Big Data - How Spring supports Hadoop

Spring shows the world that Hadoop can now be integrated with Enterprise Applications very easily. Undoubtedly It will help accelerating Hadoop's growth.

Online PR News – 27-July-2014 – Gurgaon, Haryana – Spring shows the world that Hadoop can now be integrated with Enterprise Applications very easily. Undoubtedly It will help accelerating Hadoop's growth.

Spring aims to make enterprise aplication development as simple as possible. Spring makes life of a developer very easy by providing JDBC, JMS, Web Services, Security and many more frameworks under one umbrella. Spring reduces the complexity and provide power to developer to do whole lot of things from spring context. Now Spring has extended its scope to add Big Data frameworks like Hadoop, HDFS, PIG, HIVE, No Sql Databases.

Spring announced its first milestone release 1.0.0.M1 for Spring for Apache Hadoop. This Spring initiative reflects the growing importance of Big Data within enterprise applications. Spring has simplified the programming model for complex hadoop jobs. Spring shows the world that Hadoop can now be integrated with Enterprise Applications very easily. Undoubtedly It will help accelerating Hadoop's growth.

Spring supports almost all the features of Hadoop and provides very easy and elegant ways to configure Hadoop job. Some basic features supported by Spring are:

1. Supports Configuration, creation and execution of MapReduce Job.
2. HDFS data access support through JVM scripting languages (Groovy, JRuby, Jython, Rhino, etc.)
3. Support for use with Spring Integration that provides easy access to a wide range of existing systems of big data companies. Like you can integrate Hadoop Job with Spring MVC.
4. Powerful Hadoop configuration options and a template mechanism for client connections to Hadoop.
5. Declarative and programmatic support for Hadoop Tools, including FsShell and DistCp.

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