Big Data Processing for Apache Hadoop with Spring Integration and Batch

Track: Data + Integration
Skill Level: Intermediate
Room: Room 102
Time Slot: Tue 2/19, 4:00 PM

Big Data is quickly proving to be more than hype, as organizations face an increasing volume of information and the challenge to react to that information effectively. New tools and techniques are needed to address that challenge. However, Spring Integration and Spring Batch are both flexible enough to support these new tools and techniques upon their proven foundations for messaging and batch-processing.

In this session, we will walk through a couple Big Data use-cases implemented with Spring Integration, Spring Batch, and the Spring for Apache Hadoop project. The underlying theme is that the frameworks can be combined to provide a platform for Big Data processing, both real-time and batch-oriented, while also incorporating new tools and techniques such as HDFS and Map Reduce.

Mark Fisher

Mark has been a member of the Spring team for over a decade, contributing to the Spring Framework and several other projects. He founded Spring Integration in 2007 and is one of the authors of Spring Integration in Action, published by Manning in 2012. Currently he co-leads Spring Cloud Data Flow and contributes to other Spring Cloud projects.