In a post earlier, we had introduced Spring for Hadoop. The framework has since then made significant progress and now has multiple components.
source: http://blog.gopivotal.com/products/programming-with-hadoop-101-getting-started-with-spring-hadoop
Using Hadoop alongside Spring Hadoop we can now support scenarios such as:
- Managing batches of data or running batch processes like calculations or formatting with Spring Batch and loading these on or off Hadoop workflows.
- Building integration patterns via Spring Integration that can check a directory or FTP folder for new information, trigger a workflow, send an email, invoke an AMQP message, write a file, continuously query Pivotal GemFire, poll Twitter, and more.
- Using Spring Data to interact with data from Redis, MongoDB, Neo4j, Pivotal GemFire, any JDBC oriented database, Couchbase, FuzzyDB, Elasticsearch, or Solr and push it into or from Hadoop.
- Having a user interface or some other business logic start a MapReduce job or move data into HDFS as part of a general Spring Framework interaction.
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