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InfoQ Homepage Presentations Introduction to Spring for Apache Hadoop

QCon New York (June 13-15): Learn best practices from senior developers at early adopter companies.

Introduction to Spring for Apache Hadoop

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01:20:18

Summary

Thomas Risberg introduces the Spring for Apache Hadoop project and discusses how it can make developing workflows with Map Reduce, Hive and Pig jobs easier, while providing portability across ASF, Cloudera, HortonWorks, and Pivotal distros. He also discusses integration with Spring XD, batch jobs and external data sources.

Bio

Thomas Risberg works as a software engineer on the Spring Data and Spring XD teams at Pivotal.

About the conference

Pivotal and No Fluff Just Stuff bring you SpringOne 2GX 2014, a one-of-a-kind conference for application developers, solution architects, web operations and IT teams who develop business applications, create multi-device aware web applications, design cloud architectures, and manage high performance infrastructure. The sessions are specifically tailored for developers using the hugely popular open source Spring IO projects, Groovy & Grails, Cloud Foundry, Hadoop and Tomcat technologies. Whether you're building and running mission-critical business applications, designing the next killer cloud or big data application, SpringOne 2GX will keep you up to date with the latest enterprise open source technology.

Recorded at:

Jan 10, 2015

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Community comments

  • Spring data and apache hadoop

    by Sonam Gupta,

    Your message is awaiting moderation. Thank you for participating in the discussion.

    Thanks for your post! Spring for Apache Hadoop extends Spring Batch by providing support for reading from and writing to HDFS, running various types of Hadoop jobs (Java MapReduce, Streaming, Hive, Pig) and HBase. An important goal is to provide excellent support for non-Java based developers to be productive using Spring Hadoop and not have to write any Java code to use the core feature set. Spring for Apache Hadoop also applies the familiar Spring programming model to Java MapReduce jobs by providing support for dependency injection of simple jobs as well as a POJO based MapReduce programming model that decouples your MapReduce classes from Hadoop specific details such as base classes and data types. Learn more at intellipaat.com

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