19B/s</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="how-to-clean-up-pinot-deployment"></a>How to clean up Pinot deployment<a class="hash-link" href="#how-to-clean-up-pinot-deployment" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl delete ns pinot-quickstart</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><a class="jump-to jump-to--undefined" href="/docs/administration/"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Administration</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/administration/installation/cloud/on-premise.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_3DPF"></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/docs/administration/installation/containers/docker"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">« Docker</div></a></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/docs/administration/installation/cloud/aws"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">AWS »</div></a></div></nav></div></div><div class="col col--3"><div class="tableOfContents_35-E thin-scrollbar"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#setup-a-pinot-cluster-for-demo" class="table-of-contents__link">Setup a Pinot cluster for demo</a><ul><li><a href="#update-helm-dependency" class="table-of-contents__link">Update helm dependency</a></li><li><a href="#start-pinot-with-helm" class="table-of-contents__link">Start Pinot with Helm</a></li></ul></li><li><a href="#troubleshooting-for-helm-v2121" class="table-of-contents__link">Troubleshooting (For helm v2.12.1)</a></li><li><a href="#load-data-into-pinot-through-kafka" class="table-of-contents__link">Load data into Pinot through Kafka</a><ul><li><a href="#bring-up-a-kafka-cluster-for-realtime-data-ingestion" class="table-of-contents__link">Bring up a Kafka Cluster for realtime data ingestion</a></li><li><a href="#check-kafka-deployment-status" class="table-of-contents__link">Check Kafka deployment status</a></li><li><a href="#create-kafka-topics" class="table-of-contents__link">Create Kafka topics</a></li><li><a href="#load-data-into-kafka-and-create-pinot-schematables" class="table-of-contents__link">Load data into Kafka and Create Pinot Schema/Tables</a></li></ul></li><li><a href="#how-to-query-pinot-data" class="table-of-contents__link">How to query pinot data</a><ul><li><a href="#pinot-query-console" class="table-of-contents__link">Pinot Query Console</a></li></ul></li><li><a href="#use-superset-to-query-pinot" class="table-of-contents__link">Use Superset to query Pinot</a><ul><li><a href="#bring-up-superset" class="table-of-contents__link">Bring up Superset</a></li><li><a href="#first-time-set-up-admin-account" class="table-of-contents__link">(First time) Set up Admin account</a></li><li><a href="#first-time-init-superset" class="table-of-contents__link">(First time) Init Superset</a></li><li><a href="#load-demo-data-source" class="table-of-contents__link">Load Demo Data source</a></li><li><a href="#access-superset-ui" class="table-of-contents__link">Access Superset UI</a></li></ul></li><li><a href="#access-pinot-using-presto" class="table-of-contents__link">Access Pinot Using 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+</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">Query 20191112_051114_00006_xkm4g, FINISHED, </span><span class="token number">1</span><span class="token plain"> node</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">Splits: </span><span class="token number">17</span><span class="token plain"> total, </span><span class="token number">17</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">done</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">100.00</span><span class="token plain">%</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token number">0</span><span class="token plain">:00 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">1</span><span class="token plain"> rows, 8B</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">2</span><span class="token plain"> rows/s, 19B/s</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="how-to-clean-up-pinot-deployment"></a>How to clean up Pinot deployment<a class="hash-link" href="#how-to-clean-up-pinot-deployment" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl delete ns pinot-quickstart</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><a class="jump-to jump-to--undefined" href="/docs/administration/"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Administration</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/administration/installation/cloud/on-premise.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_13-_"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/docs/administration/installation/containers/docker"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">« Docker</div></a></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/docs/administration/installation/cloud/aws"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">AWS »</div></a></div></nav></div></div><div class="col col--3"><div class="tableOfContents_35-E thin-scrollbar"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#setup-a-pinot-cluster-for-demo" class="table-of-contents__link">Setup a Pinot cluster for demo</a><ul><li><a href="#update-helm-dependency" class="table-of-contents__link">Update helm dependency</a></li><li><a href="#start-pinot-with-helm" class="table-of-contents__link">Start Pinot with Helm</a></li></ul></li><li><a href="#troubleshooting-for-helm-v2121" class="table-of-contents__link">Troubleshooting (For helm v2.12.1)</a></li><li><a href="#load-data-into-pinot-through-kafka" class="table-of-contents__link">Load data into Pinot through Kafka</a><ul><li><a href="#bring-up-a-kafka-cluster-for-realtime-data-ingestion" class="table-of-contents__link">Bring up a Kafka Cluster for realtime data ingestion</a></li><li><a href="#check-kafka-deployment-status" class="table-of-contents__link">Check Kafka deployment status</a></li><li><a href="#create-kafka-topics" class="table-of-contents__link">Create Kafka topics</a></li><li><a href="#load-data-into-kafka-and-create-pinot-schematables" class="table-of-contents__link">Load data into Kafka and Create Pinot Schema/Tables</a></li></ul></li><li><a href="#how-to-query-pinot-data" class="table-of-contents__link">How to query pinot data</a><ul><li><a href="#pinot-query-console" class="table-of-contents__link">Pinot Query Console</a></li></ul></li><li><a href="#use-superset-to-query-pinot" class="table-of-contents__link">Use Superset to query Pinot</a><ul><li><a href="#bring-up-superset" class="table-of-contents__link">Bring up Superset</a></li><li><a href="#first-time-set-up-admin-account" class="table-of-contents__link">(First time) Set up Admin account</a></li><li><a href="#first-time-init-superset" class="table-of-contents__link">(First time) Init Superset</a></li><li><a href="#load-demo-data-source" class="table-of-contents__link">Load Demo Data source</a></li><li><a href="#access-superset-ui" class="table-of-contents__link">Access Superset UI</a></li></ul></li><li><a href="#access-pinot-using-presto" class="table-of-contents__link">Access Pinot Using Presto</a><ul><li><a href="#deploy-presto-with-pinot-plugin" class="table-of-contents__link">Deploy Presto with Pinot Plugin</a></li><li><a href="#query-presto-using-presto-cli" class="table-of-contents__link">Query Presto using Presto CLI</a></li><li><a href="#sample-queries-to-execute" class="table-of-contents__link">Sample queries to execute</a></li><li><a href="#how-to-clean-up-pinot-deployment" class="table-of-contents__link">How to clean up Pinot deployment</a></li></ul></li></ul></div></div></div></div></main></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li 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target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener noreferrer" class="footer__link-item">Getting Started</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Pinot Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/users" target="_blank" rel="noopener noreferrer" class="footer__link-item">User Guide</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" 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class="margin-bottom--sm"><a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footerLogoLink_qW4Z"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
+<script src="/assets/js/runtime~main.664acf57.js"></script>
+<script src="/assets/js/main.a1de4389.js"></script>
</body>
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diff --git a/content/docs/administration/installation/containers/docker/index.html b/content/docs/administration/installation/containers/docker/index.html
index cc6e5d0..7382222 100644
--- a/content/docs/administration/installation/containers/docker/index.html
+++ b/content/docs/administration/installation/containers/docker/index.html
@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,15 +11,15 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
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href="/docs/administration/installation/containers/docker">Docker</a></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Cloud</a></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Operating Systems</a></li></ul></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Components</a></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1 class="h1Heading_27L5">Running Pinot in Docker</h1></header><p>Apache Pinot started maintaing the <a href="https://hub.docker.com/r/apachepinot/pinot" target="_blank" rel="noopener noreferrer"><code>apachepinot/pinot</code></a> Docker images
-available on <a href="https://hub.docker.com/r/apachepinot/pinot/tags" target="_blank" rel="noopener noreferrer">Docker Hub</a></p><blockquote><b>Prerequisites:</b> <br> <p> <a href="https://hub.docker.com/editions/community/docker-ce-desktop-mac" target="_blank" rel="noopener noreferrer">Install Docker</a><br> Try <a href="https://hub.docker.com/editions/community/docker-ce-desktop-mac" target="_blank" rel="noopener noreferrer">Kubernetes Quickstart</a> if you already have a minikube cluster or docker kubernetes setup.</p></blockquote><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="running"></a>Running<a class="hash-link" href="#running" title="Direct link to heading">#</a></h2><p>Create an isolated bridge network in docker</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker network create -d bridge pinot-demo</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>We'll be running a docker image apachepinot/pinot:latest to run a quick start, which does the following:</p><ul><li>Sets up the Pinot cluster QuickStartCluster</li><li>Creates a sample table and loads sample data</li></ul><p>There's 3 types of quick start</p><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs tabs--block"><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_1uMI tabs__item--active">Batch</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">Streaming</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">Hybrid</li></ul><div class="margin-vert--md"><div role="tabpanel"><p>Batch</p><ol><li><p>Starts Pinot deployment by starting:</p><ul><li>Apache Zookeeper</li><li>Pinot Controller</li><li>Pinot Broker</li><li>Pinot Server</li></ul></li><li><p>Creates a demo table:</p><ul><li>baseballStats</li></ul></li><li><p>Launches a standalone data ingestion job:</p><ul><li>build one Pinot segment for a given csv data file for table baseballStats</li><li>push built segment to Pinot controller</li></ul></li><li><p>Issues sample queries to Pinot</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker run </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --network</span><span class="token operator">=</span><span class="token plain">pinot-demo </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name pinot-quickstart </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -p </span><span class="token number">9000</span><span class="token plain">:9000 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -d apachepinot/pinot:latest QuickStart </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -type batch</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></li></ol></div><div role="tabpanel" hidden=""><p>Streaming:</p><ol><li><p>Starts Pinot deployment by starting:</p><ul><li>Apache Kafka</li><li>Apache Zookeeper</li><li>Pinot Controller</li><li>Pinot Broker</li><li>Pinot Server</li></ul></li><li><p>Creates a demo table: <strong>meetupRsvp</strong></p></li><li><p>Launches a <strong>meetup</strong> stream and publish data to a Kafka: <strong>meetupRSVPEvents</strong> to be subscribed by Pinot</p></li><li><p>Issues sample queries to Pinot</p></li></ol></div><div role="tabpanel" hidden=""><p>Hybrid:</p><ol><li><p>Starts Pinot deployment by starting:</p><ul><li>Apache Kafka</li><li>Apache Zookeeper</li><li>Pinot Controller</li><li>Pinot Broker</li><li>Pinot Server</li></ul></li><li><p>Creates a demo table: <strong>airlineStats</strong></p></li><li><p>Launches a standalone data ingestion job:</p><ul><li>build Pinot segments under a given directory of Avro files for table airlineStats</li><li>push built segments to Pinot controller</li></ul></li><li><p>Launches a stream of flights stats and publish data to a Kafka topic airlineStatsEvents to be subscribed by Pinot</p></li><li><p>Issues sample queries to Pinot</p></li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)"># Stop previous container, if any, or use different network</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker run </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --network</span><span class="token operator">=</span><span class="token plain">pinot-demo </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name pinot-quickstart </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -p </span><span class="token number">9000</span><span class="token plain">:9000 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -d apachepinot/pinot:latest QuickStart </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -type hybrid</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div></div></div><p>That's it! We've spun up a Pinot cluster.</p><p>It may take a while for all Pinot components to start and for the sample data to be loaded. Use the below command to check the container logs</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker logs pinot-quickstart -f</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can head over to Exploring Pinot to check out the data in the <code>baseballStats</code>, <code>meetupRSVP</code> or the <code>airlineStats</code> table.</p></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/administration/installation/containers/docker.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" 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menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">About</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">Administration</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/running_locally">Running Pinot locally</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#" tabindex="0">Installation</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#" tabindex="0">Containers</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/docs/administration/installation/containers/docker">Docker</a></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Cloud</a></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Operating Systems</a></li></ul></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Components</a></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>Running Pinot in Docker</h1></header><p>Apache Pinot started maintaing the <a href="https://hub.docker.com/r/apachepinot/pinot" target="_blank" rel="noopener noreferrer"><code>apachepinot/pinot</code></a> Docker images
+available on <a href="https://hub.docker.com/r/apachepinot/pinot/tags" target="_blank" rel="noopener noreferrer">Docker Hub</a></p><blockquote><b>Prerequisites:</b> <br> <p> <a href="https://hub.docker.com/editions/community/docker-ce-desktop-mac" target="_blank" rel="noopener noreferrer">Install Docker</a><br> Try <a href="https://hub.docker.com/editions/community/docker-ce-desktop-mac" target="_blank" rel="noopener noreferrer">Kubernetes Quickstart</a> if you already have a minikube cluster or docker kubernetes setup.</p></blockquote><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="running"></a>Running<a class="hash-link" href="#running" title="Direct link to heading">#</a></h2><p>Create an isolated bridge network in docker</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker network create -d bridge pinot-demo</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>We'll be running a docker image apachepinot/pinot:latest to run a quick start, which does the following:</p><ul><li>Sets up the Pinot cluster QuickStartCluster</li><li>Creates a sample table and loads sample data</li></ul><p>There's 3 types of quick start</p><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs tabs--block"><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_1uMI tabs__item--active">Batch</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">Streaming</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">Hybrid</li></ul><div class="margin-vert--md"><div role="tabpanel"><p>Batch</p><ol><li><p>Starts Pinot deployment by starting:</p><ul><li>Apache Zookeeper</li><li>Pinot Controller</li><li>Pinot Broker</li><li>Pinot Server</li></ul></li><li><p>Creates a demo table:</p><ul><li>baseballStats</li></ul></li><li><p>Launches a standalone data ingestion job:</p><ul><li>build one Pinot segment for a given csv data file for table baseballStats</li><li>push built segment to Pinot controller</li></ul></li><li><p>Issues sample queries to Pinot</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker run </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --network</span><span class="token operator">=</span><span class="token plain">pinot-demo </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name pinot-quickstart </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -p </span><span class="token number">9000</span><span class="token plain">:9000 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -d apachepinot/pinot:latest QuickStart </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -type batch</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></li></ol></div><div role="tabpanel" hidden=""><p>Streaming:</p><ol><li><p>Starts Pinot deployment by starting:</p><ul><li>Apache Kafka</li><li>Apache Zookeeper</li><li>Pinot Controller</li><li>Pinot Broker</li><li>Pinot Server</li></ul></li><li><p>Creates a demo table: <strong>meetupRsvp</strong></p></li><li><p>Launches a <strong>meetup</strong> stream and publish data to a Kafka: <strong>meetupRSVPEvents</strong> to be subscribed by Pinot</p></li><li><p>Issues sample queries to Pinot</p></li></ol></div><div role="tabpanel" hidden=""><p>Hybrid:</p><ol><li><p>Starts Pinot deployment by starting:</p><ul><li>Apache Kafka</li><li>Apache Zookeeper</li><li>Pinot Controller</li><li>Pinot Broker</li><li>Pinot Server</li></ul></li><li><p>Creates a demo table: <strong>airlineStats</strong></p></li><li><p>Launches a standalone data ingestion job:</p><ul><li>build Pinot segments under a given directory of Avro files for table airlineStats</li><li>push built segments to Pinot controller</li></ul></li><li><p>Launches a stream of flights stats and publish data to a Kafka topic airlineStatsEvents to be subscribed by Pinot</p></li><li><p>Issues sample queries to Pinot</p></li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)"># Stop previous container, if any, or use different network</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker run </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --network</span><span class="token operator">=</span><span class="token plain">pinot-demo </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name pinot-quickstart </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -p </span><span class="token number">9000</span><span class="token plain">:9000 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -d apachepinot/pinot:latest QuickStart </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -type hybrid</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div></div></div><p>That's it! We've spun up a Pinot cluster.</p><p>It may take a while for all Pinot components to start and for the sample data to be loaded. Use the below command to check the container logs</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker logs pinot-quickstart -f</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can head over to Exploring Pinot to check out the data in the <code>baseballStats</code>, <code>meetupRSVP</code> or the <code>airlineStats</code> table.</p></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/administration/installation/containers/docker.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_13-_"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/docs/administration/running_locally"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">« Running Pinot locally</div></a></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/docs/administration/installation/cloud/on-premise"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Kubernetes »</div></a></div></nav></div></div><div class="col col--3"><div class="tableOfContents_35-E thin-scrollbar"><ul 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<head>
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class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 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+<script src="/assets/js/runtime~main.664acf57.js"></script>
+<script src="/assets/js/main.a1de4389.js"></script>
</body>
</html>
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diff --git a/content/docs/administration/installation/operating-systems/macos/index.html b/content/docs/administration/installation/operating-systems/macos/index.html
index 9ccbcc8..b4c408d 100644
--- a/content/docs/administration/installation/operating-systems/macos/index.html
+++ b/content/docs/administration/installation/operating-systems/macos/index.html
@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,14 +11,14 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
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+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img 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menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">About</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">Administration</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/running_locally">Running Pinot locally</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#" tabindex="0">Installation</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Containers</a></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Cloud</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#" tabindex="0">Operating Systems</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/administration/installation/operating-systems/macos">MacOS</a></li><li class="menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/docs/administration/installation/operating-systems/ubuntu">Ubuntu</a></li></ul></li></ul></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Components</a></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="markdown"><header><h1>Install Pinot On Ubuntu</h1></header><p>Pinot can be installed on the Ubuntu through the following methods:</p></div><footer class="docusaurus-mt-lg"><div 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href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener 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and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
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diff --git a/content/docs/administration/running_locally/index.html b/content/docs/administration/running_locally/index.html
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@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,18 +11,18 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
<link rel="search" type="application/opensearchdescription+xml" title="Apache Pinot™" href="/opensearch.xml">
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class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1 class="h1Heading_27L5">Running Pinot locally</h1></header><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="running-pinot-locally"></a>Running Pinot locally<a class="hash-link" href="#running-pinot-locally" title="Direct link to heading">#</a></h2><p>Pinot Quickstart local</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="getting-pinot"></a>Getting Pinot<a class="hash-link" href="#getting-pinot" title="Direct link to heading">#</a></h3><p>First, let's get Pinot. You can either build it, or download it</p><blockquote><b>Prerequisites:</b> <br> <p> <a href="https://linuxize.com/post/install-java-on-ubuntu-18-04/#installing-openjdk-8" target="_blank" rel="noopener noreferrer">Install Java 8 or higher...</a> </p></blockquote><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="build"></a>Build<a class="hash-link" href="#build" title="Direct link to heading">#</a></h3><p>Follow these steps to checkout code from <a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer">Github</a> and build Pinot locally</p><blockquote><b>Prerequisites:</b> <br> <p> Install <a href="https://maven.apache.org/install.html" target="_blank" rel="noopener noreferrer">Apache Maven</a> 3.6 or higher. </p></blockquote><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)"># checkout pinot</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">git</span><span class="token plain"> clone https://github.com/apache/pinot.git</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked 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stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><aside class="docSidebarContainer_3Kbt"><div class="sidebar_15mo sidebarWithHideableNavbar_267A"><a tabindex="-1" class="sidebarLogo_3h0W" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m"></a><nav class="menu thin-scrollbar menu_Bmed menuWithAnnouncementBar_2WvA"><ul class="menu__list"><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">About</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">Administration</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/docs/administration/running_locally">Running Pinot locally</a></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#" tabindex="0">Installation</a></li></ul></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Components</a></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>Running Pinot locally</h1></header><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="running-pinot-locally"></a>Running Pinot locally<a class="hash-link" href="#running-pinot-locally" title="Direct link to heading">#</a></h2><p>Pinot Quickstart local</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="getting-pinot"></a>Getting Pinot<a class="hash-link" href="#getting-pinot" title="Direct link to heading">#</a></h3><p>First, let's get Pinot. You can either build it, or download it</p><blockquote><b>Prerequisites:</b> <br> <p> <a href="https://linuxize.com/post/install-java-on-ubuntu-18-04/#installing-openjdk-8" target="_blank" rel="noopener noreferrer">Install Java 8 or higher...</a> </p></blockquote><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="build"></a>Build<a class="hash-link" href="#build" title="Direct link to heading">#</a></h3><p>Follow these steps to checkout code from <a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer">Github</a> and build Pinot locally</p><blockquote><b>Prerequisites:</b> <br> <p> Install <a href="https://maven.apache.org/install.html" target="_blank" rel="noopener noreferrer">Apache Maven</a> 3.6 or higher. </p></blockquote><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)"># checkout pinot</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">git</span><span class="token plain"> clone https://github.com/apache/pinot.git</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token comment" style="color:rgb(98, 114, 164)"># build pinot</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">mvn </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> package -DskipTests -Pbin-dist</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
-</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token comment" style="color:rgb(98, 114, 164)"># navigate to directory containing the setup scripts</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot-distribution/target/apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">-bin/apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">-bin</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="download"></a>Download<a class="hash-link" href="#download" title="Direct link to heading">#</a></h3><p>Download the latest binary release from Apache Pinot, or use this command</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">wget</span><span class="token plain"> https://downloads.apache.org/pinot/apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">/apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">-bin.tar.gz</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Once you have the tar file,</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)"># untar it</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">tar</span><span class="token plain"> -zxvf apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">-bin.tar.gz</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
+</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token comment" style="color:rgb(98, 114, 164)"># navigate to directory containing the setup scripts</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot-distribution/target/apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">-bin/apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">-bin</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="download"></a>Download<a class="hash-link" href="#download" title="Direct link to heading">#</a></h3><p>Download the latest binary release from Apache Pinot, or use this command</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">wget</span><span class="token plain"> https://downloads.apache.org/pinot/apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">/apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">-bin.tar.gz</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Once you have the tar file,</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)"># untar it</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">tar</span><span class="token plain"> -zxvf apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">-bin.tar.gz</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token comment" style="color:rgb(98, 114, 164)"># navigate to directory containing the launcher scripts</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> apache-pinot-incubating-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">${pinot.version}</span><span class="token plain">-bin</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>If you want to run Pinot using a Docker image instead, head over to Running Pinot in Docker</p><div type="info"><p>Pro-tip: These field names can be controlled via the
-[global <code>log_schema</code> options][docs.reference.global-options#log_schema].</p></div></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/administration/running_locally.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_3DPF"></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/docs/about/features_of_pinot"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">« Features of Pinot</div></a></div><div class="pagination-nav__item 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diff --git a/content/docs/components/broker/index.html b/content/docs/components/broker/index.html
index 18fdde2..ec5835a 100644
--- a/content/docs/components/broker/index.html
+++ b/content/docs/components/broker/index.html
@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,14 +11,14 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
<link rel="search" type="application/opensearchdescription+xml" title="Apache Pinot™" href="/opensearch.xml">
<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Ubuntu|Roboto|Source+Code+Pro">
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class="docItemContainer_33ec"><article><div class="markdown"><header><h1 class="h1Heading_27L5">Broker</h1></header><p>Brokers are the components that handle Pinot queries. They accept queries from clients and forward them to the right servers. They collect results back from the servers and consolidate them into a single response, to sent it back to the client.</p><p><img alt="Broker" src="/assets/images/Broker-356f92896de988004ef75c8ae79d4bf1.png"></p></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/components/broker.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_3DPF"></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/docs/administration/installation/operating-systems/ubuntu"><div 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menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">About</a></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Administration</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">Components</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/docs/components/broker">broker</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/components/cluster">cluster</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/components/controller">PQL</a></li></ul></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="markdown"><header><h1>Broker</h1></header><p>Brokers are the components that handle Pinot queries. They accept queries from clients and forward them to the right servers. They collect results back from the servers and consolidate them into a single response, to sent it back to the client.</p><p><img alt="Broker" src="/assets/images/Broker-356f92896de988004ef75c8ae79d4bf1.png"></p></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/components/broker.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_13-_"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/docs/administration/installation/operating-systems/ubuntu"><div 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diff --git a/content/docs/components/cluster/index.html b/content/docs/components/cluster/index.html
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class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">About</a></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Administration</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">Components</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/components/broker">broker</a></li><li class="menu__list-item"><a aria-current="page" class="menu__link menu__link--active active" tabindex="0" href="/docs/components/cluster">cluster</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/components/controller">PQL</a></li></ul></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1 class="h1Heading_27L5">Cluster</h1></header><p>Cluster is a set a nodes comprising of servers, brokers, controllers and minions.</p><p>Pinot leverages <a href="http://helix.apache.org" target="_blank" rel="noopener noreferrer">Apache Helix</a> for cluster management. Helix is a cluster management framework to manage replicated, partitioned resources in a distributed system. Helix uses Zookeeper to store cluster state and metadata.</p><p><img alt="Cluster Components" 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"></p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="cluster-components"></a>Cluster components<a class="hash-link" href="#cluster-components" title="Direct link to heading">#</a></h2><p>Briefly, Helix divides nodes into three logical components based on their responsibilities</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="participant"></a>Participant<a class="hash-link" href="#participant" title="Direct link to heading">#</a></h3><p>The nodes that host distributed, partitioned resources</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="spectator"></a>Spectator<a class="hash-link" href="#spectator" title="Direct link to heading">#</a></h3><p>The nodes that observe the current state of each Participant and use that information to access the resources. Spectators are notified of state changes in the cluster (state of a participant, or that of a partition in a participant).</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="controller"></a>Controller<a class="hash-link" href="#controller" title="Direct link to heading">#</a></h3><p>The node that observes and controls the Participant nodes. It is responsible for coordinating all transitions in the cluster and ensuring that state constraints are satisfied while maintaining cluster stability.</p><ul><li>Pinot Servers are modeled as Participants, more details about server nodes can be found in <a href="/docs/components/server">Server</a></li><li>Pinot Brokers are modeled as Spectators, more details about broker nodes can be found in <a href="/docs/components/broker">Broker</a></li><li>Pinot Controllers are modeled as Controllers, more details about controller nodes can be found in <a href="/docs/components/controller">Controller</a></li></ul><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="logical-view"></a>Logical view<a class="hash-link" href="#logical-view" title="Direct link to heading">#</a></h2><p>Another way to visualize the cluster is a logical view, wherein a cluster contains <a href="/docs/components/segments">tenants</a>, tenants contain <a href="/docs/components/tables">tables</a>, and tables contain <a href="/docs/components/segments">segments</a>.</p><p><img alt="Logical View" src="/assets/images/ClusterLogical-a82f8d136804e81aa069c9cb7f1f53ec.png"></p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="setup-a-pinot-cluster"></a>Setup a Pinot Cluster<a class="hash-link" href="#setup-a-pinot-cluster" title="Direct link to heading">#</a></h2><p>Typically, there is only cluster per environment/data center. There is no needed to create multiple Pinot clusters since Pinot supports the concept of <a href="/docs/components/tenants">tenants</a>.</p><p>At LinkedIn, the largest Pinot cluster consists of 1000+ nodes.</p><p>To setup a Pinot cluster, we need to first start Zookeeper:</p><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs Install"><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI"><i class="Using docker images"></i> Using docker images</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI"><i class="Using launcher scripts"></i> Using launcher scripts</li></ul><div class="margin-vert--md"><div role="tabpanel" hidden=""><ol><li>Create a Network
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menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">About</a></li><li class="menu__list-item menu__list-item--collapsed"><a class="menu__link menu__link--sublist" href="#">Administration</a></li><li class="menu__list-item"><a class="menu__link menu__link--sublist menu__link--active" href="#">Components</a><ul style="display:block;overflow:visible;height:auto" class="menu__list"><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/components/broker">broker</a></li><li class="menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/docs/components/cluster">cluster</a></li><li class="menu__list-item"><a class="menu__link" tabindex="0" href="/docs/components/controller">PQL</a></li></ul></li></ul></nav></div></aside><main class="docMainContainer_3ufF"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>Cluster</h1></header><p>Cluster is a set a nodes comprising of servers, brokers, controllers and minions.</p><p>Pinot leverages <a href="http://helix.apache.org" target="_blank" rel="noopener noreferrer">Apache Helix</a> for cluster management. Helix is a cluster management framework to manage replicated, partitioned resources in a distributed system. Helix uses Zookeeper to store cluster state and metadata.</p><p><img alt="Cluster Components" 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"></p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="cluster-components"></a>Cluster components<a class="hash-link" href="#cluster-components" title="Direct link to heading">#</a></h2><p>Briefly, Helix divides nodes into three logical components based on their responsibilities</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="participant"></a>Participant<a class="hash-link" href="#participant" title="Direct link to heading">#</a></h3><p>The nodes that host distributed, partitioned resources</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="spectator"></a>Spectator<a class="hash-link" href="#spectator" title="Direct link to heading">#</a></h3><p>The nodes that observe the current state of each Participant and use that information to access the resources. Spectators are notified of state changes in the cluster (state of a participant, or that of a partition in a participant).</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="controller"></a>Controller<a class="hash-link" href="#controller" title="Direct link to heading">#</a></h3><p>The node that observes and controls the Participant nodes. It is responsible for coordinating all transitions in the cluster and ensuring that state constraints are satisfied while maintaining cluster stability.</p><ul><li>Pinot Servers are modeled as Participants, more details about server nodes can be found in <a href="/docs/components/server">Server</a></li><li>Pinot Brokers are modeled as Spectators, more details about broker nodes can be found in <a href="/docs/components/broker">Broker</a></li><li>Pinot Controllers are modeled as Controllers, more details about controller nodes can be found in <a href="/docs/components/controller">Controller</a></li></ul><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="logical-view"></a>Logical view<a class="hash-link" href="#logical-view" title="Direct link to heading">#</a></h2><p>Another way to visualize the cluster is a logical view, wherein a cluster contains <a href="/docs/components/segments">tenants</a>, tenants contain <a href="/docs/components/tables">tables</a>, and tables contain <a href="/docs/components/segments">segments</a>.</p><p><img alt="Logical View" src="/assets/images/ClusterLogical-a82f8d136804e81aa069c9cb7f1f53ec.png"></p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="setup-a-pinot-cluster"></a>Setup a Pinot Cluster<a class="hash-link" href="#setup-a-pinot-cluster" title="Direct link to heading">#</a></h2><p>Typically, there is only cluster per environment/data center. There is no needed to create multiple Pinot clusters since Pinot supports the concept of <a href="/docs/components/tenants">tenants</a>.</p><p>At LinkedIn, the largest Pinot cluster consists of 1000+ nodes.</p><p>To setup a Pinot cluster, we need to first start Zookeeper:</p><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs Install"><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI"><i class="Using docker images"></i> Using docker images</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI"><i class="Using launcher scripts"></i> Using launcher scripts</li></ul><div class="margin-vert--md"><div role="tabpanel" hidden=""><ol><li>Create a Network
Create an isolated bridge network in docker</li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker network create -d bridge pinot-demo</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ol start="2"><li>Start Zookeeper</li></ol><p>Start Zookeeper in daemon.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker run </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --network</span><span class="token operator">=</span><span class="token plain">pinot-demo </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --name pinot-zookeeper </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --restart always </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -p </span><span class="token number">2181</span><span class="token plain">:2181 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -d zookeeper:3.5.6</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ol start="3"><li>Start Zookeeper UI
-Start ZKUI to browse Zookeeper data at http://localhost:9090.</li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker run </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --network pinot-demo --name</span><span class="token operator">=</span><span class="token plain">zkui </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -p </span><span class="token number">9090</span><span class="token plain">:9090 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -e </span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">ZK_SERVER</span><span class="token operator">=</span><span class="token plain">pinot-zookeeper:2181 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -d qnib/plain-zkui:latest</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ol start="4"><li></li></ol></div><div role="tabpanel" hidden=""><p>Download Pinot Distribution using instructions in Download</p><p>Start Zookeeper</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">bin/pinot-admin.sh StartZookeeper</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ol start="2"><li>Start Zooinspector</li></ol><p>Install <a href="https://github.com/jfim/zooinspector" target="_blank" rel="noopener noreferrer">zooinspector</a> to view the data in Zookeeper, and connect to localhost:2181</p></div></div></div><p>Once we've started Zookeeper, we can start other components to join this cluster. If you're using docker, pull the latest <code>apachepinot/pinot</code> image.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="using-docker-images"></a>Using docker images<a class="hash-link" href="#using-docker-images" title="Direct link to heading">#</a></h3><h4><a aria-hidden="true" tabindex="-1" class="anchor" id="pull-pinot-docker-image"></a>Pull pinot docker image<a class="hash-link" href="#pull-pinot-docker-image" title="Direct link to heading">#</a></h4><p>(Optional) You can also follow the instructions here to build your own images.<br></p><p>You can try out pre-built Pinot all-in-one docker image.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">export PINOT_VERSION</span><span class="token operator">=</span><span class="token number">0.3</span><span class="token number">.0</span><span class="token operator">-</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SNAPSHOT</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">export PINOT_IMAGE</span><span class="token operator">=</span><span class="token plain">apachepinot</span><span class="token operator">/</span><span class="token plain">pinot:${PINOT_VERSION}</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker pull ${PINOT_IMAGE}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>To start other components to join the cluster</p><ul><li>Start Controller</li><li>Start Broker</li><li>Start Server</li></ul><p>Explore your cluster via Pinot Data Explorer</p></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/components/cluster.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_3DPF"></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/docs/components/broker"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">« broker</div></a></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/docs/components/controller"><div class="pagination-nav__sublabel">Next</div><div 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-<script src="/assets/js/runtime~main.59053854.js"></script>
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+Start ZKUI to browse Zookeeper data at http://localhost:9090.</li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker run </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --network pinot-demo --name</span><span class="token operator">=</span><span class="token plain">zkui </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -p </span><span class="token number">9090</span><span class="token plain">:9090 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -e </span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">ZK_SERVER</span><span class="token operator">=</span><span class="token plain">pinot-zookeeper:2181 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -d qnib/plain-zkui:latest</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ol start="4"><li></li></ol></div><div role="tabpanel" hidden=""><p>Download Pinot Distribution using instructions in Download</p><p>Start Zookeeper</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">bin/pinot-admin.sh StartZookeeper</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ol start="2"><li>Start Zooinspector</li></ol><p>Install <a href="https://github.com/jfim/zooinspector" target="_blank" rel="noopener noreferrer">zooinspector</a> to view the data in Zookeeper, and connect to localhost:2181</p></div></div></div><p>Once we've started Zookeeper, we can start other components to join this cluster. If you're using docker, pull the latest <code>apachepinot/pinot</code> image.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="using-docker-images"></a>Using docker images<a class="hash-link" href="#using-docker-images" title="Direct link to heading">#</a></h3><h4><a aria-hidden="true" tabindex="-1" class="anchor anchor__h4 anchorWithHideOnScrollNavbar_3R7-" id="pull-pinot-docker-image"></a>Pull pinot docker image<a class="hash-link" href="#pull-pinot-docker-image" title="Direct link to heading">#</a></h4><p>(Optional) You can also follow the instructions here to build your own images.<br></p><p>You can try out pre-built Pinot all-in-one docker image.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">export PINOT_VERSION</span><span class="token operator">=</span><span class="token number">0.3</span><span class="token number">.0</span><span class="token operator">-</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SNAPSHOT</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">export PINOT_IMAGE</span><span class="token operator">=</span><span class="token plain">apachepinot</span><span class="token operator">/</span><span class="token plain">pinot:${PINOT_VERSION}</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker pull ${PINOT_IMAGE}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>To start other components to join the cluster</p><ul><li>Start Controller</li><li>Start Broker</li><li>Start Server</li></ul><p>Explore your cluster via Pinot Data Explorer</p></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/components/cluster.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_13-_"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/docs/components/broker"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">« broker</div></a></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/docs/components/controller"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">PQL »</div></a></div></nav></div></div><div class="col col--3"><div class="tableOfContents_35-E thin-scrollbar"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#cluster-components" class="table-of-contents__link">Cluster components</a><ul><li><a href="#participant" class="table-of-contents__link">Participant</a></li><li><a href="#spectator" class="table-of-contents__link">Spectator</a></li><li><a href="#controller" class="table-of-contents__link">Controller</a></li></ul></li><li><a href="#logical-view" class="table-of-contents__link">Logical view</a></li><li><a href="#setup-a-pinot-cluster" class="table-of-contents__link">Setup a Pinot Cluster</a><ul><li><a href="#using-docker-images" class="table-of-contents__link">Using docker images</a></li></ul></li></ul></div></div></div></div></main></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Plugins Architecture</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Integrations</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/presto" target="_blank" rel="noopener noreferrer" class="footer__link-item">Presto</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/superset" target="_blank" rel="noopener noreferrer" class="footer__link-item">Superset</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer" class="footer__link-item">ThirdEye</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Docs</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/getting-started" target="_blank" rel="noopener noreferrer" class="footer__link-item">Getting Started</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Pinot Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/users" target="_blank" rel="noopener noreferrer" class="footer__link-item">User Guide</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/operating-pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Administration</a></li></ul></div><div class="col footer__col"><h4 class="footer__title">Community</h4><ul class="footer__items"><li class="footer__item"><a href="https://join.slack.com/t/apache-pinot/shared_invite/zt-5z7pav2f-yYtjZdVA~EDmrGkho87Vzw" target="_blank" rel="noopener noreferrer" class="footer__link-item">Slack</a></li><li class="footer__item"><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Github</a></li><li class="footer__item"><a href="https://twitter.com/ApachePinot" target="_blank" rel="noopener noreferrer" class="footer__link-item">Twitter</a></li><li 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target="_blank" rel="noopener noreferrer" class="footer__link-item">Sponsorship</a></li><li class="footer__item"><a href="https://www.apache.org" target="_blank" rel="noopener noreferrer" class="footer__link-item">Foundation</a></li></ul></div></div><div class="footer__bottom text--center"><div class="margin-bottom--sm"><a href="https://pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footerLogoLink_qW4Z"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
+<script src="/assets/js/runtime~main.664acf57.js"></script>
+<script src="/assets/js/main.a1de4389.js"></script>
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diff --git a/content/docs/components/controller/index.html b/content/docs/components/controller/index.html
index f51084b..883f08e 100644
--- a/content/docs/components/controller/index.html
+++ b/content/docs/components/controller/index.html
@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,14 +11,14 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
<link rel="search" type="application/opensearchdescription+xml" title="Apache Pinot™" href="/opensearch.xml">
<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Ubuntu|Roboto|Source+Code+Pro">
-<link rel="stylesheet" href="https://at-ui.github.io/feather-font/css/iconfont.css"><title data-react-helmet="true">Pinot Query Language (PQL) | Apache Pinot™</title><meta data-react-helmet="true" property="og:url" content="https://pinot.apache.org/docs/components/controller"><meta data-react-helmet="true" name="docsearch:language" content="en"><meta data-react-helmet="true" name="docsearch:version" content="current"><meta data-react-helmet="true" name="docsearch:docusaurus_tag" content="docs-default-current"><meta data-react-helmet="true" property="og:title" content="Pinot Query Language (PQL) | Apache Pinot™"><meta data-react-helmet="true" name="description" content="Pinot Query Language"><meta data-react-helmet="true" property="og:description" content="Pinot Query Language"><link data-react-helmet="true" rel="shortcut icon" href="/img/favicon.ico"><link data-react-helmet="true" rel="canonical" href="https://pinot.apache.org/docs/components/controller"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/docs/components/controller" hreflang="en"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/docs/components/controller" hreflang="x-default"><link data-react-helmet="true" rel="preconnect" href="https://BH4D9OD16A-dsn.algolia.net" crossorigin="anonymous"><link rel="stylesheet" href="/assets/css/styles.f8c6b66d.css">
-<link rel="preload" href="/assets/js/runtime~main.59053854.js" as="script">
-<link rel="preload" href="/assets/js/main.5e591844.js" as="script">
+<link rel="stylesheet" href="https://at-ui.github.io/feather-font/css/iconfont.css"><title data-react-helmet="true">Pinot Query Language (PQL) | Apache Pinot™</title><meta data-react-helmet="true" name="twitter:card" content="summary_large_image"><meta data-react-helmet="true" property="og:url" content="https://pinot.apache.org/docs/components/controller"><meta data-react-helmet="true" name="docsearch:language" content="en"><meta data-react-helmet="true" name="docsearch:version" content="current"><meta data-react-helmet="true" name="docsearch:docusaurus_tag" content="docs-default-current"><meta data-react-helmet="true" property="og:title" content="Pinot Query Language (PQL) | Apache Pinot™"><meta data-react-helmet="true" name="description" content="Pinot Query Language"><meta data-react-helmet="true" property="og:description" content="Pinot Query Language"><link data-react-helmet="true" rel="shortcut icon" href="/img/favicon.ico"><link data-react-helmet="true" rel="canonical" href="https://pinot.apache.org/docs/components/controller"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/docs/components/controller" hreflang="en"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/docs/components/controller" hreflang="x-default"><link data-react-helmet="true" rel="preconnect" href="https://BH4D9OD16A-dsn.algolia.net" crossorigin="anonymous"><link rel="stylesheet" href="/assets/css/styles.14a15550.css">
+<link rel="preload" href="/assets/js/runtime~main.664acf57.js" as="script">
+<link rel="preload" href="/assets/js/main.a1de4389.js" as="script">
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class="docItemContainer_33ec"><article><div class="markdown"><header><h1>Pinot Query Language (PQL)</h1></header><p>A</p></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/components/controller.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_13-_"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"><a class="pagination-nav__link" href="/docs/components/cluster"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">« cluster</div></a></div><div 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+<script src="/assets/js/runtime~main.664acf57.js"></script>
+<script src="/assets/js/main.a1de4389.js"></script>
</body>
</html>
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diff --git a/content/docs/components/index.html b/content/docs/components/index.html
index 188ba8c..4560842 100644
--- a/content/docs/components/index.html
+++ b/content/docs/components/index.html
@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,14 +11,14 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
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<meta charset="UTF-8">
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-<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button" title="Scroll to top"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="markdown"><header><h1 class="h1Heading_27L5">Pinot Architecture</h1></header><p><img alt="Arch" src="/assets/images/pinot-architecture-f75b926076ed34c98eb24be7ed1c1107.png"></p><ul><li><p>Terminology:
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="markdown"><header><h1>Pinot Architecture</h1></header><p><img alt="Arch" src="/assets/images/pinot-architecture-f75b926076ed34c98eb24be7ed1c1107.png"></p><ul><li><p>Terminology:
First, a bit of naming notions. Pinot has has different components, and different ways of representing the data. In particular, data is represented by:</p></li><li><p>Table:
A table is a logical abstraction to refer to a collection of related data. It consists of columns and rows (documents).</p></li><li><p>Segment:
-Data in table is divided into (horizontal) shards referred to as segments.</p></li></ul></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/concepts/pinot-architecture.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_3DPF"></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"></div></nav></div></div></div></div></main></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 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diff --git a/content/docs/how-to/index.html b/content/docs/how-to/index.html
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@@ -3,7 +3,7 @@
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<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
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@@ -11,14 +11,14 @@
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build Pinot related docker images is located at <a href="https://github.com/apache/pinot/tree/master/docker/images" target="_blank" rel="noopener noreferrer">here</a></p><p>You can access those scripts by running below command to checkout Pinot repo:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">git</span><span class="token plain"> clone git@github.com:apache/pinot.git pinot</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot/docker/images</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can find current supported 3 images in this directory:</p><ul><li>Pinot: Pinot all-in-one distribution image</li><li>Pinot-Presto: Presto image with Presto-Pinot Connector built-in.</li><li>Pinot-Superset: Superset image with Pinot connector built-in.</li></ul><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="pinot"></a>Pinot<a class="hash-link" href="#pinot" title="Direct link to heading">#</a></h2><p>This is a docker image of <a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer">Apache Pinot</a></p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="how-to-build-a-docker-image"></a>How to build a docker image<a class="hash-link" href="#how-to-build-a-docker-image" title="Direct link to heading">#</a></h3><p>There is a docker build script which will build a given Git repo/branch and tag the image.</p><p>Usage:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build.sh </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Docker Tag</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Git Branch</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Pinot Git URL</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>This script will check out Pinot Repo <code>[Pinot Git URL]</code> on branch <code>[Git Branch]</code> and build the docker image for that. <br>
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>Build Docker Images</h1></header><p>The scripts to build Pinot related docker images is located at <a href="https://github.com/apache/pinot/tree/master/docker/images" target="_blank" rel="noopener noreferrer">here</a></p><p>You can access those scripts by running below command to checkout Pinot repo:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">git</span><span class="token plain"> clone git@github.com:apache/pinot.git pinot</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot/docker/images</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can find current supported 3 images in this directory:</p><ul><li>Pinot: Pinot all-in-one distribution image</li><li>Pinot-Presto: Presto image with Presto-Pinot Connector built-in.</li><li>Pinot-Superset: Superset image with Pinot connector built-in.</li></ul><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="pinot"></a>Pinot<a class="hash-link" href="#pinot" title="Direct link to heading">#</a></h2><p>This is a docker image of <a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer">Apache Pinot</a></p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="how-to-build-a-docker-image"></a>How to build a docker image<a class="hash-link" href="#how-to-build-a-docker-image" title="Direct link to heading">#</a></h3><p>There is a docker build script which will build a given Git repo/branch and tag the image.</p><p>Usage:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build.sh </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Docker Tag</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Git Branch</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Pinot Git URL</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>This script will check out Pinot Repo <code>[Pinot Git URL]</code> on branch <code>[Git Branch]</code> and build the docker image for that. <br>
The docker image is tagged as <code>[Docker Tag]</code>. <br>
Docker Tag: Name and tag your docker image. Default is <code>pinot:latest</code>. <br>
Git Branch: The Pinot branch to build. Default is master. <br>
Pinot Git URL: The Pinot Git Repo to build, users can set it to their own fork. <br>
Please note that, the URL is <code>https://</code> based, not <code>git://</code>. <br>
-Default is the <a href="https://github.com/apache/pinot.git" target="_blank" rel="noopener noreferrer">Apache Repo: https://github.com/apache/pinot.git</a>. <br></p><ul><li>Example of building and tagging a snapshot on your own fork:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build.sh pinot_fork:snapshot-5.2 snapshot-5.2 https://github.com/your_own_fork/pinot.git</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Example of building a release version:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build.sh pinot:release-0.1.0 release-0.1.0 https://github.com/apache/pinot.git</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Example of building current master branch as a snapshot:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build.sh apachepinot/pinot:0.3.0-SNAPSHOT master</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="how-to-publish-a-docker-image"></a>How to publish a docker image<a class="hash-link" href="#how-to-publish-a-docker-image" title="Direct link to heading">#</a></h2><p>Script <code>docker-push.sh</code> publishes a given docker image to your docker registry.
-In order to push to your own repo, the image needs to be explicitly tagged with the repo name.</p><ul><li>Example of publishing an image to <code>[apachepinot/pinot](https://hub.docker.com/u/apachepinot/repository/docker/apachepinot/pinot)</code> dockerHub repo.</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-push.sh apachepinot/pinot:latest</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>You can also tag a built image, then push it.</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker tag pinot:release-0.1.0 apachepinot/pinot:release-0.1.0</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker push apachepinot/pinot:release-0.1.0</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li><p>Script docker-build-and-push.sh builds and publishes this docker image to your docker registry after build.</p></li><li><p>Example of building and publishing an image to <code>[apachepinot/pinot](https://hub.docker.com/u/apachepinot/repository/docker/apachepinot/pinot)</code> dockerHub repo.</p></li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build-and-push.sh apachepinot/pinot:latest master https://github.com/apache/pinot.git</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="kubernetes-examples"></a>Kubernetes Examples<a class="hash-link" href="#kubernetes-examples" title="Direct link to heading">#</a></h2><p>Please refer to <a href="/docs/administration/installation/cloud/on-premise">Kubernetes Quickstart</a> for deployment examples.</p><p><a href="/docs/administration/installation/cloud/on-premise">Kubernetes Quickstart</a></p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="pinot-presto"></a>Pinot Presto<a class="hash-link" href="#pinot-presto" title="Direct link to heading">#</a></h2><p>Docker image for Presto with Pinot integration.
-This docker build project is specialized for Pinot.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="how-to-build"></a>How to build<a class="hash-link" href="#how-to-build" title="Direct link to heading">#</a></h3><p>Usage:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build.sh </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Docker Tag</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Git Branch</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Presto Git URL</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>This script will check out Pinot Repo <code>[Pinot Git URL]</code> on branch <code>[Git Branch]</code> and build the docker image for that. <br>
+Default is the <a href="https://github.com/apache/pinot.git" target="_blank" rel="noopener noreferrer">Apache Repo: https://github.com/apache/pinot.git</a>. <br></p><ul><li>Example of building and tagging a snapshot on your own fork:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build.sh pinot_fork:snapshot-5.2 snapshot-5.2 https://github.com/your_own_fork/pinot.git</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Example of building a release version:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build.sh pinot:release-0.1.0 release-0.1.0 https://github.com/apache/pinot.git</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>Example of building current master branch as a snapshot:</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build.sh apachepinot/pinot:0.3.0-SNAPSHOT master</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="how-to-publish-a-docker-image"></a>How to publish a docker image<a class="hash-link" href="#how-to-publish-a-docker-image" title="Direct link to heading">#</a></h2><p>Script <code>docker-push.sh</code> publishes a given docker image to your docker registry.
+In order to push to your own repo, the image needs to be explicitly tagged with the repo name.</p><ul><li>Example of publishing an image to <code>[apachepinot/pinot](https://hub.docker.com/u/apachepinot/repository/docker/apachepinot/pinot)</code> dockerHub repo.</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-push.sh apachepinot/pinot:latest</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>You can also tag a built image, then push it.</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker tag pinot:release-0.1.0 apachepinot/pinot:release-0.1.0</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker push apachepinot/pinot:release-0.1.0</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li><p>Script docker-build-and-push.sh builds and publishes this docker image to your docker registry after build.</p></li><li><p>Example of building and publishing an image to <code>[apachepinot/pinot](https://hub.docker.com/u/apachepinot/repository/docker/apachepinot/pinot)</code> dockerHub repo.</p></li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build-and-push.sh apachepinot/pinot:latest master https://github.com/apache/pinot.git</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="kubernetes-examples"></a>Kubernetes Examples<a class="hash-link" href="#kubernetes-examples" title="Direct link to heading">#</a></h2><p>Please refer to <a href="/docs/administration/installation/cloud/on-premise">Kubernetes Quickstart</a> for deployment examples.</p><p><a href="/docs/administration/installation/cloud/on-premise">Kubernetes Quickstart</a></p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="pinot-presto"></a>Pinot Presto<a class="hash-link" href="#pinot-presto" title="Direct link to heading">#</a></h2><p>Docker image for Presto with Pinot integration.
+This docker build project is specialized for Pinot.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="how-to-build"></a>How to build<a class="hash-link" href="#how-to-build" title="Direct link to heading">#</a></h3><p>Usage:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">./docker-build.sh </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Docker Tag</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Git Branch</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">Presto Git URL</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>This script will check out Pinot Repo <code>[Pinot Git URL]</code> on branch <code>[Git Branch]</code> and build the docker image for that. <br>
The docker image is tagged as <code>[Docker Tag]</code>. <br>
Docker Tag: Name and tag your docker image. Default is <code>pinot:latest</code>. <br>
Git Branch: The Pinot branch to build. Default is master. <br>
Pinot Git URL: The Pinot Git Repo to build, users can set it to their own fork. <br>
Please note that, the URL is <code>https://</code> based, not <code>git://</code>. <br>
-Default is the <a href="https://github.com/apache/pinot.git" target="_blank" rel="noopener noreferrer">Apache Repo: https://github.com/apache/pinot.git</a>. <br></p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="how-to-push"></a>How to push<a class="hash-link" href="#how-to-push" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker push apachepinot/pinot-presto:latest</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="configuration"></a>Configuration<a class="hash-link" href="#configuration" title="Direct link to heading">#</a></h3><p>Follow the instructions provided by Presto for writing your own configuration files under etc directory.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="volumes"></a>Volumes<a class="hash-link" href="#volumes" title="Direct link to heading">#</a></h3><p>The image defines two data volumes: one for mounting configuration into the container, and one for data.
+Default is the <a href="https://github.com/apache/pinot.git" target="_blank" rel="noopener noreferrer">Apache Repo: https://github.com/apache/pinot.git</a>. <br></p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="how-to-push"></a>How to push<a class="hash-link" href="#how-to-push" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker push apachepinot/pinot-presto:latest</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="configuration"></a>Configuration<a class="hash-link" href="#configuration" title="Direct link to heading">#</a></h3><p>Follow the instructions provided by Presto for writing your own configuration files under etc directory.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="volumes"></a>Volumes<a class="hash-link" href="#volumes" title="Direct link to heading">#</a></h3><p>The image defines two data volumes: one for mounting configuration into the container, and one for data.
The configuration volume is located alternatively at <code>/home/presto/etc</code>, which contains all the configuration and plugins.
-The data volume is located at <code>/home/presto/data</code>.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="kubernetes-examples-1"></a>Kubernetes Examples<a class="hash-link" href="#kubernetes-examples-1" title="Direct link to heading">#</a></h3><p>Please refer to presto-coordinator.yaml as k8s deployment example.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="pinot-superset"></a>Pinot Superset<a class="hash-link" href="#pinot-superset" title="Direct link to heading">#</a></h2><p>Docker image for Superset with Pinot integration.
-This docker build project is based on Project docker-superset and specialized for Pinot.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="how-to-build-1"></a>How to build<a class="hash-link" href="#how-to-build-1" title="Direct link to heading">#</a></h3><p>Please modify file <code>Makefile</code> to change image and <code>superset_version</code> accordingly.
