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| <link rel="stylesheet" href="https://at-ui.github.io/feather-font/css/iconfont.css"><title data-react-helmet="true">11 posts tagged with "linkedin" | Apache Pinot™</title><meta data-react-helmet="true" property="og:title" content="11 posts tagged with "linkedin" | Apache Pinot™"><meta data-react-helmet="true" property="og:url" content="https://pinot.apache.org/blog/tags/linked-in"><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,Data Scaling,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/linked-in"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/blog/tags/linked-in" hreflang="en"><link data-react-helmet="true" rel="alternate" href="https://pinot.apache.org/blog/tags/linked-in" 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>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. |
| 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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