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class="menu__link header-linkedin-link" aria-label="Hudi Linkedin Page"><div class="labelWrapperDropdown_Mqbj"></div></a></li></ul></div><div class="navbar-sidebar__item menu"><button type="button" class="clean-btn navbar-sidebar__back">← Back to main menu</button></div></div></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_GMj9"><button aria-label="Scroll back to top" class="clean-btn theme-back-to-top-button backToTopButton_i9tI" type="button"></button><main class="docMainContainer_Q970 docMainContainerEnhanced_ipQ4"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_zHA2"><div class="theme-doc-version-banner alert alert--warning margin-bottom--md" role="alert"><div>This is documentation for <!-- -->Apache Hudi<!-- --> <b>0.5.1</b>, which is no longer actively maintained.</div><div class="margin-top--md">For up-to-date documentation, see the <b><a href="/docs/overview">latest version</a></b> (<!-- -->0.14.1<!-- -->).</div></div><div class="docItemContainer_oiyr"><article><span class="theme-doc-version-badge badge badge--secondary">Version: <!-- -->0.5.1</span><div class="tocCollapsible_aw-L theme-doc-toc-mobile tocMobile_Tx6Y"><button type="button" class="clean-btn tocCollapsibleButton_zr6a">On this page</button></div><div class="theme-doc-markdown markdown"><header><h1>Talks & Powered By</h1></header><h2 class="anchor anchorWithStickyNavbar_y2LR" id="adoption">Adoption<a class="hash-link" href="#adoption" title="Direct link to heading"></a></h2><h3 class="anchor anchorWithStickyNavbar_y2LR" id="uber">Uber<a class="hash-link" href="#uber" title="Direct link to heading"></a></h3><p>Apache Hudi was originally developed at <a href="https://uber.com" target="_blank" rel="noopener noreferrer">Uber</a>, to achieve <a href="http://www.slideshare.net/vinothchandar/hadoop-strata-talk-uber-your-hadoop-has-arrived/32" target="_blank" rel="noopener noreferrer">low latency database ingestion, with high efficiency</a>. |
| It has been in production since Aug 2016, powering the massive <a href="https://eng.uber.com/uber-big-data-platform/" target="_blank" rel="noopener noreferrer">100PB data lake</a>, including highly business critical tables like core trips,riders,partners. It also |
| powers several incremental Hive ETL pipelines and being currently integrated into Uber's data dispersal system.</p><h3 class="anchor anchorWithStickyNavbar_y2LR" id="amazon-web-services">Amazon Web Services<a class="hash-link" href="#amazon-web-services" title="Direct link to heading"></a></h3><p>Amazon Web Services is the World's leading cloud services provider. Apache Hudi is <a href="https://aws.amazon.com/emr/features/hudi/" target="_blank" rel="noopener noreferrer">pre-installed</a> with the AWS Elastic Map Reduce |
| offering, providing means for AWS users to perform record-level updates/deletes and manage storage efficiently.</p><h3 class="anchor anchorWithStickyNavbar_y2LR" id="emis-health">EMIS Health<a class="hash-link" href="#emis-health" title="Direct link to heading"></a></h3><p><a href="https://www.emishealth.com/" target="_blank" rel="noopener noreferrer">EMIS Health</a> is the largest provider of Primary Care IT software in the UK with datasets including more than 500Bn healthcare records. HUDI is used to manage their analytics dataset in production and keeping them up-to-date with their upstream source. Presto is being used to query the data written in HUDI format.</p><h3 class="anchor anchorWithStickyNavbar_y2LR" id="yieldsio">Yields.io<a class="hash-link" href="#yieldsio" title="Direct link to heading"></a></h3><p>Yields.io is the first FinTech platform that uses AI for automated model validation and real-time monitoring on an enterprise-wide scale. Their data lake is managed by Hudi. They are also actively building their infrastructure for incremental, cross language/platform machine learning using Hudi.</p><h3 class="anchor anchorWithStickyNavbar_y2LR" id="yotpo">Yotpo<a class="hash-link" href="#yotpo" title="Direct link to heading"></a></h3><p>Using Hudi at Yotpo for several usages. Firstly, integrated Hudi as a writer in their open source ETL framework <a href="https://github.com/YotpoLtd/metorikku" target="_blank" rel="noopener noreferrer">https://github.com/YotpoLtd/metorikku</a> and using as an output writer for a CDC pipeline, with events that are being generated from a database binlog streams to Kafka and then are written to S3. </p><h3 class="anchor anchorWithStickyNavbar_y2LR" id="tathastuai">Tathastu.ai<a class="hash-link" href="#tathastuai" title="Direct link to heading"></a></h3><p><a href="https://www.tathastu.ai" target="_blank" rel="noopener noreferrer">Tathastu.ai</a> offers the largest AI/ML playground of consumer data for data scientists, AI experts and technologists to build upon. They have built a CDC pipeline using Apache Hudi and Debezium. Data from Hudi datasets is being queried using Hive, Presto and Spark.</p><h2 class="anchor anchorWithStickyNavbar_y2LR" id="talks--presentations">Talks & Presentations<a class="hash-link" href="#talks--presentations" title="Direct link to heading"></a></h2><ol><li><p><a href="https://conferences.oreilly.com/strata/strata-ca/public/schedule/detail/56511" target="_blank" rel="noopener noreferrer">"Hoodie: Incremental processing on Hadoop at Uber"</a> - By Vinoth Chandar & Prasanna Rajaperumal |