-Below command will build docker image and tag it as <code>superset_version</code> and <code>latest</code>.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">make</span><span class="token plain"> latest</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can also build directly with <code>docker build</code> command by setting arguments:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker build </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --build-arg </span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">NODE_VERSION</span><span class="token operator">=</span><span class="token plain">latest </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --build-arg </span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">PYTHON_VERSION</span><span class="token operator">=</span><span class="token number">3.6</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --build-arg </span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">SUPERSET_VERSION</span><span class="token operator">=</span><span class="token number">0.34</span><span class="token plain">.1 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --tag apachepinot/pinot-superset:0.34.1 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --target build </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">.</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>How to push</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">make</span><span class="token plain"> push</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="configuration-1"></a>Configuration<a class="hash-link" href="#configuration-1" title="Direct link to heading">#</a></h3><p>Follow the <a href="https://superset.apache.org/installation.html#configuration" target="_blank" rel="noopener noreferrer">instructions</a> provided by Apache Superset for writing your own superset_config.py.</p><p>Place this file in a local directory and mount this directory to /etc/superset inside the container. This location
-is included in the image's <code>PYTHONPATH</code>. Mounting this file to a different location is possible, but it will need to be in the PYTHONPATH.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="volumes-1"></a>Volumes<a class="hash-link" href="#volumes-1" title="Direct link to heading">#</a></h3><p>The image defines two data volumes: one for mounting configuration into the container, and one for data (logs, SQLite DBs, &c).</p><p>The configuration volume is located alternatively at <code>/etc/superset</code> or <code>/home/superset</code>; either is acceptable. Both of these directories are included in the PYTHONPATH of the image. Mount any configuration (specifically the superset_config.py file) here to have it read by the app on startup.</p><p>The data volume is located at <code>/var/lib/superset</code> and it is where you would mount your SQLite file (if you are using that as your backend), or a volume to collect any logs that are routed there. This location is used as the value of the <code>SUPERSET_HOME</code> environmental variable.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="kubernetes-examples-2"></a>Kubernetes Examples<a class="hash-link" href="#kubernetes-examples-2" title="Direct link to heading">#</a></h3><p>Please refer to superset.yaml as k8s deployment example.</p></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/misc/build-docker.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_3DPF"></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"></div></nav></div></div><div class="col col--3"><div class="tableOfContents_35-E thin-scrollbar"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#pinot" class="table-of-contents__link">Pinot</a><ul><li><a href="#how-to-build-a-docker-image" class="table-of-contents__link">How to build a docker image</a></li></ul></li><li><a href="#how-to-publish-a-docker-image" class="table-of-contents__link">How to publish a docker image</a></li><li><a href="#kubernetes-examples" class="table-of-contents__link">Kubernetes Examples</a></li><li><a href="#pinot-presto" class="table-of-contents__link">Pinot Presto</a><ul><li><a href="#how-to-build" class="table-of-contents__link">How to build</a></li><li><a href="#how-to-push" class="table-of-contents__link">How to push</a></li><li><a href="#configuration" class="table-of-contents__link">Configuration</a></li><li><a href="#volumes" class="table-of-contents__link">Volumes</a></li><li><a href="#kubernetes-examples-1" class="table-of-contents__link">Kubernetes Examples</a></li></ul></li><li><a href="#pinot-superset" class="table-of-contents__link">Pinot Superset</a><ul><li><a href="#how-to-build-1" class="table-of-contents__link">How to build</a></li><li><a href="#configuration-1" class="table-of-contents__link">Configuration</a></li><li><a href="#volumes-1" class="table-of-contents__link">Volumes</a></li><li><a href="#kubernetes-examples-2" class="table-of-contents__link">Kubernetes Examples</a></li></ul></li></ul></div></div></div></div></main></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a 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+The data volume is located at <code>/home/presto/data</code>.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="kubernetes-examples-1"></a>Kubernetes Examples<a class="hash-link" href="#kubernetes-examples-1" title="Direct link to heading">#</a></h3><p>Please refer to presto-coordinator.yaml as k8s deployment example.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="pinot-superset"></a>Pinot Superset<a class="hash-link" href="#pinot-superset" title="Direct link to heading">#</a></h2><p>Docker image for Superset with Pinot integration.
+This docker build project is based on Project docker-superset and specialized for Pinot.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="how-to-build-1"></a>How to build<a class="hash-link" href="#how-to-build-1" title="Direct link to heading">#</a></h3><p>Please modify file <code>Makefile</code> to change image and <code>superset_version</code> accordingly.
+Below command will build docker image and tag it as <code>superset_version</code> and <code>latest</code>.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">make</span><span class="token plain"> latest</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>You can also build directly with <code>docker build</code> command by setting arguments:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">docker build </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --build-arg </span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">NODE_VERSION</span><span class="token operator">=</span><span class="token plain">latest </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --build-arg </span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">PYTHON_VERSION</span><span class="token operator">=</span><span class="token number">3.6</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --build-arg </span><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">SUPERSET_VERSION</span><span class="token operator">=</span><span class="token number">0.34</span><span class="token plain">.1 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --tag apachepinot/pinot-superset:0.34.1 </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --target build </span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">.</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>How to push</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">make</span><span class="token plain"> push</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="configuration-1"></a>Configuration<a class="hash-link" href="#configuration-1" title="Direct link to heading">#</a></h3><p>Follow the <a href="https://superset.apache.org/installation.html#configuration" target="_blank" rel="noopener noreferrer">instructions</a> provided by Apache Superset for writing your own superset_config.py.</p><p>Place this file in a local directory and mount this directory to /etc/superset inside the container. This location
+is included in the image's <code>PYTHONPATH</code>. Mounting this file to a different location is possible, but it will need to be in the PYTHONPATH.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="volumes-1"></a>Volumes<a class="hash-link" href="#volumes-1" title="Direct link to heading">#</a></h3><p>The image defines two data volumes: one for mounting configuration into the container, and one for data (logs, SQLite DBs, &c).</p><p>The configuration volume is located alternatively at <code>/etc/superset</code> or <code>/home/superset</code>; either is acceptable. Both of these directories are included in the PYTHONPATH of the image. Mount any configuration (specifically the superset_config.py file) here to have it read by the app on startup.</p><p>The data volume is located at <code>/var/lib/superset</code> and it is where you would mount your SQLite file (if you are using that as your backend), or a volume to collect any logs that are routed there. This location is used as the value of the <code>SUPERSET_HOME</code> environmental variable.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="kubernetes-examples-2"></a>Kubernetes Examples<a class="hash-link" href="#kubernetes-examples-2" title="Direct link to heading">#</a></h3><p>Please refer to superset.yaml as k8s deployment example.</p></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/misc/build-docker.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_13-_"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"></div></nav></div></div><div class="col col--3"><div class="tableOfContents_35-E thin-scrollbar"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#pinot" class="table-of-contents__link">Pinot</a><ul><li><a href="#how-to-build-a-docker-image" class="table-of-contents__link">How to build a docker image</a></li></ul></li><li><a href="#how-to-publish-a-docker-image" class="table-of-contents__link">How to publish a docker image</a></li><li><a href="#kubernetes-examples" class="table-of-contents__link">Kubernetes Examples</a></li><li><a href="#pinot-presto" class="table-of-contents__link">Pinot Presto</a><ul><li><a href="#how-to-build" class="table-of-contents__link">How to build</a></li><li><a href="#how-to-push" class="table-of-contents__link">How to push</a></li><li><a href="#configuration" class="table-of-contents__link">Configuration</a></li><li><a href="#volumes" class="table-of-contents__link">Volumes</a></li><li><a href="#kubernetes-examples-1" class="table-of-contents__link">Kubernetes Examples</a></li></ul></li><li><a href="#pinot-superset" class="table-of-contents__link">Pinot Superset</a><ul><li><a href="#how-to-build-1" class="table-of-contents__link">How to build</a></li><li><a href="#configuration-1" class="table-of-contents__link">Configuration</a></li><li><a href="#volumes-1" class="table-of-contents__link">Volumes</a></li><li><a href="#kubernetes-examples-2" class="table-of-contents__link">Kubernetes Examples</a></li></ul></li></ul></div></div></div></div></main></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" 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<meta charset="UTF-8">
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-<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img 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class="themedImage_1VuW themedImage--light_3UqQ footer__logo"><img src="/img/logo.svg" alt="Apache Pinot™" class="themedImage_1VuW themedImage--dark_hz6m footer__logo"></a></div><div class="footerCopyright_2yvt">Copyright © 2021 The Apache Software Foundation.<br>Apache Pinot, Pinot, Apache, the Apache feather logo, and the Apache Pinot project logo are registered trademarks of The Apache Software Foundation.<br><br>This page has references to third party software - Presto, PrestoDB, ThirdEye, that are not part of the Apache Software Foundation and are not covered under the Apache License.</div></div></div></footer></div>
+<script src="/assets/js/runtime~main.664acf57.js"></script>
+<script src="/assets/js/main.a1de4389.js"></script>
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+</html>
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diff --git a/content/docs/user-guide/clients/golang/index.html b/content/docs/user-guide/clients/golang/index.html
index f5b5343..b9cad63 100644
--- a/content/docs/user-guide/clients/golang/index.html
+++ b/content/docs/user-guide/clients/golang/index.html
@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
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<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
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@@ -11,15 +11,15 @@
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-<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img 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react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button" title="Scroll to top"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1 class="h1Heading_27L5">GoLang</h1></header><p>Applications can use this golang client library to query Apache Pinot.</p><p>Source Code Repo: <a href="https://github.com/fx19880617/pinot-client-go" target="_blank" rel="noopener noreferrer">https://github.com/fx19880617/pinot-client-go</a></p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="examples"></a>Examples<a class="hash-link" href="#examples" title="Direct link to heading">#</a></h2><p>Please follow this Pinot Quickstart link to install and start Pinot batch QuickStart locally.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">bin/quick-start-batch.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Check out Client library Github Repo</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">git</span><span class="token plain"> clone git@github.com:fx19880617/pinot-client-go.git</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot-client-go</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Build and run the example application to query from Pinot Batch Quickstart</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">go build ./examples/batch-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">./batch-quickstart</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="usage"></a>Usage<a class="hash-link" href="#usage" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="create-a-pinot-connection"></a>Create a Pinot Connection<a class="hash-link" href="#create-a-pinot-connection" title="Direct link to heading">#</a></h3><p>Pinot client could be initialized through:</p><ol><li>Zookeeper Path</li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">pinotClient </span><span class="token operator">:=</span><span class="token plain"> pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">NewFromZookeeper</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"localhost:2123"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">""</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"QuickStartCluster"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ol><li>A list of broker addresses.</li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">pinotClient </span><span class="token operator">:=</span><span class="token plain"> pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">NewFromBrokerList</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"localhost:8000"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ol><li>ClientConfig</li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">pinotClient </span><span class="token operator">:=</span><span class="token plain"> pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">NewWithConfig</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">&</span><span class="token plain">pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ClientConfig</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ZkConfig</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token plain"> </span><span class="token operator">&</span><span class="token plain">pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ZookeeperConfig</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ZookeeperPath</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token plain"> zkPath</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> PathPrefix</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token plain"> strings</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Join</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain">zkPathPrefix</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> pinotCluster</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"/"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> SessionTimeoutSec</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token plain"> defaultZkSessionTimeoutSec</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ExtraHTTPHeader</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">map</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"extra-header"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token string" style="color:rgb(255, 121, 198)">"value"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="query-pinot"></a>Query Pinot<a class="hash-link" href="#query-pinot" title="Direct link to heading">#</a></h2><p>Please see this <a href="https://github.com/fx19880617/pinot-client-go/blob/master/examples/batch-quickstart/main.go" target="_blank" rel="noopener noreferrer">example</a> for your reference.</p><p>Code snippet:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">pinotClient</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> err </span><span class="token operator">:=</span><span class="token plain"> pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">NewFromZookeeper</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"localhost:2123"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">""</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"QuickStartCluster"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">if</span><span class="token plain"> err </span><span class="token operator">!=</span><span class="token plain"> </span><span class="token boolean">nil</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> log</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Error</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">err</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> err </span><span class="token operator">:=</span><span class="token plain"> pinotClient</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">ExecuteSQL</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token string" style="color:rgb(255, 121, 198)">"baseballStats"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"select count(*) as cnt, sum(homeRuns) as sum_homeRuns from baseballStats group by teamID limit 10"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">if</span><span class="token plain"> err </span><span class="token operator">!=</span><span class="token plain"> </span><span class="token boolean">nil</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> log</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Error</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">err</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">log</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Infof</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token string" style="color:rgb(255, 121, 198)">"Query Stats: response time - %d ms, scanned docs - %d, total docs - %d"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">TimeUsedMs</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">NumDocsScanned</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">TotalDocs</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Response Format</p><p>Query Response is defined as the struct of following:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">type</span><span class="token plain"> BrokerResponse </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">struct</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> AggregationResults </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token operator">*</span><span class="token plain">AggregationResult </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"aggregationResults,omitempty"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> SelectionResults </span><span class="token operator">*</span><span class="token plain">SelectionResults </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"SelectionResults,omitempty"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ResultTable </span><span class="token operator">*</span><span class="token plain">ResultTable </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"resultTable,omitempty"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> Exceptions </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain">Exception </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"exceptions"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> TraceInfo </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">map</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"traceInfo,omitempty"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumServersQueried </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numServersQueried"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumServersResponded </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numServersResponded"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumSegmentsQueried </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numSegmentsQueried"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumSegmentsProcessed </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numSegmentsProcessed"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumSegmentsMatched </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numSegmentsMatched"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumConsumingSegmentsQueried </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numConsumingSegmentsQueried"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumDocsScanned </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numDocsScanned"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumEntriesScannedInFilter </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numEntriesScannedInFilter"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumEntriesScannedPostFilter </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numEntriesScannedPostFilter"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumGroupsLimitReached </span><span class="token builtin" style="color:rgb(189, 147, 249)">bool</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numGroupsLimitReached"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> TotalDocs </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"totalDocs"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> TimeUsedMs </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"timeUsedMs"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> MinConsumingFreshnessTimeMs </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"minConsumingFreshnessTimeMs"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Note that <code>AggregationResults</code> and <code>SelectionResults</code> are holders for PQL queries.</p><p>Meanwhile <code>ResultTable</code> is the holder for SQL queries. <code>ResultTable</code> is defined as:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)">// ResultTable is a ResultTable</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">type</span><span class="token plain"> ResultTable </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">struct</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> DataSchema RespSchema </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"dataSchema"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> Rows </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">interface</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"rows"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p><code>RespSchema</code> is defined as:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)">// RespSchema is response schema</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">type</span><span class="token plain"> RespSchema </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">struct</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ColumnDataTypes </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"columnDataTypes"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ColumnNames </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"columnNames"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>There are multiple functions defined for <code>ResultTable</code>, like:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetRowCount</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnCount</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnName</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnDataType</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">Get</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">interface</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetString</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetInt</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetLong</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetFloat</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">float32</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetDouble</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">float64</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Sample Usage is <a href="https://github.com/fx19880617/pinot-client-go/blob/master/examples/batch-quickstart/main.go#L58" target="_blank" rel="noopener noreferrer">here</a></p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)">// Print Response Schema</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">for</span><span class="token plain"> c </span><span class="token operator">:=</span><span class="token plain"> </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> c </span><span class="token operator"><</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnCount</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> c</span><span class="token operator">++</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> fmt</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Printf</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token string" style="color:rgb(255, 121, 198)">"%s(%s)\t"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnName</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">c</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnDataType</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">c</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">fmt</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Println</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
-</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token comment" style="color:rgb(98, 114, 164)">// Print Row Table</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">for</span><span class="token plain"> r </span><span class="token operator">:=</span><span class="token plain"> </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> r </span><span class="token operator"><</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">GetRowCount</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> r</span><span class="token operator">++</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">for</span><span class="token plain"> c </span><span class="token operator">:=</span><span class="token plain"> </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> c </span><span class="token operator"><</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnCount</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> c</span><span class="token operator">++</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> fmt</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Printf</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token string" style="color:rgb(255, 121, 198)">"%v\t"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Get</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> c</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> fmt</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Println</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/user-guide/clients/golang.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" 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+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img 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stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>GoLang</h1></header><p>Applications can use this golang client library to query Apache Pinot.</p><p>Source Code Repo: <a href="https://github.com/fx19880617/pinot-client-go" target="_blank" rel="noopener noreferrer">https://github.com/fx19880617/pinot-client-go</a></p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="examples"></a>Examples<a class="hash-link" href="#examples" title="Direct link to heading">#</a></h2><p>Please follow this Pinot Quickstart link to install and start Pinot batch QuickStart locally.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">bin/quick-start-batch.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Check out Client library Github Repo</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token function" style="color:rgb(80, 250, 123)">git</span><span class="token plain"> clone git@github.com:fx19880617/pinot-client-go.git</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot-client-go</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Build and run the example application to query from Pinot Batch Quickstart</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">go build ./examples/batch-quickstart</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">./batch-quickstart</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="usage"></a>Usage<a class="hash-link" href="#usage" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="create-a-pinot-connection"></a>Create a Pinot Connection<a class="hash-link" href="#create-a-pinot-connection" title="Direct link to heading">#</a></h3><p>Pinot client could be initialized through:</p><ol><li>Zookeeper Path</li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">pinotClient </span><span class="token operator">:=</span><span class="token plain"> pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">NewFromZookeeper</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"localhost:2123"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">""</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"QuickStartCluster"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ol><li>A list of broker addresses.</li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">pinotClient </span><span class="token operator">:=</span><span class="token plain"> pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">NewFromBrokerList</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"localhost:8000"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ol><li>ClientConfig</li></ol><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">pinotClient </span><span class="token operator">:=</span><span class="token plain"> pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">NewWithConfig</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">&</span><span class="token plain">pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ClientConfig</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ZkConfig</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token plain"> </span><span class="token operator">&</span><span class="token plain">pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ZookeeperConfig</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ZookeeperPath</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token plain"> zkPath</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> PathPrefix</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token plain"> strings</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Join</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain">zkPathPrefix</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> pinotCluster</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"/"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> SessionTimeoutSec</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token plain"> defaultZkSessionTimeoutSec</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ExtraHTTPHeader</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">map</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"extra-header"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">:</span><span class="token string" style="color:rgb(255, 121, 198)">"value"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="query-pinot"></a>Query Pinot<a class="hash-link" href="#query-pinot" title="Direct link to heading">#</a></h2><p>Please see this <a href="https://github.com/fx19880617/pinot-client-go/blob/master/examples/batch-quickstart/main.go" target="_blank" rel="noopener noreferrer">example</a> for your reference.</p><p>Code snippet:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">pinotClient</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> err </span><span class="token operator">:=</span><span class="token plain"> pinot</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">NewFromZookeeper</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"localhost:2123"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">""</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"QuickStartCluster"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">if</span><span class="token plain"> err </span><span class="token operator">!=</span><span class="token plain"> </span><span class="token boolean">nil</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> log</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Error</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">err</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> err </span><span class="token operator">:=</span><span class="token plain"> pinotClient</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">ExecuteSQL</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token string" style="color:rgb(255, 121, 198)">"baseballStats"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"select count(*) as cnt, sum(homeRuns) as sum_homeRuns from baseballStats group by teamID limit 10"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">if</span><span class="token plain"> err </span><span class="token operator">!=</span><span class="token plain"> </span><span class="token boolean">nil</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> log</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Error</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">err</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">log</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Infof</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token string" style="color:rgb(255, 121, 198)">"Query Stats: response time - %d ms, scanned docs - %d, total docs - %d"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">TimeUsedMs</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">NumDocsScanned</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">TotalDocs</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Response Format</p><p>Query Response is defined as the struct of following:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">type</span><span class="token plain"> BrokerResponse </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">struct</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> AggregationResults </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token operator">*</span><span class="token plain">AggregationResult </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"aggregationResults,omitempty"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> SelectionResults </span><span class="token operator">*</span><span class="token plain">SelectionResults </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"SelectionResults,omitempty"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ResultTable </span><span class="token operator">*</span><span class="token plain">ResultTable </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"resultTable,omitempty"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> Exceptions </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain">Exception </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"exceptions"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> TraceInfo </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">map</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"traceInfo,omitempty"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumServersQueried </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numServersQueried"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumServersResponded </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numServersResponded"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumSegmentsQueried </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numSegmentsQueried"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumSegmentsProcessed </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numSegmentsProcessed"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumSegmentsMatched </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numSegmentsMatched"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumConsumingSegmentsQueried </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numConsumingSegmentsQueried"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumDocsScanned </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numDocsScanned"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumEntriesScannedInFilter </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numEntriesScannedInFilter"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumEntriesScannedPostFilter </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numEntriesScannedPostFilter"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> NumGroupsLimitReached </span><span class="token builtin" style="color:rgb(189, 147, 249)">bool</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"numGroupsLimitReached"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> TotalDocs </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"totalDocs"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> TimeUsedMs </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"timeUsedMs"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> MinConsumingFreshnessTimeMs </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"minConsumingFreshnessTimeMs"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Note that <code>AggregationResults</code> and <code>SelectionResults</code> are holders for PQL queries.</p><p>Meanwhile <code>ResultTable</code> is the holder for SQL queries. <code>ResultTable</code> is defined as:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)">// ResultTable is a ResultTable</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">type</span><span class="token plain"> ResultTable </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">struct</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> DataSchema RespSchema </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"dataSchema"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> Rows </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">interface</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"rows"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p><code>RespSchema</code> is defined as:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)">// RespSchema is response schema</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">type</span><span class="token plain"> RespSchema </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">struct</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ColumnDataTypes </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"columnDataTypes"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ColumnNames </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">`json:"columnNames"`</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>There are multiple functions defined for <code>ResultTable</code>, like:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetRowCount</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnCount</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnName</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnDataType</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">Get</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">interface</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetString</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">string</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetInt</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetLong</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">int64</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetFloat</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">float32</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">func</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">GetDouble</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">rowIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> columnIndex </span><span class="token builtin" style="color:rgb(189, 147, 249)">int</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token builtin" style="color:rgb(189, 147, 249)">float64</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>Sample Usage is <a href="https://github.com/fx19880617/pinot-client-go/blob/master/examples/batch-quickstart/main.go#L58" target="_blank" rel="noopener noreferrer">here</a></p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly go"><pre tabindex="0" class="prism-code language-go codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)">// Print Response Schema</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">for</span><span class="token plain"> c </span><span class="token operator">:=</span><span class="token plain"> </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> c </span><span class="token operator"><</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnCount</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> c</span><span class="token operator">++</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> fmt</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Printf</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token string" style="color:rgb(255, 121, 198)">"%s(%s)\t"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnName</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">c</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnDataType</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">c</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">fmt</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Println</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
+</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token comment" style="color:rgb(98, 114, 164)">// Print Row Table</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">for</span><span class="token plain"> r </span><span class="token operator">:=</span><span class="token plain"> </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> r </span><span class="token operator"><</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">GetRowCount</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> r</span><span class="token operator">++</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">for</span><span class="token plain"> c </span><span class="token operator">:=</span><span class="token plain"> </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> c </span><span class="token operator"><</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">GetColumnCount</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">;</span><span class="token plain"> c</span><span class="token operator">++</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> fmt</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Printf</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token string" style="color:rgb(255, 121, 198)">"%v\t"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> brokerResp</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain">ResultTable</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Get</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">r</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> c</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> fmt</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token function" style="color:rgb(80, 250, 123)">Println</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/user-guide/clients/golang.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 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diff --git a/content/docs/user-guide/clients/java/index.html b/content/docs/user-guide/clients/java/index.html
index 8395664..0f53e6e 100644
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-<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button" title="Scroll to top"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="markdown"><header><h1 class="h1Heading_27L5">Java</h1></header><p>The java client can be found in pinot-clients/pinot-java-client. Here's an example of how to use the pinot-java-client to query Pinot.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly java"><pre tabindex="0" class="prism-code language-java codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.pinot.client.Connection;</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.pinot.client.ConnectionFactory;</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.pinot.client.Request;</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.pinot.client.ResultSetGroup;</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.pinot.client.ResultSet;</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="markdown"><header><h1>Java</h1></header><p>The java client can be found in pinot-clients/pinot-java-client. Here's an example of how to use the pinot-java-client to query Pinot.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly java"><pre tabindex="0" class="prism-code language-java codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.pinot.client.Connection;</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.pinot.client.ConnectionFactory;</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.pinot.client.Request;</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.pinot.client.ResultSetGroup;</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.pinot.client.ResultSet;</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">/**</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> * Demonstrates the use of the pinot-client to query Pinot from Java</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> */</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">public class PinotClientExample {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> public static void main(String[] args) {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> // pinot connection</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> String zkUrl = "localhost:2181";</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> String pinotClusterName = "PinotCluster";</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> Connection pinotConnection = ConnectionFactory.fromZookeeper(zkUrl + "/" + pinotClusterName);</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
@@ -33,8 +33,8 @@
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">System.out.println("Number of result groups:" +</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> resultSetGroup.getResultSetCount(); // 2, min(foo) and max(foo)</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">ResultSet resultSetMax = resultSetGroup.getResultSet(0);</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">System.out.println("Max foo: " + resultSetMax.getInt(0));</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">ResultSet resultSetMin = resultSetGroup.getResultSet(1);</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">System.out.println("Min foo: " + resultSetMin.getInt(0));</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>In case of aggregation group by, there will be as many ResultSets as the number of aggregations, each of which will contain multiple results grouped by a group key.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly java"><pre tabindex="0" class="prism-code language-java codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">ResultSetGroup resultSetGroup =</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> connection.execute(</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> new Request("pql", "select min(foo), max(foo) from bar group by baz"));</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">System.out.println("Number of result groups:" +</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> resultSetGroup.getResultSetCount(); // 2, min(foo) and max(foo)</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">ResultSet minResultSet = resultSetGroup.getResultSet(0);</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">for(int i = 0; i < minResultSet.length(); ++i) {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> System.out.println("Minimum foo for " + minResultSet.getGroupKeyString(i, 1) +</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ": " + minResultSet.getInt(i));</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
-</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">ResultSet maxResultSet = resultSetGroup.getResultSet(1);</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">for(int i = 0; i < maxResultSet.length(); ++i) {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> System.out.println("Maximum foo for " + maxResultSet.getGroupKeyString(i, 1) +</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ": " + maxResultSet.getInt(i));</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/user-guide/clients/java.md" target="_blank" rel="noreferrer noopener"><svg 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+</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">ResultSet maxResultSet = resultSetGroup.getResultSet(1);</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">for(int i = 0; i < maxResultSet.length(); ++i) {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> System.out.println("Maximum foo for " + maxResultSet.getGroupKeyString(i, 1) +</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> ": " + maxResultSet.getInt(i));</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/user-guide/clients/java.md" target="_blank" rel="noreferrer 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diff --git a/content/docs/user-guide/index.html b/content/docs/user-guide/index.html
index f164eea..8fe1969 100644
--- a/content/docs/user-guide/index.html
+++ b/content/docs/user-guide/index.html
@@ -3,7 +3,7 @@
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<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,14 +11,14 @@
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<link rel="search" type="application/opensearchdescription+xml" title="Apache Pinot™" href="/opensearch.xml">
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-<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button" title="Scroll to top"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1 class="h1Heading_27L5">PQL</h1></header><p>PQL is a derivative of SQL derivative that supports selection, projection, aggregation, grouping aggregation. There is no support for Joins or Subqueries. Specifically, for Pinot:</p><ul><li>Aggregations are computed in parallel</li><li>Results of aggregations with large amounts of group keys (>1M) are approximated</li></ul><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="pql-limitations"></a>PQL Limitations<a class="hash-link" href="#pql-limitations" title="Direct link to heading">#</a></h2><p>PQL is only a derivative of SQL, and it does not support Joins nor Subqueries. In order to support them, we suggest to rely on <a href="https://prestodb.io/" target="_blank" rel="noopener noreferrer">PrestoDB</a>, although Subqueries are not completely supported by PrestoDB at the moment of writing.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="pql-examples"></a>PQL Examples<a class="hash-link" href="#pql-examples" title="Direct link to heading">#</a></h2><p>The Pinot Query Language (PQL) is very similar to standard SQL:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">COUNT</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="aggregation"></a>Aggregation<a class="hash-link" href="#aggregation" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">COUNT</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">SUM</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="grouping-on-aggregation"></a>Grouping on Aggregation<a class="hash-link" href="#grouping-on-aggregation" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MIN</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">SUM</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">AVG</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> baz </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="ordering-on-aggregation"></a>Ordering on Aggregation<a class="hash-link" href="#ordering-on-aggregation" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MIN</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">SUM</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">AVG</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> baz</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">ORDER</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">DESC</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="filtering"></a>Filtering<a class="hash-link" href="#filtering" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">COUNT</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> foo </span><span class="token operator">=</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'foo'</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">AND</span><span class="token plain"> bar </span><span class="token operator">BETWEEN</span><span class="token plain"> </span><span class="token number">1</span><span class="token plain"> </span><span class="token operator">AND</span><span class="token plain"> </span><span class="token number">20</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">OR</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">baz </span><span class="token operator"><</span><span class="token plain"> </span><span class="token number">42</span><span class="token plain"> </span><span class="token operator">AND</span><span class="token plain"> quux </span><span class="token operator">IN</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token string" style="color:rgb(255, 121, 198)">'hello'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'goodbye'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token operator">AND</span><span class="token plain"> quuux </span><span class="token operator">NOT</span><span class="token plain"> </span><span class="token operator">IN</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">42</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token number">69</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="selection-projection"></a>Selection (Projection)<a class="hash-link" href="#selection-projection" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token operator">*</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> quux </span><span class="token operator"><</span><span class="token plain"> </span><span class="token number">5</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="ordering-on-selection"></a>Ordering on Selection<a class="hash-link" href="#ordering-on-selection" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> bar </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> baz </span><span class="token operator">></span><span class="token plain"> </span><span class="token number">20</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">ORDER</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">DESC</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token number">100</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="pagination-on-selection"></a>Pagination on Selection<a class="hash-link" href="#pagination-on-selection" title="Direct link to heading">#</a></h3><p>Note: results might not be consistent if column ordered by has same value in multiple rows.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> bar </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> baz </span><span class="token operator">></span><span class="token plain"> </span><span class="token number">20</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">ORDER</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">DESC</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token number">50</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token number">100</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="wild-card-match-in-where-clause-only"></a>Wild-card match (in WHERE clause only)<a class="hash-link" href="#wild-card-match-in-where-clause-only" title="Direct link to heading">#</a></h3><p>To count rows where the column <code>airlineName</code> starts with U</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">count</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> SomeTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> regexp_like</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">airlineName</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'^U.*'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> airlineName </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token number">10</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="udf"></a>UDF<a class="hash-link" href="#udf" title="Direct link to heading">#</a></h3><p>As of now, functions have to be implemented within Pinot. Injecting functions is not allowed yet. The example below demonstrate the use of UDFs. More examples in Transform Function in Aggregation Grouping</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">count</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> timeConvert</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">timeColumnName</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'SECONDS'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'DAYS'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="bytes-column"></a>BYTES column<a class="hash-link" href="#bytes-column" title="Direct link to heading">#</a></h3><p>Pinot supports queries on BYTES column using HEX string. The query response also uses hex string to represent bytes value.
-E.g. the query below fetches all the rows for a given UID.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token operator">*</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> UID </span><span class="token operator">=</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"c8b3bce0b378fc5ce8067fc271a34892"</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="pql-specification"></a>PQL Specification<a class="hash-link" href="#pql-specification" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="select"></a>SELECT<a class="hash-link" href="#select" title="Direct link to heading">#</a></h3><p>The select statement is as follows</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token operator"><</span><span class="token plain">outputColumn</span><span class="token operator">></span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> outputColumn</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> outputColumn</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> </span><span class="token operator"><</span><span class="token plain">tableName</span><span class="token operator">></span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">ORDER</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p><code>outputColumn</code> can be <code>*</code> to project all columns, columns (<code>foo</code>, <code>bar</code>, <code>baz</code>) or aggregation functions like (<code>MIN(foo), MAX(bar), AVG(baz)</code>).</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="supported-aggregations-on-single-value-columns"></a>Supported aggregations on single-value columns<a class="hash-link" href="#supported-aggregations-on-single-value-columns" title="Direct link to heading">#</a></h3><ul><li>COUNT</li><li>MIN</li><li>MAX</li><li>SUM</li><li>AVG</li><li>MINMAXRANGE</li><li>DISTINCT</li><li>DISTINCTCOUNT</li><li>DISTINCTCOUNTHLL</li><li>DISTINCTCOUNTRAWHLL: Returns HLL response serialized as string. The serialized HLL can be converted back into an HLL (see pinot-core/**/HllUtil.java as an example) and then aggregated with other HLLs. A common use case may be to merge HLL responses from different Pinot tables, or to allow aggregation after client-side batching.
-FASTHLL (WARN: will be deprecated soon. FASTHLL stores serialized HyperLogLog in String format, which performs worse than DISTINCTCOUNTHLL, which supports serialized HyperLogLog in BYTES (byte array) format)</li><li>PERCENTILE[0-100]: e.g. PERCENTILE5, PERCENTILE50, PERCENTILE99, etc.</li><li>PERCENTILEEST[0-100]: e.g. PERCENTILEEST5, PERCENTILEEST50, PERCENTILEEST99, etc.</li></ul><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="supported-aggregations-on-multi-value-columns"></a>Supported aggregations on multi-value columns<a class="hash-link" href="#supported-aggregations-on-multi-value-columns" title="Direct link to heading">#</a></h3><ul><li>COUNTMV</li><li>MINMV</li><li>MAXMV</li><li>SUMMV</li><li>AVGMV</li><li>MINMAXRANGEMV</li><li>DISTINCTCOUNTMV</li><li>DISTINCTCOUNTHLLMV</li><li>DISTINCTCOUNTRAWHLLMV: Returns HLL response serialized as string. The serialized HLL can be converted back into an HLL (see pinot-core/**/HllUtil.java as an example) and then aggregated with other HLLs. A common use case may be to merge HLL responses from different Pinot tables, or to allow aggregation after client-side batching.</li><li>FASTHLLMV (WARN: will be deprecated soon. It does not make lots of sense to configure serialized HyperLogLog column as a dimension)</li><li>PERCENTILE[0-100]MV: e.g. PERCENTILE5MV, PERCENTILE50MV, PERCENTILE99MV, etc.</li><li>PERCENTILEEST[0-100]MV: e.g. PERCENTILEEST5MV, PERCENTILEEST50MV, PERCENTILEEST99MV, etc.</li></ul><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="where"></a>WHERE<a class="hash-link" href="#where" title="Direct link to heading">#</a></h3><p>Supported predicates are comparisons with a constant using the standard SQL operators (<code>=, <, <=, >, >=, <>, '!='</code>) , range comparisons using <code>BETWEEN (foo BETWEEN 42 AND 69)</code>, set membership (<code>foo IN (1, 2, 4, 8)</code>) and exclusion (foo NOT IN (1, 2, 4, 8)). For <code>BETWEEN</code>, the range is inclusive.</p><p>Comparison with a regular expression is supported using the regexp_like function, as in <code>WHERE regexp_like(columnName, 'regular expression')</code></p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="group-by"></a>GROUP BY<a class="hash-link" href="#group-by" title="Direct link to heading">#</a></h3><p>The GROUP BY clause groups aggregation results by a list of columns, or transform functions on columns (see below)</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="order-by"></a>ORDER BY<a class="hash-link" href="#order-by" title="Direct link to heading">#</a></h3><p>The ORDER BY clause orders selection results or group by results by a list of columns. PQL supports ordering DESC or ASC.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="top"></a>TOP<a class="hash-link" href="#top" title="Direct link to heading">#</a></h3><p>The TOP n clause causes the 'n' largest group results to be returned. If not specified, the top 10 groups are returned.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="limit"></a>LIMIT<a class="hash-link" href="#limit" title="Direct link to heading">#</a></h3><p>The LIMIT n clause causes the selection results to contain at most 'n' results. The LIMIT a, b clause paginate the selection results from the 'a' th results and return at most 'b' results.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="transform-function-in-aggregation-and-grouping"></a>Transform Function in Aggregation and Grouping<a class="hash-link" href="#transform-function-in-aggregation-and-grouping" title="Direct link to heading">#</a></h2><p>In aggregation and grouping, each column can be transformed from one or multiple columns. For example, the following query will calculate the maximum value of column foo divided by column bar grouping on the column time converted from time unit MILLISECONDS to SECONDS:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">DIV</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> TIMECONVERT</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">time</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'MILLISECONDS'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'SECONDS'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="supported-transform-functions"></a>Supported transform functions<a class="hash-link" href="#supported-transform-functions" title="Direct link to heading">#</a></h3><table><thead><tr><th>Functions</th><th>Decription</th></tr></thead><tbody><tr><td>ADD</td><td>Sum of at least two values</td></tr><tr><td>SUB</td><td>Difference between two values</td></tr><tr><td>MULT</td><td>Product of at least two values</td></tr><tr><td>DIV</td><td>Quotient of two values</td></tr><tr><td>TIMECONVERT</td><td>Takes 3 arguments, converts the value into another time unit. <br> Examples - <code>TIMECONVERT(time, 'MILLISECONDS', 'SECONDS')</code> - This expression converts the value of column <code>time</code> (taken to be in milliseconds) to the nearest seconds (i.e. the nearest seconds that is lower than the value of <code>date</code> column) <br> <br> Takes 4 arguments, converts the value into another date time format, and buckets time based on the given time granularity. <br> <br> <code>DATETIMECONVERT(columnName, inputFormat, outputFormat, outputGranularity)</code> where: <br><code>columnName</code> - column name to convert <br> <code>inputFormat</code> - format of the column columnName <br> <code>outputFormat</code> - format of the result desired after conversion <br> <code>outputGranularity</code> - the granularity in which to bucket the result</td></tr><tr><td>DATETIMECONVERT</td><td>Format is expressed as <code><time size>:<time unit>:<time format>:<pattern></code> <br> where: <br> <code>time size</code> - size of the time unit eg: 1, 10 <br> <code>time unit</code> - HOURS, DAYS etc <br> <code>time format</code> - EPOCH or SIMPLE_DATE_FORMAT <br> <code>pattern</code> - this is defined in case of SIMPLE_DATE_FORMAT. eg: yyyyMMdd. A specific timezone can be passed using tz(timezone) <br> <code>timezone</code> - can be expressed as long form tz(Asia/Kolkata), or short form tz(IST) or in terms of GMT tz(GMT+0530). Default is UTC. It is recommended to use long form timezone, as short forms are ambiguous with daylight savings (eg: PDT works during daylight savings, PST otherwise) <br> <br> Granularity is expressed as <code><time size>:<time unit></code> <br> <strong>Examples</strong> <br> 1. To convert column <code>Date</code> from <code>hoursSinceEpoch</code> to <code>daysSinceEpoch</code> and bucket it to 1 day granularity <br> 2. To simply bucket millis "Date" to 15 minutes <code>granularity dateTimeConvert(Date, '1:MILLISECONDS:EPOCH', '1:MILLISECONDS:EPOCH', '15:MINUTES')</code> <br> 3. To convert column "Date" from hoursSinceEpoch to format yyyyMdd and bucket it to 1 days granularity <code>dateTimeConvert(Date, '1:HOURS:EPOCH', '1:DAYS:SIMPLE_DATE_FORMAT:yyyyMMdd', '1:DAYS')</code> <br> 4. To convert column "Date" from format yyyy/MM/dd to weeksSinceEpoch and bucket it to 1 weeks granularity <code>dateTimeConvert(Date, '1:DAYS:SIMPLE_DATE_FORMAT:yyyy/MM/dd', '1:WEEKS:EPOCH', '1:WEEKS')</code> <br> 5. To convert column "Date" from millis to format yyyyMdd in timezone PST <code>dateTimeConvert(Date, '1:MILLISECONDS:EPOCH', '1:DAYS:SIMPLE_DATE_FORMAT:yyyyMMdd tz(America/Los_Angeles)', '1:DAYS')</code></td></tr><tr><td>DATETRUNC</td><td>(Presto) SQL compatible date truncation, equivalent to the Presto function date_trunc. Takes at least 3 and upto 5 arguments, converts the value into a specified output granularity seconds since UTC epoch that is bucketed on a unit in a specified timezone. Examples DATETRUNC('week', time_in_seconds, 'SECONDS') This expression converts the column time_in_seconds, which is a long containing seconds since UTC epoch truncated at WEEK (where a Week starts at Monday UTC midnight). The output is a long seconds since UTC epoch. <br> <code>DATETRUNC('quarter', DIV(time_milliseconds/1000), 'SECONDS', 'America/Los_Angeles', 'HOURS')</code> This expression converts the expression <code>time_in_milliseconds/1000</code> (which is thus in seconds) into hours that are truncated at <code>QUARTER</code> at the Los Angeles time zone (where a Quarter begins on 1/1, 4/1, 7/1, 10/1 in Los Angeles timezone). The output is expressed as hours since UTC epoch (note that the output is not Los Angeles timezone)</td></tr><tr><td>VALUEIN</td><td>Takes at least 2 arguments, where the first argument is a multi-valued column, and the following arguments are constant values. The transform function will filter the value from the multi-valued column with the given constant values. The <code>VALUEIN</code> transform function is especially useful when the same multi-valued column is both filtering column and grouping column. <br><br> Examples <br> <code>VALUEIN(mvColumn, 3, 5, 15)</code></td></tr></tbody></table><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="differences-with-sql"></a>Differences with SQL<a class="hash-link" href="#differences-with-sql" title="Direct link to heading">#</a></h2><div class="alert alert--info alert--icon" role="alert"><i class="feather icon-info"></i> These differences only apply to the PQL endpoint. They do not hold true for the standard-SQL endpoint, which is the recommended endpoint. <br>More information about the two types of endpoints in Querying Pinot.. </div><ul><li>TOP works like LIMIT for truncation in group by queries</li><li>No need to select the columns to group with.
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>PQL</h1></header><p>PQL is a derivative of SQL derivative that supports selection, projection, aggregation, grouping aggregation. There is no support for Joins or Subqueries. Specifically, for Pinot:</p><ul><li>Aggregations are computed in parallel</li><li>Results of aggregations with large amounts of group keys (>1M) are approximated</li></ul><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="pql-limitations"></a>PQL Limitations<a class="hash-link" href="#pql-limitations" title="Direct link to heading">#</a></h2><p>PQL is only a derivative of SQL, and it does not support Joins nor Subqueries. In order to support them, we suggest to rely on <a href="https://prestodb.io/" target="_blank" rel="noopener noreferrer">PrestoDB</a>, although Subqueries are not completely supported by PrestoDB at the moment of writing.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="pql-examples"></a>PQL Examples<a class="hash-link" href="#pql-examples" title="Direct link to heading">#</a></h2><p>The Pinot Query Language (PQL) is very similar to standard SQL:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">COUNT</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="aggregation"></a>Aggregation<a class="hash-link" href="#aggregation" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">COUNT</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">SUM</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="grouping-on-aggregation"></a>Grouping on Aggregation<a class="hash-link" href="#grouping-on-aggregation" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MIN</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">SUM</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">AVG</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> baz </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="ordering-on-aggregation"></a>Ordering on Aggregation<a class="hash-link" href="#ordering-on-aggregation" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MIN</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">SUM</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">AVG</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> baz</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">ORDER</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">DESC</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="filtering"></a>Filtering<a class="hash-link" href="#filtering" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">COUNT</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> foo </span><span class="token operator">=</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'foo'</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">AND</span><span class="token plain"> bar </span><span class="token operator">BETWEEN</span><span class="token plain"> </span><span class="token number">1</span><span class="token plain"> </span><span class="token operator">AND</span><span class="token plain"> </span><span class="token number">20</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">OR</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">baz </span><span class="token operator"><</span><span class="token plain"> </span><span class="token number">42</span><span class="token plain"> </span><span class="token operator">AND</span><span class="token plain"> quux </span><span class="token operator">IN</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token string" style="color:rgb(255, 121, 198)">'hello'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'goodbye'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token operator">AND</span><span class="token plain"> quuux </span><span class="token operator">NOT</span><span class="token plain"> </span><span class="token operator">IN</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token number">42</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token number">69</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="selection-projection"></a>Selection (Projection)<a class="hash-link" href="#selection-projection" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token operator">*</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> quux </span><span class="token operator"><</span><span class="token plain"> </span><span class="token number">5</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="ordering-on-selection"></a>Ordering on Selection<a class="hash-link" href="#ordering-on-selection" title="Direct link to heading">#</a></h3><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> bar </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> baz </span><span class="token operator">></span><span class="token plain"> </span><span class="token number">20</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">ORDER</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">DESC</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token number">100</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="pagination-on-selection"></a>Pagination on Selection<a class="hash-link" href="#pagination-on-selection" title="Direct link to heading">#</a></h3><p>Note: results might not be consistent if column ordered by has same value in multiple rows.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> bar </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> baz </span><span class="token operator">></span><span class="token plain"> </span><span class="token number">20</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">ORDER</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">DESC</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token number">50</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token number">100</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="wild-card-match-in-where-clause-only"></a>Wild-card match (in WHERE clause only)<a class="hash-link" href="#wild-card-match-in-where-clause-only" title="Direct link to heading">#</a></h3><p>To count rows where the column <code>airlineName</code> starts with U</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">count</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> SomeTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> regexp_like</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">airlineName</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'^U.*'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> airlineName </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token number">10</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="udf"></a>UDF<a class="hash-link" href="#udf" title="Direct link to heading">#</a></h3><p>As of now, functions have to be implemented within Pinot. Injecting functions is not allowed yet. The example below demonstrate the use of UDFs. More examples in Transform Function in Aggregation Grouping</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">count</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> timeConvert</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">timeColumnName</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'SECONDS'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'DAYS'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="bytes-column"></a>BYTES column<a class="hash-link" href="#bytes-column" title="Direct link to heading">#</a></h3><p>Pinot supports queries on BYTES column using HEX string. The query response also uses hex string to represent bytes value.
+E.g. the query below fetches all the rows for a given UID.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token operator">*</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> UID </span><span class="token operator">=</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"c8b3bce0b378fc5ce8067fc271a34892"</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="pql-specification"></a>PQL Specification<a class="hash-link" href="#pql-specification" title="Direct link to heading">#</a></h2><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="select"></a>SELECT<a class="hash-link" href="#select" title="Direct link to heading">#</a></h3><p>The select statement is as follows</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token operator"><</span><span class="token plain">outputColumn</span><span class="token operator">></span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> outputColumn</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> outputColumn</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> </span><span class="token operator"><</span><span class="token plain">tableName</span><span class="token operator">></span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">WHERE</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">ORDER</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token plain"> </span><span class="token operator">|</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">LIMIT</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">.</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p><code>outputColumn</code> can be <code>*</code> to project all columns, columns (<code>foo</code>, <code>bar</code>, <code>baz</code>) or aggregation functions like (<code>MIN(foo), MAX(bar), AVG(baz)</code>).</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="supported-aggregations-on-single-value-columns"></a>Supported aggregations on single-value columns<a class="hash-link" href="#supported-aggregations-on-single-value-columns" title="Direct link to heading">#</a></h3><ul><li>COUNT</li><li>MIN</li><li>MAX</li><li>SUM</li><li>AVG</li><li>MINMAXRANGE</li><li>DISTINCT</li><li>DISTINCTCOUNT</li><li>DISTINCTCOUNTHLL</li><li>DISTINCTCOUNTRAWHLL: Returns HLL response serialized as string. The serialized HLL can be converted back into an HLL (see pinot-core/**/HllUtil.java as an example) and then aggregated with other HLLs. A common use case may be to merge HLL responses from different Pinot tables, or to allow aggregation after client-side batching.
+FASTHLL (WARN: will be deprecated soon. FASTHLL stores serialized HyperLogLog in String format, which performs worse than DISTINCTCOUNTHLL, which supports serialized HyperLogLog in BYTES (byte array) format)</li><li>PERCENTILE[0-100]: e.g. PERCENTILE5, PERCENTILE50, PERCENTILE99, etc.</li><li>PERCENTILEEST[0-100]: e.g. PERCENTILEEST5, PERCENTILEEST50, PERCENTILEEST99, etc.</li></ul><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="supported-aggregations-on-multi-value-columns"></a>Supported aggregations on multi-value columns<a class="hash-link" href="#supported-aggregations-on-multi-value-columns" title="Direct link to heading">#</a></h3><ul><li>COUNTMV</li><li>MINMV</li><li>MAXMV</li><li>SUMMV</li><li>AVGMV</li><li>MINMAXRANGEMV</li><li>DISTINCTCOUNTMV</li><li>DISTINCTCOUNTHLLMV</li><li>DISTINCTCOUNTRAWHLLMV: Returns HLL response serialized as string. The serialized HLL can be converted back into an HLL (see pinot-core/**/HllUtil.java as an example) and then aggregated with other HLLs. A common use case may be to merge HLL responses from different Pinot tables, or to allow aggregation after client-side batching.</li><li>FASTHLLMV (WARN: will be deprecated soon. It does not make lots of sense to configure serialized HyperLogLog column as a dimension)</li><li>PERCENTILE[0-100]MV: e.g. PERCENTILE5MV, PERCENTILE50MV, PERCENTILE99MV, etc.</li><li>PERCENTILEEST[0-100]MV: e.g. PERCENTILEEST5MV, PERCENTILEEST50MV, PERCENTILEEST99MV, etc.</li></ul><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="where"></a>WHERE<a class="hash-link" href="#where" title="Direct link to heading">#</a></h3><p>Supported predicates are comparisons with a constant using the standard SQL operators (<code>=, <, <=, >, >=, <>, '!='</code>) , range comparisons using <code>BETWEEN (foo BETWEEN 42 AND 69)</code>, set membership (<code>foo IN (1, 2, 4, 8)</code>) and exclusion (foo NOT IN (1, 2, 4, 8)). For <code>BETWEEN</code>, the range is inclusive.</p><p>Comparison with a regular expression is supported using the regexp_like function, as in <code>WHERE regexp_like(columnName, 'regular expression')</code></p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="group-by"></a>GROUP BY<a class="hash-link" href="#group-by" title="Direct link to heading">#</a></h3><p>The GROUP BY clause groups aggregation results by a list of columns, or transform functions on columns (see below)</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="order-by"></a>ORDER BY<a class="hash-link" href="#order-by" title="Direct link to heading">#</a></h3><p>The ORDER BY clause orders selection results or group by results by a list of columns. PQL supports ordering DESC or ASC.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="top"></a>TOP<a class="hash-link" href="#top" title="Direct link to heading">#</a></h3><p>The TOP n clause causes the 'n' largest group results to be returned. If not specified, the top 10 groups are returned.</p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="limit"></a>LIMIT<a class="hash-link" href="#limit" title="Direct link to heading">#</a></h3><p>The LIMIT n clause causes the selection results to contain at most 'n' results. The LIMIT a, b clause paginate the selection results from the 'a' th results and return at most 'b' results.</p><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="transform-function-in-aggregation-and-grouping"></a>Transform Function in Aggregation and Grouping<a class="hash-link" href="#transform-function-in-aggregation-and-grouping" title="Direct link to heading">#</a></h2><p>In aggregation and grouping, each column can be transformed from one or multiple columns. For example, the following query will calculate the maximum value of column foo divided by column bar grouping on the column time converted from time unit MILLISECONDS to SECONDS:</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token operator">DIV</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> TIMECONVERT</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">time</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'MILLISECONDS'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">'SECONDS'</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="supported-transform-functions"></a>Supported transform functions<a class="hash-link" href="#supported-transform-functions" title="Direct link to heading">#</a></h3><table><thead><tr><th>Functions</th><th>Decription</th></tr></thead><tbody><tr><td>ADD</td><td>Sum of at least two values</td></tr><tr><td>SUB</td><td>Difference between two values</td></tr><tr><td>MULT</td><td>Product of at least two values</td></tr><tr><td>DIV</td><td>Quotient of two values</td></tr><tr><td>TIMECONVERT</td><td>Takes 3 arguments, converts the value into another time unit. <br> Examples - <code>TIMECONVERT(time, 'MILLISECONDS', 'SECONDS')</code> - This expression converts the value of column <code>time</code> (taken to be in milliseconds) to the nearest seconds (i.e. the nearest seconds that is lower than the value of <code>date</code> column) <br> <br> Takes 4 arguments, converts the value into another date time format, and buckets time based on the given time granularity. <br> <br> <code>DATETIMECONVERT(columnName, inputFormat, outputFormat, outputGranularity)</code> where: <br><code>columnName</code> - column name to convert <br> <code>inputFormat</code> - format of the column columnName <br> <code>outputFormat</code> - format of the result desired after conversion <br> <code>outputGranularity</code> - the granularity in which to bucket the result</td></tr><tr><td>DATETIMECONVERT</td><td>Format is expressed as <code><time size>:<time unit>:<time format>:<pattern></code> <br> where: <br> <code>time size</code> - size of the time unit eg: 1, 10 <br> <code>time unit</code> - HOURS, DAYS etc <br> <code>time format</code> - EPOCH or SIMPLE_DATE_FORMAT <br> <code>pattern</code> - this is defined in case of SIMPLE_DATE_FORMAT. eg: yyyyMMdd. A specific timezone can be passed using tz(timezone) <br> <code>timezone</code> - can be expressed as long form tz(Asia/Kolkata), or short form tz(IST) or in terms of GMT tz(GMT+0530). Default is UTC. It is recommended to use long form timezone, as short forms are ambiguous with daylight savings (eg: PDT works during daylight savings, PST otherwise) <br> <br> Granularity is expressed as <code><time size>:<time unit></code> <br> <strong>Examples</strong> <br> 1. To convert column <code>Date</code> from <code>hoursSinceEpoch</code> to <code>daysSinceEpoch</code> and bucket it to 1 day granularity <br> 2. To simply bucket millis "Date" to 15 minutes <code>granularity dateTimeConvert(Date, '1:MILLISECONDS:EPOCH', '1:MILLISECONDS:EPOCH', '15:MINUTES')</code> <br> 3. To convert column "Date" from hoursSinceEpoch to format yyyyMdd and bucket it to 1 days granularity <code>dateTimeConvert(Date, '1:HOURS:EPOCH', '1:DAYS:SIMPLE_DATE_FORMAT:yyyyMMdd', '1:DAYS')</code> <br> 4. To convert column "Date" from format yyyy/MM/dd to weeksSinceEpoch and bucket it to 1 weeks granularity <code>dateTimeConvert(Date, '1:DAYS:SIMPLE_DATE_FORMAT:yyyy/MM/dd', '1:WEEKS:EPOCH', '1:WEEKS')</code> <br> 5. To convert column "Date" from millis to format yyyyMdd in timezone PST <code>dateTimeConvert(Date, '1:MILLISECONDS:EPOCH', '1:DAYS:SIMPLE_DATE_FORMAT:yyyyMMdd tz(America/Los_Angeles)', '1:DAYS')</code></td></tr><tr><td>DATETRUNC</td><td>(Presto) SQL compatible date truncation, equivalent to the Presto function date_trunc. Takes at least 3 and upto 5 arguments, converts the value into a specified output granularity seconds since UTC epoch that is bucketed on a unit in a specified timezone. Examples DATETRUNC('week', time_in_seconds, 'SECONDS') This expression converts the column time_in_seconds, which is a long containing seconds since UTC epoch truncated at WEEK (where a Week starts at Monday UTC midnight). The output is a long seconds since UTC epoch. <br> <code>DATETRUNC('quarter', DIV(time_milliseconds/1000), 'SECONDS', 'America/Los_Angeles', 'HOURS')</code> This expression converts the expression <code>time_in_milliseconds/1000</code> (which is thus in seconds) into hours that are truncated at <code>QUARTER</code> at the Los Angeles time zone (where a Quarter begins on 1/1, 4/1, 7/1, 10/1 in Los Angeles timezone). The output is expressed as hours since UTC epoch (note that the output is not Los Angeles timezone)</td></tr><tr><td>VALUEIN</td><td>Takes at least 2 arguments, where the first argument is a multi-valued column, and the following arguments are constant values. The transform function will filter the value from the multi-valued column with the given constant values. The <code>VALUEIN</code> transform function is especially useful when the same multi-valued column is both filtering column and grouping column. <br><br> Examples <br> <code>VALUEIN(mvColumn, 3, 5, 15)</code></td></tr></tbody></table><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="differences-with-sql"></a>Differences with SQL<a class="hash-link" href="#differences-with-sql" title="Direct link to heading">#</a></h2><div class="alert alert--info alert--icon" role="alert"><i class="feather icon-info"></i> These differences only apply to the PQL endpoint. They do not hold true for the standard-SQL endpoint, which is the recommended endpoint. <br>More information about the two types of endpoints in Querying Pinot.. </div><ul><li>TOP works like LIMIT for truncation in group by queries</li><li>No need to select the columns to group with.
