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Hadoop Workflows and Distributed YARN Apps using Spring Technologies
Recorded at:

| by Thomas Risberg Janne Valkealahti on Feb 21, 2016 |
01:26:57

Summary
Thomas Risberg and Janne Valkealahti discuss how Spring for Apache Hadoop can make developing workflows with Map Reduce, Spark, Hive and Pig jobs easier, while providing portability across Apache, Cloudera, Hortonworks, and Pivotal distros. They also show how useful Spring Cloud is when building distributed apps which can be run on Hadoop YARN.

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Bio

Thomas Risberg is a software engineer making Big Data more accessible for Spring developers. Janne Valkealahti is a member of Spring Data team focusing on Spring for Apache Hadoop, Spring YARN and Spring XD.

This is a one-of-a-kind conference for application developers, solution and data architects: people who develop business applications, create multi-device aware web applications, process vast quantities of enterprise data, design cloud architectures, and manage high performance infrastructure. The sessions are specifically tailored for Developers and Architects using the popular open source Spring IO Projects, Groovy & Grails, Cloud Foundry, RabbitMQ, Redis, Geode, Hadoop and Tomcat technologies. Whether you're building mission-critical web or business applications, crunching huge amounts of distributed data, or designing the next killer cloud native application, SpringOne2GX will keep you up to date with the latest enterprise technology.

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