| Mar 2017, Strata + Hadoop World, San Jose, CA</p></li><li><p><a href="http://www.dataengconf.com/hoodie-an-open-source-incremental-processing-framework-from-uber" target="_blank" rel="noopener noreferrer">"Hoodie: An Open Source Incremental Processing Framework From Uber"</a> - By Vinoth Chandar. |
| Apr 2017, DataEngConf, San Francisco, CA <a href="https://www.slideshare.net/vinothchandar/hoodie-dataengconf-2017" target="_blank" rel="noopener noreferrer">Slides</a> <a href="https://www.youtube.com/watch?v=7Wudjc-v7CA" target="_blank" rel="noopener noreferrer">Video</a></p></li><li><p><a href="https://spark-summit.org/2017/events/incremental-processing-on-large-analytical-datasets/" target="_blank" rel="noopener noreferrer">"Incremental Processing on Large Analytical Datasets"</a> - By Prasanna Rajaperumal |
| June 2017, Spark Summit 2017, San Francisco, CA. <a href="https://www.slideshare.net/databricks/incremental-processing-on-large-analytical-datasets-with-prasanna-rajaperumal-and-vinoth-chandar" target="_blank" rel="noopener noreferrer">Slides</a> <a href="https://www.youtube.com/watch?v=3HS0lQX-cgo&feature=youtu.be" target="_blank" rel="noopener noreferrer">Video</a></p></li><li><p><a href="https://conferences.oreilly.com/strata/strata-ny/public/schedule/detail/70937" target="_blank" rel="noopener noreferrer">"Hudi: Unifying storage and serving for batch and near-real-time analytics"</a> - By Nishith Agarwal & Balaji Vardarajan |
| September 2018, Strata Data Conference, New York, NY</p></li><li><p><a href="https://databricks.com/session/hudi-near-real-time-spark-pipelines-at-petabyte-scale" target="_blank" rel="noopener noreferrer">"Hudi: Large-Scale, Near Real-Time Pipelines at Uber"</a> - By Vinoth Chandar & Nishith Agarwal |
| October 2018, Spark+AI Summit Europe, London, UK</p></li><li><p><a href="https://www.youtube.com/watch?v=1w3IpavhSWA" target="_blank" rel="noopener noreferrer">"Powering Uber's global network analytics pipelines in real-time with Apache Hudi"</a> - By Ethan Guo & Nishith Agarwal, April 2019, Data Council SF19, San Francisco, CA.</p></li><li><p><a href="https://www.slideshare.net/ChesterChen/sf-big-analytics-20190612-building-highly-efficient-data-lakes-using-apache-hudi" target="_blank" rel="noopener noreferrer">"Building highly efficient data lakes using Apache Hudi (Incubating)"</a> - By Vinoth Chandar |
| June 2019, SF Big Analytics Meetup, San Mateo, CA</p></li><li><p><a href="https://docs.google.com/presentation/d/1FHhsvh70ZP6xXlHdVsAI0g__B_6Mpto5KQFlZ0b8-mM" target="_blank" rel="noopener noreferrer">"Apache Hudi (Incubating) - The Past, Present and Future Of Efficient Data Lake Architectures"</a> - By Vinoth Chandar & Balaji Varadarajan |
| September 2019, ApacheCon NA 19, Las Vegas, NV, USA</p></li><li><p><a href="https://www.portal.reinvent.awsevents.com/connect/sessionDetail.ww?SESSION_ID=98662&csrftkn=YS67-AG7B-QIAV-ZZBK-E6TT-MD4Q-1HEP-747P" target="_blank" rel="noopener noreferrer">"Insert, upsert, and delete data in Amazon S3 using Amazon EMR"</a> - By Paul Codding & Vinoth Chandar |
| December 2019, AWS re:Invent 2019, Las Vegas, NV, USA<br> |
| </p></li><li><p><a href="https://www.slideshare.net/SyedKather/building-robust-cdc-pipeline-with-apache-hudi-and-debezium" target="_blank" rel="noopener noreferrer">"Building Robust CDC Pipeline With Apache Hudi And Debezium"</a> - By Pratyaksh, Purushotham, Syed and Shaik December 2019, Hadoop Summit Bangalore, India</p></li></ol><h2 class="anchor anchorWithStickyNavbar_y2LR" id="articles">Articles<a class="hash-link" href="#articles" title="Direct link to heading"></a></h2><ol><li><a href="https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop" target="_blank" rel="noopener noreferrer">"The Case for incremental processing on Hadoop"</a> - O'reilly Ideas article by Vinoth Chandar</li><li><a href="https://eng.uber.com/hoodie/" target="_blank" rel="noopener noreferrer">"Hoodie: Uber Engineering's Incremental Processing Framework on Hadoop"</a> - Engineering Blog By Prasanna Rajaperumal</li></ol></div><footer class="theme-doc-footer docusaurus-mt-lg"><div 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