The following two queries are both supported in PQL, where the non-aggregation columns are ignored.</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MIN</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">SUM</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">AVG</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> mytable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> baz</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token number">50</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> baz</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MIN</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">SUM</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">AVG</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> mytable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> baz</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><ul><li>The results will always order by the aggregated value (descending).
-The results for query</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MIN</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>will be the same as the combining results from the following queries</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MIN</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token number">50</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>where we don't put the results for the same group together.</p><ul><li>No support for <strong>ORDER BY</strong> in aggregation group by. However, ORDER BY support was added recently and is available in the standard-SQL endpoint. It can be used in the PQL endpoint by passing <code>queryOptions</code> into the payload as follows</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"pql"</span><span class="token plain"> : </span><span class="token string" style="color:rgb(255, 121, 198)">"SELECT SUM(foo), SUM(bar) from myTable GROUP BY moo ORDER BY SUM(bar) ASC, moo DESC TOP 10"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"queryOptions"</span><span class="token plain"> : </span><span class="token string" style="color:rgb(255, 121, 198)">"groupByMode=sql;responseFormat=sql"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>where:</p><ul><li><code>groupByMode=sql</code> - standard sql way of execution group by, hence accepting order by</li><li><code>responseFormat=sql</code> - standard sql way of displaying results, in a tabular manner</li></ul></div><footer class="row docusaurus-mt-lg"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/user-guide/pql.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 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+The results for query</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MIN</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>will be the same as the combining results from the following queries</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MIN</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token number">50</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">SELECT</span><span class="token plain"> </span><span class="token function" style="color:rgb(80, 250, 123)">MAX</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">foo</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">FROM</span><span class="token plain"> myTable</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">BY</span><span class="token plain"> bar</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">TOP</span><span class="token plain"> </span><span class="token number">50</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>where we don't put the results for the same group together.</p><ul><li>No support for <strong>ORDER BY</strong> in aggregation group by. However, ORDER BY support was added recently and is available in the standard-SQL endpoint. It can be used in the PQL endpoint by passing <code>queryOptions</code> into the payload as follows</li></ul><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"pql"</span><span class="token plain"> : </span><span class="token string" style="color:rgb(255, 121, 198)">"SELECT SUM(foo), SUM(bar) from myTable GROUP BY moo ORDER BY SUM(bar) ASC, moo DESC TOP 10"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"queryOptions"</span><span class="token plain"> : </span><span class="token string" style="color:rgb(255, 121, 198)">"groupByMode=sql;responseFormat=sql"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><p>where:</p><ul><li><code>groupByMode=sql</code> - standard sql way of execution group by, hence accepting order by</li><li><code>responseFormat=sql</code> - standard sql way of displaying results, in a tabular manner</li></ul></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/user-guide/pql.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" 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This example assumes broker is running on <code>localhost:8099</code></p><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs tabs--block"><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_1uMI tabs__item--active">Standard-SQL endpoint</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">PQL endpoint</li></ul><div class="margin-vert--md"><div role="tabpanel"><p>The Pinot REST API can be accessed by invoking POST operation with a JSON body containing the parameter sql to the <code>/query/sql</code> endpoint on a broker.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">$ curl </span><span class="token operator">-</span><span class="token plain">H </span><span class="token string" style="color:rgb(255, 121, 198)">"Content-Type: application/json"</span><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"sql":"select foo, count(*) from myTable group by foo limit 100"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> http:</span><span class="token comment" style="color:rgb(98, 114, 164)">//localhost:8099/query/sql</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel" hidden=""><div class="alert alert--info alert--icon" role="alert"><i class="feather icon-info"></i> This endpoint is deprecated, and will soon be removed. The standard-SQL endpoint is the recommended endpoint.</div><p>The PQL endpoint can be accessed by invoking POST operation with a JSON body containing the parameter pql to the <code>/query</code> endpoint on a broker.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">$ curl </span><span class="token operator">-</span><span class="token plain">H </span><span class="token string" style="color:rgb(255, 121, 198)">"Content-Type: application/json"</span><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"pql":"select count(*) from myTable group by foo top 100"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> http:</span><span class="token comment" style="color:rgb(98, 114, 164)">//localhost:8099/query</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="query-console"></a>Query Console<a class="hash-link" href="#query-console" title="Direct link to heading">#</a></h2><p>Query Console can be used for running ad-hoc queries (checkbox available to query the PQL endpoint). The Query Console can be accessed by entering the <code><controller host>:<controller port></code> in your browser</p><p><img alt="PQL-Query-Console" src="/assets/images/pql-query-console-9172787dd283a81158000e46310114f3.png"></p><h3><a aria-hidden="true" tabindex="-1" class="anchor" id="pinot-admin"></a>pinot-admin<a class="hash-link" href="#pinot-admin" title="Direct link to heading">#</a></h3><p>You can also query using the pinot-admin scripts. Make sure you follow instructions in Getting Pinot to get Pinot locally, and then</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot/pinot-tools/target/pinot-tools-pkg</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">bin/pinot-admin.sh PostQuery </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -queryType sql </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -brokerPort </span><span class="token number">8000</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -query </span><span class="token string" style="color:rgb(255, 121, 198)">"select count(*) from baseballStats"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
-</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token number">2020</span><span class="token plain">/03/04 </span><span class="token number">12</span><span class="token plain">:46:33.459 INFO </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">PostQueryCommand</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">main</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> Executing command: PostQuery -brokerHost localhost -brokerPort </span><span class="token number">8000</span><span class="token plain"> -queryType sql -query </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">select</span><span class="token plain"> count</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> from baseballStats</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token number">2020</span><span class="token plain">/03/04 </span><span class="token number">12</span><span class="token plain">:46:33.854 INFO </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">PostQueryCommand</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">main</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> Result: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"resultTable"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"dataSchema"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"columnDataTypes"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token string" style="color:rgb(255, 121, 198)">"LONG"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"columnNames"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token string" style="color:rgb(255, 121, 198)">"count(*)"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"rows"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">97889</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"numServersQueried"</span><span class="token plain">:1,</span><span class="token string" style="color:rgb(255, 121, 198)">"numServersResponded"</span><span class="token plain">:1,</span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsQueried"</span><span class="token plain">:1,</span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsProcessed"</span><span class="token plain">:1,</span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsMatched"</span><span class="token plain">:1,</span><span class="token string" style="color:rgb(255, 121, 198)">"numConsumingSegmentsQueried"</span><span class="token plain">:0,</span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">:97889,</span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedInFilter"</span><span class="token plain">:0,</span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedPostFilter"</span><span class="token plain">:0,</span><span class="token string" style="color:rgb(255, 121, 198)">"numGroupsLimitReached"</span><span class="token plain">:false,</span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">:97889,</span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">:185,</span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"minConsumingFreshnessTimeMs"</span><span class="token plain">:0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="pinot-clients"></a>Pinot Clients<a class="hash-link" href="#pinot-clients" title="Direct link to heading">#</a></h2><p>Here's a list of the clients available to query Pinot from your application</p><ul><li><a href="/docs/user-guide/clients/golang">Java client</a></li><li><a href="/docs/user-guide/clients/java">Go client</a></li><li>Coming soon - JDBC client</li></ul></div><footer class="row docusaurus-mt-lg"><div 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+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>Querying Pinot</h1></header><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="rest-api-on-the-broker"></a>REST API on the Broker<a class="hash-link" href="#rest-api-on-the-broker" title="Direct link to heading">#</a></h2><p>Pinot can be queried via a broker endpoint as follows. This example assumes broker is running on <code>localhost:8099</code></p><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs tabs--block"><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_1uMI tabs__item--active">Standard-SQL endpoint</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">PQL endpoint</li></ul><div class="margin-vert--md"><div role="tabpanel"><p>The Pinot REST API can be accessed by invoking POST operation with a JSON body containing the parameter sql to the <code>/query/sql</code> endpoint on a broker.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">$ curl </span><span class="token operator">-</span><span class="token plain">H </span><span class="token string" style="color:rgb(255, 121, 198)">"Content-Type: application/json"</span><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"sql":"select foo, count(*) from myTable group by foo limit 100"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> http:</span><span class="token comment" style="color:rgb(98, 114, 164)">//localhost:8099/query/sql</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel" hidden=""><div class="alert alert--info alert--icon" role="alert"><i class="feather icon-info"></i> This endpoint is deprecated, and will soon be removed. The standard-SQL endpoint is the recommended endpoint.</div><p>The PQL endpoint can be accessed by invoking POST operation with a JSON body containing the parameter pql to the <code>/query</code> endpoint on a broker.</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">$ curl </span><span class="token operator">-</span><span class="token plain">H </span><span class="token string" style="color:rgb(255, 121, 198)">"Content-Type: application/json"</span><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"pql":"select count(*) from myTable group by foo top 100"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> http:</span><span class="token comment" style="color:rgb(98, 114, 164)">//localhost:8099/query</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="query-console"></a>Query Console<a class="hash-link" href="#query-console" title="Direct link to heading">#</a></h2><p>Query Console can be used for running ad-hoc queries (checkbox available to query the PQL endpoint). The Query Console can be accessed by entering the <code><controller host>:<controller port></code> in your browser</p><p><img alt="PQL-Query-Console" src="/assets/images/pql-query-console-9172787dd283a81158000e46310114f3.png"></p><h3><a aria-hidden="true" tabindex="-1" class="anchor anchor__h3 anchorWithHideOnScrollNavbar_3R7-" id="pinot-admin"></a>pinot-admin<a class="hash-link" href="#pinot-admin" title="Direct link to heading">#</a></h3><p>You can also query using the pinot-admin scripts. Make sure you follow instructions in Getting Pinot to get Pinot locally, and then</p><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot/pinot-tools/target/pinot-tools-pkg</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">bin/pinot-admin.sh PostQuery </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -queryType sql </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -brokerPort </span><span class="token number">8000</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">\</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> -query </span><span class="token string" style="color:rgb(255, 121, 198)">"select count(*) from baseballStats"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
+</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token number">2020</span><span class="token plain">/03/04 </span><span class="token number">12</span><span class="token plain">:46:33.459 INFO </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">PostQueryCommand</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">main</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> Executing command: PostQuery -brokerHost localhost -brokerPort </span><span class="token number">8000</span><span class="token plain"> -queryType sql -query </span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">select</span><span class="token plain"> count</span><span class="token punctuation" style="color:rgb(248, 248, 242)">(</span><span class="token plain">*</span><span class="token punctuation" style="color:rgb(248, 248, 242)">)</span><span class="token plain"> from baseballStats</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token number">2020</span><span class="token plain">/03/04 </span><span class="token number">12</span><span class="token plain">:46:33.854 INFO </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">PostQueryCommand</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain">main</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"> Result: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"resultTable"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"dataSchema"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token string" style="color:rgb(255, 121, 198)">"columnDataTypes"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token string" style="color:rgb(255, 121, 198)">"LONG"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"columnNames"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token string" style="color:rgb(255, 121, 198)">"count(*)"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"rows"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token number">97889</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"numServersQueried"</span><span class="token plain">:1,</span><span class="token string" style="color:rgb(255, 121, 198)">"numServersResponded"</span><span class="token plain">:1,</span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsQueried"</span><span class="token plain">:1,</span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsProcessed"</span><span class="token plain">:1,</span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsMatched"</span><span class="token plain">:1,</span><span class="token string" style="color:rgb(255, 121, 198)">"numConsumingSegmentsQueried"</span><span class="token plain">:0,</span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">:97889,</span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedInFilter"</span><span class="token plain">:0,</span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedPostFilter"</span><span class="token plain">:0,</span><span class="token string" style="color:rgb(255, 121, 198)">"numGroupsLimitReached"</span><span class="token plain">:false,</span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">:97889,</span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">:185,</span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">{</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span><span class="token plain">,</span><span class="token string" style="color:rgb(255, 121, 198)">"minConsumingFreshnessTimeMs"</span><span class="token plain">:0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="pinot-clients"></a>Pinot Clients<a class="hash-link" href="#pinot-clients" title="Direct link to heading">#</a></h2><p>Here's a list of the clients available to query Pinot from your application</p><ul><li><a href="/docs/user-guide/clients/golang">Java client</a></li><li><a href="/docs/user-guide/clients/java">Go client</a></li><li>Coming soon - JDBC client</li></ul></div><footer class="docusaurus-mt-lg"><div class="row"><div class="col"><a href="https://github.com/apache/pinot/edit/master/website/docs/user-guide/query-pinot.md" target="_blank" rel="noreferrer noopener"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_2_ui" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_13-_"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"></div></nav></div></div><div class="col col--3"><div class="tableOfContents_35-E thin-scrollbar"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#rest-api-on-the-broker" class="table-of-contents__link">REST API on the Broker</a></li><li><a href="#query-console" class="table-of-contents__link">Query Console</a><ul><li><a href="#pinot-admin" class="table-of-contents__link">pinot-admin</a></li></ul></li><li><a href="#pinot-clients" class="table-of-contents__link">Pinot Clients</a></li></ul></div></div></div></div></main></div></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a 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+<script src="/assets/js/runtime~main.664acf57.js"></script>
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@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,20 +11,20 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
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Note, this is the response returned from the standard-SQL endpoint. For PQL endpoint response, skip to <a href="/docs/user-guide/response-format">PQL endpoint response</a></p><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs tabs--block"><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">Selections</li><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_1uMI tabs__item--active">Aggregations</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">GroupBy</li></ul><div class="margin-vert--md"><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">$ curl </span><span class="token operator">-</span><span class="token plain">H </span><span class="token string" style="color:rgb(255, 121, 198)">"Content-Type: application/json"</span><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"sql":"SELECT moo, bar, foo FROM myTable ORDER BY foo DESC"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> http:</span><span class="token comment" style="color:rgb(98, 114, 164)">//localhost:8099/query/sql</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"minConsumingFreshnessTimeMs"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numConsumingSegmentsQueried"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedInFilter"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedPostFilter"</span><span class="token plain">: </span><span class="token number">18</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numGroupsLimitReached"</span><span class="token plain">: </span><span class="token boolean">false</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsMatched"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsProcessed"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsQueried"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersQueried"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersResponded"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"resultTable"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"dataSchema"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnDataTypes"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"LONG"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"INT"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"STRING"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnNames"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"moo"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"bar"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"foo"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"rows"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">40015</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2019</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"xyz"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">1002</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2001</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"pqr"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">20555</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">1988</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"pqr"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">203</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2010</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"pqr"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">500</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2008</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"abc"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">60</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2003</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"abc"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">: </span><span class="token number">4</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">: {}</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel"><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">$ curl </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"sql":"SELECT SUM(moo), MAX(bar), COUNT(*) FROM myTable"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> localhost:</span><span class="token number">8099</span><span class="token operator">/</span><span class="token plain">query</span><span class="token operator">/</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">sql</span><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">H </span><span class="token string" style="color:rgb(255, 121, 198)">"Content-Type: application/json"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"minConsumingFreshnessTimeMs"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numConsumingSegmentsQueried"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedInFilter"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedPostFilter"</span><span class="token plain">: </span><span class="token number">12</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numGroupsLimitReached"</span><span class="token plain">: </span><span class="token boolean">false</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsMatched"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsProcessed"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsQueried"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersQueried"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersResponded"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"resultTable"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"dataSchema"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnDataTypes"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"DOUBLE"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"DOUBLE"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"LONG"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnNames"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"sum(moo)"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"max(bar)"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"count(*)"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"rows"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">62335</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2019.0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">6</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">: </span><span class="token number">87</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">: {}</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">$ curl </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"sql":"SELECT SUM(moo), MAX(bar) FROM myTable GROUP BY foo ORDER BY foo"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> localhost:</span><span class="token number">8099</span><span class="token operator">/</span><span class="token plain">query</span><span class="token operator">/</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">sql</span><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">H </span><span class="token string" style="color:rgb(255, 121, 198)">"Content-Type: application/json"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"minConsumingFreshnessTimeMs"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numConsumingSegmentsQueried"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedInFilter"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedPostFilter"</span><span class="token plain">: </span><span class="token number">18</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numGroupsLimitReached"</span><span class="token plain">: </span><span class="token boolean">false</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsMatched"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsProcessed"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsQueried"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersQueried"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersResponded"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"resultTable"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"dataSchema"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnDataTypes"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"STRING"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"DOUBLE"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"DOUBLE"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnNames"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"foo"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"sum(moo)"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"max(bar)"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"rows"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"abc"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">560.0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2008.0</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"pqr"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">21760.0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2010.0</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"xyz"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">40015.0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2019.0</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">: </span><span class="token number">15</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">: {}</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div></div></div><p>where:</p><table><thead><tr><th>Response Field</th><th>Description</th></tr></thead><tbody><tr><td>resultTable</td><td>This contains everything needed to process the response</td></tr><tr><td>resultTable.dataSchema</td><td>This describes schema of the response (columnNames and their dataTypes)</td></tr><tr><td>resultTable.dataSchema.columnNames</td><td>columnNames in the response.</td></tr><tr><td>resultTable.dataSchema.columnDataTypes</td><td>DataTypes for each column</td></tr><tr><td>resultTable.rows</td><td>Actual content with values. This is an array of arrays. number of rows depends on the limit value in the query. The number of columns in each row is equal to the length of (resultTable.dataSchema.columnNames)</td></tr><tr><td>timeUsedms</td><td>Total time taken as seen by the broker before sending the response back to the client</td></tr><tr><td>totalDocs</td><td>This is number of documents/records in the table</td></tr><tr><td>numServersQueried</td><td>represents the number of servers queried by the broker (note that this may be less than the total number of servers since broker can apply some optimizations to minimize the number of servers)</td></tr><tr><td>numServersResponded</td><td>This should be equal to the numServersQueried. If this is not the same, then one of more servers might have timed out. If numServersQueried != numServersResponded the results can be considered partial and clients can retry the query with exponential back off.</td></tr><tr><td>numSegmentsQueried</td><td>Total number of segmentsQueried for this query. it may be less than the total number of segments since broker can apply optimizations.</td></tr><tr><td>numSegmentsMatched</td><td>This is the number of segments actually processed. This indicates the effectiveness of pruning logic (based on partitioning, time etc).</td></tr><tr><td>numSegmentsProcessed</td><td>Actual number of segments that were processed. This is where the majority of the time is spent.</td></tr><tr><td>numDocScanned</td><td>The number of docs/records that were scanned to process the query. This includes the docs scanned in filter phase (this can be zero if columns in query are indexed) and post filter.</td></tr><tr><td>numEntriesScannedInFilter</td><td>This along with numEntriesScannedInPostFilter should give an idea on where most of the time is spent during query processing. If this is high, enabling indexing for columns in tableConfig can be one way to bring it down.</td></tr><tr><td>numEntriesScannedPostFilter</td><td>This along with numEntriesScannedInPostFilter should give an idea on where most of the time is spent during query processing. A high number for this means the selectivity is low (i.e. pinot needs to scan a lot of records to answer the query). If this is high, adding regular inverted/bitmap index will not help. However, consider using start-tree index.</td></tr><tr><td>numGroupsLimitReached</td><td>If the query has group by clause and top K, pinot drops new entries after the numGroupsLimit is reached. If this boolean is set to true then the query result may not be accurate. Note that the default value for numGroupsLimit is 100k and should be sufficient for most use cases.</td></tr><tr><td>exceptions</td><td>Will contain the stack trace if there is any exception processing the query.</td></tr><tr><td>segmentStatistics</td><td>N/A</td></tr><tr><td>traceInfo</td><td>If trace is enabled (can be enabled for each query), this will contain the timing for each stage and each segment. Advanced feature and intended for dev/debugging purposes</td></tr></tbody></table><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="pql-response"></a>PQL response<a class="hash-link" href="#pql-response" title="Direct link to heading">#</a></h2><div class="alert alert--info alert--icon" role="alert"><i class="feather icon-info"></i> PQL endpoint is deprecated, and will soon be removed. The standard sql endpoint is the recommended endpoint..</div><p>The response received from PQL endpoint is different depending on the type of the query.</p><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs tabs--block"><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">Selections</li><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_1uMI tabs__item--active">Aggregations</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">GroupBy</li></ul><div class="margin-vert--md"><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">curl </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"pql":"select * from flights limit 3"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> http:</span><span class="token comment" style="color:rgb(98, 114, 164)">//localhost:8099/query</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
