DEV 302 - Launch Jobs and Advanced Hadoop MapReduce

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About this Course

This course teaches how to work with sequence files, the distributed cache and Apache HBase. Covered are implementing programmatic job control in the driver, MapReduce chaining, and using Use Oozie to manage MapReduce workflows. Lastly, students are shown how to configure MapReduce streaming parameters and to define the programming contract for mappers and reducers.

This is the third course in the MapReduce Series from MapR.

What’s Covered

Course Lessons Lab Activities
7: Working with Data
Work with Sequence Files
Working with the Distributed Cache
Working with HBase
Run a MapReduce Program Using HBase as Source
8: Launching Jobs
Implement Programmatic Job Control in the Driver
Use MapReduce Chaining
Use Oozie to Manage MapReduce Workflows
Write a MapReduce Driver to Launch Two Jobs
9: Using Non-Java Programs (Streaming MapReduce)
Overview of the MapReduce Streaming Paradigm
Configure MapReduce Streaming Parameters
Define the Programming Contract for Mappers and Reducers
Monitor and Debug MapReduce Streaming Jobs
Implement a MapReduce Streaming Application

Get Certified

This course is part of the MapReduce course series, which helps prepare you for the MapR Certified Hadoop Developer (MCHD).


  • Completion of the MapR Academy on-demand courses: ESS 100 - 102, and DEV 300 - 301
  • Beginner-to-intermediate fluency with Java or object-oriented programming in an IDE
  • A Linux, PC or Mac with a MapR Sandbox downloaded