Apache Hadoop is an OpenSource framework for creating reliable and distributable compute clusters. Credited with the IBM Watson Jeopardy win in 2011, Hadoop can be used (with other related frameworks) to process large unstructured or semi-structured data sets from multiple sources to dissect, classify, learn from and make suggestions for business analytics, decision support, and other advanced forms of machine intelligence.

This class is targeted towards the Java Developer and assumes working knowledge of Java programming in Eclipse and comfort in a Unix shell environment. We will go well beyond the "Hello World" word-count example into practical, applied uses of Hadoop in large-scale real-world scenarios, including fraud detection, algorithmic trading, and data mining. Students will develop in an environment architected for a dynamically changing business-rule driven infrastructure with multiple disparate data sources and large-scale datasets on a real Hadoop/Drools cluster.

This class is focused on the Hadoop 2.0 (pre-)release.

Attendees are expected to have completed our Introductory Hadoop development course, or have equivalent experience in Java programming and Hadoop.

This course is approximately 40% lecture and 60% hands-on labs.