+<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_31aa"><button class="clean-btn backToTopButton_35hR" type="button"><svg viewBox="0 0 24 24" width="28"><path d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z" fill="currentColor"></path></svg></button><main class="docMainContainer_3ufF docMainContainerEnhanced_3NYZ"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_3FnS"><div class="docItemContainer_33ec"><article><div class="tocCollapsible_1PrD tocMobile_3Hoh"><button type="button" class="clean-btn tocCollapsibleButton_2O1e">On this page</button></div><div class="markdown"><header><h1>Response Format</h1></header><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="standard-sql-response"></a>Standard-SQL response<a class="hash-link" href="#standard-sql-response" title="Direct link to heading">#</a></h2><p>Response is returned in a SQL-like tabular structure. Note, this is the response returned from the standard-SQL endpoint. For PQL endpoint response, skip to <a href="/docs/user-guide/response-format">PQL endpoint response</a></p><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs tabs--block"><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">Selections</li><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_1uMI tabs__item--active">Aggregations</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">GroupBy</li></ul><div class="margin-vert--md"><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">$ curl </span><span class="token operator">-</span><span class="token plain">H </span><span class="token string" style="color:rgb(255, 121, 198)">"Content-Type: application/json"</span><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"sql":"SELECT moo, bar, foo FROM myTable ORDER BY foo DESC"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> http:</span><span class="token comment" style="color:rgb(98, 114, 164)">//localhost:8099/query/sql</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"minConsumingFreshnessTimeMs"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numConsumingSegmentsQueried"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedInFilter"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedPostFilter"</span><span class="token plain">: </span><span class="token number">18</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numGroupsLimitReached"</span><span class="token plain">: </span><span class="token boolean">false</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsMatched"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsProcessed"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsQueried"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersQueried"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersResponded"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"resultTable"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"dataSchema"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnDataTypes"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"LONG"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"INT"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"STRING"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnNames"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"moo"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"bar"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"foo"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"rows"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">40015</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2019</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"xyz"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">1002</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2001</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"pqr"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">20555</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">1988</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"pqr"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">203</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2010</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"pqr"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">500</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2008</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"abc"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">60</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2003</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"abc"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">: </span><span class="token number">4</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">: {}</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel"><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">$ curl </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"sql":"SELECT SUM(moo), MAX(bar), COUNT(*) FROM myTable"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> localhost:</span><span class="token number">8099</span><span class="token operator">/</span><span class="token plain">query</span><span class="token operator">/</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">sql</span><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">H </span><span class="token string" style="color:rgb(255, 121, 198)">"Content-Type: application/json"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"minConsumingFreshnessTimeMs"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numConsumingSegmentsQueried"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedInFilter"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedPostFilter"</span><span class="token plain">: </span><span class="token number">12</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numGroupsLimitReached"</span><span class="token plain">: </span><span class="token boolean">false</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsMatched"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsProcessed"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsQueried"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersQueried"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersResponded"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"resultTable"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"dataSchema"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnDataTypes"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"DOUBLE"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"DOUBLE"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"LONG"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnNames"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"sum(moo)"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"max(bar)"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"count(*)"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"rows"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">62335</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2019.0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">6</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">: </span><span class="token number">87</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">: {}</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">$ curl </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"sql":"SELECT SUM(moo), MAX(bar) FROM myTable GROUP BY foo ORDER BY foo"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> localhost:</span><span class="token number">8099</span><span class="token operator">/</span><span class="token plain">query</span><span class="token operator">/</span><span class="token keyword" style="color:rgb(189, 147, 249);font-style:italic">sql</span><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">H </span><span class="token string" style="color:rgb(255, 121, 198)">"Content-Type: application/json"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"minConsumingFreshnessTimeMs"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numConsumingSegmentsQueried"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedInFilter"</span><span class="token plain">: </span><span class="token number">0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numEntriesScannedPostFilter"</span><span class="token plain">: </span><span class="token number">18</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numGroupsLimitReached"</span><span class="token plain">: </span><span class="token boolean">false</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsMatched"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsProcessed"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numSegmentsQueried"</span><span class="token plain">: </span><span class="token number">2</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersQueried"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numServersResponded"</span><span class="token plain">: </span><span class="token number">1</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"resultTable"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"dataSchema"</span><span class="token plain">: {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnDataTypes"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"STRING"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"DOUBLE"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"DOUBLE"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columnNames"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"foo"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"sum(moo)"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"max(bar)"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"rows"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"abc"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">560.0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2008.0</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"pqr"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">21760.0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2010.0</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"xyz"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">40015.0</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token number">2019.0</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">: </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">: </span><span class="token number">15</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">: </span><span class="token number">6</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">: {}</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div></div></div><p>where:</p><table><thead><tr><th>Response Field</th><th>Description</th></tr></thead><tbody><tr><td>resultTable</td><td>This contains everything needed to process the response</td></tr><tr><td>resultTable.dataSchema</td><td>This describes schema of the response (columnNames and their dataTypes)</td></tr><tr><td>resultTable.dataSchema.columnNames</td><td>columnNames in the response.</td></tr><tr><td>resultTable.dataSchema.columnDataTypes</td><td>DataTypes for each column</td></tr><tr><td>resultTable.rows</td><td>Actual content with values. This is an array of arrays. number of rows depends on the limit value in the query. The number of columns in each row is equal to the length of (resultTable.dataSchema.columnNames)</td></tr><tr><td>timeUsedms</td><td>Total time taken as seen by the broker before sending the response back to the client</td></tr><tr><td>totalDocs</td><td>This is number of documents/records in the table</td></tr><tr><td>numServersQueried</td><td>represents the number of servers queried by the broker (note that this may be less than the total number of servers since broker can apply some optimizations to minimize the number of servers)</td></tr><tr><td>numServersResponded</td><td>This should be equal to the numServersQueried. If this is not the same, then one of more servers might have timed out. If numServersQueried != numServersResponded the results can be considered partial and clients can retry the query with exponential back off.</td></tr><tr><td>numSegmentsQueried</td><td>Total number of segmentsQueried for this query. it may be less than the total number of segments since broker can apply optimizations.</td></tr><tr><td>numSegmentsMatched</td><td>This is the number of segments actually processed. This indicates the effectiveness of pruning logic (based on partitioning, time etc).</td></tr><tr><td>numSegmentsProcessed</td><td>Actual number of segments that were processed. This is where the majority of the time is spent.</td></tr><tr><td>numDocScanned</td><td>The number of docs/records that were scanned to process the query. This includes the docs scanned in filter phase (this can be zero if columns in query are indexed) and post filter.</td></tr><tr><td>numEntriesScannedInFilter</td><td>This along with numEntriesScannedInPostFilter should give an idea on where most of the time is spent during query processing. If this is high, enabling indexing for columns in tableConfig can be one way to bring it down.</td></tr><tr><td>numEntriesScannedPostFilter</td><td>This along with numEntriesScannedInPostFilter should give an idea on where most of the time is spent during query processing. A high number for this means the selectivity is low (i.e. pinot needs to scan a lot of records to answer the query). If this is high, adding regular inverted/bitmap index will not help. However, consider using start-tree index.</td></tr><tr><td>numGroupsLimitReached</td><td>If the query has group by clause and top K, pinot drops new entries after the numGroupsLimit is reached. If this boolean is set to true then the query result may not be accurate. Note that the default value for numGroupsLimit is 100k and should be sufficient for most use cases.</td></tr><tr><td>exceptions</td><td>Will contain the stack trace if there is any exception processing the query.</td></tr><tr><td>segmentStatistics</td><td>N/A</td></tr><tr><td>traceInfo</td><td>If trace is enabled (can be enabled for each query), this will contain the timing for each stage and each segment. Advanced feature and intended for dev/debugging purposes</td></tr></tbody></table><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="pql-response"></a>PQL response<a class="hash-link" href="#pql-response" title="Direct link to heading">#</a></h2><div class="alert alert--info alert--icon" role="alert"><i class="feather icon-info"></i> PQL endpoint is deprecated, and will soon be removed. The standard sql endpoint is the recommended endpoint..</div><p>The response received from PQL endpoint is different depending on the type of the query.</p><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs tabs--block"><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">Selections</li><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_1uMI tabs__item--active">Aggregations</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI">GroupBy</li></ul><div class="margin-vert--md"><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">curl </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"pql":"select * from flights limit 3"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> http:</span><span class="token comment" style="color:rgb(98, 114, 164)">//localhost:8099/query</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"selectionResults"</span><span class="token plain">:{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"columns"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"Cancelled"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"Carrier"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"DaysSinceEpoch"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"Delayed"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"Dest"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"DivAirports"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"Diverted"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"Month"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"Origin"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"Year"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"results"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"0"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"AA"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"16130"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"0"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"SFO"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"0"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"3"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"LAX"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"2014"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"0"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"AA"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"16130"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"0"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"LAX"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"0"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"3"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"SFO"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"2014"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"0"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"AA"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"16130"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"0"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"SFO"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"0"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"3"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"LAX"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"2014"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">:{}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">:</span><span class="token number">3</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"aggregationResults"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">:</span><span class="token number">10</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">:</span><span class="token number">102</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel"><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">curl </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"pql":"select count(*) from flights"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> http:</span><span class="token comment" style="color:rgb(98, 114, 164)">//localhost:8099/query</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">:{}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">:</span><span class="token number">17</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"aggregationResults"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"function"</span><span class="token plain">:</span><span class="token string" style="color:rgb(255, 121, 198)">"count_star"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"value"</span><span class="token plain">:</span><span class="token string" style="color:rgb(255, 121, 198)">"17"</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">:</span><span class="token number">27</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">:</span><span class="token number">17</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly sql"><pre tabindex="0" class="prism-code language-sql codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">curl </span><span class="token operator">-</span><span class="token plain">X POST \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token operator">-</span><span class="token plain">d </span><span class="token string" style="color:rgb(255, 121, 198)">'{"pql":"select count(*) from flights group by Carrier"}'</span><span class="token plain"> \</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> http:</span><span class="token comment" style="color:rgb(98, 114, 164)">//localhost:8099/query</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
-</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">{</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"traceInfo"</span><span class="token plain">:{}</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"numDocsScanned"</span><span class="token plain">:</span><span class="token number">23</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"aggregationResults"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"groupByResult"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"value"</span><span class="token plain">:</span><span class="token string" style="color:rgb(255, 121, 198)">"10"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"group"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token string" style="color:rgb(255, 121, 198)">"AA"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"value"</span><span class="token plain">:</span><span class="token string" style="color:rgb(255, 121, 198)">"9"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"group"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token string" style="color:rgb(255, 121, 198)">"VX"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> {</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"value"</span><span class="token plain">:</span><span class="token string" style="color:rgb(255, 121, 198)">"4"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"group"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token string" style="color:rgb(255, 121, 198)">"WN"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"function"</span><span class="token plain">:</span><span class="token string" style="color:rgb(255, 121, 198)">"count_star"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"groupByColumns"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token string" style="color:rgb(255, 121, 198)">"Carrier"</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> }</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"timeUsedMs"</span><span class="token plain">:</span><span class="token number">47</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"segmentStatistics"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"exceptions"</span><span class="token plain">:</span><span class="token punctuation" style="color:rgb(248, 248, 242)">[</span><span class="token punctuation" style="color:rgb(248, 248, 242)">]</span><span class="token punctuation" style="color:rgb(248, 248, 242)">,</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> </span><span class="token string" style="color:rgb(255, 121, 198)">"totalDocs"</span><span class="token plain">:</span><span class="token number">23</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div></div></div></div><footer class="row docusaurus-mt-lg"><div 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index 057845d..e62501f 100644
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<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
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<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
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<link rel="search" type="application/opensearchdescription+xml" title="Apache Pinot™" href="/opensearch.xml">
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diff --git a/content/download/index.html b/content/download/index.html
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@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
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<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
<link rel="preconnect" href="https://www.google-analytics.com">
@@ -11,14 +11,14 @@
<script async src="https://www.google-analytics.com/analytics.js"></script>
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href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.7.1</div><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.6.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.5.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.4.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.3.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.2.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.1.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC</div></a></a></div></div></div></section></main></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/plugins/plugin-architecture" target="_blank" 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href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-0.8.0/apache-pinot-0.8.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.7.1</div><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://downloads.apache.org/pinot/apache-pinot-incubating-0.7.1/apache-pinot-incubating-0.7.1-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.6.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.6.0/apache-pinot-incubating-0.6.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.5.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.5.0/apache-pinot-incubating-0.5.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.4.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.4.0/apache-pinot-incubating-0.4.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.3.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.3.0/apache-pinot-incubating-0.3.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.2.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.2.0/apache-pinot-incubating-0.2.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC </div></a></a></div><div class="col"><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-bin.tar.gz" class="panel panel--link text--center"><div class="panel--icon"><i class="feather icon-download"></i></div><div class="panel--title">0.1.0</div><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-src.tar.gz"><div class="panel--title">Official source release</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-src.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-src.tar.gz.asc"><div class="panel--subtitle">ASC</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-bin.tar.gz"><div class="panel--title">Binary download</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-bin.tar.gz.sha512"><div class="panel--subtitle">SHA512</div></a><a href="https://archive.apache.org/dist/incubator/pinot/apache-pinot-incubating-0.1.0/apache-pinot-incubating-0.1.0-bin.tar.gz.asc"><div class="panel--subtitle">ASC</div></a></a></div></div></div></section></main></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" target="_blank" rel="noopener noreferrer" class="footer__link-item">Architecture</a></li><li 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diff --git a/content/index.html b/content/index.html
index df6cb9c..b314d53 100644
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@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
-<meta name="generator" content="Docusaurus v2.0.0-beta.4">
+<meta name="generator" content="Docusaurus v2.0.0-beta.5">
<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
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GEaQFEkP6LZiqTyCJMsVbq49TgeesByjyYd0sGqOC/P/bYie7EE52TmTYIbnnZSl4i7WsZWAak/jnZNEKZmURF5NxxMujUDLQTgIYRw7IQAOy/t3CW8GUh0E04mgiSKKoHageSKMCCxRhMi2in6wlCwiAArbceM0o+vKaE0cLn828EQezSS6Pk0047VMIKoocBgt8ZdlEQsihDlO5WQ2+pAxCyAFbmskI3KUBGd6r/pZG33945mWVr6nzewOKPZMci6VNWEmRHCIJcr17J1OriRgCmSeippWDzdOsqwiAQKAREd64jOqPs6qHz2cFC48TwShxKdg6wr35/QEzr8dy++0oZLoB7lbKHsLDzyXryyZEU3r//2tIAhpKUgEsUL65A0/GMXCRs68jEg1VF4RzAG2/k1DFKrPEXaX/jjcVW4as1AuphEpD8Te+3dLl7pV3YVW2haTkQWgxtGcFqwnB8yXRLVagxH+nUyY7X/GogvuB2E8I1RCZO3Rex/nHjjiGaBzCHLNvIu+lYG69dswFg/RiMsjBb0VIKh6RWia3ox8svn32i1hjTGYCOzjLtpoKV19RyWLqe0xQqELVQewrrAiMAprwYFsABgPnC5NAUI4tYIQRgoFWqBuSFSzwhnCjsJnTaXy/rW3eiCThX8YsS14VRphk+at11+8iYMjgvA7T2dV5adMno5/vqZf1WqDSAADSuWRPtXq2htn4XdFqtZZCf9tAyrgKgD7baqiC5qgT2HgDsP4hhnhGARKhg2LEb04hMmaKmj9teOm6Yp5Ushhs6HiZ3vBAO4HSGjjvqqD2IJuBvil+ZuC6MMn/b6Of53NHPtPFk4UNxCsYQ2CassinA/jwATgRRIRDWC/kjtt5ymErMmpksg3kcY1c9YASQ4OQfW9M9pwKZCgxgyC88+KDMgbdEEjbWqxhOVPhrIaM/dD7pOmRB815WvIxEigu5VRbkuAlS7VJLLenYupUFBI6zs5dFYkizWLeaClKrgq8Aa2Byymtquc3xPJpFPQBHscFMPWN42whAYykHvtLVSFJuuCGaX2NBianhZOH5wmVlUAgd0KHDkjJdhuxKBv4tHCNM0hTphaBFDQHWXHP1hLmXpMuFMKbSwFLuRoGNKi2mTAq7jSq+YeXgIKoHkg4qBMkYZhsBWEIyfF4XL8mFGBwc2KYF5O8Gy9SqWKcTsAJVjRo1XPblWJQO4sQflQ0aqgymksydiwXH8n+pyI12UTSUyZTt1A0D9H9gzpxIDsh+S0he5H9sWsNfkvAjzCpHAFT6VlgHbFrLqpxs7e7WW53TWrtwzW5WQLtxokj4ZfaQNFUlDB0aZXznnQ+0dfux+CnCrM4ZJ2YCKoGRpKlzf6ZARUwQpGzqjLFlcQLTbtgYk4CnKhHABGWeL5NmUD+wCyB0MZewl122dzVcD7fJJtJXAqBDXRrHqwsgrP79o7yHH36GJFQ4h9hOCYCVYYiqVxcuUWyoF/fefz/KYSOmVP5FKR1OaTYc+iwGdIIZdlEuZM4PK1A52Ijlx8kVL0ccsZts0maz/03N9mmx2uBFY8cO7znwwJ1VxiZFy9HI9LvtFq1w5blGIt463s9ybxwmMgo1tPxGfmutZbEWkjrhLEvsLppKp1fiAOQ5QXisqOgz1CStVs1Z8bL55huRRyAyczeFWK0/nI6BxREYP/5G7dlDwSiEP0q0gFXnrWopzFhHilnuTEdOCk11FNeqHsFPAmi1cNLQdTtp1RAAI+N0YXehGHZYyw9XCDBggCmlM3X9nzi1toC5nIUSrJAB9t//K7M5RAn6ZSMnssfvf59JamjE1Enmf2BxkQEgaBP60OhioJbXE6+GAOJn3OeKPCiUZSBsypTxp4uMFcvF96fFYe0BRg/s+FrkEIwfCCza4BiEMUpj5+2+++rEg1Oj5V21v6HyE6YjGyFgNjXTaeWnW28OhFqA9YqaBgzuUeQtLmohAHuYUKYTBMIVCWLIlm4ptYTY8rE1jB4dmVK1l8397W/RdDNqVLQgEtdoc4FZxzRHZgDP26IMGLWsXlq1lIQz7aK9RWoMw7DPHrWGQInxp37Al44EjnS/7bZO6wAjWwOUCwfAKtkoM2uxr8QVDCTNrxBAwnceZajjFy8j6hdlYTxrpAGr1OfA0czgw3oOLegxeECRKXZRLwdYigKyPnvV0MWTp5VcY8gUYI1/4IGRhRGrHJQ7fLhzQ4fWWGCN2SEyIOlYsmkhulP779tvRwdRwcGYTlqq81H7aDu+H7PvGWdkvl1f4Y7IXClSLwG0oRD0pAjejcOmBazhZ3TgTk3avJENmhuwawBmESTeVAJgCtMePi1pj/YLtMTIh9DwamLHQAA86qisEKgqnSJ8hroZ1EsAoi3mZzOXyaXXAKCBbCMHqiHA6G+00ScqOfvLOgBWO/F+8wlwt6mmZsrVEfGuV69oOsOx1pyAsefFFyOjD52vtY7hOn7ngwoz2pt9R70EMI8CPv1UZBbAwviyCQHTgFbCOh2JEuCgg5pQWJWPMlJhZvjfeXejgJ08nE2I7MLaSp1Z4LRFLOwQMtdsI95FWXPmRO5s5BbY/v77y8w3I1O6JKmw8JcpIAdE83WB5EudpvvBx/HDBeXWVSgP0Vh0AkITjiI4QHMAo0XLuMNyNw55Apijk2AqIWlMB8nrZL5icewIrOcztm+bU9i9BCL0srCD3USbbqrTGqR9UO9qBV3sFajLLNBF2oeA4VhaQu60zyFp8Jmp79ObXFE2XS8BBNsSHrwFCxZqFW0QCYq1Q11peCCpkE74KLoHr65CaQE1gU7PcGzR0pLrHD0fY5R29OZAkhtMnRrZKtjRUw1AvIx+g3zfAhqPjnEJyCJU1hFqz4X8KtGUgVAMwfFdEAXtwfzOaIe4YPGkARCz9hIEWQNOkIDrFd9XqBzFoV4CeJfivv56vnv77fe1IFO1bSBgbgaSHRCl1PfLimbc11gSaTiARu3TJ5rzcXAh/TMqDbiftAmsu64Wsl/s3BVX6E8Exzqn83bKQv5INi2j2EOMYKY8m/b4Do605fv4Lt6FqRqiYuTT4SyExSPKYNF29HyBVZOAO1J4TbH3JdPqJYBXrZBZs2aLAJaxy4aENlpg0Xj+fv3r+opF/x49Wv8aeVV2tNORsOahQ8svJGVUYqE0YK0fz3GOL3M7lsnDD88KrZavVMgILQd8D9MERAB3AOE6NcJrys+EdqGwcYJZkY/ooTQYkB87Fg/geQ31nGmUhmNdKF+dEP5nR+yu6newG+d3v3Ne26HDN4qNeskSnjOD8IpVgxplBe+TWTU8y//+SF0MZ/XYeQRizQX57ZvxLFp7lQovvzw6wiXhadUYDx62cs9+ojyQyRjhQKH4Vm1QLweQ2BLBI49If4oOp7SkJofsY0eYYZfMP/8Z+QUQdippBMyPHLfOHgM8YLBhNmiwmgkvYjlgzjWBDYm9mAUQ+wQrkfr2jaYTLGzqOKeNofKLRJwmubPH3seC2nIAa2eVFfliL6RqG/ZqLBGHKyjsKJREEP6+lo5/R6iv+WbgDr02UGanTh21MZL/3ik9Auq9Jyk3jFx71zbbOC+CCP+5kyxTU4bXrqJwLJzl5SwcRlWp0c4BS+wnlKesoLxk2flxqVg5ZWq7dmaEioC8VMqCtpAlLpPHvi8ZsuGW79xpp0y+K3W/RaAeDoCohFoR4LPPPtfZu69oiZgmsLC5OL7RgIANH/gEdEJmUG0YcSBOIww2CEZwBhaWmvuWtQKM+HyVjs9BqsbpBDLK64F84xD7+QyQ0pEN8Cuwz9EASb4UMO/rr2bD96MexiD+1zKQEHOqfuEhyjmc3Jg5sXd37txR7BrjINNWYwFBDH0ZXRn7Nu5NJHkaHumeaxoetozVjUOSk+yeaYBGRtJn+xjCXS36fH5tkL6TXkKMSEwLAomHYW9l3ylTonYRxwpqnLhIIGTWPJh6x/fg9Bo9Wrx+lcjnERtuVKPw5xALFDY7qHlqglHK/Xdhe1QVDCgjRyIJr6AOGSip+faaCqs1M4YP1CnMtnQ8ox5uwPyZdOJQLnO4jXab22t9X7H8qF0QHMD7kTFin8HnSuojVKuERTNBhmEhC5xKQqnTAVLBsIVaBxGikaDq4iv461/1VAS7KrjWLpo7bF/DC3ZRXuam9owq7MyMNIwdL700V+rL+w6Kb05AL8cvwGjHqIPARGfwPYws2Dp5GOVcNxrgPNb5lI2amnAYieTCnwwxSK4Q7sqR9Kzjh0tgh4BbmnmWAYT+P2ZMVv/XM+cIW6zz9a6qYTflhO515InzkrTDwQcILvxVOuk77JB7YGO+8LQ4XIv95wiAqIDUXZ0ZQsXFHwIw658rtPSw2FTaSRASOWmccwTFBez+QuUdKxQptz7YU5+U6Xyx/SDlskKXAxE5jFmjLZzNO2dOoQTcWjpewluBdF7rt0nmyBCARnLoeGwNHDGjNjLcMNGFv1Jc4zxzz/Ikw1m6v3nimRaNlpFPw3cw8i8TtoPNniMGFe8QCsKNLePCwwVrxAnRaLBFmk0pF8kd+aEpIGLJKQNZAGsdC1lZu4AuH8P+FlF4qVATlhstfEL4qVATiZst1MzvRgglCYQj3xW0PkC+DdT6l78UjiDNwWFEYGEjn9S2cFx5rSOrXP5az9gpVhacSXN1kziA5uvM6GfqM/avhaohPfEPX3Qy8sAiAZU4QKgIEitCXz4gwSJwIYXjzcJJkZBm87PXdZ3YyVrX84xS1LamagIIbAZwJU7+pP52WAMnhMYgMdRtaxetPaxEAK9SASRdpO5iwNZqgAUIANMAunIjALaLQ4SwHkBLwCjDypymAieRGCD90x64hjFbA5ztYz5/XX5jc3r4mBp+KhHAdCsLHbYYoHpx8iSrafBlwwVGjy6Ws/Y0CM/cnrU+jUeRjqezkqO31nLIj/yQUPeCPk96cv0A1j7+kTSGbMxSWmlYiQBus+9OnAxmSZkQSxYs9pBDIsuX/lIlc6JYJlMdEVg3ox9/dy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font-weight="bold"><tspan x="0" y="19">EVENTS</tspan></text><g fill-rule="nonzero"><circle cx="32.5" cy="32.5" r="32.5" fill="#000" transform="translate(549 104)"></circle><circle cx="32.5" cy="32.5" r="32.5" fill="#FFF" transform="translate(549 104)"></circle></g><g transform="translate(549 104)"><mask id="pinot-overview-user_svg__h" fill="#fff"><use xlink:href="#pinot-overview-user_svg__g"></use></mask><image mask="url(#pinot-overview-user_svg__h)" x="10.432" y="12.84" width="43.333" height="43.333" 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"></image></g></g><image 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icon-zap"></i></div><h3>Blazing Fast</h3><p>Pinot is designed to answer OLAP queries with low latency on immutable data</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-unlock"></i></div><h3>Pluggable indexing</h3><p>Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-rss"></i></div><h3>Near Real time ingestion</h3><p>Near Realtime ingestion with <a href="https://kafka.apache.org/" target="_blank" rel="noopener noreferrer">Apache Kafka</a> supports StringSerializer or <a href="https://avro.apache.org/" target="_blank" rel="noopener noreferrer">Avro</a> formats</p></div></div><div class="row"><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-code"></i></div><h3>Horizontally scalable</h3><p>Horizontally scalable and fault tolerant</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-shuffle"></i></div><h3>Joins using PrestoDB</h3><p>Joins are currently not supported, but this problem can be overcome by using <a href="https://prestodb.io/" target="_blank" rel="noopener noreferrer">PrestoDB</a> for querying</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-search"></i></div><h3>SQL-like Query Interface (PQL)</h3><p>SQL like language that supports selection, aggregation, filtering, group by, order by, distinct queries on data</p></div></div><div class="row"><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-list"></i></div><h3>Hybrid tables</h3><p>Consist of of <a href="http://pinot.apache.org/img/dynamic-table.png" target="_blank" rel="noopener noreferrer">both offline and realtime table</a>. Use realtime table only to cover segments for which offline data may not be available yet</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-bar-chart"></i></div><h3>Anomaly Detection</h3><p>Run ML Algorithms to detect Anomalies on the data stored in Pinot. Use <a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer">ThirdEye</a> with Pinot for Anomaly Detection and Root Cause Analysis</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-bell"></i></div><h3>Smart Alerts in ThirdEye</h3><p>Detect the right anomalies by customizing anomaly detect flow and notification flow</p></div></div></div></section><section class="topologies"><div class="container"><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="ingest-query"></a>Ingest and Query Options<a class="hash-link" href="#ingest-query" title="Direct link to heading">#</a></h2><div class="sub-title">Ingest with Kafka, Spark, HDFS or Cloud Storages</div><div class="sub-title">Query using PQL(Pinot Query Language ), SQL or Presto(supports Joins)</div><svg width="800" height="400" viewBox="0 0 800 400" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" class="svg 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"></image></g><image 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"></image><path 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1.78-.523 2.79-.523 3.378 0 5.067 1.517 5.067 4.551 0 2.186-.567 3.947-1.702 5.285-1.135 1.35-2.686 2.105-4.654 2.267a17.76 17.76 0 003.499.349c.922 0 1.722-.18 2.402-.54.19-.105.322-.216.399-.332.378.314.567.782.567 1.403 0 .623-.3 1.115-.898 1.475-.599.361-1.481.542-2.648.542-1.166 0-2.424-.25-3.773-.752a13.464 13.464 0 01-3.764-2.145zm19.384-2.913c.24.28.36.69.36 1.232 0 .54-.224.975-.67 1.308-.45.33-1.065.496-1.845.496-.455 0-1.035-.047-1.74-.14-1.387-.197-2.28-.296-2.677-.296-.396 0-.677.009-.842.027l-.641.06 2.287-11.512h4.142l-1.89 9.593c.163.024.32.036.472.036h.473c1.058 0 1.915-.268 2.57-.804z" fill="#CCC"></path><path fill="#000" d="M682 231h6v1h-6zM689 231h6v1h-6zM682 235h4v1h-4zM686 235h4v1h-4zM691 235h4v1h-4z"></path><path fill="#000" d="M694 235h4v1h-4zM682 238h5v1h-5z"></path><path fill="#000" d="M686 238h5v1h-5zM692 238h5v1h-5zM697 238h5v1h-5zM682 242h2v1h-2zM684 242h2v1h-2zM686 242h2v1h-2zM689 242h2v1h-2zM691 242h2v1h-2zM693 242h2v1h-2zM695 242h2v1h-2zM697 242h2v1h-2zM699 242h2v1h-2zM701 242h2v1h-2zM704 242h2v1h-2zM706 242h2v1h-2zM683 245h2v1h-2zM686 245h2v1h-2zM689 245h2v1h-2zM691 245h2v1h-2zM695 245h2v1h-2zM697 245h2v1h-2zM700 245h2v1h-2zM703 245h2v1h-2zM682 251h2v1h-2zM684 251h2v1h-2zM687 251h2v1h-2zM690 251h2v1h-2zM692 251h2v1h-2zM695 251h2v1h-2z"></path><path fill="#000" d="M696 251h2v1h-2zM699 251h2v1h-2z"></path></g></g></svg></div></section><section class="topologies"><div class="container"><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="who-uses"></a>Who Uses Apache Pinot?