The SpringSource community today released the first milestone of Spring For Apache Hadoop 2.0.
The Spring For Apache Hadoop project focuses on bringing Spring features into application development based on Apache Hadoop technology. It provides a consistent programming and configuration model for Hadoop-based projects. Whether writing standalone MapReduce applications, interacting with data from multiple data stores, or scheduling complex HDFS/Pig/Hive workflows, Spring for Apache Hadoop can leverage Spring concepts to offer a simplified programming model and address the incidental complexity caused by infrastructure.
The new 2.0 version adds support for Hadoop 2.0 and YARN (Hadoop’s Map-Reduce framework), and has been modularized, splitting the existing code into several sub-projects: Core M/R, FSShell, Hive, Pig, etc. Batch and Cascading have also been spun out with their own independent namespaces. Additionally, a Test sub-project has been added for testing spring-yarn in the new version.
This version is not yet a production release, so it is not recommended for production environments.
Download: Spring for Apache Hadoop 2.0 M1
Documentation: Spring for Apache Hadoop Reference Manual
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