HDP Developer: Java (Hadoop) Training

Experienced Java software engineers who need to develop Java MapReduce applications for Hadoop.

At the completion of the course students will be able to:

• Describe Hadoop 2.X and the Hadoop Distributed File System
• Describe the YARN framework
• Develop and run a Java MapReduce application on YARN
• Use combiners and in-map aggregation
• Write a custom partitioner to avoid data skew on reducers
• Perform a secondary sort
• Recognize use cases for built-in input and output formats
• Write a custom MapReduce input and output format
• Optimize a MapReduce job
• Configure MapReduce to optimize mappers and reducers
• Develop a custom RawComparator class
• Distribute files as LocalResources
• Describe and perform join techniques in Hadoop
• Perform unit tests using the UnitMR API
• Describe the basic architecture of HBase
• Write an HBase MapReduce application
• List use cases for Pig and Hive
• Write a simple Pig script to explore and transform big data
• Write a Pig UDF (User-Defined Function) in Java
• Write a Hive UDF in Java
• Use JobControl class to create a MapReduce workflow
• Use Oozie to define and schedule workflows