<a class="hash-link" href="#who-uses" title="Direct link to heading">#</a></h2><div class="sub-title">Pinot powers several big players, including LinkedIn, Uber, Microsoft, Walmart, WePay, Factual, Weibo, Slack and more</div><div class="installationPlatforms_1UKi"><a href="https://www.linkedin.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by LinkedIn" title="apache_pinot_user_LinkedIn"></a><a href="https://www.ubereats.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Uber" title="apache_pinot_user_Uber"></a><a href="https://teams.microsoft.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Microsoft" title="apache_pinot_user_Microsoft"></a><a href="https://slack.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Slack" title="apache_pinot_user_Slack"></a><a href="https://www.factual.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Factual" title="apache_pinot_user_Factual"></a><a href="https://www.weibo.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Weibo" title="apache_pinot_user_Weibo"></a><a href="https://eero.com/" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Amazon eero" title="apache_pinot_user_Amazon eero"></a><a href="https://www.confluera.com/" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Confluera" title="apache_pinot_user_Confluera"></a><a href="https://startree.ai" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by StarTree" title="apache_pinot_user_StarTree"></a><a href="https://stripe.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Stripe" title="apache_pinot_user_Stripe"></a><a href="https://www.target.com/" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Target" title="apache_pinot_user_Target"></a><a href="https://www.walmart.com/" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Walmart" title="apache_pinot_user_Walmart"></a><a href="https://www.publicissapient.com/" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Publicis Sapient" title="apache_pinot_user_Publicis Sapient"></a><a href="https://cloudkitchens.com/" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by CloudKitchens" title="apache_pinot_user_CloudKitchens"></a><a href="https://www.guitarcenter.com/" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by GuitarCenter" title="apache_pinot_user_GuitarCenter"></a><a href="https://go.wepay.com/" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Wepay" title="apache_pinot_user_Wepay"></a><a href="https://www.traceable.ai" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Traceable" title="apache_pinot_user_Traceable"></a><a href="https://www.adbeat.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Adbeat" title="apache_pinot_user_Adbeat"></a><a href="https://razorpay.com/" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by RazorPay" title="apache_pinot_user_RazorPay"></a></div></div><p align="center"></p><div class="hero--buttons"><a class="button button--primary button--highlight" href="/who_uses">Read More on use cases..</a></div><p></p></section><section class="topologies"><div class="container"><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="user-facing-analytics"></a>User-Facing Analytics<a class="hash-link" href="#user-facing-analytics" title="Direct link to heading">#</a></h2><p align="center"></p><h3 class="installSubTitle_1qZ7">Building Latency Sensitive User Facing Analytics via Apache Pinot</h3><div><div style="border:1px solid white;width:720px;height:480px"></div></div><h3 class="installSubTitle_1qZ7">Using Apache Kafka and Apache Pinot for User-Facing Analytics</h3><div><div style="border:1px solid white;width:720px;height:480px"></div></div><div class="hero--buttons"><a href="https://docs.pinot.apache.org/community-1/videos" target="_blank" rel="noopener noreferrer" class="button button--primary button--highlight">More Videos</a></div><p></p></div></section><section><div class="container"><h2><a aria-hidden="true" tabindex="-1" class="anchor" id="installation"></a>Installs Everywhere<a class="hash-link" href="#installation" title="Direct link to heading">#</a></h2><div class="sub-title">Pinot can be installed using docker with presto</div><div class="installationChecks_utNn"><div><i class="feather icon-package"></i> Helm or K8s crds</div><div><i class="feather icon-cpu"></i> On-Premise</div><div><i class="feather icon-zap"></i> Public Cloud</div><div><i class="feather icon-feather"></i> Locally</div></div><h3 class="installSubTitle_1qZ7">Install:</h3><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs mini"><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_1uMI tabs__item--active"><i class="feather icon-download-cloud"></i> Using Helm</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI"><i class="feather icon-download"></i> Using Binary</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI"><i class="feather icon-github"></i> Build From Source</li></ul><div class="margin-vert--md"><div role="tabpanel"><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm repo </span><span class="token function" style="color:rgb(80, 250, 123)">add</span><span class="token plain"> pinot https://raw.githubusercontent.com/apache/pinot/master/kubernetes/helm</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl create ns pinot</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> pinot pinot/pinot -n pinot --set cluster.name</span><span class="token operator">=</span><span class="token plain">pinot</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">VERSION</span><span class="token operator">=</span><span class="token number">0.8</span><span class="token plain">.0</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">wget</span><span class="token plain"> https://downloads.apache.org/pinot/apache-pinot-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">$VERSION</span><span class="token plain">/apache-pinot-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">$VERSION</span><span class="token plain">-bin.tar.gz</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">tar</span><span class="token plain"> vxf apache-pinot-*-bin.tar.gz</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> apache-pinot-*-bin</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">bin/quick-start-batch.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)"># Clone a repo</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">git</span><span class="token plain"> clone https://github.com/apache/pinot.git</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
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Check the release notes</a><h1 class="hero__title">Apache Pinot™</h1><p class="hero__subtitle">Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency<svg width="724" height="341" viewBox="0 0 724 341" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" class="svg image-overview figure"><title>PinotOverview</title><defs><circle id="pinot-overview-user_svg__a" cx="32.5" cy="32.5" r="32.5"></circle><circle id="pinot-overview-user_svg__c" cx="32.5" cy="32.5" r="32.5"></circle><circle id="pinot-overview-user_svg__e" cx="32.5" cy="32.5" r="32.5"></circle><circle id="pinot-overview-user_svg__g" cx="32.5" cy="32.5" r="32.5"></circle><circle id="pinot-overview-user_svg__i" cx="32.5" cy="32.5" r="32.5"></circle><circle id="pinot-overview-user_svg__k" cx="32.5" cy="32.5" r="32.5"></circle><circle id="pinot-overview-user_svg__n" cx="32.5" cy="32.5" r="32.5"></circle><circle id="pinot-overview-user_svg__p" cx="32.5" cy="32.5" 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font-weight="bold"><tspan x="0" y="19">EVENTS</tspan></text><g fill-rule="nonzero"><circle cx="32.5" cy="32.5" r="32.5" fill="#000" transform="translate(549 104)"></circle><circle cx="32.5" cy="32.5" r="32.5" fill="#FFF" transform="translate(549 104)"></circle></g><g transform="translate(549 104)"><mask id="pinot-overview-user_svg__h" fill="#fff"><use xlink:href="#pinot-overview-user_svg__g"></use></mask><image mask="url(#pinot-overview-user_svg__h)" x="10.432" y="12.84" width="43.333" height="43.333" 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VVfUvnzV4aFQksLx0NYkEAAQQQQAABBBBAAIGKF3BOkOMb6t7Qm7TS5mJl7FP2olRq2urVt4Sxq61/vvqsgh8YE/qyvD/eJ8nMsQVkeHUdK5nctbzcC3YXcFwFbSq+MXq11r03Ryhou15qTJLlbbGWxGIvxeTEIu93NgQQQAABBBBAAAEEEEAAgXIKHHTnQKPeK2dqteWMx6N9x+tak/Ueja3kYcWbYx9Uxvwq144lHbpN1k970FnHKqMyfzq+dUtHrm1VSr18zX3i9Eh4hH12zbVdctmotzYSWN46HkSDAAIIIIAAAggggAACFSKw/YPHjnxld/U8ben3yOVI75BhB3kx6LyPqsx6+X2sJfmuvBsKSAOSgNKyoPt9clJ/TpZD2iWGvQkrbck6VjcnmM2WJZxTrKO59jxt9DJ5GHFRzW9FN/eEUmedcPOz27wYOJcQevGoEBMCCCCAAAIIIIAAAggEUmDTwnFjq9ORdytLvWd3tzpPEgrDJHnFlp1Axa9/1ZdJElcmqc2lttJ/kffQcX1f2/c4LTmuh5yF1yVJet+2I8b++cxrH00NUI5dQwhsbqw5WZJXbVIsyMmrHUZb7/Jq8so5RCSwhnij8jICCCCAAAIIIIAAAgggkI+Aswi7NuY9km94j8qo6bI4coikVU6iJLD6sUVbOpPx+bEpyjLfkZfOkPdYlzLWeqMy9x8xvGfFmBue23mgSuLAQx5lLdDVWHNsWlv3SIVjsq7kv4JppfXF9S3xf3k5dC4h9PLRITYEEEAAAQQQQAABBBDwpUBHY91kpe13yWLI50tSYboMgnOvPI+kMdap9Uvj6/NshuoIZC2wvmFy1cjwjj/Jd++crCv5saDRH69bmviZ10NnBpbXjxDxIYAAAggggAACCCCAgOcFeu8c+FTddEuSVnJF4IVyh7gT9wbN9YEFOng9u9IjNxaoLZpBYEgBZ42xZGTH9fJ1zpCF/VzAmO/VLU16PnnlEJPA8vMbjdgRQAABBBBAAAEEEECgbAKbL5swzOrpmWkp6/zEBtWgtT2edFWRDodRT0xuW99TpNZpFoFDBGSB/Ctl2uTCQ14I0A75vPpDXbrzCr8MiQSWX44UcSKAAAIIIIAAAggggEDZBbYuHHfknnToXEtbDaYnfYFS1iiSVsU/LMZSrH9VfGZ62CfQ0Vh7sSSvvhpkEBnf34al9lwiS9Nn/DJOElh+OVLEiQACCCCAAAIIIIAAAmUR2NJw3JieSGiepXRDT0a9Ve4cWEXSqrSHwlIksEorXrm9tc+vma61/rUISI4nsNsWy7YvGNu2fZefRkgCy09Hi1gRQAABBBBAAAEEEECgJALxS2Kv1Za5SO4YeFFKqTfLmaxF0qok9IN1wgyswWTYXzCB3juGKvsOaXBYwRr1XkMv25b9rrrWLt/dlpIElvfeTESEAAIIIIAAAggggAACZRDof+dASVgFeQZGGYTz6DKkHsujNlURGFJgY/MJo7Tdfad8148ZsrB/C9jK6AUTlnT91Y9DIIHlx6NGzAgggAACCCCAAAIIIFAQgX1JK1mA3VysjH3K3kaZa1UQ3MI18u/YTcnOwjVHSwgcLPDIoimR6l1bb1Nan3rwKwF7ZvTn65YmnBlmvtxIYPnysBE0AggggAACCCCAAAII5CJgFisr/lTddEvb75I01fuUsl/b245cK8jmUQHD7CuPHpnAhDV219YfyYTLtwRmQAMP5FeSvPr+wC/5Yy8JLH8cJ6JEAAEEEEAAAQQQQACBHAVMgwrFw3XTJGnVkNioLtbaPo45VjlilqEadyAsA3oFdZlojH5ePg8+GughG7ViZ/qojymV9PUwSWD5+vARPAIIIIAAAggggAACCAwk0LWo5ojMTmueswi7rFT8Tq3so3qTVmSuBuLy9D7uQOjpw+Pr4OKNsfcYba729SCGDv5fmerwhZOXru8Zuqi3S5DA8vbxIToEEEAAAQQQQAABBBDIUmDzZROOtnpSb7GUPj+9S10oizGPyLIqxTwsYBvLlwtOe5iU0ESgfX7NG5Q2S+Sh5EgDuz2nLXXBxBvbXwzCCElgBeEoMgYEEEAAAQQQQAABBCpUIHlp7WsyafVOSVo1mJ70W2UdmyomWQXqzZCyq6z1gRoRgym7QHx+rEZZ5i4J5MiyB1O8ALpt275gQmvXpuJ1UdqWSWCV1pveEEAAAQQQQAABBBBAIE+Brktr6lJp6+0ybeJ8O63eLsuvh0la5Ynq0epyXNfL7JFuj4ZHWD4U2NYwZsRuy/xePjeiPgw/25Cd21J8aMItXWuzreCHciSw/HCUiBEBBBBAAAEEEEAAgQoX2NxYc7Jl6Qu10Rel0+pM556BJK2C/6bQyvw9+KNkhKUScG7okIgMa5X31etL1Wc5+tFGLY4tTbaUo+9i9kkCq5i6tI0AAggggAACCCCAAAI5C3Q01k1WcudASVa9SxqZQsYqZ0rfVtRaP+Hb4AnccwKJcOy7kvo+33OBFTQgc2t0aedVBW3SI42RwPLIgSAMBBBAAAEEEEAAAQQqXcAsVlZ8Q90blLLPl6RVo3w9sdJNGL/aiAEChRBINEY/JHcc/HQh2vJuG2b1nheGv18+PwM5QZUElnffeUSGAAIIIIAAAggggEDgBZxLeuLhummWzLRKbFDv08quCfygGWDWAsbSJLCy1qLgYALxptjbjDI/H+z1gOzf3BNKv3fSsk17AjKeQ4ZBAusQEnYggAACCCCAAAIIIIBAMQU2XzZhWCideavKqIsS2shsK3t0IKcLFBOxMtq2dbd5ujKGyiiLJdB7KbKyb5X2g5z/eCFj7HeccPOz24rl6IV2g3wAveBLDAgggAACCCCAAAIIICACXYtqjkjtVOdZ2mowPekLZNco5azEzobA4ALrY23J3YO/zCsIHF6gq7Hm2LS275RSRx2+pK9fTcmlkQ0TW7ue9PUosgieBFYWSBRBAAEEEEAAAQQQQAAB9wLJS2tfY2esC7QxF6Z3qbdoraqZaeXesXJr6OWVO3ZGnq9AoiE6PK3V3dLOa/Nty8v15e8AH61r6bzPyzEWKjYSWIWSpB0EEEAAAQQQQAABBBBQcnng0aFU5iJZQrjRTptzZC3hEEkr3hjuBUx7pir8dff1qIFA7wrmOlGlb1TGnBVkD2PU/9QtTf4qyGPsOzYSWH01eIwAAggggAACCCCAAAKuBZyZDnaVeae2dZPqSb9DGqh23QgVENgr0C3Jz1ad1p+f2Nr+IigI5CKQaK69SpJXF+dS10d1fld3UvILPoo371C56jxvQhpAAAEEEEAAAQQQQKAyBRLN0dOMMR9VSjeLwKjKVGDUBRDokfXQ7pfZJLdbKXWbrHv17wK0SRMVKtDRVHupVvrXAR/+I+ER9tk113a9EvBxHjQ8ElgHcfAEAQQQQAABBBBAAAEEDiewvmFy1YjIixdoZS2SC3XOk7KcUxwOjNcGE3hF3jj328q0pVPVd7627ZkdgxVkPwLZCsgdB2dqbTtrpwV5FmiXpc3UaEtnMluXoJTjh01QjiTjQAABBBBAAAEEEECgiAJymeBoO6I+KV18VE4ixhaxK5oOrsB2Gdpdcse0O+xIZPnEG9u7gztURlZqgURTdJKst7dO+n1NqfsuVX8yvp0hy8yKLun8R6n69FI/rIHlpaNBLAgggAACCCCAAAIIeEzAuQ19SluXy4nTpyRxdbTHwiMc7wvE5X3zR9vY92wfOf6PZ177aMr7IROh3wR6E+xK3S3vtcAmr+SY2NrSC6JLkhWZvHLekySw/PadSbwIIIAAAggggAACCJRAoH1B/XjLtj+fVmaRnBQeWYIu6SIoAkb9U2lzu22ZOyYs6frrgWF1HXjIIwQKJOBc1mzCO34rn1MnFahJTzYjf0T4TP2SxF2eDK5EQZHAKhE03SCAAAIIIIAAAggg4AeBvWtc7fiosjNXSbwj/RAzMZZdwJYI/iYn2PfITKtbJi7terLsERFAxQiMiuz4ibz35gR5wHKDg+vqlyZ/HOQxZjM2EljZKFEGAQQQQAABBBBAAIEKEOhorDlf6x0/lKEeXwHDZYj5CWRk/f4/G1mE3QrLnQNvSnbm1xy1EXAvEG+q/aIkr+SGEoHe/lS3JfmxQI8wy8GRwMoSimIIIIAAAggggAACCARVoP2S8adYobD8dd/MDeoYGVdBBF7WRi2T+07eka4K/14WYX+xIK3SCAI5CHQ0175PGe3MFA3y9vgePexivUKlgzzIbMcml4myIYAAAggggAACCCCAQCUKyMwFHW+KflhOCn4g4z+iEg0Y85AC/5b3x+9tZe4enupZNrZt+64ha1AAgSILdDTVTdHKXindBPdzS6utaZM56/jWLR1F5vRN8ySwfHOoCBQBBBBAAAEEEEAAgcIJbG6YcFwokr5BWpxXuFZpKSACCTlRXMadAwNyNAM2jMSl0VqTUg/JTMDagA2t73C6LW3OibZ0/rnvzkp/zCWElf4OYPwIIIAAAggggAACFSeQaIy+3ej0Uhn40RU3eAY8mMC/nDsHqox1R+yWxKOSwJIJes7GnQP3OvC/FwQ2Np8wyqS7nctYg5y8kjXbzaUkrw59x5HAOtSEPQgggAACCCCAAAIIBFagoym6SDIT18gAI4EdJAPLVuBf8l5oM5nMrRNu3fJEtpUoh0A5BEyDCiXMniXS92nl6L9UfRptvlTf0tlWqv781A8JLD8dLWJFAAEEEEAAAQQQQCBHgd6Tv0jUucPg5Tk2QTX/C6Rk2bMHZW7V7Tpi7uTOgf4/oJU0gkQk+iOZGHh+sMdsbpTk1beDPcbcR0cCK3c7aiKAAAIIIIAAAggg4AuB3sXaI9FfyGVhH/JFwARZSIHdctzvs5W6OxVK3XHCzc9uK2TjtIVAKQRk5uinpJ+Pl6KvsvVh1Ko9Lw7/SNn690HH8lnGhgACCCCAAAIIIIAAAkEVcJJXiabYz2TmAidGQT3Ih47rBa30clvZ98idA3/HnQMPBWKPfwQSzdF5sijUXRJxkCfgPBNJpc8a37Z1u3+OTOkjDfIboPSa9IgAAggggAACCCCAgMcEEk3RH5O88thBKU44SWn2Dlk/5466zs4H9QqVLk43tIpA6QSSC2rPyNjqVpl5E+TcxfMyvreTvBr6fRXkN8HQo6cEAggggAACCCCAAAIBFog3xT4qySvWvAruMX5GTnzvsY3VVrc0vkYey4Q7NgSCIbC5YcJxtp2+S97XI4MxogFHkbKNuXjC0s6NA77KzoME5L3AhgACCCCAAAIIIIAAAkETSDbXnmUbmYejVHXQxlbh4+m9c6BS1t31rfFHK9yC4QdUINEQHW6q1AOSkp0a0CH2DktrtSjWkrwuyGMs5NiYgVVITdpCAAEEEEAAAQQQQMADAslLa19jp/RtSpO88sDhyDeEtMw6WCmN3K7l8sBoS6dzqSAbAoEVMIuVldiglgQ9eaW0+WaspZPklYt3MgksF1gURQABBBBAAAEEEEDADwJ2yvqenBzV+iFWYhxQoFuSVrIIu7o7YyJ3Hr9087MDlmInAgEUiD8V/bbMTLoogEN7dUjaqNuiJ3Z+9dUdPMhKgEsIs2KiEAIIIIAAAggggAAC/hBINEbPNlouvZG7D/ojYqLcJ/DqnQOPGLbn9jE3PLcTGQQqTSDeGPuAJN9vCPi4HwmPsM+uubbrlYCPs+DD44dawUlpEAEEEEAAAQQQQACB8gg8smhKZOyuZ/8pvZ9Yngjo1aVAl6y7fqcxodu3jxyz4sxrH025rE9xBAIj0N5Ye66l9R9lQJHADOqQgZj2tKk6i1mVh8BktYNLCLNiohACCCCAAAIIIIAAAt4XGLtz2wKZd0XyytuHarPMIri7986BJ8XX6sVKrhR0tvjeL/yPQAUKdC6oOSljy7p9AU5eyS1Cd1pGX0DyKvc3OAms3O2oiQACCCCAAAIIIICAZwSchY/jG8wVXGLhmUPSNxDuHNhXg8cI9BFwbjqRSeu7ZdcxfXYH7WFGLo1sirV2Pha0gZVyPCSwSqlNXwgggAACCCCAAAIIFEkgvqH2vZK8OqlIzdOsO4GM3EFtlaxFdnskbN9Rc1MX06vc+VG6QgQ2zjuh2k7vvkOGOynQQzb6k/WtyXsCPcYSDI4EVgmQ6QIBBBBAAAEEEEAAgWILaK0/KEkTtvIJdMu6+auNMvfYqfCtE9vat5YvFHpGwPsC8nGlk8d0X2eUnun9aPOI0Ogf1i1N/CyPFqi6T4AEFm8FBBBAAAEEEEAAAQR8LtDVWHNs2qjzfD4MP4b/ssx6e8BWpq1HD79jUsuml/w4CGJGoBwCyaboVyWJtbAcfZewz2WxdOJzJewv0F2RwAr04WVwCCCAAAIIIIAAApUgkNLWRZJICfCduzx1FJ8T62W2sdt2pY/50+S29T2eio5gEPCBQEdTbYMkr670Qaj5hLg+lapq1G0qk08j1D0gQALrgAWPEEAAAQQQQAABBBDwpYAkVN7my8B9E7Rp10rfZSv77rqurhV6hUrvDb3LNyMgUAS8IhBvjr1JGXOjxCMfXYHdtoRse15d2zM7AjvCMgyMBFYZ0OkSAQQQQAABBBBAAIECC7y5wO3RnFLcOZB3AQIFFtg8f8IEZVJyx0F9RIGb9lJzuyUz957aW7oSXgoqCLGQwArCUWQMCCCAAAIIIIAAAhUr0L6gfryyM9GKBSjcwG05qV4ni7DfHcqY26O3dm4oXNO0hAACG5tPGBUy3XfJ99m4AGvYWqvmWEvy4QCPsWxDI4FVNno6RgABBBBAAAEEEEAgf4FQJnOGCfKFOPkTHa6FPXKyuVzu3nh7OJW+a3zb1u2HK8xrCCCQm8Aji6ZEqndtvU2SV6fl1oI/ammj/ivWmrzdH9H6L0oSWP47ZkSMAAIIIIAAAggggMCrAnIL+vFKMjBsWQs461fdY4xZesTwPcvG3PDczqxrUhABBHISGLfr2Wvks+otOVX2SSX5FL6+bmnyOz4J15dhksDy5WEjaAQQQAABBBBAAAEE9grIJW/jmICV1buhW2Z/fF/Z6qd1tyRYpQ4XEgAAQABJREFUfT0rMgohkL+ALNr+WUkYL8q/Je+2IJ/B920bMe5jSiW9G2QAIiOBFYCDyBAQQAABBBBAAAEEKldAaz2WGVhDHv+NRlvvqW+J/2vIkhRAAIGCCcSbYhfIHQf/p2ANerEhbZ5IRyLvO/PaR1NeDC9IMVlBGgxjQQABBBBAAAEEEECg0gS0MvxOP8RBl0t7ZIH2zFsTDdHRQxTlZQQQKJBA+4KaN0pyvUWaC/Jn1HaVts6feGP7iwVio5nDCAT5jXSYYfMSAggggAACCCCAAAKBEZBL49gOJyCX95ykjf6BiaiuRFPsNx1NNXMlqcWVl4dD4zUE8hDY1jBmhGVbt0gTR+bRjNer9mhLXVx3a+JprwcalPi4hDAoR5JxIIAAAggggAACCFSkgEwt6iYTk/Whr5Y1wxq0shriTdGn4lpfF7Yzv65Z2vVc1i1QEAEEhhTYHan+gXwuTRqyoI8LyB0HPxdbklzh4yH4LnRmYPnukBEwAggggAACCCCAAAIHCbxw0DOeZCXgzMqStXm+m9ZWMt5Uu7S9sfZcZmVlRUchBA4r0NVYc6x8f1122EI+f1HGd190afIanw/Dd+EzA8t3h4yAEUAAAQQQQAABBBA4IGBss0lbcjrFlqtAtVxNOF8I5yeaohsTWl2/x0rdeMLNz27LtUHqIVDJAulQ6BRlm0DnGmxlXy2fupLzZiulQKDfVKWEpC8EEEAAAQQQOCAwc+bMY4wJy5oz5hT5/W6sXLIzSis9QkoMk+e75GTxJbml9g45YUxkVOTva9fe/4y8xi+CBwh5hEDWAiFLb+CbJ2uuoQpOMkb9d1UmclWiMXqXraxr606K36cXO4vAsyGAQFYCWgV+VqiVsv6alQWFCirAn2oKykljCCBQLIFp06aNDlmRb8nprfvPLaOXr173YFuxYitHuzOmzfq03DZdEgMF29LS3vPyV/zntTbPG8s88cILLzy+fv36noL14IOGZk6b/Sl5h70uh1B3r1678tM51AtMldlTZ0/KhM152ljnSR5qhgxsvMvB7ZTyj0hS666ICd2x4s8r2l3WL2nxWdNnzZePo3PcdGoZ9YuV61b+zU2dXMvOnD77S1K3zk39VGbP5x966KGX3NQpRdk5b5pzXDpif60UfQ3Vh9GZz61Zs8Z5r3pqe2TRlMjYXc9KYlhVeSqw4ATzjNHmeqPDN05Y0rElOMNiJAgUR8AsVlZiQ/Qpaf2E4vRQ/lYtbWLRls5k+SOprAjcnwhWlg+jRQABjwjMmjH7O/IX0c/lFo6+Z/XaB8/Pra43a82YPnuzfIBPKHJ0u6WPB+Qk/bYjdlX/5t7H7n25yP2Vtflp0+acHNL24xJETrOTbZUet3bt2oq63GTatHNrQzq9QMwuk38ny7+CbfLe+4uRO4aFq3XbihUr0gVruEANzZo++08y4+WtbpqTmRynrV274p9u6uRYVksCy7md9ygX9XdKEvYoKe+5iTwzZ559vlyKcpeLsRSr6A4xOsaLRs6A443RlZKAn1WswdNur0BKvkPukc+na6MnJe9lVhbvCgQGF5B15T4js62/P3gJv7+iP1DXmrjR76PwW/ws4u63I0a8CFSggHOSLMmrj+U+dHNG7nW9V3Pq1KlyKZaqL0Fkw+VM9h1yPnvDKyO6k7NmnP3VOXPmOJeABXILa/u/ZWA5Ja8cEMuuOj2QMAMMavr0s6fNnH723ZK86pCXr5Z/BU1eOV3Ke+9NSpvWdI/91KyzZjkzujy1SXynuQyoZ8eO7Rtc1smp+OzZsydIRTfJK6cfJ3krw/LeJnd5cmtdnEFo5SQfPWnkDNhodX9xBk6rfQQikiS8UKyXJZ6KxmW9rKufaRpf3+d1HiKAwD6BYame6+ST6dmggmhlPhnUsXl5XCSwvHx0iA0BBHoF5CT56/LgiDw4Ym9+83mvyaO+p6pWW9WnSkCSwyrpdrRc2vU1SSasn3nWnLkl7bkEncl6TVPlrDS/WXqWHahE6UDsM2acPUtm9iy3lFkrv5S+S8qEBipX4H3HG23VFLjNvJpzLmmWBlxeIqmfKNUluSZt3CdTdW8CKy+XYlWWP2B4IoGlbe8a9doba3mxjgHtDiCgVa383LgirEKb4o21d7bPr32naSjJZ+IAwbALAe8JjG3bvktm8X/be5EVJiL5/n+Dc+fSwrRGK9kKkMDKVopyCCBQFoEZM2acJB1fmm/nVVUZT5wA5TsOp37GyuHktBAd722jTqYa/XHGtNk5Xs5ZuEAK2lJGO7OI8ksKauU+aVDQQRSvMWcNopnTZ90kC7I/KL3IGlel3Wyt2kvb4+F7C4WqczjW9mOHb7Vwr8oJg/vPO28nZ9yPp3Ccr7YkJyuluPzz1f7cPtg+csxDUme723qUz1sgrLR+t2XpexKR6OaOpujizvk1sbxbpQEEAiDQ88KwX8gvVx0BGMqAQ5Dv+2/Jz4b8fn8csGV2DiZAAmswGfYjgIAnBLQJO4mFnC/renUQdlmTPq+GUYgHcic3ZwZWObeQ1uo7spD8V8oZRKH6njlt5rvk5GNO3u0ZHcQZWHrGjFkfkQW0n5DfzxaKUVl+SctkwvG8j08BG9C2+4S4fM84l+iVZsthxpLcDbJ08blQmDx5sixKbia5qFK0ol412j/gM699VNZn0i37n/O1LAIx+ZC8MmNZ7fGm2P91NNU2OAvslyUSOkXAAwKTlm3aI39UWeyBUIoTglFTE02xdxencVodSIAE1kAq7EMAAU8IzJo2681y4nJBQYIxwUlgyQosOcz+KIjiQY3IXQu/Lnfty3t23EGNlv6JpbR1VWG6NafsPdkuTGvlbsVZa02O7y3a6J9LLEeXMZ7dDz10n6cWx5e/trqeEWTsUOkSRDnMBuxOR9aX8RgP2vXoEaOd9dUkiVX+zatGB8mE1a8Oes6TcgnIOZaZK39w+o3cHbLDWSurfWH9xHIFQ78IlFMglkrcLP3/q5wxFLdv800uHy6ucN/WSWD11eAxAgh4SsDoAlzWtX9EWgVpdky5Z2DtV3Xm4/xU1o+qO7DDX48kQePcQe/1BYq6at/JdoGaK18zsmj6GyOh6r/J8b24fFG82nOHPJKckYc2o10nkY2VKsklhHKjhWEidYJLreTDD9/3vMs6pSke8kbCXgbb6VmjPkei7uaEc5njI3128bD8AuPlA+wKK5PZFG+OLks0Ry9kVlb5DwoRlE5At6mMzEwMxKz9QdQmxyO1zYO8xu4CC5DAKjAozSGAQGEEZsyYLXe/U+cUprXeVibLiV3+lyIWMKBcmpozdU5U6jm3cffKNkLZoe95JRg3cfTOltLqSjd1hizrnZPtIUMdrIAs1H6OsfQD8vrxg5Up6X5t2kva39CdyaQK9bqhix1U4t9r1qzpOmhPkZ6k0+nJ0rS7zzrjzcsHHSI58Xc9260otNqUbgZdngMw2jh3VGXznoDc/0K9XW5K8LuxLz/bewfD+CWx13ovTCJCoPACsdbk76TVPxe+ZW+0KAm6r22cd0K1N6IJdhQksIJ9fBkdAn4VcH7J+0aBgx9ud9ueWEcln3GlwrbrmR/59JddXfPe6dPneGdWWHZBq6NHjf6YFC1oksY2lgePT5YgUmzmtLMvlIXa/yAPR2Vfq9gltTMDyzObzDicKMGMdBnQP1yWz7m4tnNYwN3LyRmTw3hy1hu8orEt3ySw6lo6fysjKcmMv8HFeOWwAkYd58zKUiGzYf9aWesbnPXe2BAIroA26r8CPLoJ1aP3fCi44/POyEhgeedYEAkCCOwTmDV9VpP8JeMNhQbJBGB2jGXKvoD7QIdFW8r+6EAveHWfzMYbIWt4faHQ8Vna+PZSVfm+m6+0uU1MnEvQPLMZZTyVwMopQVTCZEIuM5bk89a7yRntjRlYJV2EP8/vPjmeMsnHFPqPQHlGRfVBBORcbO9aWSMjO7bKWlm/7Gisc2ZRsiEQOIHY0uSDsvbE8sANbN+AjDFf3f7BY93+gSuoHEUbFwmsotHSMAII5CLgXNYlJ2CLc6k7VB3L9v9d4myvXE5zKPb7ZJdvfqZkUub/SbxjDx1GfnvkvVuo9bTyC8Rlbblhwnlyl6AbpZrnjqEkjDyVwBIn15e0mVLe4S+HBdyN5c3L4yTR7Nw8oNbl27koxS1jnLWlfLPVndg7C+th3wRMoI7AMfIzZJHW9uOSyLpPZmbN55Ik3hhBE9DKfEnGJG/14G3yx4Oxu7urPxG8kXlrRGFvhUM0CCBQ6QLHHHXsR+TnWlHWhJB1QXx9eZfz3pAfjq5PnqXaX6XmIL8sGOeShdHyL9+TxLFyadVpq1evLtmlUhJzTtusWbPGmIz5dE6Vh640durU88bJXfOeHbqoN0rMmDHnTGPsOySaQq/d8Ix8Lz+ktfVPW5lOaX+n/EvLv+HKNuNlBtwk+RV2irypp8i+QX8fkUsaPZXAkphPc74R3WyWXcIEkftL7tIjR4580s14SlU2lTKnCbVLbfWcVCnwe8YYq9p6olTjLkQ/ctN6O9GoPizJ00elvUG/vwrRF20UXMD5gX2ufH6eW31M94uSzPqNfBdcE2tJenemZMEJaDCoArIW1sPxpujtMr6LgjlG/flEQ/QXsbbkv4M5vvKPih9o5T8GRIAAAvsEnMu60j32F4sI4tvLuxyTKVOmROQX2pNd+mxbvXalkyA47DbnTXOOS1VlPqCN/rIUPOKwhQd50WSss+QlzyewjK2vlDhHDjKMvHeHw2knUfp/eTdUggamTZs2WpuMXDaoRxSmO/O0Mvr6jLJuW7duxaZs2pw6deqocLjaWXvrQxLHzP510jrS3n9fWZ+7v6TNHv7y8PWliHlvclaNc9WXURuWLVu2x1WdEhWWs3jXCXtJjP5k1ZoHv16iED3djVyu81i8MXaN/P2iWAl7T48/IMEdLcmsRZI4XyQn/Y/K42sjI+wlNdd2vRKQ8TGMChQIWfYXM7b1bhl6EHMRR6sq9XkZW8GXqajAt8qAQ/bcpQIDRslOBBCoCAFJXn1OBuru5MudTPTNbz7vNe6qeKf0sGHDTpRo3M6Syeovtiv+smLrmjWrvq0se7b0sSuXUcsaMZ5fJH/27NkT5UTgw7mML+s6tm/WwdJhHflfSRrVZz22wQv+U2Z6vHf12lWTVq9beXW2ySunuYceeuilNWtW/lrqzpJfSs6WXTJj8NWtZ926+7e8+qzMD+bNm+d8/7l9nz9972P3vlyK0E0q5DpJ7+W1nSSp6TqBpYzt+SR6Kd4L+/sYlu7+ikxhK/CMtP2t87XEAlPkWP4yvctKSGLyBx3NdW7vhlricOkOgYEFapd0PSV/kL154Ff9v1cWIfxk+4L68f4fiTdHQALLm8eFqBCoOAFn5oAM+jPFHnhVVcb9CVGxg8qyfctYrmN3e3IqlwA+Kj94v5ZlSAcVk1+sowft8OATO22+KWEV9U5P2ieXqs6cfvYn5K/5zl9A89kk2ak/JbP8zpAk1O+kIWky923l2pUrx9eOe7O08BX5l5HmEvJVln7zxvbyiy87J4yu/mIsIKW7G5zl/jJpiS+rJHc5joCxcpiBFdal8y4Hiss+x7Zt3yXfQZdItR6XVSnuXYHRzqw6bez1MivrkY6m6KKtC8cd6d1wiQyBQwXCYbNY9npy9u+h0brec4Rl0s4VDWxFECCBVQRUmkQAAfcCdqb3hHWU+5oua2Rs1zMUXPZQvOLGOt1t48a4P5lLZZxZOe6TBrK4tad/gZ41dZb4aedErrib9v7NAuZMnSPJxvzuUiaJj79ZYXX66rUP/lhAC5Zkamtry0hC7Bsyk+Y9Wmn5K613Nhmk+yRyCRNEckxcx6cs958RJToistavcns3tpdWrlzZXqL4fNNN7JakrEXX+zPWNzETaNYCvbOyejKRTucOhsmm2tdnXZOCCJRRoOamrrgsOfDzMoZQ3K6N/nD8klhR1vQtbuDeb50ElvePEREiEHgB57IuOVFd5H6g2v26Mto3l3cdyqGN25M5+d1Au55d8fDD9z0vJ445XHJiIocG7Z09xtJXSzRuf+7JLCD1hKtRGHWyczdNV3VKXDgVsn8oXY7MtVuZbXerbVIzJFmwOdc2hqq3et3qe0JV1vuHKlfK13UOM4Lkm7BkM4LkuLhOYIXT7j8jSmE+ffq5ddLP0e76Mo615PHY+gtEW5LfkX139t/P88AIHCVv/EW20n/bPytrW8OYAq1tGBgjBuIxgbDKOLPiX/JYWIUKJ2L2zjIrVHu0s0/A7S/ywCGAAAIFFzBpdZU06nZtJzkvVJ+Qei+6C8j9LCZ37RevtFza5/bkNNPdvfNfOUWk1Q7X9YwqyTo/ruOSCrOnz54td3Ga57auJARukfPhZS7rVR1zzDGnuKxTsuIzZpz9FhnXe3PtUGbaXX9c7bjmdevW7c61jWzrrVixQu4o550th+9BuQ6yNAmihoaGkLxX3a6Js3PFn1d0eEf4QCSW6XH7eSeVS5csPBCpPx7J97y8fa0PyKVn7hLy/hgeUR4s0DsrqztSnYw31/6UWVkH4/DMOwI1S7uek8TrD7wTUWEjkRuRNCWaozn8LCtsHEFrjQRW0I4o40HAZwKzp80+TX54NboP26xes+bBB+Rv7S4vMTKnyt0OXa1h4z62wtdw7tQmCZgJ7lrWmx599NEc71RkjnHXl5wdae3Zv6LJe8yZfeV2y6SN9Q2ZtOXyPSbd2CHXl3u6DS7X8rJuyldzrSvfb79Zs/bB/3Qu88u5DX9XdPeLqCR1161b8UwphpxMbp8k/Qx305ckNf4p5eXbw3ubzJh0Z+0MxJRwvTHvkQ0ZUX1r/AX5xf+tUjA5ZGEKBEHgKPnB/DFmZQXhUAZ3DMNTe74rP4S2BXSElrHzW64hoC55DYsEVl58VEYAgXwFZE2Z/5Y2XH8WyV81ehdHlBOwJ13GUJ3JZE50Wafsxaut6lMlCBmuq8315YNO63svf9PjXPXkFDZ23HWdElSYNX3We+WXo2muu9KqRZIPT1rKuH2PORieXGtNZqKdK2+jma4t9lZYO/LoIy+Vh/JtW3nbtGnTRsuoa1yO3EkQlcTLsmzXSVP5vsjpM8KlQU7F5TPefQJLMwNrKOxoS2fStuwLpFxOd5sdqn1e96xA76ys3ZHqLmetrI7Gulx/Dnh2gATmTwHnRhPaaOdcIJib1u9un18zPZiDK8+oXJ80lidMekUAgSAKyKVMs3K5rEtOuu5ftW7Vg46JbRn3s2MyyvWJXrn9ZbqL+5M5YzvrwbjeRo8a7SR7hrmtqLW1yW2dYpd3LquSS96cS1TdbhmjMt9yKqVVOocEljffY5JJ+aJbiH3lX7BVuGnZsmV7cqzv+2qhULX7zw3duyZTScaeW8LHeDaBJYlWt595JpPpdr8uYkmOjrc6mbCk66/GWPPkZ+lOb0VGNMUWkL+CjZTjvkhre5WslbVe7mB4RaIh6iTn2RAom0CmOvQz6TxRtgCK3LGlrVyuAihyVP5tngSWf48dkSPgewFtTE4f6LLQy9f2D17bluvkglzq5snZMfvHNNBX+bB2ZmC52rSynNkfrjfxaXJdSSpYxvw9l3rFrLO1a+sHpH3X61FJ0uvmNWvW9CZH165d60xt/7fLOF/vsnzRi8ui2K+VTmQGVg6bUZ9eu/b+jhxqBqaKtjNuEyrOlMmSJYjkpNR1fJZduvjcvBH23QTB1UxZsX76oYce8uxlzG7GX4qy9Uvjq5W2SWKVAtu7fbxOvm+ultuvyB0MY7/paKqZ691QiSzIAhNvbO+WP8J8PbBj1GqWzHp8S2DHV+KBkcAqMTjdIYDAXoFZ02a9Rx65n1KrzfKVa1eu3O+ow7brGVjyQ9L9TIr9HZbpqyxY7/rk1NYh1zOwZk+d7ayjc1kOw/z3ynUrPTX7QdY6G2aM/moOY8loK/PtvvXkl3y377Mxc94057i+bZT7cUhn3i8xyFBcb6tWr1t5s+taAauQS4JIVpdy/T2YK1sun2t7MlU5JblzjTHbeqNHjD5ZylZlW94px/pXbrT2lq1v6VrjJLHkmcubobjvixqeFhhmlGmQP3r9X7wx+vd4Y+xjTzccf5SnIya4wAlEtyRvlJ+zbn/X8o2DzHr8lowvl9/BfDPGUgXqu4WMSwVDPwggUDwB57KuLZ3bZHFs+Sh3ucldlA76C80rr7yycXj1kSlpJpJtU9Kr72ZgydjcJrB2yYyZzdmaOOUk4TMi3WP/Vh66OnHs7UOr++RrSdb66e0vi/8yPeaTUiyWRdH+RX69evXqDX13yi/3MtNPT+u7b6jHmXDGeZ9tHapciV6XCXL2pbn87qRt8wWJ0f03a4kGVqputNKnukXIaF09c+bMKcWO0cpY1bbrmzyorocfvu/5YseWS/uygLvrGadyWvBiIa3lM+BvErunPtNysRyqjpPEctZD0jpzj3w+TBiqPK8HXEA7vx+Zn0YiPd+TWVl32ypzbX1r1/KAj5rheUBAr1DpjibzFfkc+o0HwilGCGcmG6MXqaVJ5/dstjwESGDlgVcpVeWkNtzTY9XKLzd18hfeCVrZRyttjTTGOHdFO1ocRsqveCPlB95IZ/9+Fznh26Hldlf7nztfZZG+V2QmyYtyKvSi1H9R1sx53mjTLmsxxI3ZE5fbsru9TKdv8zz2icCW5LPvl/fOZLfhyp8t7l295sFVfevJXfZSM6fPdhI1bi43qZX39bErVqx4rm9bXn08bdq5tbISk9s1KpyZFQd9/x1ufHLid2I6ZbdJmdMOV26w1+Ry0FsHe60c++X4Hi3JuCty6DulLPubh9bT7v8qaPXO9PvToW2Vfo/c7fMMeTPU59Dzg6v+vGpNDvWCVkV+/Ln/zJJp7n+ShfqKbiHJK/dbCdfnch2czmmW7AfF+oOu+xq4wguy2+1n7sAt+WCvXE64vqux5k1pbd0hv8vN8EHIhFh8gf2zshpk0fcn5efHjRFj/6pmaZcvfm8qPg89FEOgrrXztkRz9CE5T5xajPbL3aacA3/LzFF3Osm6csfi5/5JYPn56BUwdmdGjHML7rDOvF4Z63TJNNVJAkpOdnS9nATWWHJP+P1/f5e1YeT3G/lV3tn2fXF2Sdk+O/Y+k9v3Oi+8uvUW31dH673lnbMCSYrJfxEliYiXZO96qfaY1H1Mvj7e3b1LchSPvvJqIzzwtYAkFobJe+rKXAZhLOuqgerJe+ZJeRu5SWCpVMo4iZoHBmrPa/tCys4hqTT04sxvPf2tR+4a0T1DTq8vkW/BhTLurGex9TN6Lm3Sf+i3r6xP5T32XxJADieg5kaZefFM/+C1zMDq/ezr/8LhnhvvrLVmLDO3/+fx4ULf/5p8BjsLq1b8Nnv27Al2Wo0KEoSxrZKtz+XWTT7TT5PP9LJt0rdnbYqF4iQmuhbVvDW9UxZT1ub9xeqHdv0nIN8PJ8v35NWS4LxSklm32ca6tncNNf8NhYg9LiDvMxNXztIPxhN//CsC14mJ2tilsl79DUVou2KaJIFVMYf6wED3zqgyb5AZE2+UE9fXywnK62VGzGkhrY7sPUFzMkq9m3yMlH4bJb1Pk8TYNCc75oTiXB4mia2/SCir5CRy1fBdw1fc+9i9L5c+NHoshEBqj3255C7rXLdl1LLVq1esHqjevsu73j3Qa4Pus23n8q4HBn3dQy/ITMbT939XZh+WXijfN+87TPnIK6p7RCHmhkgy+ifr1q7bfZi+SvrSjBkzauTj4xM5dJqywvqgta/2t2Fr+0ltQvufZvVVjtnpWRUsQSGJ5dwcunkxErHuyqFe4KqYtJFjWZafiUWzlM9hzyZp5P2aQ9K+cFRetincKA9tqebaLuePhZdJkmKVHIOfyOPhh5ZiTwULDJf3xUJZy2ehrJW1SqfV22JtSc/87K/g4xKoode1JO6Vu2M+ID9xzwnUwPYPxpgrN847oWXSsk179u/iqzsBEljuvHxbWi4POl4mUc2VjNBcmZkwV05aj3F+F5cfRHs3b/9e7swKcRb7ni4prSteGdHdPXPGrNXK1vdYEfW7lStXJvaNgi8eF5g7Ze5Re3TPf736vnMTb8j+2qDFjVze5fI9LCconkkuDDqufS8YZct6MC4HqNQwqe78K+omUT2ftnuuKWonLhvXxlosVY5wWc0hvkE+TzYPVC8SiTwtn5098pqb9cFOmTdvXvWyZcvK/UuK5P51DpcF6eVymW33QB6Vtk9+9pQ1oVIMb1tpTyawnJ8T3aonWowxZ9um/FHEuQS7YrdYa/JXicboX+QPnEsEIXDv/Yo9sIUb+KNpnVl4fNsWkleFM6WlPgIhbb5oG72uz64gPayrGr37ozKgHwZpUKUcSyH++F7KeOkrS4Fp06aNnjlt9gdnTZ99i8zC2CbrQjwt6apfSsaqQZo4JstmvFpsmJyMSTJO/VAu6eiYOX3WqlkzZn3I+aXXqwET116BPVWpKyR59ZocPH4vl3U9NFg9+SCTBbbdbt65vGvoyOWyXo9utjZf9tLadc5aXpKJ+kAOXKlwxrp6sHqSyHHWK5DPUVdbeMeO3ae4qlGEwmISk2ZHum3aaPs+t3UCW94E7iQ+XVWVy+dm8Y9w9/C0kzBxnbEvZGRWxruz0wo5zsO1FVuafGxn6qgz5Q+fzpqArNdyOKzKec2Wof40UxWeeXzrlo7KGTYjLbVAtKXzz9LnnaXut2T9Gf2F7R881vXvZSWLz+MdkcDy+AFyE55cGnj0rOmzLpPE1R9COrJVfv37lSQLLpE2xrhpx2dl5ZdcPdMYfV13dc8WSWa1zpw5Z6bPxlAR4c6aNWu8/FX7k7kMVi53/frh6qVUKocElpo8ZcqUXNd8Olw4BX3NueRXks8nF7TRAjUmny/3r1mz6toCNVeQZmRdn29JQznMLjbXr/jzivbDB+F+IXe51MK5VLWsm87onJJocnONR8sauJc61wFLYBm1wbOz62zncs3ybqFhofXljcAbvU9uW99T19L5Zbn771nyu9ZfvREVUZRDQH7ePyU/E86ua01ePvHGdmbmluMgVFif8n77kgw5E8Rhy8nr2O7dwz4TxLGVYkwksEqhXMQ+5AT8CElaLZCk1V1yectWuczhfyVxNU+69PyJeRFYhssvWI3Ktlc5a2bNmDG7efLkyW4u9ylCSDS5X8DY+kp5bx65/3nWX426e9W6VQ8frvy+GUDbD1dmgNeqhw37/9m7Evioqut975uZhJAAAgICCQEUNxCXqDgzmUmKiMWlrbWpQtXaxaXqX22r1VaraF1rV9tqta0LCqhpa60LrSINWUXFHXfZkrCICztJZubd/3dDwBCyzHvz3sx9d879/QIz79177jnffe/Nu98959x+8NZRuyQSCaljrnJacrYuEDO+Bb3kiqwSJRQqOwYvBV+3oUybyQK399mOC8tEKcjXjE/G8btghwAViUTLe31ikgUVZBgozJygk6kq53jCPSM9sDJZGkHubcykAqr1XTxv9dKiAxuPwSLUt6Gb1d9a1cwhfawhEMfv6p2BAvMoStxuDTiqnRoCcndUzOvmpiZF3dbYPfiKD88eMVxdDdXVjAgsdcemV82CwfID4G30ayQ4b8Lk5CEQA6eigXqT3F6tcPXk0UgA//DgQUM/ioTKfkBElqtY9yk8OiU6AeGr3+2zYjcVTM673Xmwm6rWyQXTn3FyoRs79jyUUDJX12aeECdXvVS1bk9lM/vNYOJWaIB3bYuFs7/U1y9a1VcrTKytEzoK5FrjjI/oy7Zuzm9esmTJ5m6OZ92hjjBQG1596kIFbwol819JxISRWW83PECUxSaTVxSfzcziec1zDL84BLmx/gBdZE5AKlojwF/B7+oxyIl2WUeCf62tJePUQyBh+q6HVlo+a/BbMyAnEbhSPdTV14gILPXHqLOGBrytTt4ZImhiIsV/hJNez2fV2T43PhdixfCuwYOGvC/zZHkhZMwNEDIt0/Szm6FDwLoe/F/19YvlDpRJFOveMcjtkfHwrr4MA0E9sa86aT7/OTOMk2teqFEqnCQSjJwIHI63gUWLP95z7qvO8kzus0ySIl9fxq8xYYiBne1I8vOWJOtpX80QpvpEt8VRAAGhKkmDDQdYRp95KpN7FofZleqFc5o/LZ7bdKnfb07ABEyGkGsZ4uMKeN4R2oL74IYtsYHBwnnNr7mkNi4fKoRA7wiMe2TlSvxe3dN7LU+fvaT5zFEyTykVCwgQgWUBrExVleELIK7+D2FxH2Ay+1RHiCCNnaUB4cUyTxY81l4PhaLTLTWlyikhEA6XH40JyTdsCBHYJeuG5NtZz08EvZSfmOINTyEdxUcJYYRqa6tqkx+XtNTkgvNbbPZ0b9WSqqZk2gYCtpJeD5P535KR72Idy4lCMXmhpM0dA8Iz7BHkxnXh86lJYHVsOLCPGzYnKxMMWlbvQJgsTqPmrFkNz5wLBDcm43fqIbSjZ0ay4Kldr9pIiMOL5zXNljnQnFR1ypQpA8PBsl9iIX55OBwucFI2ydIXgYQZkIvg2zS1sJ9pGNdqaptrZhEJ4hq0qQuW3kJ4yJ+zZeO2d0Bc3QmJ41OXmvUSDsFF/9/ScOS56HFRW4mNsx5BiwBwlrAX1iXY4/X1VUmv/GHSYd07hrOMe8f0BScSTKlBYHFW6c/xHd3QUGUd576MTPF8abDsTIg4yoaYloTw/zLZdu15cZD7K9n6u+qJuC+z15ng/Xfpkuz/mJAOTbau7vWEfjsQbq2url6p4rhxk2c6/xVCGIWq3mkqDhkrnrv6bRBZ5yRM/wQo+Cf87VBSUVKqLwQQMs4vwliWFz7a/H5fla2eR17akwK+3Dc5F1diIX5AXV0deflaBTFL64+fv2I9gst/q6v5WDD8buOsQvn8pJIkAlrldEjSZuWrSeIqLyd/JsKbroOy+yuvsBcVFHyaabBX4NV2+47WbTcvXbo05kUzVNe59LjyaUyY0+zoCY+azRifq5Jtawo+Ai9GyVbfVW8UdvnbF8TEJ7sOqPQ/VigHwKTijOok2NvISXNlXV31MxnVo4fO28OCuYk8aaBcLBf+kY/Hz8J1lnxLwSw/K3BdShLyP8l34nBNLtrgbWi1DMC90U/ZneqsWpNa/YyTKqmpv1dr6WFk/YrYS4zzB+ApfZitW9k5VeIDBgxQjqR3zjz3JMlQH0i/5KOK8df4A23n4rdLEhWj3euRJDuIwAKEhF4oveoclNkuCl6Vg5mJMH3Bzu8ke3mnz/SREOgTgVgs91eBQNsPUFHHxTU/0t3cCNtm9gkEVWhHgAgsxS4EeBKAuJKTMUlc2ZmQKWaQ2ur0g3rX98/NPwlEwXewGoTdLqg4iABnhrjNrjx4VJ1rpa0N8qpdvNnWnt9mkZW+0lVXCP8k4JCJBwGcTtj/8Aj6fV199VOw10yXzVb7AdkvX4ptEv1C5tqxfY0mq6vIdK41IeB6b+MyamH7wcaVydqpY71gMDgEdo2yZBtIX7jxXGapjc3Kwkh8CUn6f2atuboeRtgdcZJVZg32X4Rdbj+whkH3tYVPtC5YsKC1+7N0NBkE9q9cvgn1fr+sYuLdBYGNZ2J8rsB33UjgZKDwQp3Pcb9djXDBe91QFnOaCmYK6ZU3bE/5nAisPQGhb30gIJ8rjTMLb8cbcdJe832IVOw0P2PlmaN+OfaRNa8qppiS6hCBpciwgECZyE3jj/C6Krc10VDEDi+qgR/vY7jwLYUXxjW19dW/gQ1W35+9aLbrOsNd/JtMiBLXO0qxgw5yQUkCC+Gu6Xzp34grvwFw/pf5zMframsdX4lNcaj2aj598vT87UbLtcrfsRnOtcY53yQZSaslzs0Q2qy02k6n+n7mP8wydFwsqW2oWpgOHPC7VWq1H1CZyobIAWurIdPgruIP171A4UhWrwO363fkT5qDfuasmjmm1ODmVRjfk/HdBpvutrbZJx/EYqU/Frt4ZOW6DU5bL/M+4sb8E94BT+tONrzzVnR3nI4RAr0hEM/1/8HXFr8UdQp7q+fRc5wbxk3QXT4jqfSBABFYfQDk9mmEv/RHYvGfYAL2U/yk57jdH8nvEYFcnPkVcmN92d/mO7vqpSrLeW56lJyFJ2RYF15QpCeh8sUUhtUJU9psEsyEB5bFd33BHkOTvl4O4zBiC2RvRsjOCsM0P6peUv0RjinradUd6Nvyd/wI2dull5Dq5eCMhuMJATLS4nUkEeWsDP/OUx1cN/VDqPlheJZZKvAiSh9BJPNzWR1awd6wZFCaKreHAzN2kMXuVlAuHYuIZaB68fzVtei2tiPPyyW4pb6P75Zz82VAdR27XItn1MVFcxsfd8E4XhoqO08kxB2QPbBH+X2/o/TYlE5kLwLjHljZsmrm6JuwKPdnHVHAT/lJjWcVlhc93FSlo31O2kQElpNoWpQFD5Uz8GL8azSjHAEWsXOtOnJjxQPmy+Fw2cy6usU1rvWjueD+uQXfRzy3RxISisPVHQ5uWbcEM65pqK/6UF2bnNFM5i6Lt5kyNMULxW+2mnLTiEy5htsN15gGnSU9YpHC8cKQJKcjCFLLXpAi4UsfgcWte2m2JnJkDizlSn5O/sFg0C0t5OHCTB/WyiHmPYWQIFyGel62tmK/m9oC/u/i4SK9KayF6HrPbFU0lvkIHkYWx8uLKps+c1qpUGjq/pzFEYoopvYpW5h2f5P6FE0V9EZgTLz5r02Bwsvx7D9YR0vhuXgT7LLsWa0jFr3ZZPR2ks65gwBca4eFQ9F/gbx6BD0QeeUOzKlIHc2FWBQJRf4vFSHZ2hY5Y/JAXl3jFfvxQndox8q/cirjAT3RolLbGxqqsuLFMBEz5TXW8wqvReDcrp7JPFjYVe0dm/aNx3PwJJttdWk22aohMZEeAks+a6HbeIv6rXnxxec/tdgmLdVBXlkmC/H8JgIrLaPjbCcybA15l25v/bzfeLwvfBsUuZKkqrNWZ1TacvwGnSB3i3SavMJikh87pl9miPjruB/7Jq8AA3LNrcgoGtS5ZxHglSwhGL/Bswb0qbgIw1M129+7+kSJCKw+IXK2QigUnS4S/DU85L/qrGSS5jAC2BGC34n8IveoSm44bK9j4nw88CMI8xIxm5ubO8Bq2IpjePUkKBicOhorTEN7Ot/DcTkJwDxQ74KV3mLkdJK70XimZDJUtba2VpKa6+2AZTIu7+dsLfipZodaNP6TJUuet4W1xX6Yz+eTuvkstlOX8EG4pkVb5BYXRHxYBU2h+hMWfNhaPK95zpj5TYcJYURwwz0F9fDTR8UhBOLA9M4cX2xy8dzm5x2SuVtMZEpkMjyhG+Cn+zv85e8+0fuH+I4dOxp7r0JnCYGeESia1/gonMNf6bmGt8/gAXibmM2Io+llGAmcXsBx8hRIkP6RYPRuAP4fyCV3aSfBdVfW+Xn9+j+DJPsD3O1GD+nt2yUz9mOvWWOI9p0IlVLbx0zLkzm89qs7OXUQXYPHb4Q4mbfOOyXjOxGyF+2AhcnP1Egwcrydtl5vE41Gx8IGS15+ePFMW34pbloPb0xrfi6rF4DM52WxGIa6OypaNCXrq8s8WfAQOtVIiIMl6QJAdmQ9KKkB8CbjPARML9vvofXYida5InM6YoF3tvDxlyD1aEuSBWtcunRpzFIbqkwIdEIAzweBncev7XRIt4+HNb5f9E3djHLSHiKwnESzB1nhcPnRebkFr2Cl8EJUwX1HxVMIIC8WF/7/hUKh4Z7SOxPKmlz+oAzORNcp9ZlpcqEb5bmRsDyZgxjtCaxQqHwSiLpvdQOZ0ofwY2s5n5mTBiHp6QK78vCm+OCxxx4/1G57r7ZLJKwTKviBT5tHEMgyy88IYSr9jLBqT+v27ds/8Or1RXp3j0Dho83vS9IlEfOPxzxV5oP5pPuadLQHBFowvb/244IRJWPmNkqCydESOS4ShteVzOd4Pf4s5axrV4SzrEhz4CjoJGwvBIrmNsl3muq9TmhzQNz48vklAW3McdgQIrAcBrSruAh24+DCrMOPsHIhSl11pe+9ISBKDOF/IRgsP6C3Wtl8Toa8gZ/1VFjX7vHilrdu393UrQ8IkbM6mWNGOnc/c8vwPuQaTNyKKlbDpvqQ6v5pkA1D4cmZOe9bn/kvWGk3vHR0jj/+V7R37Z0BK/oF2DxjhvsjkXwPyFNp+R7EqnAaSWTrHlgYwDTqlzzW00qmDULtouRbyJr8XfLksIaYl2qPq1y5bsy85p8jT1Zhe54sxt72kv6Z0BUelvVmInHUmPmNNx99r7NeTtMnT8+H19VtwuCSNLCdQBvpOVZkAhvqUz8EBDd/pp9Vuy2aMGzr+u/s/kYf9kDAtZfRPXrJwi8yb1JpOPpH/OhiRw4bKxRZiJnyJnM2zsfNxZiEEhnZzWAZPCFXSvO6OaX+IWF9tz/3jTIsJ4+Os3javD/ct3/vHkpLy7Ezizhl7zNeOeLPmBdWTU3NWqBUYx8p8TVMXv5SUVHhOHkYDUWjWNFfiheSY+zr53xLeFNZJrCQKDmdBNEki1bHjVzDbkJ/i11Zq96SF5dYW/JQBymcTqytGUS1HUNgV54seGVNEsw8ARcJ5cnaG93tuB+uLmxrio59dK3j97hcXNhe0CIJxKvwl9LcEQttRGDtPX50xAYCxXPX1OG6f8ZGU080wbPu+jXnj+rvCWXTrGRKD6E06+qZ7mSoRb/c/P8gzOVizyhNiiaLwCgufIuxk6TVxL7JyvdkPXimIWeFOMuTyu9UeqRKIaJyVx8QNdZWODlbV19f/7GHx6Bv1YV5W9+V1K3BTZExAqsdFcH/lCI6313bvP7pKVOOH5GinPbmyJl3IBZ65sItrAoHDmTCXO2EXKdk2PCCFChp8RLBDoRDYOdIi7Z+UFVV1WKxTVqq496wTBbiBZYIrLSMjhqdYDIniuetWdieJ8sQR+K7XCBW8npOK2Kc/SfOEofKXR3lDm1O9i3zmsrNjLAztyQJxjgiW5gUQugIkCREIgBC9Gr8Z9e7XHUQR8W3+i5SXclM6EcElsOoyx05sNvHS/hhneqwaBKnDgIjsJPkouhx0UPUUSmzmvi5eTs0AOni3eITPssTKLesTSQSB0J2riX5midwD4ejX8GiQNgSJqpV5sKyV52TJuxo2yrDCJtSlHliwBd7qzRUdtHEiROt5z/B+6ZMCh8ORf/OTGMZxnQW9MFPpvyHK0NgzZgxIxcKyfvQSllRV1e3xUoDu3V9vlzr15LCzwh41lh+/ppcaO1xavfayIZ2hQ83vw4i64K4CIyFB8YNsPnTbLC7i40bYfsFyAV00vh5a1d1OZfy19JgWQWe0e9B0PkpC+skQBiCPLA64UEfU0MA1z8WMsRjqUlRubX42Ypzx+6jsoaZ0M3TE85MANZbn6XB0lMQ2/0IXnqT3Uq2N3F0Tm0ERpgGezYUmlpaX7/I8RcHtU3fUzus0E1BYuBT9zya7Df+49r6xb9JtnYy9WQulZbcto3J1O1cR3BDesc4vs105z6S/Wxid7H2GX2yDdrrpTV0yZJmDlQ2uOA34iXFhii+DNeYnOw7ukIHAqcS+nzDkkIZDlWV+YKg9y+g9z2W9N678r6Q8afBg4ZeWxqKPGQw/nT+oPwlCxYsaN27KjPwnBznY7GgyYwyeGqeilEc0d31HROGMgTWpk07DjEskvKwK20eQdxMHIb3jW7g7uWQ0jnyuNVwSMZNtm/pceXTerHY8qkEN95paFjUbLkhNcgIAuPnr1iPjmd/MOOAW3MG7zgDOaCuRgJz7RcXcec/JUx+QfEjjWucBh4RBiMh+09MiNOcli3lYUMR8sByA9gslonFr+vw+3s6INAx6flgIxb/IWy7PouHeC/TicDaCxJ7B7BSMZNx8SBa63jz2ANF/1aFPhZfiNCzsPahW72NZYLfhnmUxZlUu8C1O1q3/rk30XbOLVy6cBPCktaB69jPSnu4yFv3aLDSgYW6tpJHp3HybMEUR6pGQpFzkE/QVvgdchJdByUcJa92GiXkyrS1Ao8euf14JsO4/Dn8vngb+xEIKCdy+Y3EdOQnAPcnWzZtS0RC0RUIu/uUGWILJpFYMeQD0M84xuI5kmwBedUbXmKfffIae6uQznPYLMCyRxAegmkjsICndcKHKU1yW8YbF9SDksVysvgEmwF5RGA5CWoaZMk8WehmjpjNHl79/qipBjMuw9PGw/kSewANqQJwyV9SNL/pHz3USOUwxwLHeSIh7oCQgakI6qXtVuRj3NDLeTpFCFhGAN6YH6yaWfgACOzzLDf2QAPMCX60fOa4uzoIew9o7L6KWGCkkioC4XDkQpBXD0MOkVepgumx9nhBOsDH/E9hUlrgMdUdUVd6HWI5rdyOMExmb4VHyHY7bftqg0n0+33V6XpecGaLIOkqx4nvmAhbn8yZ7A0n+lZNhgxTE4JLEspOebOurlqGzTlfbFxjUMKfaElkNH8eyLM4yBmZU6FXNskGYJj7swNAKkwBeSW9Yo7uIMmSDTNc14MHlw1VUm9iI/8VzGZpC2mz84xA6E7aCDYrIxCNRuXug0qESCSYoSRGVvDM5rp8NjN35ckyTfMo3CcPAY+YBpjg8cIe4m1sohvkFbxk90dY90I8s+8BVm6RV3IYVmgwFmSCggjAS3821NqhoGpOqFTgZ3GZ64tKBwJEYKV4KYC8+ilumrshhrBMEUuvNsek7Zh4q/mYG7tzKY4JIocMhCPZKmviIv5XWy2TaARyzLp3DGOH2szpk4RG1qrYmDwn4jz+jrVevFF78KB9LwEpMs6Wtga/Bu2cddHYpYjPtHONMWG0h6rukpKR/6vrqxehY/m7pU4RbLU6ysB3zLCek8lIH0GEBVk20RJegm2rra1daalNmionEjYIe3d0+5zCB90BNhNSxz6y5lV4ZpyTiPnH4H65ATp8lgk9HOhzBXLETZe2FFU2OWoDFl/9pcHoZYaIvw6CbKoDuvYqAuOwvNcKdJIQsInAmPZwWqHWe41NW7ptxsVFK88utvcu3K1Abx8k0sX++MHVNnI7yKtb7IugltogwNmMdWvW/0obe5IwBC89ctfBI5KoulcVEDQ3NjQ07NjrhGMHuB1yIWfowKFOhFWlZEU4HB4AwmasNSH8Q3fxtKaNU7XbsWDiKnvy+NLa2sVP2Wvbdyu/32/nGoPDohqhqv239vsJJhOv9m1pmmpw3pimnpLrRnCrXpCt27dv/yA54anVKj+uvBgSrHlJ7Mx/5Q6Zm5o5MgpwcooiHGmO+4G8rxxBUi0h4ypXrsMOfbP7xVqLMcYX4M/WszsDVpkgle6F3pOlV5nT/ctNpxJtZj3eN36Hv3yn5XcrT1D+q25xoYOOIOAX4lYI2uyIMPWE5BjxxLXqqZUZjYjAsok7tpX9rcz9YbM5NdMQAZAyl0eQP0BD0/Yyqd1TidtNKChWbdz86f17CXXygLDnHZMwMj+REsIvc9vgvdVC4ULL8EEufJK8Gm4BiS+qCi5/6DFXcacgFG8jJH9sVTqeE0qEqj77xrPbGE/IHDHNVm1wp75Y5Y5c61KDweAQtBptrSV/VybJt9bGXu2433p+LtwK6pIzhhoeWMifoi5G9i4VatUJgeGVG7aCyLp3zIFNhwphfgU/s46TQp26S+2jYG/hJSAod1qUeqcmbM/W8LrqhznMbOHjL+EH8pg9z7r7zeDmCnd7IOnZjMCo+Ws+wTWN+bmmhbNvrzxjpPabVCQzekRgJYNSlzqRcNmNOHRZl8P0lRDAbFn8CVvEl+kOxT4Dh8gcOuNt2Ynd5JYtW9Zmq22yjXzWc2C1izZ5xskFPJSten4wYSo8OU12zLrUw+YIkri6tMvhZL/W1zZU/SfZyinUs7OSn/FrbJe9dXV1a7AzoCSxPtl1LFP/CyGaMtV31379zG/9Hkyj9452mzwI68+8rmPmxHf8fqcth5kT+pIMewi058mav+bJMfMaTzANswREkcyTFbcnzfFWMehze+vGfkeDvHrRaemR4yLheJv5CuRej79k8xM6pgae80RgOYYmCeoOgbxY669AYlleXOxOloLHfD7DJzmIrC+YK1GxggB26LgUD+CfW2lDdbMKgYDg/LFgcKrF1XvvYCQT1mMb5J/a0RgvZh/6c405dtpaaYPwLplnwbI3hArhXdgN0fLkGQ9y7TwHDOabjTEcYGXcd9UFHul5RttL5D5EpedDfX3VayCxvgTs5Hb0mSsGX525zvfs2bThEZTOexDeI9JL01IRhk/JZ0RJSUkAhmQ8dFuCaST0e45aukiysPLYh9e8InNLmYZvV56szzMIwwtCGEdCn6s7dlV0TBXcZ/3hdXWbMHg1hGbMg4P7KYTQsUElQd0iID0WMUf5ZbcnNTiI3RxObzyzcIoGpqRkAt65qCSLALZyPxdu+L9Ltj7Vy1oEhvt5vLLjxVw7EBIxIUNnbYV1Yev3G+UuaG6DsrMPGy9KCuxEiB8nywRWggeUnJzaHWfsSjYO4R3fs9de1HYkKbfX3EIrbtjaLIAZRlwZLyxpbn191Vv+hHE0Pr4gv2eicG6uykS/3fWJ3JaW70Ekq0njPWhdP84Ty7qzNdPHcnMHSPIq7Z4g3dgtfP18SmLUja50yGEExj68aq3Mk5XXr6U9TxbEW97JOAWVtsNj5OqiWFNp8fzVjl+D4XDZjLzc/HegnwzJz+S8TyBP4MoUcKKmhEBSCCQCvj+holp5NZPSPKlKXBjsxqRqalwpkw8yT8EK8up0TL7/CqW5pxQnZTOCAF5Ggv1yCm7OSOcudhqJRIbBA/Fym12878/h8222tdzM1k6Egu3XEbpmuT+nGuABY827AruL1dcv0sotX8TZrcDT1qQW4VXXOjUWfckxma3NAiBWKEVgSTurllQ1+XOMLyGM6g/4mvZk31gxXS31UKHgHrRMYAXiPC0EVsfCyIEWcVpbU1OzwWKbtFQ3bHicuqRYY0deO5fEk1gvIDDsvk+2yDxZRQc2HdKRJ6vOZb2r8bw5An3ezitZwsm+SktLB8Pr6h54dT8DuWOclG1LFmfrkSdwu6221IgQsIDAuAdWtmAedpOFJl6rOn3lzNFTvaa0k/oSgZUEmqFQdDrIKznx9iVRnaoQAu0IIBztChCfX9UJDmHy62GPrbAueBZdlw7vq114m8IeuWCYORnbEQu77o3Cj+7QXTYk+b/M25J2wiFJ3SxXw0v34cCgwnLDnQ2eq2moWWyzrY1mCTs5sBiWzzJ2jfVmJO7Plrr6mksFN8JYq3m9t7oOn9sOgiXjebg6bAIHyiZatG8TCMBmi21sVc/PyT8YDS2Ru5ggp4Vcs2OQHbLQTj9JtFEWoyR0pyoOI8BnM7N4Z56sUsGMo3GdOp0nayOeMxcgXLAcfx84rD4rDZZVMNOQv0/nOy3btjzBlttuSw0JAYsIjIk1/Q337bsWm3mmusH5rXiGwMTsLERg9THumFAeBJAeRbVAH1XpNCHQFQFMhPgDodDU/bue8OL39rAuwc6zpztfVldXXWmvrb1WhmHaCwEwzIx5xximYdnzAznX9Jp4mcYdGHFbv00gXq6zd7XYa9XS0iJfyC3nWlPRA6szAnV1VS/U1i8+ihn8K3g/Wtr5nMOfP4e8e5GDS+ZzwLtY5kv5ceXF0GKgNU3aN1FIi/5gqq0/IxQmsOyETFsbmyRrpzUENEmdqJoSCBTPW720PU+Wz3cgZou3Qym5A63tAhlPcT+bJD298NnR5wa85EeWhqP/xCrJY1BwmG0lXWgIW1e4IJZEEgLdIiA9GgU2jer2pB4Hj208q+hUPUyxboWtSYL1brzZQrrfYhv3J6H9Pt60gLRWAIF9DB7/J7Zlz1NAl5RUMOPiZgiwtPK/q0PBhSQWMPdKX8Gk2JZ3DNYzMucdY1jvGy+F2hBYHTt4nmDnKiVC5sYAAEAASURBVAEOz0jixU5bu20QDiHJq5U22h/ogWeCWVu7+EkQWccgaVcENt6LP0k4pVY4W4c52/0gLk7/fNOn+9XWV19QjxxcqQl1rnXMZ9q5/9N2D3LGrYUYAxpgnTb9rI+EaZmQs95H3y3AIihzDfatLdXIBAJjH1q1QiZYR54smfD9cvzmrLKmh1iPEO1vQsapRXOamq217bM2Lw1GzxEJvgyU2Gl91s5EBW4jL2km9KQ+tUGgaH7jI7hPX9XGoK6GJMTNYra9Bd+uorz23e81hdOlL3Za82OrWekxMiFdfVI/miIg2GQfD8jk/xd42UK/6ftZ3B+3lV+orrY27StvLS1bX8jLy7Ps/YZcPDsyNU6tsZz7cnJa/2Gl//6b+6+3Ul/luq2JnLdgv+Uxkza1xWIZCUETPFGOa6afVVxz/bk2PLes9uJIfVFbW1ULSbUVFRUXrVmz4UhmmuV4KTwGxMgE/C9/Iwt66OkznH8Pk703QWK/ibDqhtra2ldQF4fULPF4a1UgELB6DaZO7CULh9/8LRNC5uNMupiJxNqkK6e5ouHnXzJNpMDPcFEZowxDQ913QUDmycKh32Pi+IfV7406mXHjp7iAg12q7fEVxHMl94sfFM5p/nSPEw58kV7+nMXlAsNUB8S5JkII8sByDVwS3C0CuC/FKiygY2OWJ7ut4PWDnE1qeq9wFmNND3vdFKv6Z/ylwarC6aqPxIdyB4OL0tUf9aM/Akgq/p2a+poH9LeULCQECIFsQgCh9gMCbYH8eG68f4fdn4OokmE2yhJV2TQ+ZCshQAi4i8Dqs4oiwhSXYVJ1MnrqvKDxAnJJXF00v2mx0xq0L7S3mhdD7s3wHM93Wr7T8pBMvjy9OSqdtoDkeRWB1bOKsAgnwl7Vvw+9l2+JDTpkYuWytj7qaXWaCKxuhhNuuBfjx+CP3ZyiQ4RAKghsh7fGsXV1dctSEUJtCQFCgBAgBAgBQoAQIATUQuCDbx0wMEdsP9YQxiDMI95wI0G7tDgyJTKZ+fhfsUJwjFoI9KKNYRZjYWN1LzXoFCHgCgIgsKIgsBwnkV1R1o5Qzi8ZM7dROt5kTSECq8tQh0JlxxhMyHAJW7l+uoijr4RAFwT4sh2tW4+lrYS7wEJfCQFCgBAgBAgBQoAQIAR6RABeV/0SreI6hGRfiUr+Hiuqd6Jt5OgR/SsrKxPqqaauRkjKPywej29taGjIWGoLddGxptnqbxUugE/4l6218kzttTm+2IT9Hlq/zTMap6goJXHvBOC0kmmDDCHkjoNEXnXChT46iYCYmJeTf6eTEkkWIUAIEAKEACFACBAChIC+CESD0RBy874C8uqnsNJL5JUclFVEXlm7NktKSvqzBH/CMHInWmtJtbtDwODiahxP62ZS3enh0rGRrfHA/7kkW0mxRGB1GpaW3Na74fI7rtMh+kgIOI8AZ98rDZWd7bxgkkgIEAKEACFACBAChAAhoAsCkshAXt7bsNVBDWw6xIt2IdxnhRf1zpTOGPMAFrv/jhDRIHKHKbFTa6awcKrfwoebX8dmCpY2SXKq73TI4Zxd1VhROCQdfanQBxFYHaMQDkcuZIzPVGFQSIdsQEDcFQyWH5wNlpKNhAAhQAgQAoQAIUAIEALWEAiHy2bk5ea/g1ZX4c+7czbBlluzPKtr8365BffCoWLGThQEeWA5dDnwhCl3Uo87JE41MfsIP79CNaXc0se7D0MHEcEOShOxxeavHRRJogiBvhAo8HHzsWAwmNdXRTpPCBAChAAhQAgQAoQAIZAdCJSWlg6G19U98L55BhaP8bzVnJMHVpKDGAlHf4ldy8/dVR3ea7Y9sD6qGD9olxz6n7HCR5vfBw4PaosFF5euPKt4pLb2dTIs6wms6ZOn53PhqwQmu7b/7gQPfSQEXEXgMB/3E3HqKsQknBAgBAgBQoAQIAQIAW8gUBosq2Cm8S60Pd8bGiejpUkeWEnAVBqMXiwE28OLBmGEk5Jo2m2VQE7bf1fPKvyocVbhPatmja6Qu2R2WzGLDvr95o0wt1VTk/MNM3GNprbtYRaI3ewuWOH4PRC4NLtRIOszioBg36ptqJ6XUR2oc0KAECAECAFCgBAgBAiBjCCAaJABTPgewsTsqxlRwM1ODfPo2trapW524XXZIC5nMi4ehh17OZe0xQP7vvji859atXH1zMI3EYrYmQBrxfVVh0zmz/qY+O/oeTIvFPbmy7KyembRb4H15Zqa3SaYcUjxvNVak8Z73SSaDma3ZoXD5cfhxMXdnqSDhEC6EODsz3AXPzBd3VE/hAAhQAgQAoQAIUAIEALqIIBokPlakleAOJFIUAhhL5da6XHl00CoPIAq3c7Lc31tnUmoXiTteYobbNWeR1gu2KqpuM5uMxl/FZ5Z6xtnFT22albh+Y3nFI7uUlfbr36WuBk4bNHUwByDmbM1tW23Wd3eKLvPavxhxowZudw0/wYTfRqbSaZ5AgH+PNTc4AlVSUlCgBAgBAgBQoAQIAQIAccQiIaiUQg72TGBagna1NDQ8JlaKqmjDRawS5hh/hMa5fSklWDcFoEF36q3epLZcXyYYKIChNY9Is6aOsINf79q1qhpH8w4ILePtp49PWr+mk+QZ0xGYGlZQM59q+ms0YdraVyHUX6djevNti2bt82GW+WhvdWhc4SAywi04sflqtqGxXeiHzxvqBAChAAhQAgQAoQAIUAIZBMCgrNTdX0LxMut1qFMqVynodDU/ZkZfxoyBvQmBwSTfQILjS2U8RivSzkzLs0d3LJ99ayiehBcC+EYthAhaVqFgMZiub8KBNp+AGyGWsDHK1UN0+Q3QNmveUVhq3pmpQdWKFR+BH4ofmwVLKpPCDiFAH4gVmLFpQy5r+QKAJFXTgFLcggBQoAQIAQIAUKAEPAQAkjcfYiH1LWqKhFY3SAWiUSGGSwud5kc0c3pPQ4JLmwRWJyLvjyw9uinyxdsbiamgf+6jTPz5dXfKlyLkMM5Mhn8qlljBnep67mv+1cu38Q5+6XnFE9e4a82zRwdTL66t2pmHYFVXl7uR2yoDB0MeGuoSFttEBDsn4Ec40gktFyijU1kCCFACBAChAAhQAgQAoSAHQTG22nkhTYGZyu8oGc6dZQJ+0WC/wd9Jpn/lh+GutZ8qdBgx+d57+C/OP5SL4Lth9X2sznjj4HQ2oBww5dBaN0mww1fPr/Ek3PqeMAvI2CaUgdHTQkm57epqVnqWmUdgRVvM6Xn1VGpQ0cSCAHLCOzA788F8Lo6vaqqaqPl1tSAECAECAFCgBAgBAgBQkAnBCQxUayTQZ1tEYITgdUJkJKSkgAS9lfikJW56KDyKeWWk6xPWPBhK5LDf9Cpe6c+yvzRJSC0rkK44XPDt67/DGTWkzIZ/PJZIz1zLY97YGUL5mW3OAWKgnKikmBUUK+UVcqqHFihUGg4EPtZyqiRAELAMgL8PWYkzoDX1euWm1IDQoAQIAQIAUKAECAECAHtEIA3zkgkkkC4lqZFcAoh/GJoeV6//L9ivE/84lByn+JGex4sy95CXBhvIY+V2yGqBSCzTgETe4ofe6PBO2s5Pi80kT+rjef9d8LcDzcnZ2X6a31cMPyvIOCkc8v+6e/d/R5BMN6KsXke44H/9ClZRWAZ3H8jhm+gPsPnqCXywv4Q+HwItv4TfN7ABN8Ah9VdF3wejvXDThhDcWgkPkt35wn4y6prCPbaKOIhf45xUVVV7VYbjakJIUAIEAKEACFACBAChICGCBgJY5zQOB5GGLEVGg6bLZPCwbJfMyHOsdOYGwkZRijDDq0VgTxYnFVYa5RybZkM/nyEG56fK1riILRex/enkAz+yTHzVr+iEply9L1LY40zC2djI4WHUrZaTQFHN80qPI3Na5I7XWpTsoZ8QOL2SUyY39dm5FI3JIGHSZ3BxVMmM17Oawm8snDpwk1WxE6cODFnyIAhk4RhlOKBXIYH5HS0L7AiQ/O620H2XVxTX/OA5naSeYQAIUAIEAKEACFACBACFhEQnGvp+dEBgzlw4MCVFiHRsnokVPYTeEL90LZxJp9oq63B3tztimBLQMqNJNdQAtKqhDHzeoQabmhkvEp6Zxl+9nTRnKbmlHtIUUDhQU3zGt8rvALz2MNTFKVkc5OxW0Q5+zevcigfmgJWZg2BhcTtvwLeMmY328sL2O3kgbgZ+NeSJc+vTwWMZcuWtaH9Kx1/dyJBfr9EW+JEsNgXwntLusfieZWthS/jPvObNTU1b2crAmQ3IUAIEAKEACFACBAChEAvCHA2rpezXj+1ZsGCBa1eNyJV/UuD0Vkgr1JKqI25lT0CS7BUdiJM1fTu2g8DFhWYIFYIpJfvCDeEM4X5ZNvn/Wva83Z118rFY3w2M1fP4tcjyu5fLnaTMdHA+qDGUUVnMdb4QMaUcLjjrCAYSoPlX2bcXOAwdl4SZ2Kgn4Kn1B21tVW16VAcMf0HIUnhpehLuspml1eWYH/b0bbt0qVLl25PB9bUByFACBAChAAhQAgQAoSA9xCIBKMPgJz4tvc071tjRHpU19VXl/VdU98akWDkeHjZPQMLc1K0cnttffUAyIBDTfJFzGZG4/uFMgdVfvKtMlYT8yZeD4JrIcINFxbPW700nZogCX095svBdPaZrr5g16qWz/sdlAmC0A0bs4PACkWrAV7EDQDVlylqeYJdXLOk5o1M6BoMBof4eOAX6PsC/OnuAbdVep/V1VXPzQTW1CchQAgQAoQAIUAIEAKEgHcQKNV4jsIFe7Cmofpc74yGs5qGQmXHGEwsglRHFvJN5j+gvn7RR1a1hJfTS2hztNV2Ga/P2TpcQ88h3PBJTCElofW5mzqtnlUUhRfWYjf7yKRsEMqXFc9rujOTOjjVt8ZpA3dCJB8e+JSN5NXniHm+vLa+pixT5JUcgYaGhs+wYnAx8mwdjYDCup2jouG/gr0teOI4Iq80HFsyiRAgBAgBQoAQIAQIAXcQkJsiaVmwqLtCS8OSMCoYLD8A5BWIF2fIK9kl53F7YYQMidy9WATbD6TL2UgG/xhn5gYQcS8jh9Ztq2aNmvby+SUBp00aM68RDi/iOaflqiIPXkvXbvjuvtKLz/NFewILBv7E86Nk0QDc7ItMFj+4tqH692hqydXUYldJV6+vr3qttq46gofQRWjUknRDD1TE6sCf/blGSV1d3TIPqEsqEgKEACFACBAChAAhQAhkGAGZOxYqyJ29NS18uaaG9WpWJBIZaXBTEiEjeq1o8aTB+CSLTXZW54Y3Caw9jZVRPCWY417FmfHc8K3rPwOZ9STC/s5fPmtk8Z5VU/hmGj9Da3SjZRm2oyXvMh0s05rAikaj43ANnqbDQCVpg7zh7mxp3fbl+vr6j5Nsk85qoqZ+8d2GYCF0qsOP2hYkq58F9+gfVFVVaUXKpfOioL4IAUKAECAECAFCgBDINgRaW9lY2KzvXMzgK7JtTKdMmTLQTPCn4e0ix9bRgtxQ9jyw1Evk7gQuBZj0ngKc7/Ez30p4Z30EQuueVbNGV3zwrQMG2u1gzCONL6Pt43bbq99OXNF0zuih6uvZu4b6PjRht5lgP8Z/uudd2jXCbXDVPRPhepcheXhs10EV/69uqH6VGSZisflTKuqXnE58KWLRj6xtWDw/ufpUixAgBAgBQoAQIAQIAUKAENiJgGGY43XGQoiYDovVSQ/RxIkTcwK+3L+DVDky6UZWKgpuj8Ay2ZtWuvFo3fEgtM6X4Ya5ouVj5LN6rnFm4ZVNZ40+HMcxJMkXwY2fo7YSEUzJa510zUGJBL8q6dqKVrQ0oIra0K1acMstiLea63DJ5ndbQa+DrZyJ02vqa572mFkGklfeDZ3P95DeAisgfxw4qOBK2hrYQ6NGqhIChAAhQAgQAoQAIaAQAuFw5BIu+B8UUslJVVqwqN4fAsEfZEUxSsPRR2BthYvWtvpzjAJEfcSt9gEPpU/QxvOeN1bt7qi/AcRWFZLBLzT87OmiOU3NfckB+VUJx5Bv9FXPo+dbDC4mFM5tbvKo/szvVcX70jvehtDBLCGvmMEramqrvUZeySE08eN2YSQc3QxW6Iq+xlSB85vxMDuvrq7mMQV0IRUIAUKAECAECAFCgBAgBDyKAHKojvOo6smovQKVsoW8YliQ/43L5JXEPBdhpwfg/3flF4tF5umNWmyjS/VhcD6ogNdOhQD1BzLvbXx+0mTmwrbP+9dMWPBha1dDORc3C8ZPx3EdnX36YXO1a2HbhV3t9sp3fUMIuTnLK4OQgp64/nhFbe3iJ1OQkemmoqau+kooMTvTivTav2BL/KZxOHYZJPKqV6DoJCFACBAChAAhQAgQAoRAnwhwri2BhVm/JLCyooC8ugaGpiU5tp8n7IURsqwII0z2ejsUzGp7MvjcwS2fyXBDJIO/atWsMSW7BBTOa34N3NXzu75r978Q32s+a9RBXrVLSw8s7P4wTCT4NK8OigW9b/Q4ebXbVHhi3VAaisDVmKu2a6RcPfrD55s/vXLZsmVtuxWmD4QAIUAIEAKEACFACBAChIBdBARHDixNnZSEFps19TmykVDkLIzgL/qs6FAFeAXJnQj/YVkcF29h4ynLzbKgAeaeYhqQAW9gSu+sFYzzZ5Ga5784fhcihHTlE/wJ07gO4/stL46xnh5YCXYmBkNLcu6Li4w/BdInbQ/ML/p171Ntfc3VcNSc414PliVvwgPsm8D5MiKvLGNHDQgBQoAQIAQIAUKAECAEekRAaOuBJThf0aPZmpwAeXUyCKX7YU76mCHObHlgCdP3liawu23GOCbEBSCu/ok/3aNuzmg6Y/SBbgPqhnw9CSzGZ7oBlkIyt8YS/u9DH912SBCfb/z0PKxkLMo41pzVIdHfYUiM//eM60IKEAKEACFACBAChAAhQAhogwA2m9oXxgzUxqCuhgi9QwgjwcixQvBHYXZ6HSZMewRWPO5/E7piikXFAgLpHVsLijlU1Wca3tyRUDsCqz18kLHjHBpYVcX8esmS59erqlwqeklPp7zWnK9DxvupyEmhLRZT2G3+gFFeXV3dmIIcakoIEAKEACFACBAChAAhQAjshUCiNTF+r4M6HfAllutkTmdbolOiE+Bh9iTmC+nf6Z6zA2fMmJHbWZ9kPu9fuXwT6vW5+14ysqiORghwdvaKM8eO9ZpF2hFYIm6UYxDS58qZ/hH/WPDEr9Pfbfp6XLh04SZkp5c7P2xPX6/tPX2C8PBTauuqf2pni9o060rdEQKEACFACBAChAAhQAh4EQHOtCawYrGYliGE4XB4lOkTz+GSG56hy86/beM2u2Ff0guLCiHQGYGAzxeTm6l5qmhHYDFufslTI2BRWSHEn+vq6rZYbOa56vX1VW+BTDo/jYovTgj/Edhl8Jk09kldEQKEACFACBAChAAhQAhkGwLc0JnA+mTJkiWbdRvSaSXTBnHhxzyBF2fSNsGFvTxYnFEerEwOnKp9C/7d1WcWjVJVve700o/AYlxrAosZpu4J5XZfpyCT5iJa+2+7D7jzwQQpeOPI0SOOb2hYRK617mBMUgkBQoAQIAQIAUKAECAEOhAwBRunKxgIg9HO+wo5y/q15LY9iTRSh2d63JDrxBaBBd2XZVp36l9JBPoJn7hASc16UEorAgv5r0bCzoN7sFWHw2/B+yqrHj472rZdih/CD10avA1ciJPqGmqur6ysTLjUB4klBAgBQoAQIAQIAUKAECAEdiOAXa61JbCwe5tWBFZFRYUvHjPnYfAiuwcwox/4JFvdC9qJ0BZuWdCIC3bey+eXBLxiqlYElohr7n3FxLNeubCc0nPp0qXbQWBJVlg4JbNdDhcLY4nAYTUNNf91VC4JIwQIAUKAECAECAFCgBAgBHpDQGicA8tgWiVwX9O87reYhZzW23Cm95yYbKe/QEH8HbTTbQd7O1BQm70RGDli2/pT9j6s5hG9CCzGj1ATZme04sx41xlJ3pJSXV+9CGn573VIa+lpdcPIUft9WdedHB3CicQQAoQAIUAIEAKEACFACDiMAMLR/HivLXJYrDriBNfGA6s0FL2eM/5/6oDbrsk4JJMfYFWnUfeukZtjaTM2Vu2n+r0jAM/Js3qvoc5ZrQgsw2ZSO3WGow9NhPl+HzW0PR2Lt/4Exq1O0cD12PZ2Rm199WwKGUwRSWpOCBAChAAhQAgQAoQAIWAZgbY2oxiN/JYbeqWBybXwwIqEys4D5LMVhJ2jHGpLL0F5sGzhlh2NTl5x7th9vGCqVgQWmMNDvAC6XR2RYC1rWXO5mwnIpwvtYgfX3wXcJw6rq1sst76lQggQAoQAIUAIEAKEACFACKQdAcM0tc1/JcE0DcPz85XS0rJTBRN3pf3iSLJDLvhhSVbdsxo3aCfCPRGhb18gkGvEYl/94qu6n7QhsKZPnp4Pd1y5oqFtMU2zRVvjkjAM5NMCJJl7MImqnavE8eXq2obqk2tqajZ0PkGfCQFCgBAgBAgBQoAQIAQIgbQiYIjxae0vvZ0lWls3pRoxkV6Nu/QWDpcfx0zxCA4r6yUnbBJY2Dzg7S7m0ldCYDcCmGd/efcXhT9oQ2BtH7hd7j6ojT3dXTNwF1X2Qdqdvm4ca00Efgy5yRJRqw3ByhAyeDvaCDf0IZmEACFACBAChAAhQAgQAoRA0ghwjXcgZKwRGzDFksZCsYrILTWRC/NpqNVfMdX2VEfYS+TODUEeWHsiSd/2QICfKCqYb49DCn7RhhDhJj9Ed4bCiBv74hpao+B1lDaVXnzx+U/D4eiVYIgf6LVTwZ5MsNi5tQ0Nn/Vaj04SAhYQmFYybdD23HiRjyWKTcELOWf7YhVsqMHEEDx/hoBCHwKqNA8id8WQF+Bz121ppSflDtkt2mzCf5/LP6yKyWv1c8hchxON+FuNtb9GeA6uxXEqhAAhkCEEkHC5oLWVFfpZYoRp4L4XfATu3uH4G8g4z0f6gnzOxSAmuLzf8zv+OmnLt+CL9AZGMXHvc9z3YjPabsZ9vlH+of06YfqahC/WCG/r1Q0NDe3PiJ1t6F9CgBDQCgETOxBii21Ni2fzXwWDU0dzEX8G4zJE+bHh3NZOhDs+zXs3d3CL/D3ShgNQfqy8peDgVbmjDgfd8IrKamt08Rqj2qeDKqOdqm5G+5a7b6Qqxuvt6+qq54RD0XPw2z+1G1vkQ/lmhAzeiP9pq9huAKJDvSOAyeo+8Xj8oJ2kOIdnJz8ILSbg+VLUwtoGSjdPgTdPEE3tBRNPfO8ouz/sOtD7/3u+v+78hsnwziK/Ys9M7IDTCh1WMpl4k7O3BWdvCWEsa23d8p6XVzl7R4bOEgJpRcAoP658TMwnJuB2lvf6gbipD8T9Ng7/F8XbzHwf7sf2+779/ux0k+Jj+52LG7Pnsqu+rLGrXrvAnU3aP+Ifw2Rc+JiP++R9Lz2NG1F/uRDmG9iF+C2T+96or1+0Asfpt20ncvQvIeBNBHj7+7w3de9DazxD5TPKc0UuULYYbc/gQT/GI8oPiUQiI60uck5Y8GHrqlmFH+EXR77bUiEE9kLAMH1TcJAIrL2QceGA4GIwHjpaFyQxByPK/qW1kckZJ3wmu8Q02GuonrO7CX404cVyZk1DzYu7j9EHQqAXBKLRaJGIi6NMwY5CiG4Jqh6JySrIcPhU7W73xafdh9L7IRdT54Mw75UvG1/HyyE+miwvNz9WGoy+wg3WIExen2C++oaGRc3pVY16IwS8hcDEiRNzhgwYMgkO8keBLD4KXlNH4YaaHGdmnry3dhe83beXXf/vPpG2D8PQE/6EfDZ9Q9JnBpy4QGxtxcdlUOtVsF113M8XV1dXg+iiQggQAl5BAPfvuM6PG6/onZSe3HsEVjAYzGvhrU/h98CWV1NSuLhQKZFoT+S+1qpoXH/L0IYILKvAZU198xiYerfK5mrjgYUwnn1BXqiMdeq6CVEOITekLsj7EqpfqH4HL/J3wJJrpDUY+Se4z/xOTW2tDMeiQgjshYCcuA4dOPRoYYgwCJ8IJq1TzDhDGNAX3lR7NVL7QEDagEn4FExkL/ftnNyuxt3wPMju/3BuPldL94PaI0jauY5AaWnpYMZ8pUjIW4bOIvg7Ar8XObtfF/Am77FS0H7fM9z3jF8o4HMMj+SV8AitBq+9mPnMKtz3ng3h8dhYkLqEgGUEpkyZMhDPoKGWG3qlgeCeev5UVFT41jatfxjwlnoF4l16IiJA7kT47K7vyf4vPfmxYPP1ZOtTvWxDwOYOl2mESRsCiwsxBC91ehfOQ8cee/xQmQdKb0OTsy4hYjf7WOA0EBJ319XV/DG5VlQrixAwsJPMUUjGeSJsPgF/xyLuJg8rbJKz0rXA9Z1/By8m32HCSIDkXQJDF2AzgyeqG6rf1NVososQ2IVASUlJ/7ycvKmMG7jneRmIK7zgCxn5q23B42wsCLmxeK6dg/3r4aVVtkww8wn4bP2rvn7xyzAc82UqhAAhoAICuUbu/ngX0bYIg6/wkHEc5NU9eHZ6kszBu54ksCwXLNtiJ0L6WbAMXPY0GK+6qdoQWHj46Lua8cVVlJPjj5+Br3d9cSh7P8kkt/CqOXLZsmVt2YsCWd4ZAZm/KhYzT8aE7iT8Np/AhCnDcLK1yF1EQvLP5OwXCDd8mxv8UcETj8BD4/1sBYXs1g+BUGhqMTZWOAkv5KfglfxLsFBupICSrS/oYiImKPgTPwOJLcOKn8Ai3z8RXv8/fNZ57iwHnYr6CBjwjBwk1Uwkcvr7fG25ppnDDaNt1+YnKVsghNiK0Nsed8KLxXK3BQKt3b47+v3+LVVVVTKfqislYbBxIB60LUK0LfeKcXg+/gK6fs8r+nbVE+uxtggsRCG8xXW+CLsCRd+tIjBk1awxg4vnrVY2qgnzPD0KHkIyubmtG9ljCLxfW199CHSml1CPDRyp6w4CoVBouMECX8NkVa6gycnrF3nR3OnS81Lx7vwqksLPMVl8DojgzzxvEBmQdQgEg+UH+Lh5JhavKsBTeSpvSeYGS6yCV9r9JvM/gGTw+EyFEHAGASwe+RM7EofC++YILJSMhefjMPg9job04bg/R+J/hPK279Cp/O8z9lI4VKapgL6ulHAwegVCfmUKDP2KYNuwiZLcjVX5Eg5HLsSOskrn+UkCxFZ/jlFglXB9+fySwPCt67dCvvL3YxIYUBUXEEgI85Bx89e864JoR0Tq44GVPduBHghPijPxAzHPkSuAhBACHkQAL8sF8LQ6HQtIZ0P9cpBX0tuISpIIYOXiSGyjeCRCcG8tDUcfwwv7PQgxrE+yOVUjBDKCALw2xoiE8U1M/uCJbB7droTGngzOg8yLIXM2ksFfh0W/5+GhdV/BoILHFyxYgJ1OqRACySOAe3E8Jv9TmclL4AVyFDY/mYztM/tJCfB+Ak8qPyQvT6GaIsZjK93UB8+vcW7Kz6hszjzhfRUJRb6K3Mk6pB7JbW1lB2DMLRENR9+7NLZ6VuEHaDcxo9cLda4sAj7DN0BZ5aCYTgQWNpzPksLZbcjz8a+lS5duzxKLyUxCQCJglB5XPpUZiXPirebX8RKYT7CkjEA/TDLOQYjhOZjQvomwoz8UDOo/hya0KeNKAhxCAGR1P3m/YzZ8HibLZbjv5dSYSmoIyJxgJwjGT9iyadt6eCL8PhDw3Y1V/I2piaXWuiLQnuh67dojkGPtVLBTp8DDqqSdn9Lvblwr01O4Oo5cjG/PxelqJ5kRjsthRWZ6Tr7XSDBShmffI2ihxcKnj8k8j9YIrHa0OF8GtpkIrOQvnayqiTyaA1U2WCMCi4PA8uZyj40LpKh/Tv7taPd/NtpSE0LAUwhgArsPJrDfxk57uN7N/duXdvV7aVZhTA4TTNyLCe1NILPuhlv672hCq8KwZKcOCBE8GCGC58Kz43ugrPbd6dKRnVi4bPUIeNLcApxlvqz7DD/7VXV1daPLfZJ4byDAo6FoxGTi+2ub14O4MjpyVGn8rs3TQMAIrnyCZNuXp+IeWKFQ+SRMzB+Hfe3egrbtVKghN9rT51RaVYmbYpnc04gKIdAtAnBR7Pa4Igc1IrCwh3wWFVxWF8MF9j819TVPZ5HZZGoWIRAKlQUNLi7BxOp0TGBzaQKbtsEfjp6uB+6XYkJ7VweR9UnaeqeOshYB6eWxrnndaYLzy7EBQzhrgciM4TJvzaVmnF1YGorMNfz8FyCylPemyAxUeveK8MDBzPRVYFH4EiRbhXeH0vMYZwdDCLdD4KT3Y7GzSqsjDXNeZZ8Z5VPKC+PMfAZoyXxs2hRE7OIetVE4e8tGK2qSLQhw5q4naoo4akNgIZeDqfGaUHfDjPQ//GGsUh/T0FD1YXcV6Bgh4EEEsDtR2cm4nS+Fa/O07HGqVHKk5EveNSCyLgOR9adYovWWJUuWbFZSU1LK0wjInHbxNjFrbfPHP8Jk+SC67zM6nEjqy78DIuss3PdI+B7/eX19/ccZ1Yg6TwsCIK4O56bxU2Gy00BeZWVyZ5ABrhIwIFFGgUTBgpymxXAXP7uo4TdmX/zGLET7Irsy1G1n2iKwDMNcljAln0qFENgbAZFgSqcp0obAAvRZ5YHVcantgxCLf06fPD347BvPbtv78qMjhIA3EJgxY0bu5o3bzkV+mx8jt8aErFrxVX+IpGfGVQF/7rcjobIbt7du/Svy7/W4Pbn65pCGqiAQiURGIq/Vj0CSngedBqmiF+nRjkAA/55vMH9FJBy51Rfw/QEhxS2EjX4IRKZEJgs/vxZ7W38DC8FZ5G7VzVga3FUPrISR2JkGoZuudTgkRNxV/OxghJzB/fEb8wTaHmSnvfpt+BjoKO9bS34co1rXfNgYKJTPdG3CKdUfK+9oaAif0gvW2lCvgotN3rksHNX0sO35LXMgMbtfOhyFlISlCwFJXGFXzYuRd+lDkFd/Rr8gr6goiYBg+yFH1l15ufnLwuHoV5TUkZTyBAKSuIqEo78VCf4RPB6ugNJEXqk7coMRFvTLeFvi3dJg2Ux11STNrCKAZNbHwsvuKeHjr2Hqi5BBeo/0ueyBBYTHWR0nD9UX+VvyV6qkL8irQP/cfJkfKqSSXg7rEoAjQ3+rMnklS+C+f89qO6qfFQiYrZtzm1S2VBsCCzfhWpWBdlU3zr5eGir7oat9kHBCwEEEJHGFna8uAXH1EV7o5FbGhQ6KJ1HuIjAB8ctPgHj8d/lx5WPd7Yqk64QAiKthmDDfBuLqQxBXl8O2PJ3s09sWXoyNNOaVhiML6L739kiXH1O+H/KczUGuuRdgycn4owXQjiGNCf9Hro4uN8a7Kj+Twjlbr1g0CM/L7X8P3JJOyiQsaej7Y9u4c7YsDfpRF95DoHnCgg9bVVZbGwILD6jsJbDarzDxy1AoOl3li410IwSAAMcqfgWIq7ex89Uf8H00oeJRBDg7NW6Yb4OQmC0JSY9aQWqnAYFpJdMGdRBXq9DdVfizvFqcBjWpi2QQEPzLcW6+FQ5GLpdJ95NpQnXUQAB5gPxYeLgsHjDfxU/x2dCKiKs9h6aloWGRq3MJJOsdt2eX+nzDwtYKlawpDUdvwSX+HZV0ckcXIcMjbRVEL1Eid1vIad9IuVDgrohrQ2DhZ9jVH52uwCn43YfBfCgajWqYoFBBtEklywggXOF4TGJfxir+Y2is7yqkZWQ83UB60Fy/ZdP210tLy0s9bQkp7zgCMnwD3sHnt+S2yTAFSVyRx5XjKGdAIGf5nPPfrmle/xISf5dkQAPq0iIC+P0tQx6gV/Gu/Ds0pZDdbvHjkmA3uz3l0EFsOKXtuw92R1eGwJJELSJzrnZo2FQWs5EZ4ia7Chomf9VuW2qnMwJiqerWaUNgGdkcQvjFVTY8EWdPIBY6/4tD9IkQyCwCmOAcGAlFn0a4gtwB5qjMakO9u4OAOIiZ5mLkNboDq/yUENQdkD0lNRKKnC7zpSGv7D1QfISnlCdlk0IA7jtHMtNoCAejMo8ZvlJRDYH2PJMybJfzRdBtkmr6KaWPEOnwOhinlM1OKqOIBxZydJ6Bp9FvnDRNUVlxLsSZtbW1q+3q1y+vpQ5tZSJ3KoTAbgQQIVO/+4uiH7QhsAB2tntgtV9i8oWyI6m7NmOr6L1DavWBgNz5RYaXYYLzRhbkIOgDjaw4bciE3PFWc2k4XH50VlhMRu6FQHRKdALu+2cF43/HSdqUYS+EtDsQwAYcdyA31rMyt5J21nnYIOScOxTh+jLPlfR+pHfCvsbSYK4SWMFgUHqg6nuPCHfx62v45PlwuOxLCGV8EB91v96xpw67oKah5r/J4NJTnWH3fbIF88bbejpPx7MTgYTPRwRWuoYeW9OuTFdfyveDpO7hUOQXyutJCmqLALwvzoT3xfsw8Hr8UX4kbUe6G8M4O5QLswEkxvWUI6cbfDQ9JCdnkrA2fexNmHiCpmaSWT0hIPg05FZ6nXJx9gRQWo9zGbqLzRJeQq9HpLVnL3fmsgeRYbQncAdfoGnxGa4SgH2hFg1GD4NH0j9RT/d3TmwMKy6qbai+ry9MkjlfNK/pBjjQXgRv6ZXJ1Kc6miMg2OtjH16lvFOQNgx1XV3dGvwqfKr5ZZW0eZzxn+IFRibppEIIpA2BcDg8Ctfd4/C+mI9OKUF72pBXriM/NJqNHDmL5DWhnHakkKMIIGTjKz7ufwdCibB2FFnPCRuOl8pnkOD9BiKvMzN2U6ZMGYjf4H93hO7SZgkWhsHtHE6c+8dbUMdzVU3TyFgOLKSqGG8a7FmAto/ngLOoMOZ3V9fV1fzZYrNeq4+Z13h30YHN+wtulmIufTty1crfcyrZiADn//CC2doQWBJshCnRbgpfXHV4Bom/ysSdXxyiT4SAawi0r/hy4XsX193XXOuFBHsKATyEorgmXoNbP3nkeGrkklM2FAoNx2S5EiEb2AWJFyfXimppjoAPCd6vW9u8/gmQ1wM0t1Up8+QkPuDrh9APcYpSinlEGc7Nj1xVNaFvAnfgFhs9emiTq/j1IBx5N/dlpu8ZTAL1Dc/8wvbZNfWLf/nFV+c+cST8KJ67pg4eWVePmdt8qOnzjce8+gK8xz2FXtqc64kkqYwA8iUSgZXuAUJA8Bvp7lPx/nJwIf49FJq6v+J6knoeRkAmaUfoUC1emmWyZpqweHgsXVJ9GNz6F+AauQbytVo0cQkvT4gtDZZVGMyPRSPxDU8oTEqmG4GTQV7Xlx9XPjbdHWdjf5HjImGZUB/348RstN8Jm2Ox2Aon5PQog7NxPZ7z+AmQHKsqKysT6TZD5lrF7ppP4ro/KN19Z6C/39fWV9+Qrn7HPrRqRfG8pntBaJ2a44sNEcL8Csb5IfT/ebp0oH7SjsDS4rmr3057rzY61GoywZlBHlh7XwT7Giz++LSSabRt8t7Y0JEUEcBWxefgpXkpxIRSFEXN9UbAB/NuKg1H/067pHp7oEFYDy4NReYgxOAxWDLM29aQ9i4jMClumC/BAzPicj9ZLT4SKjtPGPx/AGF4VgORgvGYmH+6ZMmSzSmI6LMp+hjXZyXvVkh7/iuQVwHkWpU5r47zLmzJai7uB3n1w2RrO11vv4fWbyuev+ZJkFnnFMWahglhRHA9U6ih00BnWB686X+XYRWS7l4rAgveRuSB1f3QH9aS2/aPiRMn5nR/mo4SAtYQmDLl+BEgr/6NrYofRMsCa62pdtYiINhp2wta66LRaFHWYuBhw7E5w8kgrBEmzM/2sBmkenoR2BcemM/CY29mervNjt7g2XoVog/uhbWB7LDYNStdJ2AQjjXeNe0zLNjt/GHdmMf75+T/BcdP7OacVoeQU/bh2vqa78MoXEKZL7ySJYrnr67dFWoomLE/FLsc7wULoV0s8xqSBnYQwBh+3LKxX6WdtplooxWBNXBg3qsAcUcmgPRAn8cPHjTkAegJ0pwKIWAfgdLSMulOvAxX0qn2pVDL7EVAHG7GWT12DDoyezHwluVy8SMcLPsNXqQRqkFeHt4aPSW07QePvbnhYPQKJbTRRAm56ydMuU0TczJthusEFgwcm2kjXevf5R0cu+qNa/8OkGbf7npcv+/8X4Ec/h3YZapqW/G81csRavh7JII/wfCLkSDUv4mJpgw13KSqzqRXNwhwceuEBR+2dnNGyUNaEVgLFixoxUtSnZJIK6EUn4mH/o1KqEJKeA4B6a6N6+dXzBRPgKkf6jkDSGGVECg0Oatu9+hRSSvSZS8EZA6jwYOGLuZcyPAFWgDZCyE6kCQCyO3O7sBvCBEuSQLWSzUuCWWcv76XOnTKCgKCu0pgSa91qKOvt7rL+HUeyg4i/Medj2n6+bkBg/qfWVVVFfeKfYVzmj8tntdc2R5quKZp345Qwzuh/2qv2JCdeoqVbZ/l3e0l27UisCTwmFgv8tIAZEDXa7Fr1EUZ6Je69DACMuQrr1/+/2CCfGmgSayHx1Ih1Qvg0fNEex41hZQiVb5AAGMzCzmMZGh+FuQY+cJu+uQqAldFwtE70AP9jtiD2UAuwbs7CGV7EqjV3ghwtmLvg84d8fni452Tpp4k5GBzFb9dFstQZBDht+/6rvH/9f239jut3THDo0byKhbvCDW8bMy8pmKDCXjd8+tgzkv4w3SdiioIcMav9ZL3lcRNOwLLMNnzqlwQ6uoh7oTnw1fV1Y80UwmBSDByIkK+XsPPTVglvUgXLRDwYRp7XyQckfkdqCiCALYl97d7ynA2FyrRzqKKjIsuagjBrpAkDOzR7h3U7TEC+fdr/BZf4HY/2SZfmO4SMCActSawTLPVVQ82eT1GQ9GpiLK5Hx+1fm6A2XnVn2Oc/Owbz27T6T4snNf8GsIMfwEy69hALD4CoYbfBnFSCXu36GSn12zBStLzhfOa5nlNb+0eAvsV7id3RNvotYFIs74+mRQwHC4/Os39UnceQwAeGJdhc4SnofYQj6lO6noHAZ8Q/F4QJtkQEqD8qIRCoeHYllwmY71KeWVJQe8iABImHCr7W0VFhdyhlEoSCMjQKZB/SJZMxXEE/HF3CRhTawJrU0NDw2eOj0kngXK+YjL2BA7ldjqs48c3Y/HACQgb1HoeO7Jy3QaEGs4pmtf4TSPGQGaZJ4BIuRPkfLOOg6qwTZt9fvO7wN5zHnHaEViVlZUJDMMihS8WVVQr4MJ8OjolOkEVhUgPdRCYPnl6fiQUfQTeMb+DVjTBUGdodNVEhhP9CiQWkSYZHGGZWN9gvhehQlkG1aCuswQBzsS565rW/w3myvufSi8IhMPRM7IkdKoXFFw7Fd+xY0eja9IhGGM3zk35mZSNma+r5F8oNHV/zFeego365hDbOYAfcJ848cUXn/80k+OZ7r6LKpt2FM9bsxB5sy4rmt9UhJvlWPApN2Eu/3q6dcm6/gS/fNScNau9aLd2BJYcBGGwx7w4GBnQebjpY8/TlvYZQF7hLuX1sL2gtQ4vJWcorCappicCt1GOvswMLMLKz0Ji/XpMtYozowH1mo0IyJ3EEE54SzbanqzNCOMv44I9iPpavrMni4Nr9QRrXLp0acw1+VKw0JfAwrW5wi3sIpHIMIPFF0D+CLf6UERuo8n8J9TU1KxVRJ+MqIGVDDFmbuNLY+Y1/3zM/KYj4iwxFnORC3BcEphtGVFK2075n8fMb7zfq+Zp+WPY0rLtSQzIVq8OSpr1LkJ+o2dKS0sHp7lf6k5BBCJTIpNxPWAnT3G4guqRSlmBgPgjvA2+lxWmKmJke6gw43OgTj9FVCI1sgkBwa5GHrwrs8nkZG2VXvII48+G0KlkIXG8HkhU1wiY3cpyPn73Z80+cMMdD6xwODxAJPh/AJfukSLrBU+cUF+/aJVml0bK5oyft3ZV8byme+GddWoixz+CCT4L85NHIXhTysKzWAA8Quu3xAZe5mUItCSwsJKyHRe4JLGoJIfAJGYaz5SUlPRPrjrV0hEBmaxd+HgNbCvS0T6yyTMIIN8tuwe7DVV4RmOPKtqerD0c/XNHqDAWOakQAplBAHnwbqfNHPbEHvdnv4SPycnaoD3P0DcnEUAo60dOyusqa+LEiTk4NrrrcV2+4951nACUmBnC93dgdJQuOPVgxycgr46vq6t7r4fzdLgDgXEPrNwIj6H58M46syjWNFQII4KXFrkj5QcEUvIIwKPtvZgZ+PrEymWe9mjTksCSw4iLWv7oU0kegePycvIfkROa5JtQTV0QiITKftCRrH2gLjaRHZ5GALsTiofC4bKIp61QWPlpJdMGxWOJBQhtoR3NFB6nLFKNYyL8ZxDXp2WRzb2aGm81/4h32SN7rUQnU0bAbQ+soQVDi6GktrlEXcCPDx405K+YaE9PeXDVFrBJcGMGyKtlaqupnna8kiWK56+uhWfW1djV8ECQWZNwvVyN2T8iSPBWQ6UnBD4Qhu9L4+evWN9TBa8c15bAKhhUIN1OP/fKQCihJ2enxtrE3dCFVuKVGJD0KCETZ2M727vQm7YvWOlBknpxGIFcQ4jHg8HyAxyWm/Xiyo8p36+lX1s13PGnZT0YBIBKCEjieh68gZHEN7sLwnpn4U2MQqnTcBkYLuZwkuoLQ+sdCGGhszs4RsLR32AacnYahj6TXWzHovGpdXVVL2dSCV36Bpm1DKGGt4+Z11jqM81ivNtcDNuexZ+nvYwcHp83uZ99aezDq7TIs6YtgbVgwYJW/Gzc7/Dgay8OrtTfB6HxW+0NJQMlAhxj/Sv8fxvBQQioiACW0Yb6uPkkPEP3UVE/L+qEfIdj4gFzMdYoJ3tRf9JZewT6CYM/kc2by4RC5ZNAXv1F+5FWxUDhTg6n3eZxY/zuz/p9EIFAYJVTZoXDkZ8KwS53Sp6ictrAap5eV7dYpuyg4jACox9Z04hQw7vgmXWiv8AcLIT5FXhl3Iv3yY8d7soz4mD/87FYTqRoTlOzZ5TuQ1FtCSxpt8kCd+K/RB8Y0Om9EbgMxMY1ex+mI7og0J77JhR5EPb8WBebyA5tETg43mZSeLMDwwvyajxLGFUQdaAD4kgEIeAOAoLtl4izJ6ZPnp7vTgfqSpW/zQYTD0BDykmapmHy5fqWu9mVqfEOhMBtTVVVVYsT+GHzlm9xwW92QpbCMmLM4N+obaiSUUJUXEZg1L1rthfPX/MkQg0vGLOmabQpxPEgc36Pble43LU64rm4a33BiBn7Vy7XKvG91gSW3NEBjKvcepOKdQRuQkLVH1pvRi1URwDJ+gPxNjE/C1y0VR8K0i95BE4EiUWegsnjtVdNkFeHY7OOenh2jNvrJB0gBBRDAJOMI7fnt9wHtfAxe0qiTfwI0QMl2WNxxi3dAgLmE1e14FqHEDpC/oG8OgmbtzyAcdD5fk8gtO3btbWLaZMxV2+47oXzKhYfO795Ecisy+GdNV4wY39wBPD20zZv1ibG+Zlj5jZffPS9S2Pdo+Ldo1oTWO3DwrlkWqnYQAAJVX+NPAzftdGUmiiKQEVFhS8vt/+DeEH+hqIqklqEQE8I/CgSiny1p5N0vGcEosHokSCv/ocaI3quRWcIAcUQ4OybeAe5VDGtXFOn/LjysUKI61zrgAR3gwB3hIDpRnDnQ+M7f9HpM0inlPELhcqOgRy58ZbOm0gh1z3/QW3DYiweU1EBgeJ5q5cjb9bvZd4s5IYqwrP3Qui1AH9IQeTxItjjBheTxsxt1HZDO+0JLMQYy5f2Nz1+KWZKfTxv2T1IqPq1TClA/TqHgPS8Wtu0/jGsNsx0TipJIgTShgDecfn9cpKXth416Ajk1WEmb09mOlgDc8iEbEOAsztwDYeywey4Yd6Ld66sC5vM6NhykTIB05f+cCka11cdr55PdQdCuUkLQmZlpEyBVzFIUu8ra+oXU167JMFKdzWZG6p4fvM98Mw6qV+sdV/BRQXu24egx6fp1iXF/j7knJ00Zn7T1wvnNjelKEvp5toTWBJ9PGBvUnoU1FbOj50yHi0Nln9ZbTVJu94QkHk18nLyH8HL8dd7q0fnCAHFERgc95kPy+tZcT2VUC8cDh9kGu3k1b5KKERKEALWEQiAgJU58LS+hhFC9W1Ac4J1eKhFKggIk69MpX1fbYPB4BDU0XcTkhR2cMTv0yiDm88Bn+F94ejl85zza2rrq3/tZRuySffhlRu2Fs9t/jtCDc8pijWNwMppORNCjt8yhXH4EOGC3/u4YMShRXObpBeZ9iUrCKy6uupKxLm+qv1oumdgDuPmP0pLy0vd64Iku4iAEW9L3EfklYsIk+j0ISBYONaWuCF9HXqzJ+S8OpAL3/+w2+B+3rSAtCYEdiNQlGgz/7b7m2YfQM71wySJFlozMa6G6aoHlmHkjs+EWWnr02fYwm/KlCkD8fv0NLxcxqZN1wx0hFQsv62pW3xLBrqmLh1AgFeyRNH8psVj5jdfAe+sSX6/WQwPp/Mh+p/42+xAF6mIwIadDFFmfCaItoMRLnifjrmuegIoKwgsGC/govrznkCg40kh0J+Z5lPtuVSSqk6VVEEgHCz7FR5wZ6uiD+lBCKSKAGKbfyLzZqQqR9f2odDUYuS8eh72jdTVRrIruxDAi/pXdM3JiQ0qLsNoFmbXiKpirbs5sLgpxqliqRt6JBLGCqtyJ06cmBPw5/wD7Y6w2tZT9Tn7U13DYmzKQEUXBEbNWbMaHk5/AZl1etGapqHt3llcyJ0zq/G3PQ12CixKvg5a4xdIQn8AcnhNRQ6vRyTRloa+leoC5Hf2lHAouhgGR7PHYlcs3ZAQRrShoepdV6STUEcRKA1Hb8XD7mpHhZIwQkANBN4ZMCj/yAULFng/4aaDeB577PFDc/yxWog82EGxJIoQUAGBrSbzH4Edpj9SQRkndJhWMm1QS26b9GKRoWZU0owA3mcPcfN9tjQUvQom6bqDbgtC42TONtPCsBmloTIkltZ8IyHO5tTWVX/HIjYWYKSqqiHw8vklgRFb1x8Jr7ujmcEmIyn8ZOg4CbzDgBR0jaH9W3C1epUZ2C0xwf4z5pHGNSnI06ZpVuUR4YZxPbyI4G5HJQUEhvl44j/RaDRSXV3dmIIcauoyApFQ2Q/wACXyymWcSXzGEDhk88atP0Pv12dMA8U6Rr6VPB+P/RtqEXml2NiQOo4gUGCw2AOQVIY/K5NmRzp3Q8iO3NafwKOUyCs3wO1bpsCGY6v6rpZCDc7GYRFR17IShlm6D0Ho/VZ78kqwf/pzjO9ZxUbXiyRb7OoI33sR9sq/3WVFxdj9fDmJInhjjjENUcSFMQBJ4gcYgg3aXQkfTME2Il/aVnxs5EKsE37etKVl4PsTK5e1da5Hn3ciAGIvuwo8Uh7Dj0lFdlntirUfcJ8oq6mpWeuKdBKaEgKRUOR07NiGHQexDkCFENAXgRgzzGNqa2vhUp3dRSa2RyjSv4DCydmNBFmvPwL84tr6xXd53c4pU44fETBiH9HOgxkbyTXwIBrtZu8gbJ6FfD2T8wu2oLah+qRk8QsHIz/HBP3GZOt7sR4m1c8WDMr/CnmGe3H0SGcvIZB1k1t/m3EpBmiTlwZJUV0niAT/rwxXUVS/rFUrEowcC/JqDgDIuvs7awc9ew0PcNO4G+Zn3WJM1yGPtQm5RTeRV12Boe8aIiBuKT+m3PObEwR8sR8QeZXRyzMNoahifEYtdLNzgy1PVnwkHPm+7uQVHO0W+XKMrxJ5lexVQfUIAfsIZN0Et+qlqnUIq5ptHzJq2QmBw5BrZSF2uxrc6Rh9zCAC0SnRCYLzp6FC/wyqQV0TAmlDAC+NwdJg2Zlp61DBjpDc+mrOxLkKqkYqEQJuIDAonmN6elv6kpKSAID5vhvgkMwkEeBsRZI1bVWrqKjwYW2lyFZjLzQSyeFXGiw9BXmB5EKTzuWFAMirqqqqFp2NJNsIAVUQyDoCSwI/qnC/P2DS86oqg+BxPY6AB8TTCF8p8Lgdnlc/HA4PMH38cRiyr+dYZJ4QAABAAElEQVSNIQMIASsIcPHL6ZOny2SyWVfC4bIZ8OK4KesMJ4OzGwHBZoXD0aTDl1QDq39u/9Ohk6vha6rZrJw+SRIwdvXe0LhBklc5dtsr307wPj2wsMA9BcEAj8AWjXMu89cTInYyyCuZv4gKIUAIpAGBrCSwKisrE4YQFwLfeBow1r4L6QERjyUeB4nVT3tjFTVQrvQZwoeXBDFRURV1UguXPFuPvzcZFwu7/skcCKhQjVx7b6POBvzJ+lTcRaBwe0HLle52oZ70UKh8EpJ9YkcnhpV+KmlEYAf6+rzjrxF3+IpO3+l+T9NAYAvzX8vcb2nqztFucJFc7KhAEmYdAZF8CJx14UjKbJj6hg8CEJNz+dzrsUQikUMBwjOah8m+H0v4T2xoaPisRyDoBCFACDiOgCd/+J1Aoaah5kUkFLwFMdnXOSEv62UIPk0mEJ4xYwbFf2fgYljbvO4WuKp7djU6A5Al0aVYhVxir4GQek1w9gbn5iqEH68NBAIfY6XNCvltIFnvsFwjNgovfJPw2jeJCX4YXuok2TgmCUWoSnIIXAkvxHvr6uqyYothTNz3jbea/8Z1lMoWzckhm121NuKefwfbVr8NbFeCnFptcNYUE8Ya0/R9PmRIzsa+cpwgPKx/Xl7evqg/wsfM4QifGQuiezzjHDuS8UPBaU8ApFm5gOjwpXRwok2cB5meCk+SxDN+B0odxoLEWUXAZ/TpQWRVZOf6Cc7GgWTVtvRv9fdIYAWDU0eLROwZGK/xDpviI8HNLy1ZUi0XNKkQAoRAGhHI6sS3cuUu0WZW4/clmEbM9e5Kbh+ba5xhcYKvNyYuW4f8N7Mw0Zrrcje6i4/BwBfw9yxmlfVYOX0VO9tJDwtXSzAYHGIYgXI8iKdjonwCOtN6xdZVMCFcMPGHuvoauVGH1kV6XK5pXv8srpupWhvqvnFbgGED3gFeBEn9kmn6lzY0LGp2u1sZ7rptQNthhkgcg5yFEVy4UfQ5wu1+NZW/XvDEBBDXW7xiX2kogvxd/Ede0VdXPRPCX+jm/Y4dCGVo9zU64ofn5qc19dXdpquYVjJtUEtubDF+kQ/X0fYOm5oNP4tUV1f3SOJpbDuZRghkHAE8g7K7ID57PFxcXwUKA7MbCSetFw/V1tecC4km/qi4iIB00RZx/iIIrHwXu9FV9LsgPJ7jhvGc38//p0L+glBo6v4+lphuMnEmHs4RAJ/1z2iLF18LJiUHuDkpsaiPK9UxMfoFBF/rinC9hSZAVtXhpnrWZHxRTg5/SZXFlvZwUJ44lZv8q7jrj8EwkIdW8tfiTbX11T9Pvnpma+L+/Qga0GJFZoehBdeMfG9y7T0VROU8/ITPzKyZrvX+MvCTz6k9Chbl8nw88F8clO8vupYNhsnKql+ofkdXA8kuQkB1BGhyhBGKhCLnIlToftUHy2P63Ycft+9DZ8wXqLiBgFzF357fIskrhKRQSQ4BsQovlI9gxf5+rNi/l1ybzNSKRqNFZpzNwkP6+7iJDsiMFt7rVXcvrNJg+ZcZN+VOo0RwJHd5tuD+eZoz/kRb3P/Miy8+/2lyzTJXq3xKeWHMnzibC+Pb+Ak9KHOaeKRnwbZxvxhXU1OzQXWNI1Mik4WPv666nlmg37t4Rz3ETTvhHf8C3s+muNlHxmQL9lhtQ/UZnfuXnsFrm9Y/Bpu/3vm4Zp83cVNMrXmh5hXN7CJzCAFPIZC1ObA6j1JNfc0DkWC0HCEEeFmk4hAC342Eo5/V1FVnXWJlh/DrU8z2gh13g4wh8qpPpNhaztmjzBTzZe67vqurUQOu6Y3Q5Hb8/TISjEQFN67AZPZkfKeFh16GCETFeci/cbuOXlg7SU3zIZhP5FUv1wBOgbNiVbhVHurXGvjnwqULN/VeXa2zVUuqmqDRrfIvGopG4S32Q5j0FXynce9uqOCBLMz2kLyfdndapWMgr05TSZ9s1QU/oq7mv2rHlWvsZWfsjd+6pvW/05q8AlHOfMYpNfVVRF5l64OD7FYGAXoZ6hgKX65xIV55lygzMhoogiS4V8BVfrYGpihnAlb2vovJ2dnKKaaWQouxQ9tpI0ePKAKR+kMvkVddYBTQfXFt/eJTTWYchefUYzjvWthDl769+LWfj8e0yy+DxOABEQcRy1i3eUe8OFAu6PwJEqbfkRDGgfCumIp75n6vkVddMamur66GHacZCXYw7v2/4byVDSS6itP3u2AXy5yCHjDwax7QUX8VXd6BEDl2CwDiMG2BFHxFZ9si4bIb4QRwSedjmn3eIcmr2tqqWs3sInMIAU8iQCv5nYat/Jjy/eIB82UcGt3pMH1MHYGr/5+9L4GToyjbr+qZ3c0dIoQrkEsUAUUxkmR3djcrgWgAAcGoKF4oooCKfor4eeJ93/4RPEAQD6J48RmFEDa7OzNsMIhoEA8gEELCTUKu3Z3p+j+1OdhjZnamp6u76u23f79kp6ur3uOpvurt98BiQnuS8BYCAu0L2p/np4T+AqRfkHgbjkA/PBV+KX3xTcou3qi2d6QUqU9gQavza/B9fPg5oPeeTjd6h9uQ12y0aMFaBhcISn082Gjyo+7B4umrU6ZM/OlYFQJdR6K5ueMFnvQ/i4teh+nwtT9kQlEl9tPZfPcnhzRZ9RP37UOlShkvEmCV0nuEgUvkek+J1cJTPfgQszHlq82e7z1WaChsj0PeYrG4K5/P7zTFm3qoKIpPLMlmV9+s8cs0t58PL/fvm8LSArr9UqgzEa2jQ/d5YwQYAQsQ4JefEZOApO7zkNS9G83jRxzi3eAIYG0hL+zOrUbIG2/1IKC9MMY3TdRfgObXQ4fg2G1Sye+ItP8d5EHZRFC/kirtDi8S38XBF5XskOhGeSE8V/4fBQgymY6FUvn6ucRh/8Mn9C/wsvwcPBR/j+ZEeSXi2j8BCutn6vOHQ5LovacmbBt3+E133RSLUWQs5FubF71aSHXDWP0IHX8auvwEHpHfz+c77yGk15iqIOz/DBh5fjNmR0c7+CJ9RC636t5Mpv00ierjUCPlqCpjiV3EAuYN2WyX9nznjRFgBCxBgEMIR0xET0/PWtys3j2imXfrQwDPN/VdhL29uT4yPBrGq08ABTZePXsqDODnlekB73nd+dX/myTjlYZAhxfB00iHFV6MXafy/Gj5zW7qfaDv/DNOF2uA8eoa6MLGq2dPmL/r8GB49s6H8eq3aE6U8UrDgGt/Fa59Xab+s/jHYYUaFCGmbZ+809rQenwxPn63mMT/17mChLgUxsTDcI1enDTjlZ5d5KycS3iWi1u2PLJBf0DDy70Oa6dqvEJEujifjVeEz2RWzVkEqN506pqQDRse+NvMw2dp77SOugjx4KEIwAlLnHb4zFn/Ar7rhh7g39Uh0NKyqBkn5Y/R2/lFeXUaV+yFvMbi58Lzz+rJdl+7/uH12yr2Jnxw/fr1/oMPPdA79+A5V/tp/4WIKjqCsLq1qLb/YYfPyuF+c28tg2zre8gRM74DmZbYJldM8jwMY+1FqH51wYMPPfjPmGSwhi2u/cKDGx64ddaMmatwP1yMa38/a4SLSRB44s7F/dBKb++Zs2ZeijmibNjQMa2/Fyn/VDyX/3jvI/fqD0yJ3A4/fObZeOldQFT5vvFNE9bDuPMT6Ec1lQWMV+qCbLb7B0TnkNViBJxGgBfCZaYPX40+hUMkwk/KqBhHcwpfa65tbW49NQ7mLvNcunRpkyeUTuDLRmcxmENjXk+2643wmLzP5XkNU/bO2zs3Y9FwspTqEtBN7MJhKKZYTL1z6L5rvzOZRUthsHFah5Aw3wU6n4PH0ZEwXl2D34nzuKqEI/L9ZdONqZfAOHJjpX6JOCbF0QjfOsFCXZFGR77MQrnCEklX/rysO9d1Bp7LD4ZF1FU6MF7NdVX2KuQeD0ulNl5RNph/BMYrynm9qphm7sII2IuAZ69o8UuG6mXvxRP5d/FLQkqCBiG967EwezkprQwrs+3pHTox7VGG2dhOfosOlevJdS/K5TrvtF3YmORT3dnuryB8oQXGm//GJIM1bIHBq+bPX7y/NQLVIIiuYoUwOf0CDTUSvd0KT8sX46PSxygl5Q97RoHN08j5drquwhg2bdfoKU9eaJvMyK/6PMhEdcG/C8a5s/Z8+NWGLN6EoGzAoj6/l+Fc/hJ1JVk/RsBlBNiAVWH2li9fXtzVt/0N6HJbhW58qHYExmNhdmNra0dr7UOTN6K9uf04uDJ/KHmaP6sx3oh/rWTxaHhffAut7H3xLDQlf2WznX9p6mt8GQx+K0p2SE5jY0Nq4DUuqlvo9z8HuWe6KHtIMj8N2925WEgshkfHv0OiSZ2Mn82vvgRemOdB0SJ1Zcvqp8QpbW1t08sej+GAUh7Cu0luiCRT5/XkV5NNWB5g1vRHh9kBxvGQ+BH49h5DbPySsASMACNQFgE2YJWFZveBtWvX7pApdRr2/jNGVz5cGwIThO/DiIWqj7yVRQBeGOmiFDp0MJkJnKXYjJfjM7K5rtdks9mHywLFB0YhsHLtyi3pJg/3LnXVqIMJapCeeJNr6iIEShdqsM6LJCocYbBe5aXFsfAo0ucudnmrBQF4Yf4QVoU3YkxSQ4kbVdE7uxbMTPdF+gTtgUVug7H0w9257p+SU6wOhTKZzCEYPr4OEjw0FgTUVTBeXRwLa2bKCDACNSHABqwq4EJls8cQwqDzNj1eRXfuUj0CU4XvrWhf2J700LiyiBX6/AvxKe+4sh1oH1gtPfVSvBxzGG/AeUZYUQEhl+diOJIHJ3RTIgND+fNd0X7evHkNKL/+Q8ibxHx32uDyQRisT+rq6trgypzZKCcqZ/0SYV2vg2yJrFCIysdvtWxenLkH1YDbn3XIeg39E9FVyoa5iVCUlJLyV4fMOFh7rvIHE1LzyspQRYANWFXOrA5hQNjbKbi16fLAvIWHwHTfEzd3LOyYHR5JGpQ6ju84GNlvLqOhTU1a+EqpTyMH3WIYjzfVNJI7l0RA53NQSrwLB5MZfln0ziwJjIWN4xsn/g/EepGFopkVCd6WwvNOwLn6NTBK5nkaMsI6rEuHd4Fs4hZl+sMPwu8tuo4UNQPWTl+kE+slWvFSLfpswKoIkF0HcXP8XbpRnq3TxtglGUvDCDAC5RBgA1Y5ZEq0d+e71+C9+vU4lMgvmiUgCatpRtHzbx402IRFkQCdYoP/VagxlYAqtajwmFDeKdl89yf5ZaIW2Mbum813XYFcaslccEjxqrERir8HQk8OhdH6o/FLErkEtxX99Mt6ejp7IudMnCE8WK/WYV7E1Sypni/FWSUPxNIoqRmwvpTLrbo3FihtZyo5gbvtU7RPPqlWNjR6r9fe6vva+AcjwAhYjwAbsGqcop58D8pU21fhpkY1rOuOLyBHFBr8mxDqM8064WIQCDlwFgETXUAgSdsdSNT+kp5855+SpHSUuuqy0FLKJBpIFra0tBwYJdZBeEnlfRHjJgUZ6+4YdW1RDZyQz6/a6K4Odks+GOalBnMp2i1o2NJJ8eqwSQahd+K8E/WHKOvvPzXo1u+LwuU19E9WVynmJEthZ7XNpRtSr4bxapezGrDgjEBCEWADVoCJR2LZKzGMS6wGwG6MIS9CTqw/Ljl2ycQx+lE/7Cnp6TAaREEkZMNXsIFi38s5Ubv5+e7Orv68lEJ79yVp81IidbLNCsN4vwCX/Dk2yxiybP1SyHciR9ub8/n8zpBpM7kRCKCgw0V4oNw+opn2rhLHtrSc8Ny4lexr7DsybhnC5K+EvD6Xyz0aJk1StBQbsByYzzvTjd4pMF5tc0BWFpERYARGIMAGrBGAVLuLPB0fQVWZn1Tbn/tVjcDCHZN2/Wbp0qVNVY8g1rG1ZdEbkbIkSdUZf4yvYEt7e3u3EptKa9XpznZdAvPoNdYKaEAwpaTNYYQSxvtvQu2kGK2fQU7Jk7tzq39gYKqZZAkEtJeBTA+G1D1V4jDZJk8UzohbOd+TtCoQJuzZEeD8mRtgDA+JDoG/9xcaTsQ98enoWDInRoARCBMBNmAFR1Pt6N+uk6PeHJwEjyyDwEnPPL39Z8uWLUtcFa7m5maUXlafLYMLtWadWPhTMAa/HS8SnH8g2tlV6QbvfEzAX6NlGyM3KU7q6OhIxyhBWdaZTLsOF15YtgOtA49KX3Ugp+QttNSyXxtd2RFJ3S+wX9JQJVwaKrUgxHxSCdx3TJkyoSsIDEkYg2fMOOh5SBJ0dVFHfCH6r0ypV6xZc8sTLsrPMjMCjMBuBNiAVceZsHbt2gGEPb0GH83X1kGGh5ZCQIozNz/0yHdLHaLclhIN74N+MynruEc3OMSo98J4dVkCdLVSRe2RoUR6GYTbYqWA4Qs1ub9fHRc+2foozps3rwHeSEm5DjYKz2/rvq37jvpQ49FBEUBS919gEXdd0PEOjsvsMSrEJrqUHqUE7t0rVqzoiw1Myxn39YnZEJHXVnbO04aU753E1a3tnByWihGoBQG+ydaCVom+OuxJpnx84ZP/KnGYm+pAQEnxrtaW9qR4I4nBBPZSJKVa1IeQUDxxBso6LgcjQwerSCn5NhDX3nDkN0+odtuUHDduwtvx/Ig9T08EuDxUVF5HT0/PvyPgxSwqIFBQA+/F4ccqdKF0aJzf77fEqxApD6xk5VGr8cTxPH9ujUO4ezQIPIoiQSd13ta5Php2zIURYARMIsAGrBDQhTX/MS+tTgKpDSGQYxLDEfhoW6btQ8ObaO5JlXo/NNuPpnbDtPoYPK90knreLECgJ7/6N3CH0/mX6G9KLLJJSR0yLJX8mE0yGZJlI4xXL8/nO/9riD6TrQEBJM1/EkbTpHwsEUWhFtcAT9hd4fAmyOTAQgjqnWEDRIueYgOWfRP6OIxXJ6BIEDsa2Dc3LBEjEAgBNmAFgm30IJ1bwlPiFBzhpICj4amrBYvrL7U2t59bFxHLB8+fv3h/pZQOH6S+fRbGq89RV9I1/absN+EjkPke1+SuWV4pWjHGmudeSjbofEQzatbDrQFPYvHwCjZe2TVpqKZ8NRwve+ySyow0qHbZYYby2FQzmcwh6DV57J5u9JC+vNsNSeOREsWd5sTDmbmWQWArqnovhfFqXZnj3MwIMAIOImDNi7yD2I0SuSvf9Xd9o0QwzvZRB7mhHgTw/imuRKLj0+ohYvPYplThfyDfFJtlDEG2b8N49fEQ6DCJkBEYzGnie+8JmayN5Ka1LWh7oQ2CIS/PJMhxqQ2yGJMBz0I8E0/hxYMxhOshjDSEQj93khA+fJzONVcPWEHHStlAKf+V743z7g+KRTLGeXOToacTWu7AIvdV2WznX5yQloVkBBiBqhFgA1bVUFXXETfK24TwX4/eXFWtOsiq7ZXCy/bP25rb5lc7wJV+g95XUtE2Hiix4pAZB33AlTlJopw9t3WuRKzLdeR1T4mX2qBjoV+9E3IcYIMshmRA1KB47e5noiEOTLYuBFAJcg2sVzfURcSNweMnNEx4USyi0qpA+JAu/hELju4wZQ8sO+aqX0n5mq5cV5cd4rAUjAAjECYCbMAKE809tHryPTciAflbsesbIJ9kkhPwQPptS8sJsyiB0JgeuAj6aG8Mqts96SbvDcuXLy9SVZCKXv3FBu2R8RQVfUrpoYR8San2KNt2e4MQDxmGd0822/XHKHFlXrUjID3/fzGK/Ac3PyVi+fglpSKT/wrGTs5hN+YlxjmwxoTIfIcC1mDLstnVK8yzYg6MACMQBwJswDKEOl7cr4N/fhJyGhlCsCzZQzxV+ONgxb6yXdw5oJM4Q1qdB4fq9iTcMF6Fr7acG86BGe7tveURJOn9pAOiBhYRi7DjAg8OaeD4pknngNTMkMjZR0aKK3ryXd+yTzCWaCQCg1Uhpbh+ZDu1fXhwx2LA8hWdBO5I/H8ftfMiTH3a2tqmgx6ZfGdhYhMhLYWg6POxBvt9hDyZFSPACESMABuwDAKezXZ/F+klvmyQRTJJS3G08L3lyCGTdh2AlGx8G3Q40HU9yshfkEq9lpM3l0HH0uZJUyddCdEeslS8usVCmKT2wMKf2DbYCNUHY+NumrESvU89/cR7TbNh+uEhIAvqS6AG2y7dDYk0XxiHdrjRPDcOviZ44nl+rwm6VGiiEM9cKrq4qodS4hJ8PPmxq/Kz3IwAI1AdAmzAqg6nwL16ct2X4rXwR4EJ8MByCCwuDvhfKXfQhfZly5alsJJ9vwuyBpERHoifQI6VW4KM5THxIaATuuO8pGx4nwIPzjlxIdzW0nYazGdHx8XfMN/HvQaxbN26df2G+TD5EBHo7u2+S0j15xBJWkcK1rmjIFTUhmvcSulUpUNOu/utm1iLBEKFxtieKxbBEJ8oSvwhm+/6anwCMGdGgBGICgE2YJlHWh1y2EHn4+Xp1+ZZJYsDvrRcjMqEb3FV680bN5+K8+IIV+WvKLcU2UMPPZiyEaSi+q4fTDWmfgAdHnZdj3LyY6GhF7OxbPq+FQtj80xhs1bndHV1bTDPijmEjoCfoh7yOQn5MyMN20VI2cEwmU0Mfa5iIqgUhxBWhF5yBcKK+Jg+KMWJuMbJeDyahovpMwIuI8AGrAhmTyevbmj0zoGxoisCdoligbwWl7ctbLOiqljtwMsLah/jxIgt6aJ3Didtd2KuSgq5u9KU/FrJgwQalfBiecltX9h+lJByEQEIR6kgpfgWPC5Je/GMUppQQ0++U8/dfwipNEoVT/mRGq6VSsVynxmleEgNjY3y/pBIkSSDfGfsgRXvzI73ROF78YrA3BkBRiAKBNiAFQXK4KEXhOP7Gk/DzzsjYpkUNuPh1n69a0ndm5s7joBB80SSk6TEeztv61xPUrcEKbWzb9v3oS7R5PsqloUlKqFdCEyjDmMyf9YqcXfBH9DV7HhzFwEU+VXa85Lw5h8ZqXJFf26k/MwyewbvsY+bZeE2dcSLsgEr/il8RWvLojfFLwZLwAgwAiYRYAOWSXRH0F65duWWgWLDK9FM+ivnCLUj2JXPRVL3a8HImYVhShbfDXkJXn/yV0igeU0Ek84sDCOwdu3aHbiifmmYTVzkIzdgZTKZyciH8+a4FDbIVxdreFM+n99pkAeTjgCBVH9KP0eLEbCKh4UUh0fJGOXQIr/PmNOPwwfHwhYfJQnN91ja2nxcfae9vZ2NiTZPEcvGCNSJAMEFdJ2IGB6uy9R7abEYbB40zCpp5E9pbW53IiQP1RPHwdb2VoITtDU9IN9DUK/kqiT9q4gqH/lCQ/opbbwiWGJdfb37tu47iJ4niVKr8/bOzaiQ2U1WaRWtAUtQyokk1X1kz4sQFNNVsfEF9bAQSDGJ+hGY6hfFtbpQUv2kmAIjwAjYiAAbsGKYFZ3kVsniyXjYPREDe7ospfhqS0tHLKWyawG12F88Ff2fU8sYN/rKywYXQG4Iy1JWgUBPT08vvIburqKra13011ncgiPcpDwvQm4RsVL37uzbcVlEzJhNBAhI6V0fAZt4WMhoDQweJQ8sJdiAVeGsLRQKM3E4XaELH4oSASUymx9+9KNRsmRejAAjEB0CbMCKDuthnLLZ7Dp86TwZjduGHeCdehAYJ4V/zTHHHNNYDxHTY5FA+i2mecRA/5/ImfSdGPgyS8MISE9dbZhFHOSbkDdvv6gYty1oO1YI9eKo+EXGR6UuGgw1jYwhMzKNQFEM/Bo8qIYRRhxCSCikTIn7TZ97TtMvpOc6LT9B4ZVSH29pWdRMUDVWiRFIPAJswIrxFEDFpjWYgNMhQl+MYpBiDZeK454z5YBP2apUS0vLgVjIvsJW+QLL5XvvxUJ2IPB4HmgvAp74KYTz7RUwsGTTA4+sdWBavqnWIfb3lzeict2f7JeTJawFgVwu9yj6d9YyxqG+kV3zCCmbBFzwvKexoVgOG7AqTaWn2IBVCZ94jqU9pa5bsGDBlHjYM1dGgBEwhQAbsEwhWyXdrlzXKqEGFzdUv3hWiUR43ZRUl9j61UWq1BugaUN42sZPSQnx657bOlfGLwlLYAKB7u7uTaB7lwnacdL0it4BEfHHO7R4fUS8omJTULJwaVTMmE+0COB8XR4tx8i4jWtubh4fBbfiziIpg4bvexxCWOnEkVyBsBI8sR2TYk5DuomjA2KbAGbMCJhBgA1YZnCtiWpPfvVyJcXbMQi2AN5CQCCF3BNXzps3zzpDkRSS2kK2KGSR8wyEcNLaTEIpebPN8gWRDYbuSLwxMplFiyEfreS+UlwxGAYfBHgeYz0CvkjfaL2QAQX0PG9awKE1DVOe99yaBtjdWTU1ifV2ixizdL4gZbCMGc1w2aP6b2vzorPDJcrUGAFGIE4E2IAVJ/pDeGezXT/BgooNAUMwqfPnCyeMm3BRnTRCHd6xoOMwpI2eHyrRuIlJ8UssZP8VtxjM3zACniBnwMK1GIkBSwp1juHZiZr8TuRF+1zUTJlfdAjk86s24nvavdFxjJRTNAYsSgnchXi4s7NzV6Sz5BgzCU8fx0ROlrhSXd6xsGN2spRmbRkBugiwAcuiuc1mu78AT4evWCSS06IAy8uam0+YYYsSBc8/C7IgTReZTXm++CIZbViRsgg0NMhuHNxZtoODB5DUy7gBa9ALVInTHISnrMhYqH1vT1hp2T58gAICcjUFLUbqgNDhSIo3SEkpJ5Li/FcjT6TR++yBNRoTm1qmFrzitcuWLUvZJBTLwggwAsEQYANWMNyMjcrmV39YCflDYwySRXhyWha+Zo3KUmgDFpkN8a43dOW7/k5GIVakLAK7v76rtWU7uHjA94wbsMaNm9QBaCJZMEc0BTuEp74cES9mEyMCSGvQFSN7Y6z9lBdJlWKkC6ATQigl57+qcEZmMpnJeB/av0IXPmQFArJ108ZHOHejFXPBQjAC9SHABqz68DMxWh0648B3wVHntyaIJ40mXipe17qw48S49V6wYPFBkCETtxwh8lcpJTiMKERA7Scl77BfxuolRBic8QWHVP6rq5fIgZ5SXAXvq8cckJRFrBOBhqJH0gNLKRVVbkw6HjmKKxBWupxwStExVlZSlMaxT2UyHQtpqMJaMALJRYANWBbO/fLly4vpRqkTDt5qoXjuieQpHeYWa+hegzfwCshA6Xq7Cd5Xf3XvZGCJAyOgBC0PLCFMVyPDPUe+KjDe9g30i773TfvEYolMINB5W+d65MF6wATtOGmmhHkDlg5TwsezmXHqGSpvJdgDqwKgKDM7p8JhPmQXAml8WLpOe83ZJRZLwwgwArUgQGlBXYve1vfVITsDxb4zICgpr4d4gFfz2prbTo+H9x6uUr0yVv5hM1fyirBJMj27EfClR+tepKRRTwzcc47HjBKqPih/n893/tfus5SlCxUBJXtDpWcBMaXMhxBu2rRJ596MJFQxCkiVJ++Pgo+zPEjlO3N2FmoRfK5U3rdqGcB9GQFGwC4E2IBl13wMk6a3t3erTGnDh+Qqb8OQqX1HSfkZjIrrfAdfeVLtUls6QorNO/u3kS2zbinqsYs1Y8b0f0IIOonclWoyCqrnnWqUfsTEfaEuj5gls4sZAenJdTGLEDp75SG7l/EtPdc4iwgZ+H6KPbAq4c0VCCuhY+kx+ba2lrbXWyoci8UIMAJjIBDXgn4MsfjwXgR0vhEvrZZif9PeNv4bCIEXZjLtrwk0ss5B8MR4GUgcUCcZm4ZfvXbt2gGbBGJZzCOgQ5vBhY4x3TMcSqRU7Ln3QjsrkAMnl+taGRo9JuQEAjBa3uOEoDUIKaU0/+zySYWU7crnV/H7Z4VzTCrBIYQV8LH1EApmXd7a2kon1NdWoFkuRsAAAmzAMgBq2CS7urru94W3BHSfCpt2kujhJeMzHR0d6ah1hvcXHe8rJEVBHpwfRY0h87MDAbgu0PHIUNKYB9aCBQumIAeODiEkscFr5QdQxCehDCtRAwJFOtf7Hq1l0e+vAYBAXSUtj5z1AIGv/QpnAu71pDzuKqhK7dB+wvd+qnPWUVOM9WEEqCPABixHZjiX6/wHJkvnxNrliMg2ivn8Yn9RYxjphkV/e6QMDTLDi9qtnAfHIMC2k5bybttFrEE+YzmwGhrGLYIckRvLa9C9lq66cNvPahnAfWkg8PTTT/8HmhRoaLNbC9/zjBuwfEIeOXh/uY/S/BvQBRCJWQboMsloEGjb9NAjH4qGFXNhBBiBsBBgA1ZYSEZApyvX1SU8+VqwIvVCGQF0+1jAZfiCfTsR/NhTjWhBBKwiYeFJ9fNIGDETOxFQPiWPDGNJlqVSJ9g5gUGkUtlcbtUDQUbyGLcRWLdunTb2kErcH0UIoZR0QgiRMex+t89is9I3N59wKDiYrmhrVomkU5fiMwglJPOenvTpZP2TgQAbsByb556e1X9AQvBzITacYXgLgMDLUT73mADjAg3ZvGHzizFwaqDB9g1CJKv4P/vEYomiQqCgUnQMWNKch5RSYnFUc2Kcj5K/MM6DGViLAF406OS9A8pe0d9uHGxCHlh402QDVoUTJpXy51Q4zIfcQCAtfHkd1gaT3RCXpWQEGAE2YDl4DvTkVl+Ll4r/dVB0K0SWKvXOqARB/qu2qHgZ56PE7SgqwMlcjQNtL4PDDpuuFzM0KhH6ZvRAnr39gFFkRnLDZ4uSaXWDYR5M3mIEkM9ps8Xi1Syan/K31DyohgG4/seh+yE1DLG7q5IcQlhphor+3EqH+ZgrCMjnSuV9zRVpWU5GIOkIsAHL0TOgJ9/1RYjON9tg8/eWJccumRhsaI2jpFxY4wh7u0txo73CsWRRIKArEcIjg0hlMmXEEDcwoI7HXJB4tiK5y1/YaB3FlWUvD+WrR+yVLpBkRovh9PWJ2ZAKlw6NzZeSPbAqTSWthP0jNU1Y8n55HqqVnzkSBN5nBBgB+xAg8ZJtH6zRSNST6/oQcjr9NBpupLhM3Tmp7w0RaXRcRHyMs5FF9XvjTJiB9QhgZbbVeiGrElAaMWAh/xWZXBowVnLIcFXnEt1OUshHCWmn0un0Myb18Tw6+a80ThP60mzAqnDCoLr1nAqHHT8kUcRBXeu4EjWJj/n8IfJhzaxpEHdmBBiByBFgA1bkkIfKUO3q23YuFpR/DJVqAogpoc42rSZCCSbh4f8803yioa8e6O7tvisaXszFagSUmG61fFUKh+TEO6rsWls3JebXNsDe3jDGrbBXOpYsCgSQkJySB9b2zs5Oo0VwpK/mRjEvUfDAu+UTK9euNBpyGYUeJnngOUJmvkfhpNR94/qa3oP32AdGHaPbME343jW6ABNdFVkzRsB9BNiA5fgcrl27dmBH3/ZleNHIO65K1OK3zZ+/eH+TTIu7ijqBO5VrbJVJrJi2OwggJ85B7khbXlIplBkDliRjwNqWakrdUR5BPpIEBIh5YD1tfM5ohZRx/quxTxi6BixP3KcNmEp6bwIMxbGhINNj0eaHN3+AjDasCCNAEAEqi2uCU1O9SjBi7egrNLwKI/5Z/ajE90w3pfs1ZsY2PyXIhA8qJXuNAcWEnUFAf5VEWNk0ZwSuKGj4IYQtLSfMAksiBj6RM+2tUnF6+KAVCAwoj1IIoXkDFq2QMjZgVbgKly5d2oTDdBL2j9R1TwXKbHZ1Nw59c+Rhyvt45/1cS8sinc+SN0aAEbAQATZgWTgpQURas+aWJ9JFbwnGbggyPoljfCHPMKk3vly/0CT9KGl7vmIPvygBt5TXgw8+eQBEI/HcgCdZ6B5Ynup/kaVTV7NYMFR21TyIB5BDIJUqhH6dxAjSY6Z5I6RsjmkeUdGHLpz/qgLYW7dunY3DJJ6HpdQcOv/pRu9jqH5+d6l+RNsaPKGumTdv3gSi+rFajIDTCJC98To9KwGF7+ztfEjJ4lIMN1plJ6B41g1D2OUSo9UIlTjaOqWDCfTMwTMPXhdsKI+ihEAqVSSR/0rPiVIidG8MKVNUrnmhpFxD6dxlXYIhkO5L9wcbaeEoJYwbsPBeQcaAhZsAG7AqnsbpuRUPO35QKW+fBx68cXeJlH8uVEpSKOELJjRO/Jrj08jiMwIkEWADFrFpzWaz65B499VQaxcx1UyoM37nxJ0nmSC8h+ZRBmlHSXrN8uXLk/TSEiW2TvGiVGELyak3hg2+LwSVax4GvoG/hY0P03MPgR0yNeCe1GUk9swasFC4ZT9w1v9obL7cZ8CgoVC4WlBK2F8KmZEVKHt6enrhufyNUn2ptsEL7V1tLW2nU9WP9WIEXEWADViuzlwFubvz3auRoFgnXcR6irfKCMjFlY8HO7pgwWKdB0eHWzm/oWIj579yfhZDUsCn412gfLU5JFT2kcF9l4oH1qZcLvfoPsX4R2IRaGjYxR5YVc4+CrfQ8shJF9iAVWnuCYWLjlQTnoQlK1BOmjLxY+ibqHy7SsgfZjKZQ0dixPuMACMQHwJswIoPe6Ocu3Pdv4KHwQeNMiFAHGEybSbUaEoNHGOCbhw0cZP4exx8maeNCKjn2ihVEJmkkg8HGVdhDN75xQsqHHfnkFTsfeXObBmVdMqUKZQMWI8bBcujY+AHTsWdO3dyTtVKJwythP0jNS1pvFyxYkUf8se+XZ8fIwcQ3j9AqtTV0E8/43ljBBgBCxBgA5YFk2BKhO5st3b1/bYp+jToqhftcfsPVZ2iJOOJIXyZ+m+o4DAxhxGQZDwMUsVUqAas5uYT9BfaKQ5P7j7Rle+x0XofGsn+gQUrmRBCZTiE0FeSTP4rFHHYgArXZObeyFUsBZnn4Uh8kCOybP6zXG61LurzvZFjiO+f1JZpu5i4jqweI+AMAmzAcmaqggnak+t6PyqH3BBsdCJGecW+4rywNUUFQhqeGABGysK9YePD9BxFQCkqL+zF6bOnh5rQWcriTEdndZTYyHOyflQjNzACjiMgpReq0XokHLhuyBiwoFtJD5yROid8fzZZ/b3K87+zb/tH4I6UqI+bSskvtLR0vITsnLNijIBDCLABy6HJCiiqXxQD5+BBo7+Y8FYCAYQRhv9A8hWJEEKcN08gcSdXtSxx3iSt6ZhjjmmEA/0RRPR+NOzCBCnhzyKCDabZf4CKLqxHfQjAQ3lCfRTsGe37ntmQOFIhZZzAvdKZ29zc/Bwcp5Owf6SyY1SghHfeDuV552EYnPUSszV5yr9u3rx5ZO6JiZk5VpQcAmzAIjeloxXK5/M7U43eaTjyn9FHuQVGmuNCR0FKEtXI8GbC3lehnxxuEtx/yv7aKNvopvSjpA69AiGsPoeP4uJqQ1GYXei7iksC5S4Wi+OJqO1v2fLIJqO6SDoh1p4sH0JmFENHiHteExVv5NKIV1GBsqens1MqcUVpAkRbpTh6/LiJXyaqHavFCDiDABuwnJmq+gTt7Ox8XMniq0BlS32U6I2GkSZUY9P8+Yv3B0q6CqHzG4x7bPR0fhbDUaDoiZeGQyl+KqgqdE/YUviKjgFLNSg2YIV9gjhKr1hsoOFtIMWj69atM5mQHo9LRcYLU/lswKp8yfqkDVi+591fWf/dR8dvH6eLRSUr3FSJC1pbF+n1FG+MACMQEwJswIoJ+DjYZrPZfykp3gzefhz8Leb5vDBla2goHB0mvThpwbj3UJz8mbdFCCj1YoukqUsUeBeEXgZcCo+KB9YAhw3XdXqRGqyUT8MDS8nwvS6HzHQmkzkEu+OGNLn9M1VMllGixtmC59GcGoe41L3Y17flwWoEvumum7ZLpd6JvnhdTMyGKHv1o7a2Nn3N88YIMAIxIMAGrBhAj5NlNtv1e6XUp+KUwULek1taWg4MSy5PCTIJ3IEJ578K68RwnI6UkowHlvD9u0OfDqWovMxuCx0bJugsAmlVJOGBJYUyasDyih4pgwbu92zAqnTV0krYP0xTWKJqqkDZne++BQSuGkaE/s50UZRXQ014XvLGCDACUSPABqyoEbeAXzbf/VmuTDh8ItIqHVpyaoQSherRNVzSaPdQSvnpaDkyNxsRGEzg7ovwix3EpKxKqfANWFJMi0mdsNmyAStsRB2m56e8iQ6Lv090097ESGg9dx8z939s6+7uDrVKq/uQjNBACUrzPUK52kMCx/U1fgBEEuWxj3vKktaWRe8ZCR7vMwKMgHkE2IBlHmMbOah0k/cWCPZ3G4WLQybk9zksLL6eVEeGRSt2Oh4bsGKfAwsEeM7k5xyP74wkFrKAsy+dTpvwLtBVqShsbMCiMIsh6YCqW6F5J4ckUiAySiqji2tJySNH1m7ACDQpDg+C2w0pj7uhU4HwyPuH7lfze+XalVvg5fiuavrS6qO+3NraSia9Aq25YW0oI8AGLMqzW0E3JHXf5ov0q9Fla4VuyTnkq0PDUhZfZZ4fFq246Xi+Yg+suCfBAv7Kkx0WiBGWCP/G/a8QFrEhdKYO+e3yz+0uC8+yh42AR8KAJX2zObDgeU3GoAHP65oNGGGfdTbTW7ZsWQrveTNtlrEu2QJWoOzOdf8fCqT8tC7e7g1uEkXvZ83NzTRyBbqHP0ucUATYgJXQiddq53Kr7kVS9/MSDME+1fH1NJT8NR0dHWkQpeRabmKhvw93/uEIAlJ1OCLpmGLiy3no4YNI4DwZjBvGZO5EB9wNeWME9iDgK/9gCmCgcINZDyyhyBiwhOL8V5XO+Y0bn9Ae+42V+jh9rI75HyikL4a39man9a9VeCmOTsmGL9Y6jPszAoxAcATYgBUcOxIjkdT9+gR+MRk1d1LJg0Y1Bmjo6xOzMYzSi402yPGWYAR257+SzVQgwP1uTdi6IOExlfxXgEZRun+FPdWJo+cJScIDy/d8owYsnBhkDFie9NkDq8KVLmWR0kfK0ZrWUYFyzZpbnoB32vmjiZJveU9rc+up5LVkBRkBSxBgA5YlExGnGA2N8t3g/584ZYibt5IylPAfz/PJhA/qOVFCEfEqifsMc5f/c6Y8p41Q/ivhC5EPeza8Ao1E13twaQobH6bnLgJYjJIwYCHv3cOmZmHevHn6OTnDFP2o6aJSNRuwKoAufULediX09P36DJi62jleHq8vQZpykxTS+1HH8R0kPFYpTxTrRgMBNmDRmMe6tNidD0u+EUQG6iLk9GClQ4Dq3jxBKIE70MATmT2w6j4r3CYA4+6ZbmswTPq+qVMn3DGsJYQdP+2T8VqCwYKMLiFMLZPwRCjeyTED+aR+zzElQ2Pj5FmgnTJFP2q6Ms0hhBUxp5Swf7Si23K53KOjm2trQaGoCzGibjq1cY2994GFxuJVkILD8GOfChaAOgJswKI+w1Xql8utvh1f3T5TZXdy3fC0mRKGUkh++rww6NhCw/ckL2ZtmYx45NAvYqfHw9oAVyn+smLFir6wKft+isx1ggmfFDY+TM9dBPBMI+BZJI16FEnpUwopUzt27Fjv7hkbgeSSVJ7TkYCFcq3AYPw4qhK+byRx8vtKvrK1uf0C8nqygoxAzAiwASvmCbCJfUNT6guQ506bZIpKFrykTwyDF/LrHBkGHXtoKBLhI/bg6ZYkLS2LFkJiAgvYPbgr0WNiBjxPUgq7238w75kJoJimUwjoamswaOqE1a5voSzKy4EgCVUghI6b165du6OcrtwOBBRdA5YS4r6w5hhVCX8BrG4Ii54zdKT4atuCtmOdkZcFZQQcRIANWA5OmimRdWl5X8h3gj7SxCRskyKUawEv+6Q8sJDcnuP5E3YpDFUXC7NXD913/bdU6jYTOng+nRBC4COnT5rOhmsTJ4pjNDdt2qSN186HkeMDlVkDFqWQMhmeAcOx070WcefU0tmpvnVUICylZ7owGEr4ZKljhNvGqZT3M1QlH0dYR1aNEYgVgVAW7bFqwMxDRUCHEmLRem2oRN0gVnf+ij0PKzreKrvn7RA3po+lDBuBQe8Lqd4QNt0Y6amiLOZM8Ef4NWzXdLaBtGDDNZ3pDKyJUqlZgQdbNFBKsd6oOIRCynArM2rsMzoPERBHwv4JYEPWwB92BcrO2zs3wwvr/RFMjWUs1DEDferzlgnF4jACZBBgAxaZqQxPEZXyPw1qA+FRdIGSqvta8Hf5+qtc3XRsQgurcl7I2jQhEcqyeePmV4IdIYOsvCuM5LSlpkBKSex+6R9aSk9uSxoCaiYFjWFeNmuUUXIuBZwGdVB+aCFkZDAZokhT02Q916Q+WAxRT5ioQNmT77pGCfG7oXyS8FtKdXEm035yEnRlHRmBqBEgtdiOGjyq/Hp6evQLTMK8sOpfgPrSfy61cwKhF7Op6cT6VIcAvsSfW11PN3rBs/SPpiQtiPrvH6ZkC0KXWjXVIBjwGKzSydz/C4aNMoqMAcszbexz/MIilrB/1GwYq0Apizqx+VOjGNJugA1LXLVgwWIKlVxpzxRr5xwCbMBybsqiEbiovK+AEz6aJGODojvr19QjZ8DCd8bncxx//WeGaxRaWloOxNy/yjW5K8mLikg3VjpezzFyHli+PKYePHgsGQQoeGCphoaGB0zNyInzTpwK2tNM0Y+arhTSsLEvao3C5Sd9MSdcilZRM1aBMpvNPgxrziVWaRuNMAc2eANXgRVZr71oYGQujMBwBNiANRwP3tuDQD7feQ9+5pMCCJ4s9RuwKCVyfXbi036ff9Szu/wrCQh4Iv026NlASNfHDzrsoF5T+khZIBVCiJArNmCZOlncojvLLXFLSrsJBWp2lTwSQmNfQx+tD1dpw+GWIWAeKwma73l7ITVagbI72/0jMPrzXmaJ+SvF0kym7fzE6MuKMgIRIMAGrAhAdpeF/KG7stcouVQ7ahxRoruk9SK7R8OiJ7gccInZptq0dOnSJuj2Xlr6qRXLly8vmtIJeUOMLZBNyVyRrhLaaM3vBxVBSsRB9z2wTIfEeWIuoTOhv6urayMhfcJXRZGa7+H4mK9AqXyR1oacZ4Yzpr+Hit7faG9ufxF9TVlDRiAaBPgFNRqcneTSX0j/HoIbW/TZBAoeLk/ULY+ikwdjKBZSKTZgDQWE+O9tW3a8GSqSSuIND0tj+a/06VAojHua1GkhxcS2BW0vJKUTK1M7Ako4b8AyXlWPlkfOepwkfu0nSoJG0JrvYRNn/FoBt1xu1QOIprt0GONk7IzzpfgZp+RIxmSzluYRYAOWeYyd5bBmzS3aqGMs7MYmYBAy83id8iB1BNXcCLK9Tmx4uCMILFu2LKWE+pAj4lYrZkF5ymjYwrZtm8klp/XTgq/7as8wgv3a2tqm45k20XXVTCclR6GTOa5jtE9+qe7b95t/lENgdrkDzrdHVIGyJ7f6clSIWOk8XrUr8MLigP+Z2ofxCEaAERiJABuwRiLC+8MQkFLeMqyB6I7yVV0eWM3NJ2iPlfFE4TmutbWVTJJaonMUilqbN25+NQg9LxRithDBizIqqxo1MK1bt64f6pIKI4RFng1YtpzDMcjh+ykK+a8EDEz3m4VP0gkhNI6V2ZkwTX1PNblJpvnERd+0sXeIXspLyXdif9uQtkT8xP3oA60LO05MhLKsJCNgEAGSBqy2lrbTW1o6OPwhjBPH9+8Ig4ztNDzpba5HxgZZIJn/ag8mKVmUi+rBh8faj8Cg95WSl9kvaY0S+vLaGkcE6y4FrTBCJfQ1j+hL3pKIgKeKJAxYwpOGDVh0ciJJ0/nCHL+QUqkCHWNlibmIsgIlcq3dj9yRHy8hBvUmT3j+T+bPX7w/dUVZP0bAJAKkDFiZzKK2tpb2nBLytyiZ/j8mgUsK7aJs+GsydPUfrEdPX9BM4L4XE8Tun7D3N/+licDDDz3yDpgrjialnRLb002ezuVnflPiMfNMIuVwYNvCtuMi5cjM7EFAup//SoOZLoj1BkHV79AzDdKPlrQSHEJYAXFPKTrhoqX0jLgCZTbf/W0hVE8pUYi3HdqYLiSnSBbxyWT14kGAhAELuRqObs20X49k011KiGYNJQxYZ7e0tBwYD6x0uCLh4gZoU6CjUWlNfOmvL32k2laaCdz3ao8k96fiN3tj7AWE2N8lxy6ZiK/vnySmlj5hf9XZ2RlNmIJU5Kp3+Z44i9o5wfpUhwASOlPwwBqYfvh0/Q5jZENo/WEgrKu2ktjwnGcDVqWZlHS87Uqo2RdDBUpfSf8dkGVnCXmIN6kz2loWnUdcSVaPETCGgNMGrI6FHbNbW9quUUX5d6HEshEoNXki/bYRbbxbOwI+hjxS+zDnRjxYl8S0X2y06WpOS8uihXVhxIOtRWD7xJ0fgHCHWCtgQMGU8n4acGjNw8DroZoHWT4AISWvsVxEFs8YAiQMWBuWL19usJJyeq4x+GMg7DV5psMtY9AqVJaUPbAeAFL6fT/SLZvN/gsML4uUqSXMEEL5jebmjhdYIg6LwQg4hYCTBixdHae1pf2bBc+/ByvrNwHxcnpcMG/evAanZsRKYWW9Ffqs1GqIUA/jIfrMkP3af/qCcg6sQTyk8M+uHRgeYTsCLS0nzEKxhktslzOAfA8fcvj0WwOMCzQEXr/kPLAAxPMzmcwxgQDhQU4jgGqkFDywzBpkfFIhZU/BW5VWHr/wr0C6BqwYK1AeMuOgr0ohbg9/uiyniCqvKelfd8wxxzRaLimLxwhYh0A5w491gmqBdJgLDFcfhsfVf7D7Pvwby3V75vjGibzo1uDVseFFNvKvMnWIW/tQqe6ufdCIEdQ9sKAuvDFeqxN9j9Ccdx1HICUKV0IFcpWVEAJ1nVnvi+ETL6Ui54GlNZQqpT8S8ZYwBPByONN1lZEP1agBC2HXhAwaHD449vlOOFVEjOGj+jktffEW4E+qku/Y59Ngj5dO22//RHqgVYkPd2MESiLghAFLW6czmbaLdkzadS+0+CL+TS2pTenGD6PZCT1Lix9/K76MqPilMCcBytr+sx7qCxYsmILx0+uh4cjYgzZv3PxKR2RlMatAoLW5/c24uJdU0dW1LkWZKn4/UqF9YXSxHKkuw5m9vaOjY9zwJt6jjADmexLuC85XyfJMV9VThAwaMXrguHAt7Y7mkDrnGckN78GxPr+6buv6J0LqPk8S3LGUUuKS9pb2E8bqxscZAUbgWQRsN+x4WGC9YdrU/f+J5JLfgdgHPSt6lb9QVautue20Kntzt5IIqFoMhiUp2NwohfePeuRLpcbPrWe8S2OVFBe7JC/LWh4BXeQCHgRfL9/D3SNYfN/Y09NzX5QapPyUzuVBcTug0OefSVEx1qk0AgMDA7NKH3GrFb7jphfldJ79SpnGyq2TZ4S0jY2T9TVB1gPdk/HPf0NT6gvw+V07Avok7HoIc7lm/vzFzn80SMJksY52IGCtAat1YceJCBe8HXFL1wGqul4SlJQfsQNuR6VQ8mBHJa9KbF/INVV1LNMpJYrk81/tU13JE1F56cX79vmHqwjAdpW+UhHwsig1AdLzvlmq3WRbZ2+nzoEVTcVDk4qUoi3Vu0s1cxtVBFJ6se785kux3qQS+KBDJoQQurABq8LJ4nmk8p2N0tSGCpTIwVYQXvHtEG5glID0G2Y0pgZ0OgfeGAFGoAoErDNgwVtqPgxXq4Tn3wz5X1qFDtV0mc/umdXANLoPQgn2gxFx4ugjZFp2NjaKujywEKGaHAOWnnZf6vxzvDmMQFum7WKEBp/usAqVRP9HT0/n6kodDB1DFIbQ+RkJbhJ2645WgoqxSiUQQD4aEoaZYjFtzAsTIWUTkFyh9qiAEnjb0IScgcawskG/umXwCYWLlgDDlgqU8Jz+G4rK6FQxydukOBNRR+cmT3HWmBGoHQFrDFiodHRkpqX9V/CWug1qvLx2VSqPgHvmpZV78NFSCBQK4iWl2sm0SXHH4FefehRStL/MjYZGvqG5+YQZo9u5xQUEMpmOl2GxQvcFUYlvYB5gS4p+QyXCe6LnGg1H6fsfj4YTc4kdARqeRTt6e2951BSWTU2TdWQAvgPQ2JTy2IBVYSrhskzCqFtGxSdtqkD55NOPfxZy/r2MrNSbv42vRc+nriTrxwjUi0DsBiy9EG5tabsSlY7+gTeBs6CQ5CHRrgAAQABJREFUqReCk/TCrV7AEjfeV2F5wdkJnRI99QoG1/tkeWCh+mdKFj5dL248PnoETpx34lRP+T8HZ6plmx9LN3k/ix7Z3RyRT+/OuHib5guL4JJMZlGbaT5M3wIEFIHFuhoMHzRmyCYWUubvt9/4DRacefaKQLvStFXGy3Xr1vV7arAqYfJCCXXEi5/6mS5eZu/FwJIxAvEjEJsBCx5XkxEq+CkshBFyIc8DFGnTcEildEVC3mpCQJ1QU3fXOiuvs36RabuWl8HnLS0tHS8sc4ybLUQA4cDpXeP6foEV3REWiheWSN/Dl+RdYRGrlQ48sP5S6xiX+uMZ+kmX5GVZgyFAIreT6ZxORUrPfbVhxYoVfcHOloSMomDULTdVpq+VcnwrtHflu/6KwySLzFRQe88hNQ/Fyz4xdj/uwQgkF4HIDVjNzc3j21oWXQKPqwcAu34ZHh8d/OrM5uaOF0THz21Oeq6gwcvd1qKi9AXlDWQr9hjj4LJly1IwwM4coxvFwylP+HTD0AjOWLHP/4ZQ8pUEVdur0hbkTvz23p04/jb2NeoKSsa8PuLQaQTPxchTecaINt4lhgDc4Oe4rpISyqxXCaWQMsUJ3Ks43+dW0cfNLkqYvVYCojJ56sRP4ml6d8Dhrg/7CDyeKa+/XJ8flj9mBCIzYOmv/0gc/I6UbPg3Xiy+BL2nxaC7l/I4j0e1uKdEo17sTqi2v3P9pOjNZrPP1CP3pk2bdC6ohnpoODz2FDxgT3JY/sSI3tbS9h54VVxEWWGl1NeQAPapOHVcuXblFvD/b5wymOaNPJXfXnLsEsqFPUxDaDV95F/R72b7WS1kFcJ5pr1KVH3VsatQIboukhO4VwJbh97j+HMq9XH5GKqP3G+j/NorUHne2yFb0Ub5DMvkweP5GjgSkD3vDOPH5IkjEIkBq3Vhx4mFAX8tEgf/AHgeFiumSry+vbn9RbHK4Apzz3+nK6IGkVP54rdBxg0dI4vS+S/VQ/Wp+bdSV8I4PanmcTwgMgQymfbTlJA6sTnl7cmC3/8tKxSU4nYr5DAnxOE7Ju/6mDnyTDlOBGSBxjNN+d56ozhKSckjx0oDhtH5q4H4jqYC7fc8z14DZjbbeRvWjrF6VtdwqoTd9TBPNlwZNlGmxwhQQMCoAQtltztQEvQ2hHXcDDfQYy0BzIMnwkctkcVaMdrb2+cg3GiJtQKGIJgvvLoNWCg5QPvFZgycpRCzEZr2hTG68eGYENAfD6QSvwR7hLrS3aSUX+vt7d1qg4YwjHfZIIdRGZT4ADx1XmyUBxMPhIAOa9dG60CD9SCPxjPNl9KwUUbNCoyxZQPxTmwYK8sUrlEcKX1KxspR2vu+6WtlFMuaGnb1b9MfTJAvOXkb3rHPwjr6zcnTnDVmBCojYMSAhQTtx7Rm2q8Xvn8rFvgLKosQ/VElxLK2BW22GNSiB6AKjn5BfQTdjJwfVbA330WKu/L5zrpDfeDZMtu8sHZzwMvvBciLs8huKZMnHTxNW/Dx4DfQfBxl7fGC94QvCt+xRkev2GmNLOYEaRRF72fz5s2jG2JuDjtjlLXxavNDj/wI10RzYCZEqq1N6EsbM8p0HN9xMPAl43kMDxcrcyAFPofDHugTChcdjU1x69bHHhzdbE/L2rVrd6Aq4VshkW+PVBFKIsX32he0Py9CjsyKEbAegVANFNprp62l/adI0H4XPK6WWay9p1Le5yyWL1bRBr2vhHxrrEIYZq58Vb/3FWSEd8tsw6K6QB5ejfLHe3KnuCAveRkxFwt8KVZAUTKLrHKThg8SX6k3l1052kHaIcu/MG5jkLFOjZHi6AmNE7/mlMyEhdXGq00PP/JjfFB4C7ynAxtvkA9njuswaaP2nnx0RlTpb1DOYzQUmGIxzQasoYCM+C1Je9qrh9atW9c/QmXrdlGVMAeHiMutEywagSaplLgOH4waomHHXBgB+xEIxYCFHDgHtLa0f9EviH9iMfFGqB0KXbPwqVNbm1tPNcvDTer+gPgqJCd9o5QpdUMYs4PFwuww6BCgMVf43i93V2UkoI3DKujQbczFn6HCFIfVqFb0DTv7ttvjfbVXailW7/1J+S/uf+9CuNqZlHV0QTe9sNm88ZGf4MPhYKgJ5iWwAYtCWDw8o9ebnDcp1VyT9COmvaO395ZHI+bpFjsCRt3ygLvjfTfhmXEfRpHfe8vrQvcI1tbHj2ucwLkn6U4xa1YjAnUZmnQlIhiuPlzo9/UNBTcW0VQj/3i7S/ldDoEYPgVYjJyMF1jSCxI8CNajWtnfhmseeI/Ul9jAKOweeNLDD23+RJ00eHgdCKDa4OkI3daeV7pqEvlNCvUBHV5gm6KoHnSzbTKZkgdeqFdzSL4pdMemiypV48c3Tbphz8fDwQFKpYJ71CiPwjMtuAFvbMgRyETKgKXPFZw+vJVFgFbC/uFqKhH8XjGckvG9m+66absnpC4ulcjzFbk+P8bpOoyfZszAEQQCGbCOOeaYxtaWRe/dMWmXfkn4Iv45+qVfzhrfNPESR+bKuJjz5y/eH4uRK4wzipkBFr3XhyHCHnfeGWHQokJDP2BbWxe9ioo+LumRaW4/H54Hv4bMpHNe7ZsTpTq7c92/2rdv0Y++QuMfIE5SSn9PVin5x+bmE/heGPE5CO/3/VKyAd6Waqg3ebGvb8uDAUWRoDUr4FiLhvlGF+WkQspUHd56Fs24QVGIXBNlEKrHW7MMSZPNXbmuVbhH/dAkD4tp63Qd13K6DotniEWLDIFaDVgevvCfM23K/vfgBqJLlk+PTFJzjD7MyfEGwZVN6YFr8Oswc1BbQVl5RRnKw2/8+PGHQyPS1d0CzJgniurngwnEAwzmIYEQ8FA04wtYVH0fo5NyPhalL94XCK0IBq1Zc8sTeEbmI2BlC4sZKVm4QXsD2SIQdTmQq/LwwoC/Gnq2DdUVrgkb4JU4MLSt2t8wQh6Kvs4bwOsKoawKLDm3qm4udJLueODEAWfHgg5tmHf+miiLnYMGzIFi/wehz4ayOtE+cLhQHnlHA9pTyNqFgUDVBiwdWoZF0l/xhf9aCjkShoA3TifH015lQ9oS9xOhoB/Fi+/J5BWX6pau3q7/hKGnLEoKoRZhQDGchhQTkUD8j20L2146/ADvhY0AKr5OzrS03wCH+kvDpm01PRjrunu777JZRhgUf2+zfAZkm5+WDb+FVxDdxZ4B0IKQHCzSUBRrcN2XqqYc2PsolfJJPNM837hXEQmcBs89Bw0YQa6ZoGMG0rQS9o/EQXle4PvFSFpR7ff29m6FJ9L5UfGzjg+KpGFN/kbr5GKBGIEIERjTgIV42/kwbqxCaNn/lXlZilBcM6xguDl+vykHfNYMdfuptjYvOhtSftp+SeuXMMwQSd+Ts+uXiCyFqcqTf2pu7ngBWQ1jVkx7jqLia68U4vSYRYma/VPpBu9TUTOtlZ+S6ne1jnG9P56lSwp9/g1Lly51Kx+mQ8APPq99rxPvYweXEhvPuPtLtVfV5tNYrKuUCo7BGEDt+dipvXJobCl3knjHAzipfGejIFSq3zkDllYim129Ave6n4xSKCEN0P37eL8+IiHqspqMwCgEyhqw2he2HwWPqxtg5e7FqJePGkmsAVVl/ieTWbSUmFpjqtPa3PFKIZV+CGAdTHyTYvOOvh2hLSrxAJlNHLF61Zuekv7N8BI6pl5CPH44AljELvNT4na0HjX8SBL25KWdnZ2P264pCkX8GzLeYbucocsnxdJtW7azEStkYOHZls40L/oyntfXgXRZLzfpBTdIEMnt5E+ePPmBkOHfR27/SfvPwg6ZUG3fl8aMfftAc/gH3vPmOCx+ZdGV2J7L5R6r3Mneo039jTqNwEZ7JTQq2aSU51/Nlb+NYszELUZglAEL8d6HwePqCt8Td+EL36stlj1s0TxUjvpFkqop7a446P8GQDaEDaaV9JT4UdDcIKX0gcWP7otNKYWDtR0GL6FuGIeH5WkJRopH6RxDuD9/C4tYXYhgagIRubUnt/oH7ugttbEhcZtCOPozW7avamtro5AnM/b50+9lhf7irfjQ9iEIg0dPhU3VkcCcRnW9h1esWNFXAaG6DimPlkdOY6NYXxcg1AdLwu95u/Of4Xbt5rZy7cotQvnvclP6EKRWIrP54Uc/GgIlJsEIOIfAPgMWFkbP0V/3CilffzXWZUrTzmlTv8BTkA/r9x3Hd5R0za+fvD0UYLx6Hb4s/RYSlf2Sa4+0oUji+yId6sIXiWJnhyIZfSLTYBy+GQUgXkNfVXMaZjIdL0PFsTvB4b3muFhNeQeu4fMgoTMv3DLl/xzyJqUa4ciTp0UVZQ+HOYyEpbZ93DdPwXvZX2G3aq1mJAwsgT1qiDzTAutfDb5CenOr6udGp0fgzbrNDVFjklLRMlgORRGWcLPXylBmhn735HtuxL3xF4bIW09WKfXxlpZFzdYLygIyAiEj4M2bN29Ca3P7pVgY3bvn617CqwjJWYUG/w+6PHXIWNtCTsKD41MwXumFVTI8rzTyUvwul1v1QKiTwCGEtcDZhAIQv2hrWXTJ4GzUMjLhfXU+od3XrJ8DFM9PLhzyI7iG73VJ/+7u7k1YJNzikswhy/r8tPRva29pbw+ZLnlyCxYsmJJpWfQD3Df/AGUPqFZhKYOHEILHnGr5WNtPml2U+4RCynBvcjL/UbTnHqGKkyOBI1KBsr+QvgiqPTJSvYTspz2lrtPPi4Toy2oyAoMIeOOaJvZgcf8F7FE12ASZ6pcV+v2bUelnWpDBto5ZcuySiahYthzyfRL/8O6SmE2hKtFnwtR2T5LiQ8KkmQBaKSXUl1pbFv1ee3wmQN+6VWxvbm955untOo+SvmaTY3AegRxuVnmEDn53RLMTu0rJq50Q1JCQSoj9fRjxYIT9KOfrqA7klpb2JQ2ppr9Lod6BEbU8q5+B0TRQThsyycnrSWJfzfRIOh458Lhz3gOnmikL2mdPRVWyERl4NpGY/zVrbnkC53JSPdP1E2JOQ7rpO0HPcx7HCLiIgIcXpJtdFDwCmV8mfG/l/PmL94+Al3EWOrfXjkl9umLZWcaZ2cZAiRu78l0IwQhve+aZZ2aB2r4Q3PAoJ4GSOlWHwmnjTBK0DaKj/pqmc135UnTj5eToIDQIjemTvng79IEdxL3tqa2P/xpzuNk9yUOVWKck+Oymhzav1PmcQqVMiBhyhh3S2tJ2DR4sf4JaM2tWrQ6DxLRp02aDn/PJyU0bZfAONafmebF1gGIPrEpT09cnZuM43fc8VSTjgZfNdl2PjyW/rjSfpI8p8eY9FeVJq8nKMQJ7EYBjSsOV2MF1z1sJBF7amO7vxUulywtIhAwueqdKyTym+ZgSOpJv8qUM1ftKA+b73mzywJlV8HAYZzpR6fQLOjG5WVZOUfcQ0n0uvC/ugdT6iyLdl+eqp0X+b9dtXf+surtlHdetW9cvhQw1/55lKlYvjpQdxZR/J87xN1Q/iH5P7f2UaW7/IHKG/Quf098EjWEnCbCpOsIHi+m5AThaNwRuvqa9SkjgNDhx5rGy7vyoRSDP8+nMdQnF68mXV4Jc7E1eSr0bQgTyQI1d+DAEkOryjoUds8MgxTQYAdsR8AZziii12nZB45NPPhcvlbnW5o5XxidDMM46eS68OOBhp64AhQnBqDg+SokVudzq28PWAjnE5oRNM4H0GmA61/n3/tHW3PaKBOo/TGUkaV+I6zWLpeuPcIDDUzU6uH4ROviNYUA5uJMqSP2hqOCg6KGLjK9l++Mcvw7n+k2c4F14KKjy2mlTD7hLSvEVgD25HsBVPQYJKqFxaXMGrD2h73TSbaQ8Mh449Vw35cbC85fye57atWuXaWNvOWiNtOvwaUQVfcAIcTeITi14xWs5VN+NyWIp60Ngz9d9/jo8BoxThfRvxAv3F/fkPhqje7yHtUdLW2bRp1PS/zskWRyvNPFyV573aRMSeELOMkE3oTTnKin/1NbS/lPknas9bMZx0HR1QXik/FEqH16SYqHj6oQp/kaZVm8BQdg83N46ezsfglPNb93WInTpT9LPKDyrPqGLyYRO3W6CEoarM/FOcSc+hvwSp/iRoYjr+XUYJEjkdurv6uraGAqWJYikUilSBg14kpMyYJSYsvqakFuoPgIWj5bikbVr1+6wWMJAonXnun+a7GetbN208ZFLA4HHgxgBhxAYNGClm7wbpBBPOCR3HKLq3BAffmbr9jVYZL84DgGq4Omh5PbrPdlwty6tiv7jqhhDtgvO6Zuy2c7bTCiIPBt0X2xMAFYFTVgp3oi8c/9BWOF3M5nMoVUMcbpL28K2l8Jo9zsYrtbAI2Wp08qEL3xReN45QRNShy9O/RR9Ib5cPxVyFMbhWXXZ+KaJ/9Gh7kiarHNlkd30BzA8o98KXf8Kw5XO1/KiMJX16vLAEhTCpR4AnrjUDG3FFAWM9oIzMGPG/jCs81YWAUnimiitHuH8ZzLlXwClnyqteCJaP6U9+hOhKSuZWAQGDVidnZ27sHiE1Zq3MRFQ4lgssv+CL6dXLFiw+KAx+0fTwWttXfQqVBj8C0pu/xyGm9nRsLWai+9L76PmJFSMsRlwG+Fvc6FUqf8imfHXdFJjM2xioyqxgD0F1+otypNrcd89DZLgkuVtBAKf6enp7BzR5vSuDmXGRN/ktBLmhIfBWl1R6Ff/0B9hqBmy9H0s09x22TNbtj+IZ/RV0NXIRzDp15EDS0nnjTO4vu43d4qCMpUwS62KEA8sX768aBQv14kTuCbKTQHuQ3V4a5ajakc7PnxtwnvkB+2QJhYp0vgwep0uBhQLd2bKCESAwL6vnUoWf4BF4/si4EmBhcbtnQ2pgdch/OHLwO7ynp6eyK39J847cequpoE3CqUuFL46mlfBw06tq+F99ZdhLWHuSDHb/cCmMAEJnRYSu8sPqKJ4D7wVfucJdXlXrutWcIHNx71N505JiYY3YdVwPhQ4iq/VCnOoVOchhx382Qo93D2k1OeFlEvcVcC05OpI/RFmoN//Aj4SfX9cX+P3V65ducU0VxP0tbfVM8/sWILn85twHztDStFggs8QmmpADqwfsl/jTzWnxgH2dTftVaI9r518ApWcKrIGjJLaBmokcE2U0Rsl6O8vc4hEc0++68etmbZlQknn8heHNAFzG1KN3wStc0Oix2QYAasQGLaOwgtjFtK1WCWhG8JsQzjA1SrlfweGrH8bFhlJXxdlpD+YG+b1WBBPNMzPRfLPpAe853fe3rnZhPA6XwtCXraB9rDrxwQvpjkMgXsQbnSF8Pzrs9nsw8OOWLijE2lu2vDYy0XKfxsWPWdCxESH9FY5RY/gg8BLXZjfKvUZ1Q2ehd24dbSOOsANpRDQH4au8YV3dS7XeWepDja16WqC06ZMP0FJdRaSCb8GskWZ8PvhnlzXjCB4wENsOorVPBpkrGVjLgUGXzIlE0K+/wz7FQ0DtBRX9GS73mUKK9fpzp+/eP/G9MDjrutRXn55LgqkXFX+uPtHmptPmJGShX9Akyjvw1YBh+fQ2cgL9gurhGJhGIEQENjngaVp4UT/Ab5+sgGrdmAnISfSRQgtvAhGwDsw/Pqi8n6dz3f+t3ZSo0doN9DGVGMbXpxOxyydji+6B7LpZDROQ1o+Z8p4pXlMbJg4C0k22Hg1BPCIfr5ASvkNoVJfgxEghy9rv4Jx6DcwGj8YEf8x2egF7H77HbAI7tvLkEjz1cITBxD6Yj+m/nV26EMOnzO7cvYbJ+vRU0nvE1KpVfXQSNDYadD1fZ7w3wdPzL9J6f9EpuRvkajbGu8BvdBtaBhYjHP3NDyjT0EKpv3ieTiowB41+DCA8MF4pA7zXMZ7mOnzwvkwy31415MvbR8Ruj/S6QKduS4xTXhHCXy/KEHOyqZ8ftXGTKbtI1LJy60UMAKhsKa/vKXlhHwut+qBCNgxC0YgMgSGGbB29O24Hp4l2uVwamQS0GP0Uqj0UlRX+iKMWQ/jnTCrfJWTInWPSBXue+qpp9avW7euv5Ta2mPjsQ2PHY5a60eoVPEI3HSPQz9tUDwaL8ZeqTHcNgqB+yZPHTyHRx0Iq6GYEnPgccdbfAjgWoAHixStMBp/E9fZP5VQK6Xn3TxuZ0NXxCFH8IjMHCVVGtU+FcKFRAcMzPCKdH8xGPX0YvF5IcJEc1HzjZpfNrv6Vnhy/BG3kJOj5u02P/VipeTXVUF8Hdf8P3CJ3QhP5D8VRGFNPp/fGZVuOhzY8xoXwAi5CNf5iUIMHIfrHvar2Lf7g0qA3FlzLJA/qPj7xuH8CIzBPiJlfgx61G58ZGaZw+41K7o5kMKYDKnznVG4KMqAIRuSMf/ZbPcVeF5oD/iTykBBvXk/TxSuxf3r5ZzzjvpUJ0u/YQYsXVIVFcB+ipv2hcmCwZi2hwLLZfAaWTZYGMf3xLSp+/u4meqcHtux4O3DC/AAfuswwEnw2JgKM9WgoQrGK2NCkSas5AdXrFgBXM1tmJvZjqZiMgdKvJSRU0oehTxw79nV1K/gqfFvvHfejgXmX5Dn4e8iLf4Dj42HIGJdr6NILD2uUCgcqZR3JIxULwbPBaB5PKgiUeYe0nzZBj0Tvp3Ndv0o6GDXxqHE4ofhVfQKyK2r2/JWOwIvxCX3QiXlpcgtN9Da3H6H9ETeF+Iv8NK6J51O/wvFaXSYd+BNGyw2bnxitqf6j4J96gXIXYZrXulr/nm4/vfQ3fs3MJsQB9axIJUeFus26RIMlsZGeX+wkWOPwrlwGF7OGsfu6UiPVJG8B049MyF95Duj+zzvP+igg6xPw1DP/A0Zq9K+986C5/8dbZOGtCfpZ9umhx75EBT+YpKUZl1pIzDMgKVVlZ76f8iFoEuQ0r11xzun2kClwyLwjyEOcyqA5h+786t/EybNUrTwnj8bCXl5sxMBzIw6Ev8dicvrHCxohYBLI4zG2kPjv6gitREL38dghHocubQegzHSR76aLVJ5g12xiBuPceNgdJ4Ir67nYMyh+Hcg5nxGod+fCUdI2MT0xifAIAxh/CfVynRD6n/CIOUKjVyu8x84J38Cec91RWaL5WzA5bgA1+iCwatS4Xtzv6+v+QfRvgGhxo/hnqAXazrH0y4YnrWp5mmtj1L+BFzrTbjWp6B9Iu4Nh+CwvuYPwQclbbBowkvRnqvdcgNPHQnM4SU+l8AtbSuMlsZyFklZJOWRUywWjRn79LXl/CZhwKK7rU+SN07nbZ3r8WETVcnVt+hO6RiaSfGZ1tbWW5Fyo3eMnnyYEXACgVEGLJQfvRv5ZZDMnZPMOjGDLOReBLbKtIgkISmMV5RfbPbiSe0vqhqKF2Ex+yKtGMID8C4zuNzFelX/3bM43d2Ehe3wxeqeZj2UtzARQB6WdGPqbCw8YWZM1lZU6U8gwSy8c8XkZGkembYzcVnD6Dz8Woaxap8AMF4N/obxanfb4B83r3blyfv3KVbrDynm1jrEuv5SrDcrk84TRmbbgrDbJ8loY0KRwRBCN+8FVcAR/F5RBXEbuyBh/XczLe0oriHabZQvApnSwpfXIeXFcSiS80wE/JgFI2AUAXxgLLElOOFdCTS4yQEEYG+4BGFiG6IRVc2Ohg9zYQRII/CUTKtTTXpN2IyeTjAL+S6zWUaWzR0EfD91Xx3SPreOsXYMNZzTCd885tihaP1SwIRbz7lSvwAuUCA036PhDl7wYTQtZ1p86fnnQdrI8iXah4x8rlDpr9snF0vECNSOQEkD1lNbn/gVSFEoqVw7IjzCOQTwMtaVzXddGZXg+IJD5kU2KsyYDyMwAoFdyF90uvb4HdGeqN10o6dDGu5MlNKsrAkEdsEguikIYV05FeNmBBlr0xh8xDLrVULL85oNWBVOXp3/Dn7aMyt0cfoQHE/NXiuWooPwuX/jPvEJS8WLRCzkcXxHJtP+2kiYMRNGwCACJQ1YukoewmoSk1DXIL5M2jwCu/Z8VYEdy/wG99vJYLS/eU7MgREgi0ARL1HnoBpfN1kNq1RMh04iI9P56O5XOYS7MQKlENAL0kDn0LRp02ZjLBbsbm+e9M0uyhWBMMu9U2zYW20vG1f/6mrgkL3BVfnHlLuOfHlj0ra8Az52fx0R40iTk9wN3qTfRz4ssgba5M5ssjQvacDSEBRE6nv4058sOFhb1xBA7pJP6q8qUcmd8lOzo+LFfBgBigggaf7F3bnuX1PULYhO3fnuNcjTxB+MgoDHYwYRgFdwYOONLEoSHsXIWxgYgypPo7lV9rO+GyqRmMbKegwqCeh7Ppm5Lqmnn+j594u+9w7gsqskNslonKZ879rdnobJUJi1pIdAWQOWzs8BK+3P6anMGpFBQKnOg2cc+LUo9Sl6HD4YJd7MixYCWGR+Ipvt/i4trerXBsUw/0cJ00mo65eTKdiJAOpQBDdISI/EYl155gxYS45dMhEzf6Cds1+7VErVkfC/dnbOjYCLMAmjbjngU+PqypdXjqwz7fl85z0o4PEZZwQ2ICg+erRvfnjzBwyQZpKMQCQIlDVgae5F6X0Vf/BezRsjYB0CjynPf2PUpYARWjvbOiRYIEbABQSkuCKb7070S2O5adJVgaTnvQnHi+X6cDsjUBaBekLCdLU19ze1a9eu4Ea8MfTfNXEXBYye1TJVuO/ZHf41EgF8vKdswHoKoetPj9Q5afupBvll6PyXpOk9VF8Ysj/X1tw2f2gb/2YEXEGgogErl+v8BxS5yRVlWM7EIKCEJ9+ORd/DUWuMBJCzo+bJ/BgB5xGQ4meHHHrQhc7rYVCBnp7OHrxQftsgCyZNFAGp/MAGCeWTyO20ee3atTtMTS/CnikZsPzJkyc/YAorGnRJzfeIKZGB7xUjCDm9O5h/sqjeDiWSnCqnQUh5XUdHxySnJ5OFTyQCFQ1YGhFUioo0RCuRs8BK14QAFnnf7OlZ/YeaBoXUWXpqdkikmAwjkBAE5K/SDd5bovaWdBFcX/R/FNWv1rkoO8scHwIqVUf4nCRhwDLmfTU4qzQw2nuCblyxYkXf3h3+WwoBGnnhSmkmpGID1h5gunu778LPL5TEKSGNCLE6ojDg62gr3hgBpxAY04CFSlE3I1Y275RWLCxhBOTap7c+fmlsCtJ2LY8NVmZMFAElbkg3yrP1106iGoaqVj6f3ym84pkg+kyohJkYaQQGBgbqMeAQ8C5S95qcYJ/Qcx8L1nrOFZMw20SbwDVRBk7zxQ7KMLazOd3ofRaS3WGndBFJpcT5rc2LlkXEjdkwAqEgMKYBS3PxpfxkKNyYCCNQBwIwpD6Bxd1r161bF6fL7+w6VOChjEByEJDiNzv7t7+ejVe1TbmuqiqFemdto7h3ghF4rLe3d2sQ/RE6cgDGTQky1q4xZsOipPDm2KVvPdKYxaoeyWwYSy1h/0hM6yr4MJIYgX39fuILT4cSDhBQJ7gKUv2/TCZzaHACPJIRiBaBqgxY2gsLYq2OVjTmxggMQ2BAed5rsLiLzf35xHknToVE+w2TincYAUZgNAJKrJg8ZeLZyEuT7JfC0chU1dKd6/4FAvh/UFVn7pRsBJQI/EwsFArPpQCe8UW5opMTyaunYiWFk2UMHcgl7B+hL1JwBL5fjCBFZjeX67wTBZqSHkZ3gFSpqzGpVdkFyEw+K+IsAtWfqJ73MWe1ZMGdR0AKeSGSHHfGqciOpgKhr7BxIsm8SSOgxB+e2vrEGZxnpb5ZTjem3gsKyQ5tqA/CZIyWMnBImPSp5PoxuijH64eYTeZkqiPhPxkMKihS9EhXIBRKeWzAKjH/k/abcBnnnxQntbYsurgEPNzECFiHQNUGLF0hCRf3r6zTgAUij4AS6jvdudWxeyN4SrEBi/zZxgrWh4D8BcIGz4o5zLc+FSwZjdCGXUoWXwVxHrJEJBbDQgSUqKMCoZAkPLB8P2VsUd7W1nYwpn2ChVMfTCSfc2BVBM6n421XQk9/v/3GbyjRnvimwQ9uXlGHEhaTDYb6fEtLx0uSjQFr7wICVRuwBpXxih/GX65e4sLM0pHxlobG1AdsUEd6/mwb5GAZGAE7EVCX9+RWv5HDBsObnWw2+7D01emguCM8qkyJEgJ1hYTRSE6+K59ftcnUnMoCFS+13Qj5KT+wx54pjG2iKyWt+R6OrdrAntHDERm6hxQlvdj/5tC2BP5u8oT/s3nz5tEx2idwEpOgck0GrN35h9S3kgAM6xg/AkqIv47razzLmiTQvpwbPyosASNgJQJf6sl1XwDJfCulc1io7tu670BS9zdDBdwSeWMEhiOA3C3BvY+koPBM0wYZY/cdFDEi4aW256zZBaO4MWPf8DPT1T3C73mKve/GOisnT534UfT551j9iB8/avy4iV8mriOr5zgCNRmwtK47+3Zchtdo/oLj+MTbLr4U4r8NA97JK9eu3GKLrEgUyyGEtkwGy2ELAj6eBxf35LoutUUginIgqfuvodcnKOrGOtWJQLqe9zES4VLBDXhVQC9pPff1uzsbwivPO933PFmHsbsyZmSOag81X0gdSmjMKO4EWEpckMm0n+aErCxkIhGo2YCF8JAdypMXJhItVjoqBDamfO+kzts7N0fFsEo+FL5WV6kqd2MExkQAOZrEG3ryXeyVOyZU9XeAkfCzWHt+vX5KTIEQAgXP8wLltEGISAPymh7mOhbIkWnUgOXTCLMcnGZ8GOSPz5VPeEBEOtcpz3/l+R88msutzuO+8r0qulLuIqUSP0QOwEMoK8m6uYtAOojo2ezqFahUgITu6jVBxvMYRqACAo/LlFrSmetcX6FPHIfwYiNmx8GYeTICtiGAi+EJ5XlnZAeLe9gmHV15EKb5wdaWtmkwPLyNrpasWfUIqAeChthPTE+cDReDVPW87OxZVw6wqlQi4aU2qCk+OLABo8KcdxzfcVBB+GRz//D8V5j8EYd29e24dELTxKVwVzxixKEk7U4XRXk1FH4l/gGKaLbW1taZQnlfDZObLKpvIR1DdijN9pb2dl+Ki4a27f2N3KPf6853r967X8vf1uZFZwtPvbrUmKKffj9yNm4sdYzbakMgkAFLsxgopi9qSA0sws/ptbHk3oxAWQSehuvuybnurrvL9ojpQCaTOQS37/ExsWe2jIBNCNyjPP+Unp4uo54PNilskSwKYfznj2+aeCBkOsUiuViUWBAIHhKkPG2YgSna9U0Jo/chIETH85rTf1Q82/20T2euS2iq6smXV4Ie5SYdbdTa2nGe8P1V0JPAjTLYbMFqtaS1uf29UXrae0VvKgxLy4JJXHqUkt5vcGSYAQvrzVlCqZJ8lJDj0D+QAUtI9XGsF48qLYn/idLt3ForAl6tA/b27+295REklj1v7z7/ZQTqROApqdQr4Lp7e510jAyXsoH0i40R0JgoPQSUWJFu9Jp3F/Sgp54LGukqj0g0exbeqW90QV6W0SgC9wemLj0Sz7SiSN0bGIMxBi5durQJXQ4do5szh9kDp/JUFT3aeU6LxbRRY29ldN072tPT2QnT1ZXuSR6yxFJ8CV5RLw6Zqt3kpDi5vb398FqFbFvYlsGYMsarWqlx/0oIBDZgaaJILPs7/PlxJQZ8jBGoAoFHPCUWwV1zTRV94+lSpP1lLh5QmatDCGj38S/hK9ypCFl62iG5SYqqE80+teXxs/BZ+PckFWSlqkOgHo8aSSM0rrFRrK8OrNp7bd26dTZG1fWeXDtXcyNSPocQVkTXp3FNlNFxBxwPHi1zjJvLIDBQ6LsEhx4sczgpzU2i6P2subk5kiiUAeHtxAe6teX/iTtHAy//Vb6/XCuF/+ToMRVbUn5BvKVijxIHkSP83BLN3GQAgcAhhHtlwdf49xX6/Rbsv2BvG/9lBGpA4EGvKE7s6u36Tw1jou9KqxJR9PgxR5cR2AZv27fuqYTnsh6kZF+3bl3/Mcccs2za1AN+ifQUZ5BSjpWpCgHlBQ+fUz5C41wPjJFiMwzq26oCK0An6TfMEdIPMNLOIX7KX2+nZHZIRazi5EhQtfeV/hDFWw0I9Pb2bm1rbjtXSXkzhrl+x6xB8xFdpTg6JRq+iNb3jTgS+m4+3/lfEH1ZOcILFiyY0pBq2jL0uKfUuV35rtzQtgC/d2FMAf8mDY5VQhujPo9/VT0EkGpmMq6w1w6O3f3f4/hzwJB9/hkiAnV/WdIvD0i6jXAGYewlIkR9mZRVCKh7fZFut954BcxQjWOOVdCxMIxANAj80xdeMxuvogG7Vi7aiAVPrNfhrRpGLN6ShgBy2gQOIUQ4mfPPNDyXA+tfzbmCMlzOYzREzy0I/X5qyD7/HIkA5fc8w9fKSCgp7SM65BbY/q6mpFNAXd7T2tx6asCxLgx7BgaoZ9+l8IzMZBYtrlZwT3ivQ9/dxi89SIofVjuW+9WOQN0GLM2yu7v7brwMvaN29jwiwQjcNlBszORyqx5wAQOc33NdkJNlZATCQ0Bdu7Nv+8tyuc5/hEeTKYWNgDZidee6zsYL9pfDps307EZAqf7A+Z9g9HT+mYYkvIH1r2ZmlfBnV9PPkT5GsXIEg8piSun8NVFWQRncW7MszQQdGNfX9H6o+1CCVC6lqhTS+zGqdR5c6iCFNl/KHw3VA9UIq7Zt4IPS2/eNVWI7vHd/sW+ff4SOQCgGLC1VNtulrZZfC11CJkgPASl+htDTl+tCAA4pR+lLrEOws6gxIPAMDLbn9OS636wr8cTAn1nWjoDCfH0YXw8vxtCq3N1rZ8EjLENgaz6frzWvx6AKHR0dOqxhqmX61C6O8nVYlLlNydnmiEdLWQmz3mrRahM+t3nz5jWA6ozwKVtCkT2w6pqIlWtXbkEqhXfVRYTG4OmFxuJVUAXfQOhtudzqPFT72z7NpDijpaVFV32uuDU3d+g0Sgv3dZLqes/ztu7b5x+hIxCaAUtL1pPrugSn9G9Cl5IJUkEA71BIBJ3tOgehpzrW2IkNL/vjICiZSkROgM5CxoXAbchJNw8fJK6LSwDmGxwBXeoaL9lvBAUkQeWNOAKBjTf9/TRC4zxp1ihDKSeSaaxcv9YmpifOhg4p1/UoK39KBr5flKWZsANIpfB/sNrwu5GSr2xtbr+A6vQr5V89RLdGT6TfNGS/5M+ULJ439ICnJIcPDgXEwO9QDViQzy/6A/rl+TYDsjJJtxHow8LqzTByXgo1tCHLma2vT8yGsGFfK87oz4ImAoEBaHnZITMOanUhJ10iZiSgknjJ/gXylrXgJrs+IAke5gICKnhIUEr4z3VBxbFkRDyL0UU5rqHZY8ngyvF68qW5omM9chZS7ueEq6S/78v7Kx3nY9Uh0FdoeB8cNTZX15twLym+2rag7ViKGiK9zbXQa4iThdTGqbIeZyim04jD5wzB4h4klIcnF28mEQh9UQ6X9p1I6n4aTBR3mxScabuDwOBCyvMXYWH1U3ekflZSz6PxtfpZjfgXIzAUAfk3WVQvg3H5U8uXLy8OPcK/3UQgl+u8s1BsgDu76nFTA5Z6TATq8D6CMWP2mPQd6OAVPWMGrCXHLpkICKY7AENVIiIsnA0YFZCSlBO440EwaVsjz3+F+a/20Jo1tzwhlbqo2v6E+41TaXnt0qVLm6jpqOcYl8yQaDJ1ZGtrR6acns+Z+pxX4di+MEMU/7gS+1j68mYSgdANWFpYJHV/rCjSSzB9fMM0OXsu0FbihoZG7zhUv+l1QdxSMlJ5sUE4xDehH+c0KjXJyWzbqaT63519247v7u2+K5kQ0NVa5xh8asuTi6Hht/CPX6bITXVw7yN8Sp5FAI6+zt7Oh03psW1S/xxTtOOgyx44lVH3hKRwTZRT8tGb7rppe7mD3F4bAoNVmaVYXtsogr2VOHbr0zu+QFAzhNwMDwGURb9CMnd57hAM+jHYSWeNITo48dOIAUtrns+v2ihS/on4+ZATSLCQYSOwC4vjdyMny1nId/V02MSjpafmRsvPCLfik08/8WEvLV4I6n82woGJOoMArBldReW9NJvt/gIStevwQd4IIqArFMKz7mLhydNhtMBXRd7IIKCCG7Bw/VNYrN+PufRNzaenCrNN0Y6BLqa874EY+DrDUnmKwjVREm/c+415KpZkmIDGdIOnc0A9mgBVK6oIb6OLM5n2kyt2cvBgV67rVlw3/90rOjxYX9va2jpt7/7ev83NJ8zAzfUVe/cRSniDduJ5dp9/mULAmAFLCwyvm/uwYG7Hx997TSnAdK1E4B7h+QuxOP6+ldLVKhQB13LcYDfoxWxXV9f9WNC+EvnI3sQL2lpPBBL9H8Xcvy2b6+rI5zvvIaERKzEmAj09q/+QKnovwX2ga8zO3MEJBJQ3cH9gQaWcGXisLQMNe/hLKefYomoIcmzW6T1CoEOZxCzCyrEBK+TJxYf5x4WSuupv0jfYsMRVCxYsPogYEMqX6sdDdBov/NTZQ/YHf6Zk4a34sa/4g1Q+J28fCZKhfaMGLC2zXjCnB1KtSH/GISqGJtEisgXI8u0J28a9DMbLZ8uQWiRgIFGkpJDwdtgLjM5HVhSFo7Gg/XUgTHiQawhoL6tvj+trfD7m/mr8xtTzliQEEG71EAyXL8cXwvMx+xxO4vbk+1OmTFkfXAXlvAELH2CMfhjFDXJ2cHwtGynZA2fMGVEkvBJLqolz+f6SB7ixLgR68qt/jmfpDXURoTH4wAZv4Cqogtsyna2hP6V1ejZCQarzR2iHzCzirfva8FGlO9996759/mEUAeMGLC195+2dm/sHGk7AmqnHqDZMPEYE5N+01xW8e95HL9be/STu8LoZ9bKfy+UexYL2NfiK9FqcOOzyGuPVY5S1VCuVLB6nr82Va1duMcqLiduOgN+TW32lL9MvhqCrbReW5SuLwMYV/7+9ew2Oq7zvOP48Z1eyFWwuNcQxBlt2QgrDJQUXXEuWUW0nbZhJhyQkJWFyaVImM70lTae39E06nV7yprRNO8y0kzQkaVrqdJIMJG6AgCx5pZggIBS3JQXsQBIMhIuDLVmWznn6e2SvI8RK7Gr3nD3P2e/OaLR79uxz+Txnd8/+z3PZvXtqwWcXeeKqq3as0tMrF9kliKecten+KC9QDyxWIFz8kN60aVOX9liz+F4BP5tyb8WAZZouenkm+k0l8nzTCYWegDVv7e8fmB/gCbpWPnbhjPnGqUpozi8NI9xUfdzff/Wgnn9D9bHCd5/R/eTUY+6kKpBJAMvXwM/q7yeUVVfDW1KtEYlnLeCj05964fCPr1Kvq/GsM087v5Mn+6ennU/a6S+2ApGuIu1KzMwlztgvqhz6POZWEIH79CPvLXsrI2+uVCr7C1InqtECgdHRux9bs3b1DvX9/7iSe6kFSZJEhgL6kD6w1OyWRcfXL/W1eXqdhmq8rFdxq8vmnOltdZrtSi+ySz9e2lXmLPNd2bVyrfI7NQwoy7wzyauU3mqdmZQ/x5nMBjms8d+jHX+zzt60bcu2S4sEMX9IoI2jX6/WL3Luw9X7+j8Tu/Ln5jzmbsoCmQWwfD38HDwjY8Mf1OTen9DDOOW6kXzaAs7s1kTQl6lnxx/5tk07u3akXy7PbGxHvq3Pc/EJf0/0xtrzvsTYzcr73tbnT4rZCdhHfK86vS+vqlT23JldvuQUksCuXbvikcrITTrpukg9//8tpLJ3ellr9ait18TZqBABLF3nTjWAZY3ZUK9p3vdTMG7JAc+8160V5YttXIz3xIIYM6m+VxbMtkOeqFSGb3HGfK1DqrtYNZcn1nxpcHBw+WI7hfTcmvPW7FZ5n6yWWZ0BblD9VuzctPMMtfnbq9v1ffGN2cXrqhv4n7pApgGsam38ylcminbq8VPVbfwPSuB7xiVv0wqD1xR9Imj1UCjESayGENR1AjM6uuc76pnRp35Yv6Uj8oWgjsoOL6y+QB9Vu3243G0v8b3qxKHvV24ILC7gT7o0rPA9OhnYoUAWPfUW58rHs87etdSCOJMU4sd6qadU13faUpz8jxO97sylvDaXr4nsgVyWKyeFUu/zQrwnFuCcXrNmzQ8XeI7NrRKwsV+VMPAV11uCcUk8nfxZS1LKQSL+Qp+KccucoqycOe7edWzZ9A3a9prqdhdZJm+vYmT0vy0BLF+3vXuHhsrT0RW6e09GdSWb5gWe15Xf35mcOqofyHtvbz65/KdgE1OIHlgzM+W6T/b9B7aCk/9Q7o7eqBjIX6uVjuW/pTq4hH6BDGff+7q1qy9Uu31Wq+P4xRS4IdCQgJaNvnvN2te+SVcYfRd5fvA0pJfpzveXl0X/vvQco3VLf21uXvmMPueOpFWaiWUzhbhwVfVJkogAVhWj1n9rivCeqFUzv+3gyR/hCz3P9hYIaJqGH1lj/6AFSQWfhHp8fnzrLwz6TiqFuJWTaN7cVk7nSHOGD1pzqFy2vqcWtwwF2hbA8nX0Y4c1zGXnyXk4JjOsN1k1JuDnSPlU7KYv0Apmnx4fH/fzXnXGzboiBLAO+znoGm0wv0zw3tGR3yvH0QW6QumvLhAYaRQx3f1HTGR/ZW9l+Of8ajicpKaL3Qmp+2NIwyE+4z/r1X/vj1VnemHmp+E1abv7guYrfGszQWpdhCpCb5O6L8gspfk0t0mRAljTa9eu+sFSHDrlNUXugaWe2QQvMzqQR0b3+PPkb2aUXZ6zibSo1y0aand2ngtZb9mGvj10UO+ju+bs36f7vgPO7M05x4XjKkaG/9sawDpZz8TPw6GD/RLj3FCGdSerVxfwVzj/bjruusDPczU2NtZ5K23Y8OfBcKa5uUKG9g39oDK650a9Ry/WKhtf0jFBIOvV3ztp7aHecO6fI2eu0Hty2969e25TRmpibgi0TkCf9ZPqzfdX6oW5TkfXx5Qyw/1bx9toSt5eF5DKr9cFhff7+QobTeBl+1vT+7LHIT6wzX2nvVqVbZSEb3Sqku4JLm6cwqh5pyBB3Zp10+d3qsHe2pl27FaXmLJfiY+FUYw5V0Pt/qkoR4Lm9vK9sGrd1OGs67O1nmBbugJ5CGDN1lAr2D2+d2xkuz5sP6ANzZ2gpWvWCalXe1yt14/kj+7b962nO6HSNevobBF6YLXkBEbv0e+pt88NUdm80Trz9/KaqGnGxjQEHrfW/oktuXX6Efuh4bHhB9LIhDQRmCvgh2kpkPW3Gjb+Bl1l/F09d2oy07n7cT8VgXv0w/o6H0Q8cQHp7lYN61yXSmmzTDTlH+WJC//C1anmYAXCUxQL37HhvycWqpy1BxZ6iu2tF9AKv9/X71jfe5mbcdcO9F19YxEgXnzxua+qHq+MTVj3Lb+qcxHqGFodchPAOgnndLL8efX0uPDkD2R6emR7RP2fPng/Nh1PnXfihLkDe1zN8Vb317Ienj9nU5h365zAvd7KDQ8PH9Bqor+tH1br9Zo/1d8rP9TrTYz9FhOY1NCGLzprt+v9+IaRyp6/GBkZeXaxF/AcAmkIaNj4RGVs5G/0nt+ooMq7lMdIGvmQpvmJOlTe7Gx8id7z2zVk/z+aGS443/Mtl73lNG0LfliHjsFUfzBoOfje+XbBPmYFwldrOo0OcoUNYLEC5as1f+uf1+/Ym5UqK0ALQRe+burv77+49crZprh///7jyvEL83M9Ob3K/M08zkAgbwGs2Sqrp8cL/gey7+mhDf+ovzgDi07NIjHW3aVJoN+t1ecu8lfb9+3bp5NobkmS+OBVV/ASUdKSHljzHU7MkTX8yRcOP3e+Jn6+3hlzt/bRP25NCMQnHO1Hlk91r9HQzfdVKnvuUXq4NoHKS1sj4IMpCqp8WcGVbYmJLleq/vv5cGtS79hUJvQL+lZ9B79DAcLV6mH5G5oQOJXVICfPmFxfBOXYRKn4nLIpwNQB1brou/lA9T7/XynQ19d3jrb2vPKZgmwpxamc/xVEJ61qJMdnut6jxLG35jTrSru3bdsWfGcAXVjyQyJPnYvre/u5008/zffM4tYGAd/DJLc339NDhftIX9/gp61JPqmD5e16nMugW24RFy6YhgW6f4ld6eax0aFHF96tg5+ZKcYwAtfiHljzj4iTVyZu1fZbt27dquGF0Y266vdePT53/r48rimQaGtFX4u3TiddX+7oIbs1ediYR4HR0aEHVa6PqKfqR2em3Ns0P9779Z3yVm0r5bG8OSvTlDH2Tl2e3uWi+Ct7K5VM5kzRanTr1XspZxQNFydZcWTZfzf8qsZesL6x3fO7t+ZL9OfR3BYU6FJbB/+eWLB2cRzT/gvqpPeEXzhJwdEtkSt/Tt+N/nuxk2/nxzNmWEGs7Sd/1wdpoQtLj2zt3zaqj4t+X4HE2c/v3r1b3+Xc2iGQ6wBWFWR0dOhh3b9OP443miT6qA6eD+sDwXeF59aYwKTcbjfWfmFy8sh/dtRqgo05ze6trqGvL8aJTTnV4RZzaf08WXr8+/r7w61bB/tMkrxL939Vf6v1x60q4MxRvQ/v0cPbFET++thYy+a3qebAfwQyEVCvLC0sYHb5vy1btq8t2fidzrh36oLTVm3jgtNPW+Elmeg9775S6i59VW4v/vSpbO4lyfF9pVLp57PJLZ1ckqQc3/HQHUfTSX021Ujnme9IMf1Mk56xU/dnmmFgmXVP2ydnyubdgRW7ruJamyQdufhSXTrp73RywY1rZi/sJqUd+l7058HL08+59TlYa0q6MH36UlPWd5+JY3ue/jUdUO3p6ZmYOWbePLcs3dPl/XMf13PflpK73HTpVDpRlBx/tdclrvyBKEk2+P2irvi7i+0/PT19qOSWnUrf77tyovvJxV7Dc/UL+GMquNuWLVt+pmS7P6iCf0gng8GPrU25AfTjwmqIoPnS5PEjX/NzmaScX2GS7+8b+HNr7CcCr1CsCZh72hms9HOJxVPxDhfZt+k49FeiNgZuupTiz6ju4wogD+kX/R1Hp46OtLNNllIBXoNAIwKDVw6+bro7vlZD435ZJxo79NoVjby+APv6OTzv1Rwgd9lS6c5y2XzbD8EsQL2oAgIIIIAAAggg0DaBIANYc7UU2d5sXPRrmvT9OmfMqrnPdex9aw6ZxHxdQwVu7znac2fKVysLy7y17+p/VYD0+pArqPfEwcro8OzVgrzUQxM6/mxkoms0tPGXVCbfFbeIP2yP6cP1AQWsNDTQDSU2GVb340yGCeWlnSkHAlWBiy++uHvVGau2JsbpPW+3afsm/XVVny/Ifz8U+BG95++2zt15PD5+D/NJFqRlqQYCCCCAAAII5EYg+ABWVdL38lCXwkETxer6ba/V9jXV5zrgv+/2eJ+/0mui0m2VytC4Hit2wa0Zga192/bp9Vc1k0a7X6uD4G4FsHzvh1zeZt+3MzNvMnG0VUPqNOTI9amg5+aysAsXyo+B/x+V/QFrou9oTpt7JycnH6KH1cJgPNPZAn41vGMrjm1WxGdAJyFXaaLpK/SN9bqAVGKV9xGtEHq/ccl4Sf+n4qkHCVgF1IIUFQEEEEAAAQSCFChMAGu+/on5sko7tcLeTp1o+jGoZ87fJ+DHE7rK+4DqtddEtjI9fWwPJ86tb00FsJ5Rque0PuXsUvRLvGoluxuzy7H5nAYGBs4xM+YyZ6M3KQB3qT6kLlVwSPORtf09/Kzec48r0HZA5flf9XDcr55V/9XV1fUYQ4Oab3dS6GwB9cw81yb2Cg01vlQ9qi/S8O0L9f73KxGf0UYZxdic5qywj+o791HNYfJwKbH3Lz+6/Lv0bG5jq5A1AggggAACCHSsQGEDWHNbdHYOnmPxZp0Y/6IqfKVOiq/Q834yuRBufs6qh33ASifPD0aJub+0rHQ/P5jTbTr9mFqppV9/km4u6afurPtEpTLyl+nnlH4Os3PflUobTFzaqPfCemud72V5jubYOVtBpdfqh6YPNq7UX4/+6pkoc1r7HVFQ6kW9vzQpsHtRaT2jz4gfKTDsg1VPucgcimJ3MFoWHdB77oj254YAAhkK+DNfWmsAAAu3SURBVLm04nK8LonseTYx5ysor/d+crYCXKs0qewqTS67St/pfvoAPySxnuHIvsek/171Q3qf12ufVxrP6f4zes8fUm+wJ20c/TC25gdnntlzgFWGJMMNAQQQQAABBBDIiUBHBLBqWWt509da27VJc1VcoRPYy3UCe4FOXv3k0vWcANdKstlth5XAY/oh7VeMe8wk9qHIuQdXn7/6e7t27YqbTZzXNyYwsHngMleyi64w0ViK7dlbP8aur1SGb21P7u3NdTYIaW3NlVZXrlw5wQ/T9rYPuSOQhoAC3T1aae8VAexyuTxNEDoNcdJEAAEEEEAAAQSyE+jYANZCxJs371hdKs1sLJnk9cZGGxOnK73WrlJwy1/h9T08ztaf7+Vxlv4Wu1Wv8moVQDehq8XP6Grxj/WCZxSkekpDEp5V75indSX5oE6s/RAk/xy3nAgMbBm4VvObfCUnxVlyMTQM70rNiXbfkhPghQgggAACCCCAAAIIII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"></image></g></g><image 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class="featureIcon_5IMF"><i class="feather icon-zap"></i></div><h3>Blazing Fast</h3><p>Pinot is designed to answer OLAP queries with low latency on immutable data</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-unlock"></i></div><h3>Pluggable indexing</h3><p>Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-rss"></i></div><h3>Near Real time ingestion</h3><p>Near Realtime ingestion with <a href="https://kafka.apache.org/" target="_blank" rel="noopener noreferrer">Apache Kafka</a> supports StringSerializer or <a href="https://avro.apache.org/" target="_blank" rel="noopener noreferrer">Avro</a> formats</p></div></div><div class="row"><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-code"></i></div><h3>Horizontally scalable</h3><p>Horizontally scalable and fault tolerant</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-shuffle"></i></div><h3>Joins using PrestoDB</h3><p>Joins are currently not supported, but this problem can be overcome by using <a href="https://prestodb.io/" target="_blank" rel="noopener noreferrer">PrestoDB</a> for querying</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-search"></i></div><h3>SQL-like Query Interface (PQL)</h3><p>SQL like language that supports selection, aggregation, filtering, group by, order by, distinct queries on data</p></div></div><div class="row"><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-list"></i></div><h3>Hybrid tables</h3><p>Consist of of <a href="http://pinot.apache.org/img/dynamic-table.png" target="_blank" rel="noopener noreferrer">both offline and realtime table</a>. Use realtime table only to cover segments for which offline data may not be available yet</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-bar-chart"></i></div><h3>Anomaly Detection</h3><p>Run ML Algorithms to detect Anomalies on the data stored in Pinot. Use <a href="https://docs.pinot.apache.org/integrations/thirdeye" target="_blank" rel="noopener noreferrer">ThirdEye</a> with Pinot for Anomaly Detection and Root Cause Analysis</p></div><div class="col col--4 feature_2oFu"><div class="featureIcon_5IMF"><i class="feather icon-bell"></i></div><h3>Smart Alerts in ThirdEye</h3><p>Detect the right anomalies by customizing anomaly detect flow and notification flow</p></div></div></div></section><section class="topologies"><div class="container"><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="ingest-query"></a>Ingest and Query Options<a class="hash-link" href="#ingest-query" title="Direct link to heading">#</a></h2><div class="sub-title">Ingest with Kafka, Spark, HDFS or Cloud Storages</div><div class="sub-title">Query using PQL(Pinot Query Language ), SQL or Presto(supports Joins)</div><svg width="800" height="400" viewBox="0 0 800 400" xmlns="http://www.w3.org/2000/svg" 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RT/9sHH3SdF5yFiLaXZLHqGMhSRihaLBpbitA2sDWiOGFu0PKWIAQyhMKJI8dAcajU+B4xSqUIp5kffvSRVcu3oK4sKyUlcgMScHUMFLRAQz67lDa7FB1RumE2E8s4ZkkJwmYpjhwDxaHi7sUisGfvXjnujM0x302ieEtJ45LOHWvLQNicOHIIhBGQmn3CeUS/15aBohVx17IISB5W6ir5P1S07mtKP88kOQYyibaBvKRUeKoY3fPC9Y06TJVawiWVxTFQEjI1vZ+0Vq9pdawpdtLZmmMga5pIT0GkZgrTI3sRNKrYFzsGUi3F1N8UkupEkupBurDHyFJqCZs0gNSWgXR2+na6Troat+7pVOFeKi9mg5Tpv6QmRlx5astA+AzTRSNGjvSwtdeVnkunGgSkZp92tZHT+2iXa8Hf8NTDKDNUqZfrHBFxVjJx0iQPJxzsIbBQ5RPRbdNMvQtC33oNX21FfLyVyTPPuywzpZgoaWlsNQPh6BungHithGmSJCF5QG73LOkP4O87hUzyJqIBZwt41cR3gu1+4XzBA+bpM2bgJLEdhJX+NmrUKLE+guOZOLKSgZhp6Lw2bFxhphZDKbdao1QgJqK7obRoq/eem0IayXSesePGeTg6lPD7Ftc589z7wbJlfpLGdJ504p5FgJDkN8MaBlr+yCM+HXSEcqZoM+Fkgr/nn3/exxLSNt9x0uYGIy1tH+ygpJZvLOdxURxHlSsHYkE5YeJEo25b44Aocw/n6TbtlWBuqc6E08m/7dljlVkDe7O77r7bk/JE1M7BYqUz0KpVq0TNj8swRZ53WdqsWbPGt4WRrqrRUioeELMv9bWJ2JtJLvevXbuWWN1KGIh4NVRYWiiQWGuhH8aoMC1I8k4pf2V/eOONymb3/koQIkk4rF/Y3e3bYFy39IEHfI4hJPtSOwaSRTrSikjVkGox1UpWOJKtsUvqxN/tKr4Ms6uxjEMZIYBJcwYYerzQVwa/O2bOLPSu7pfmzJ0r6jMdAUK7faWxUZIOhX+tJjJOUqdA9HlOhUQxIbHDbzhLK50+w5PqxX021keVhWqVYv2fPP54Kzhbu3KW/Y09X7vwneIMFESg62R1mXab0LINzPsE0WLWMT04MUB8prz07HjrLfF+FMUJb6HTpk2L3tZ+nRbuUbTixECV2sxqR0o4QTrbqZMnU+PN5CkGIzBi/+DgN8+7up7FwfznBw96f92xQ7QvhcvLkcfUqVONDBj4nGs3y4pVuurAtmHAbfquQ1LHrD5m7FjRtX8ezBgcjqnI6+06Wp702j3LHg9hjYnZlgPztHCeIgyEoKDKUbFdA9jwGwGKN2/enBt7Rl4YR1pIUBSj44qJTqgodbv37Mldt7Q871+yxEdcbTJCHQ7003yAa6+oqahoaYDb/juKqhs2bMiMv8lwjWWwY793WvmPY7kajcZdJF0OScdNmOBNUoftJgdllqbr1q1LbZ/UB/JU2jFPHrQ8j6XPr15+uW0bsFxDU7xuxPKH2ehL5ejjvZ0729YxWjf07Zhl0W1DXC6lVRHNN3ydZfbh+VwVC2cQ/m46GnQ47yZ8f/HFF/u0Q5MwZd/HjBScp+C/LWwegB8HPH/2U2doRISbqqRrKBNXRVkGtqBsWjQRpk+fHqTnPgsggBpQmIkkddkKFK/0K5xPhdV/WtrNiokCBygml2ZZKnNCMXtW6jPyZX2R51AEnTl7dp5X3LMOAasRyLs3LaXKY4s6h9Ut4gpXGwSYGfMIdqhYYQbCsMyELL426LuC1h6BKwk2P+0qVoiBEKnaehbRrrLuN4dAEgKIrYuczeUWInCYVxf1HKZkxKj4M0ADvJP18ZI6jrvvtdwBZznzicMqNwNNnjLFiBpFXGGT7nF4d1ydOXCAl8den9Pt29UBHeYHbjmahG7z719QcV+LUi4p3MqVK1vKi0Uz0/neyRMnvMOff+59pU709+3fn6seceVYuGBBa1k6d948a1Vl4srt7pVDoKymfOYZiIO94QlxIstVIfvbVBbt2EuXLmlREwnnHFhXXrx0yR+iDMbGjx/vORF9GKHmfcfS9JWNG0sNvpkZiNPhqpY5KF8eP3q0ZZwWdHSp5gzPZvedOdMyUps1a1ZldZeq50Flx/OXbdu6muKXIi9OZWeeIL9M3FeVIiNCgAMHDrTUQKQZJwAk7nPxokX+NKVtMUHtlepOcQZizz77rN9JApY0K9M8bZyJgapQEg30p955991MZcxT6aLPPvzQQy3FzjqK8C+qjfJvXn01EctOYSKW/1u2bEnEIW/fSE3ItFWpDbb27UC871//1Z83f37LS2m752z5Da1omGfrm2+mtjWH43UcHLJircOYMZpXKqgoOkZfkrqGeQ4p8+Bt27enlkuqDFnTrWpZm7V8bJBhnLwOTZC0Iiyqar+btX55nqNfnVFHHBKuxtp2VJOdBBXyg2q/Y9K2Pk8jxD1r0rw4Lv+4e+CIY8V2y7W498L38PAzTkkhiVpRd8qrHJq3vm0ZyNTswwjx6f793ltvv922PHkrZ+L5Hz/2mI/Iu+oRG4HLdcU869ev14Yh+yJTbrJ0txV96oqS3pYZSLKUKRFsU5aQNPzfP/20VjNPFFhmatSbqmAi8IOOKn8Eb2bY50TLnnZNPxin7HmwCq2ifmnli/4OHhjrmfJZl8hAphyDfPb3v9dizxNtqOi1yeVuOG8cefxx69bEdgw/W+a7CSeGZcoXvGsKjyC/WOBNGcqhjiOxsQsqZ/ITO/5/WbjQWHiWop59ymLCvi9sXVo2PV3vH1FeUiVm4LTyxWoiEKdHmoKlm3Q+ptJHiVX5KzMiwUJQUET1XgcWQRgX/JxPnDy5EocfQT2QNDIIm/BHF+QZ/YxloNEGGGj/vn3eRx9/HDsDRgtZl2tc3Kq9kN8J2t3hcyUEKcxKJrznwDSc55hYtmbpd30YCJ/D0pvF88rheh0lblkAPajOsYYrjzKSXmVMdNQsdQ2eCc6aWPoPUKLvW5VLKl0uhzF0IxIgHn2qnGmCukY/+zAQwXwlieXHJ0pk3VRiKTdu7Fh/1pw5YiOy9ABXtG1QTg2/C0NxltRfuazKQ98oSRpL/PAsl+d9k8/2qZnkyAkoRLr+2wcf9ALaZIVN5IVbJMJWSlruEpEhzW+zibq2yyPKUO2eretvvXwisDEkho8UcSqM2Lrp9PG+fV1sbpltpUhyoJMqcxPT7cVAAxXzSC0PmH1QI9fhL7kODUGYxy+UAaCjZiPQm4EGDhSr7Q3lifLs2bNi6duWMLPQFaU6z8DhqLkI9GIgKeVBOtFl1ZmqiGRWZdPh5IRlqxSh9CmVtks3GwK9GWjw4GxvFXgKDeFOo127d3ehMSBFxApyVC0CPQzEaDYwp7gxa9HRjJUcibOWo4rniEQgRUTLdlQtAj0MhE28lAAB5sGUthPpiw6ceTupnXsYiPgsEsT+54oyK96zd2+jz36SsCPMPWbVjpqJgDgDYZuBC6FOJQ6NGUAcNROBHgaSrJ7kPkCy3LrSvim4D9JVRpdOMQTEGYglHEKETiZ3EtTc1hdnoOZC52rmECgRYCsreOyBbgjqhGUth3vOISCBQM8MJCXChnkwgupkut7h9W9y2/cwUJMr6ermEJBCoIeBpJQeByoF1U5yXB7XUFI6hnF5uXtmEehhIKls+3V1eTBRR5PCwFEzERBnoGbC5mrlEPgWAXEGQjhhmxMM040vDrLpCrn8ehAw0rZSenY9tbD8S16nGpZXxxUvhEAPA0mp27AHIsR8p9K999zj4+bKUTMREGcglnB0oEX33deR1pPKW6moj7hmdsv61KqHgTjslBJlY/gl6eLJZriHVRzZ3GZsmlC2HgbCVSqOPyQIIUKnWk9K7v861cpXoo8WTbOHgUhAUuXk1g4ciZcsXuzj4laKznWQlyMpDMum25uBlB9iCWIfNEIFoFr24IMdtQ+aMGGC6Mxri4N1iT5TlzR7MZCk1jQOS8Z2kBeZu+bP94dXFLWuLp2vCeXszUBqBpISJDALEUKdMPFNAC6tDoQ4GdbB4vs0fJryey8Gwhv+NaFlHIAhSJitohY0nZh9Jk6a5A0Q1AF0jkrs6EV9XPHQMFISM2ahUaNGeRwuNjlCwyQVmUFaaGJ7ZAa6dxDehHbvp/6yEuFNbqq/KkI2Zi1j8FwfBvpSBTKSJEblO+fNI8SJZDaVpU2s1EnCoQ+lltllQdMdYGvNmjW+7QG2YvXsf/HCC+JR6vb97/82MkodYeGlQzwSNuVXL78c23ZlmaDI+y7EYwS1CxcueLcpFRRJmjd/vtfd3e03KU4qYnpp5pFskzxpVxVkGOPMyVOmeMxONgQZjh3FmIpnzp6dB89Cz7ow94Vg63np+LFjxoPtujD3PfC3vsQyEL/8/LnnfEkpUlAMItZt2749sRzBc7Z/PrFihT/KQHTzOBw+P3RIPADvTx5/3JdelcTVLe8904NKYsclWgNTpTSxIf77p596f92xI7Es0mUomz7Mg7Is0qYqCAw5ftiwYYN2DNnTjfsuhH1V9cuDKVjgSu3okSPigwrlags468w8hS/6LJ5LP1WRu996++225SmavuR7bKDHjx9fGfOE6waOl1QQ59++9poWHJ999ll/kJKa1oFxwjjwHSyuqNhMv3n1VS1YRNMPrtsmbnLaRrJ08MCBWs1E7Aew97Gtg7XCyShG+v3rr7dt36ATRD9ZfYxTg0ITvAmBhcTMHGCWCrCpWYgCMWocOniwFnuiKvc8QeOlfRLUufvMmVxLmZUrV/rDlea8bYNCWl3b/U6/OnXypIjAJZWBnnzyydb6vl0Bdf5GZU2tX4uUG10+RPBVCQyKlPm8ilGUZVn39NNP++grNpXOdnd7//2736X2+Tz1z5SYiYPVaKGpLKPGO+++m6mM0fclrh9+6KGWjlsdOxmb61OnTnl/eOONWDxXrVrlS6lwSbRF0TSJlLhly5ZYDIqkmSkhk3uhcCVo9ANqXwQjffjRR5nKGn5f1/fFixb506ZP9yYoDeu6E3vNI4cPe3/Ztq0HT4QFneQ9lqXtpk2beupfpk0zJ/L888/7Vfl3I9L18aNHPcIlmmQklmtjlQh31qxZjdoT0GHYXDMwISyo44xaptPzLlETX9m4MXP/T8ovcwL/9sMf+tPVKFzl5pJKc2jINLz3/fczlz2p8nH358+b5w9RZheIpk1oY8SVwd0zgwCqQOvXry/Vj3K9bFqg0A5G1IAOf/6595UaSfft35+rHnHpLlywoLWBnqs0xTtxRI7DpBPulZ2Jcne8KpdySQ0KCMePH/dOnz7tffDhh5nrdP+SJf7tynanUxRAk/Dr9PtZpZRxOGXubMHLyx95xJ86dWqlS7mgLGmfCCGwb8LrKgZuVe3h0srpfq8WAfrJL196KTcvUOpCL1UllasWZpd7kxHAcG/dunW5+aGQ9iOHcogCHTkEmoIAaktoYeStTyEGIhPk6Ex9jhwCTUEAFaa8VJiByAi9NUf6EGAziyqTo2oQ4IgGjYw8uede88UlXoWqT1w56nzvxRdf7GkLTCSaoPWQ1B6sXPDDTugbyIThZlJZ4u4fUbZEWT0C9fHKE5dg2r3DSjVkxh13pD3mfk9AIMw8PBKYITRFWINe4wl1zMCZHcyDy6qbMNB3BoiM/Djhh6GGKmVWDuxvrTCmEm7JslLPqJf1hXbPuZmoHTp9f8vqXaeOWtL4FzymfDZwRrdz165c/Sw41B6uHPPfMXNmJccPWc3kc1Wsbxfoe8cxUV9M4u7kNfRClWrqtGmVdKa48ifdg2HQEjmpNL/zHGonpYciL8vZScKeXqP5ZxVra2cgCmLKIUm00nW5Rjl28+bNhbDHnRS+KqrUSUzCGYcezDp79u4tVLekdLlPqBhmI5OOTbLMQtorGoDws2ee8Ts5NmqAQ/TztBqZgz1O9Lc81zb5YmApCuP8z5//LNafwAaf4wsWLPBMmdGzDE1zoSxaYZuUT/N0Toln6WSYD+DAX1f6+O8br2IQVbnhZqmDL4sdb72lrV5p+JhUJ0ubhcQrjYMKbGo6yWAr2gHKavxG04teg/EYFXvJtEUpgwIuyarwprRcLWWnqT2hNKWtGMQZKKggB1SDlbqEjWv3oIy6P+lgGAHqWLJlKRtegogESDAzaZw58D2sbLPClq1ZyqjzGRNi/jTrVWMMBHBsgDEfsO3gTGejkhZnHVKODrOU1YTY+5g6bNS5HM1Sr+gzGD9+73vf8yT32rQl55xJ+7tSqjzRCqVdAzhRBVjSULCmEXXiD+cdkr7I0nCTDr5F+x20QI0LQ8pPPvnEYx8mRczk7bYfWjQR8hY+sEVvmicYlmu63SblxZbnJUdk0mdjbUtUjfd27uyaMmWKqINL6xiIRoAYpZEkTVDLujqbUadtNL+trbn/klgyu51WzhptIkz7qbPUwDFkyJDE6lYyA4VLE2xCEU3irHCEUt+oA7GJRsfLlIAgKybsMyUtbz/77DPv4337jO6d0+q+a/fuLrW39icpZzASwpOBbWLdVs5AAThv/ulPPY2CNImzDdNi2aAs7T4Zga+ovyQHhe3eNfHbLW1GSx35X1YekWwk2oRBbcB3Cqo6y8iARJSKuDa3hoHCFQ72EYymMNJAJf4eqjqGxOgSzjfuO6Jo9NbYqGZxjxuXhsl7aDVLETOuLXufaB0R3OAcRsLlcjtBghza0RoWuI6KSZmZYKZhQ4eKiMKRoGGngqr9dRhHOSSxbYmWBqPkIGOzASXLyhkzZojFaUo6erGagaKdJZiZuK9TYZXZ5YwawaIMG82/069379nTs8y2EQvE61LLuMD4L1pvo+dA0czLXH+t0fSZdb1jnjKtYce7MA/R6UxSbRkosGbUARa+4xy1R0DysLJ9ztl/xVUvy2+TVFsG0glSfwHJjc7y5UlLqi7XVee0nWBy9rAmyTGQSbQN5CV1BiQpnNAFSz8lbk7aq+jKI5qOY6AoIjW/Zh/gSD8CSQOIYyD9WFeaIh5vJMj0yF6kDpQxqaMXSS/8TpLys2OgMErueyICUnpmiRkW+AGdNWzOTJJjIJNou7xEEZDa/7UrtGOgdui433ohcM/ChWYPWXrlnn4BA0kt4ZLOlxwDpbdLrZ5IWqvrqIRSldGRjFgauLySmoW+SRDOOAYSa85qEv5GSIhAbTDHx7VUNTVrn+v3ly5t+YNo/1TxXzmkjSPHQHGo1PjeV4JaFYzuKPLaSC2tfSFNdI4GknB1DGRjbyhRpj9u3Soat2nO3LklSifzKnuzscqtl9T+54bSzLfCqYgMfC7VKAKSun3Y2yx94AGrlnEzlctfSTP2pOUbuLsZKNr7GnCNWr8kTVPhR2yhRffd54++7Tax2Yd6YheWRI6BkpCp8X2WHJLELES0CMk8sqZ99913i5r+I9Vs5Azka7T7kBT9Zu0IOp/Ddl9aJ46AassefLBSJsJPgbRfcMz5w/46ou3kZiCFSH8h6U0UbJPXV69eFc9u5qxZ3v1LllTCRD9YtsyfqGIGSROhaNpRrUy6cSiOcxFGnUFtXA21q3Dcb+OU83v8LTBVI8WKe6Zu9/AeNFL5yZYkQsPPV0soJf3ycXAomVc4bZjHhDSQlUmS+Dooj7FKBxnm/STyAEqCw1QI8nYeIvOmm/Q8Sx9G7zo6FInWyVS0QDwXEeLkrzt2iPcn+gPR6qRE1mEMEcYEXnTD98PfrZ2BWN8iXTHtG47DQkZu/p5//nn/0sWLHtN40jlAGEzbvl+4cMFIRDc81syaM8e7ZehQH0aScLx47z33+HfOm2ekPkE7njt7Nvia+Ck+YiTmnPADjIN/L8jEKJNQjF63mcovKccjv3n1Vevw6lXQyAVuk2fOnh25K3cZ4HTm9Glts9GCu+7yle9rz7T7Z+ryy5deSm3v1Afk4O6dMiELCcQlaRTVO8d8VwCKRi7Luy1btliDW1otVq5c6Zt0lxzgdOH8ee+0YiTwKhIzlfOdEWqvO3nqVG+4Wr6bHkyJ95plP1x5R0AwMH78+JYhlGmQ0jpf0u+s+S+qpV3YT13SszbcX7NmjXFJGYzEfhILWRipW/3h9IN7H370Ua9+R5wfBBI4RME18USltDpy1ChvgFpOJzk0lMb1xRdf7FXGpPwyPZT0ctn7T6xYIeZJsmzZsryPpCstCG2WdKSfMRFwq10dYCYCjgWz09fKc84NdR24JuMYIZCq4hiE71UOpnmibVTCQKzNkeHXwUy4XcfgN0ZVNptxjsfT3jX5exWzkMn66cqLGXLt2rWZ+cL4QSpxLaerU+wmMA+NxtKDweCnTz1lfJmUp9NcVBI5R+kInDx+PP2h0BNGGYglm6TVYKhexr9yuPuzZ56xlomQINbBu6jxhgtlSEDhvC6eM09VoXwKfa16HV6o0AVeyrsEKJBFqVdMHa6WKmQFLyMYIn5v3qyNzECdwjyAz0EsnTRvQ5h6njg6jnojgHDjiIrEXYTEGaiTmCdoACRItm7aEXYgPXT0TwQIDh2EGv3n3WzfRBmIPYGkpWC2Klb3lK1MhOgdNX1Hnse+p8x5nhgDITBoiqStTEdDn67M+1LvEiGddX8nE4PIpk2bcu97wpiJMBCmARKxKsMFr8t39kSrVq2ykonYNCP06ESCeRhEytZdhIHGKAd3jv6JABrl6Pr984493zg0ZBPdSaSLecBMOwOx76lSDcPWjoC+n62URevY1rLnLZdO5iFvrQyEloFp+528AFb1PIOKrUs5MMmqPFkVfjry1c08lEkbA+GlZbTy1uJmn+SmZnBhf5j8RLW/NJmJEN3r2PNEW0gbA0l6howWus7Xo5Savs0EEzVNb+7YkSNiWvOlpRB0BpN26lk6H+JZ1OcxzsMIDkmYTUtLrFvrYJRn6zlWlj7AM+j+rVu3TksfT8pTS+Ks7avsoIyYx44e9a6oaRqGwbFg2C4fg62ByuYERkJ7etLkyS0N6iRQpO8j9TqsVEfq4GeBfS0KwHWjrBalZetVmoEeVRalk5XNuum9DxtCmAanH7t2785dj8BkeILyv1BFB6nLLBR0MMw1pJ0YBnmV+Tzb3V1KsyBv3rk7XjSD1atXt8xxo/elrpmWUYg8oWzW977/funyU04M/MYofwzSftTCmDALMUrmVZ8Pp1HFdzRMbDwkz2NFqhO3Uh0Qydt05Wjc1OzD6HJUbQh37tpVqtxxAOL9BS//U6ZNi/tZ5F5dTMLjKo80kQNzU20fV4bAGhj/bUWVQePSzXOvlF+4cepw0ASAjNb4OCuj9JcGykcff9yl/lpO04nEZmJPZyKPtHoX/T1oCzQscARyq/Kcwx5TmmAaBh48hmbxmiNdnlIjuQnjLHS1WOq0c/CtG6QH7r/fv/POO42Yndd5Forizqw0QAlrBipBDeHmy3rUYeCk/Yl3hGSV8JUB40bzruq68AyE6Fq60ME+wSTzUKfv/Dz78++6S9ydMJ2tKRTt3MxOmLMUWaXQ9khVbXfWUpiBbhMOagSASKpMM0/QmWEi5djPv0Pti4p0gCCdtE9G7KbS719/vdQKpw64FNZEkF6/X1EeLat2pcvGVNoEmn0Dkq06dBZXxr4IFGIgpG+SozJnPDgpt4E++eQT77wy+ZUkZ3goia5s2oUYCImLJH2pzGxNxptpVxc0Gs4rP8+SFHjllMzDpS2DQCEGkvRzgEz/0MGDMrUtmOq27du7OINy5BCIIlCIgST3P4z2RVRzohXTfX3q5EndSfakx3LYZjOHnoK6L30QyM1Ayx95RHT/g+jSRiJMR7tozWXLLDmrly2bez8ZgdwMNFBjbNJosRBbS0u9onlmvUbvDn0rKRo0eLBU0i5dQQRyM1AQkkKiTOfUPiNshiCRR5k0u8+caYXoKJNG0rsm1GCS8nb3iyOQm4GKZ5X+5ldKfG0zoX/VqW6gbG6XKstmFQPdVIGXbCZ0sTDWc+QQCBCwhoFQ3bG9c6KxLSlICBrFfdYHgdwMJCVEuK5GdtsZiGYlPKEjh0CAQG4Gkh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"></image></g><image 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"></image><path 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1.78-.523 2.79-.523 3.378 0 5.067 1.517 5.067 4.551 0 2.186-.567 3.947-1.702 5.285-1.135 1.35-2.686 2.105-4.654 2.267a17.76 17.76 0 003.499.349c.922 0 1.722-.18 2.402-.54.19-.105.322-.216.399-.332.378.314.567.782.567 1.403 0 .623-.3 1.115-.898 1.475-.599.361-1.481.542-2.648.542-1.166 0-2.424-.25-3.773-.752a13.464 13.464 0 01-3.764-2.145zm19.384-2.913c.24.28.36.69.36 1.232 0 .54-.224.975-.67 1.308-.45.33-1.065.496-1.845.496-.455 0-1.035-.047-1.74-.14-1.387-.197-2.28-.296-2.677-.296-.396 0-.677.009-.842.027l-.641.06 2.287-11.512h4.142l-1.89 9.593c.163.024.32.036.472.036h.473c1.058 0 1.915-.268 2.57-.804z" fill="#CCC"></path><path fill="#000" d="M682 231h6v1h-6zM689 231h6v1h-6zM682 235h4v1h-4zM686 235h4v1h-4zM691 235h4v1h-4z"></path><path fill="#000" d="M694 235h4v1h-4zM682 238h5v1h-5z"></path><path fill="#000" d="M686 238h5v1h-5zM692 238h5v1h-5zM697 238h5v1h-5zM682 242h2v1h-2zM684 242h2v1h-2zM686 242h2v1h-2zM689 242h2v1h-2zM691 242h2v1h-2zM693 242h2v1h-2zM695 242h2v1h-2zM697 242h2v1h-2zM699 242h2v1h-2zM701 242h2v1h-2zM704 242h2v1h-2zM706 242h2v1h-2zM683 245h2v1h-2zM686 245h2v1h-2zM689 245h2v1h-2zM691 245h2v1h-2zM695 245h2v1h-2zM697 245h2v1h-2zM700 245h2v1h-2zM703 245h2v1h-2zM682 251h2v1h-2zM684 251h2v1h-2zM687 251h2v1h-2zM690 251h2v1h-2zM692 251h2v1h-2zM695 251h2v1h-2z"></path><path fill="#000" d="M696 251h2v1h-2zM699 251h2v1h-2z"></path></g></g></svg></div></section><section class="topologies"><div class="container"><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="user-facing-analytics"></a>User-Facing Analytics<a class="hash-link" href="#user-facing-analytics" title="Direct link to heading">#</a></h2><p align="center"></p><h3 class="installSubTitle_1qZ7">Building Latency Sensitive User Facing Analytics via Apache Pinot</h3><div><div style="border:1px solid white;width:720px;height:480px"></div></div><h3 class="installSubTitle_1qZ7">Using Apache Kafka and Apache Pinot for User-Facing Analytics</h3><div><div style="border:1px solid white;width:720px;height:480px"></div></div><div class="hero--buttons"><a href="https://docs.pinot.apache.org/community-1/videos" target="_blank" rel="noopener noreferrer" class="button button--primary button--highlight">More Videos</a></div><p></p></div></section><section><div class="container"><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="installation"></a>Installs Everywhere<a class="hash-link" href="#installation" title="Direct link to heading">#</a></h2><div class="sub-title">Pinot can be installed using docker with presto</div><div class="installationChecks_utNn"><div><i class="feather icon-package"></i> Helm or K8s crds</div><div><i class="feather icon-cpu"></i> On-Premise</div><div><i class="feather icon-zap"></i> Public Cloud</div><div><i class="feather icon-feather"></i> Locally</div></div><h3 class="installSubTitle_1qZ7">Install:</h3><div class="tabs-container"><ul role="tablist" aria-orientation="horizontal" class="tabs mini"><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_1uMI tabs__item--active"><i class="feather icon-download-cloud"></i> Using Helm</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI"><i class="feather icon-download"></i> Using Binary</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_1uMI"><i class="feather icon-github"></i> Build From Source</li></ul><div class="margin-vert--md"><div role="tabpanel"><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm repo </span><span class="token function" style="color:rgb(80, 250, 123)">add</span><span class="token plain"> pinot https://raw.githubusercontent.com/apache/pinot/master/kubernetes/helm</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">kubectl create ns pinot</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">helm </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> pinot pinot/pinot -n pinot --set cluster.name</span><span class="token operator">=</span><span class="token plain">pinot</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token assign-left variable" style="color:rgb(189, 147, 249);font-style:italic">VERSION</span><span class="token operator">=</span><span class="token number">0.8</span><span class="token plain">.0</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">wget</span><span class="token plain"> https://downloads.apache.org/pinot/apache-pinot-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">$VERSION</span><span class="token plain">/apache-pinot-</span><span class="token variable" style="color:rgb(189, 147, 249);font-style:italic">$VERSION</span><span class="token plain">-bin.tar.gz</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">tar</span><span class="token plain"> vxf apache-pinot-*-bin.tar.gz</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> apache-pinot-*-bin</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">bin/quick-start-batch.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div><div role="tabpanel" hidden=""><div class="codeBlockContainer_K1bP"><div class="codeBlockContent_hGly bash"><pre tabindex="0" class="prism-code language-bash codeBlock_23N8 thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_39YC"><span class="token-line" style="color:#F8F8F2"><span class="token comment" style="color:rgb(98, 114, 164)"># Clone a repo</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token function" style="color:rgb(80, 250, 123)">git</span><span class="token plain"> clone https://github.com/apache/pinot.git</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token comment" style="color:rgb(98, 114, 164)"># Build Pinot</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">mvn clean </span><span class="token function" style="color:rgb(80, 250, 123)">install</span><span class="token plain"> -DskipTests -Pbin-dist</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block">
-</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token comment" style="color:rgb(98, 114, 164)"># Run the Quick Demo</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot-distribution/target/apache-pinot-*-SNAPSHOT-bin/apache-pinot-*-SNAPSHOT-bin</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">bin/quick-start-batch.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div></div></div><h3 class="installSubTitle_1qZ7">Or choose your preferred method:</h3><div class="row"><div class="col"><a href="https://docs.pinot.apache.org/getting-started/running-pinot-in-docker" target="_blank" rel="noopener noreferrer" class="jump-to jump-to--undefined"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Containers</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a></div><div class="col"><a href="https://docs.pinot.apache.org/getting-started/kubernetes-quickstart" target="_blank" rel="noopener noreferrer" class="jump-to jump-to--undefined"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Helm</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a></div><div class="col"><a href="https://docs.pinot.apache.org/basics/getting-started/public-cloud-examples" target="_blank" rel="noopener noreferrer" class="jump-to jump-to--undefined"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Cloud</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a></div><div class="col"><a href="https://docs.pinot.apache.org/getting-started/running-pinot-locally" target="_blank" rel="noopener noreferrer" class="jump-to jump-to--undefined"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Manual/Local</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a></div></div></div></section></main></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Pinot?</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/pinot-components" target="_blank" rel="noopener noreferrer" class="footer__link-item">Components</a></li><li class="footer__item"><a href="https://docs.pinot.apache.org/basics/architecture" 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+</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token comment" style="color:rgb(98, 114, 164)"># Run the Quick Demo</span><span class="token plain"></span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"></span><span class="token builtin class-name" style="color:rgb(189, 147, 249)">cd</span><span class="token plain"> pinot-distribution/target/apache-pinot-*-SNAPSHOT-bin/apache-pinot-*-SNAPSHOT-bin</span></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">bin/quick-start-batch.sh</span></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_Ue-o clean-btn">Copy</button></div></div></div></div></div><h3 class="installSubTitle_1qZ7">Or choose your preferred method:</h3><div class="row"><div class="col"><a href="https://docs.pinot.apache.org/getting-started/running-pinot-in-docker" target="_blank" rel="noopener noreferrer" class="jump-to jump-to--undefined"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Containers</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a></div><div class="col"><a href="https://docs.pinot.apache.org/getting-started/kubernetes-quickstart" target="_blank" rel="noopener noreferrer" class="jump-to jump-to--undefined"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Helm</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a></div><div class="col"><a href="https://docs.pinot.apache.org/basics/getting-started/public-cloud-examples" target="_blank" rel="noopener noreferrer" class="jump-to jump-to--undefined"><div class="jump-to--inner"><div class="jump-to--inner-2"><div class="jump-to--main">Cloud</div><div class="jump-to--right"><i class="feather icon-chevron-right arrow"></i></div></div></div></a></div><div 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diff --git a/content/popular-blogs/index.html b/content/popular-blogs/index.html
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@@ -3,7 +3,7 @@
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<meta charset="UTF-8">
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<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
<link rel="alternate" type="application/atom+xml" href="/blog/atom.xml" title="Apache Pinot™ Blog Atom Feed">
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@@ -11,14 +11,14 @@
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processing by using a hybrid approach of both batch processing and stream processing methods.</p></div></div></div></div><div class="awssld__box"></div></div><div class="awssld__controls awssld__controls--hidden"><button aria-label="next" class="awssld__next"><span class="awssld__controls__arrow-right"></span></button><button aria-label="previous" class="awssld__prev"><span class="awssld__controls__arrow-left"></span></button></div></div><nav class="awssld__bullets"><button data-index="0" class="awssld__bullets--active">0</button><button data-index="1">1</button><button data-index="2">2</button><button data-index="3">3</button><button data-index="4">4</button><button data-index="5">5</button><button data-index="6">6</button><button data-index="7">7</button><button data-index="8">8</button><button data-index="9">9</button><button data-index="10">10</button></nav></div></div></section><section class="topologies"><div class="container"><h2><a aria-hidden="true" tabindex="-1" 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promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods.</p></div></div></div></div><div class="awssld__box"></div></div><div class="awssld__controls awssld__controls--hidden"><button aria-label="next" class="awssld__next"><span class="awssld__controls__arrow-right"></span></button><button aria-label="previous" class="awssld__prev"><span class="awssld__controls__arrow-left"></span></button></div></div><nav class="awssld__bullets"><button data-index="0" class="awssld__bullets--active">0</button><button data-index="1">1</button><button data-index="2">2</button><button data-index="3">3</button><button data-index="4">4</button><button data-index="5">5</button><button data-index="6">6</button><button data-index="7">7</button><button data-index="8">8</button><button data-index="9">9</button><button data-index="10">10</button></nav></div></div></section><section class="topologies"><div class="container"><h2><a aria-hidden="true" tabindex="-1" class="anchor anchor__h2 anchorWithHideOnScrollNavbar_3R7-" id="official-dev"></a><a href="https://medium.com/apache-pinot-developer-blog">Official Pinot Developer Blog</a><a class="hash-link" href="#official-dev" title="Direct link to heading">#</a></h2><div class="awssld awssld--cubeAnimation awssld--organic-arrows slide-show"><div class="awssld__wrapper"><div class="awssld__container"><div class="awssld__box"><div class="awssld__content" style="border-radius:5px"><img src="https://miro.medium.com/max/2776/1*mLfA_squWNDBdKXjq7eUyg.png"><div class="slide-img"><div class="slide-caption"><h1><a href="https://medium.com/apache-pinot-developer-blog/introduction-to-geospatial-queries-in-apache-pinot-b63e2362e2a9">Introduction to Geospatial Queries in Apache Pinot</a></h1><p>Geospatial data has been widely used across the industry, Will discuss the challenges of analyzing geospatial at scale and propose the geospatial support in Pinot.</p></div></div></div></div><div class="awssld__box"></div></div><div class="awssld__controls awssld__controls--hidden"><button aria-label="next" class="awssld__next"><span class="awssld__controls__arrow-right"></span></button><button aria-label="previous" class="awssld__prev"><span class="awssld__controls__arrow-left"></span></button></div></div><nav class="awssld__bullets"><button data-index="0" class="awssld__bullets--active">0</button><button data-index="1">1</button><button data-index="2">2</button></nav></div></div></section></main></div><footer class="footer"><div class="container"><div class="row footer__links"><div class="col footer__col"><h4 class="footer__title">About</h4><ul class="footer__items"><li class="footer__item"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="footer__link-item">What is Apache Pinot?</a></li><li class="footer__item"><a class="footer__link-item" href="/who_uses">Who uses Apache Pinot?</a></li><li 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diff --git a/content/search/index.html b/content/search/index.html
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diff --git a/content/who_uses/index.html b/content/who_uses/index.html
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+++ b/content/who_uses/index.html
@@ -3,7 +3,7 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
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<link rel="alternate" type="application/rss+xml" href="/blog/rss.xml" title="Apache Pinot™ Blog RSS Feed">
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-<link rel="stylesheet" href="https://at-ui.github.io/feather-font/css/iconfont.css"><title data-react-helmet="true">Who Uses Apache Pinot | Apache Pinot™</title><meta data-react-helmet="true" property="og:title" content="Who Uses Apache Pinot | Apache Pinot™"><meta data-react-helmet="true" property="og:description" content="Collection of Companies using Apache Pinot"><meta data-react-helmet="true" property="og:url" content="https://pinot.apache.org/who_uses"><meta data-react-helmet="true" name="docsearch:language" content="en"><meta data-react-helmet="true" name="docsearch:docusaurus_tag" content="default"><meta data-react-helmet="true" name="description" content="Apache Pinot"><meta data-react-helmet="true" name="description" content="Real-time Analytics"><meta data-react-helmet="true" name="description" content="User-facing Analytics"><meta data-react-helmet="true" name="description" content="user facing analytics"><meta data-react-helmet="true" name="description" content="Olap"><meta data-react-helmet="true" name="description" content="Consumer-facing facing analytics"><meta data-react-helmet="true" name="description" content="Fast Analytics"><meta data-react-helmet="true" name="description" content="Who uses Apache Pinot?"><link data-react-helmet="true" rel="shortcut icon" href="/img/favicon.ico"><link data-react-helmet="true" rel="canonical" href="https://pinot.apache.org/who_uses"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/who_uses" hreflang="en"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/who_uses" hreflang="x-default"><link data-react-helmet="true" rel="preconnect" href="https://BH4D9OD16A-dsn.algolia.net" crossorigin="anonymous"><link rel="stylesheet" href="/assets/css/styles.f8c6b66d.css">
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-<div><a href="#" class="skipToContent_1oUP">Skip to main content</a></div><div class="announcementBar_3WsW" style="background-color:#252532;color:#fff" role="banner"><div class="announcementBarContent_3EUC announcementBarCloseable_3myR">⭐️ If you love <b>Apache Pinot</b>, please give it a star on <a target="_blank" href="https://github.com/apache/pinot"><b>GitHub</b></a>! ⭐️</div><button type="button" class="announcementBarClose_38nx clean-btn" aria-label="Close"><span aria-hidden="true">×</span></button></div><nav class="navbar navbar--fixed-top navbarHideable_2qcr"><div class="navbar__inner"><div class="navbar__items"><button aria-label="Navigation bar toggle" class="navbar__toggle clean-btn" type="button" tabindex="0"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--light_3UqQ navbar__logo"><img src="/img/pinot-navbar-logo-722f37.svg" alt="Pinot" class="themedImage_1VuW themedImage--dark_hz6m navbar__logo"></a></div><div class="navbar__items navbar__items--right"><a href="https://docs.pinot.apache.org/" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link">Docs</a><a class="navbar__item navbar__link" href="/download">Download</a><a class="navbar__item navbar__link" href="/blog">Blog</a><a href="https://github.com/apache/pinot" target="_blank" rel="noopener noreferrer" class="navbar__item navbar__link"><span>GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_3J9K"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></span></a><div class="react-toggle toggle_3Zt9 react-toggle--checked react-toggle--disabled"><div class="react-toggle-track" role="button" tabindex="-1"><div class="react-toggle-track-check"><span class="toggle_71bT" style="margin-left:2px">🌙</span></div><div class="react-toggle-track-x"><span class="toggle_71bT" style="margin-left:2px">☀️</span></div><div class="react-toggle-thumb"></div></div><input type="checkbox" checked="" class="react-toggle-screenreader-only" aria-label="Switch between dark and light mode"></div><div class="searchBox_1Doo"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" 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class="grid-item" alt="Apache Pinot used by LinkedIn" title="apache_pinot_user_LinkedIn"></a><a href="https://www.ubereats.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Uber" title="apache_pinot_user_Uber"></a><a href="https://teams.microsoft.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Microsoft" title="apache_pinot_user_Microsoft"></a><a href="https://slack.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Slack" title="apache_pinot_user_Slack"></a><a href="https://www.factual.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Factual" title="apache_pinot_user_Factual"></a><a href="https://www.weibo.com" target="_blank" rel="noopener noreferrer" class="grid-item" alt="Apache Pinot used by Weibo" title="apache_pinot_user_Weibo"></a><a href="https://eero.com/" target="_blank" rel="noopener noreferrer" 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