Build Hadoop MapReduce Applications


About this Course

In this course you will learn how to write Hadoop Applications using MapReduce and YARN in Java. The course covers debugging, managing jobs, improving performance, working with custom data, managing workflows, and using other programming languages for MapReduce. This is the first course in the MapReduce Series from MapR.

What’s Covered in the Course

1: Introduction to Developing Hadoop Applications
  • Illustrate the MapReduce model conceptually
  • Brief history of MapReduce
  • Discuss how MapReduce works at a high level
  • Define how data flows in MapReduce
Lab Activities
    • Run wordcount
    • Examine Job Metrics in JobHistoryServer
2: Job Execution Framework - MapReduce v1 & v2
  • Describe the MapReduce v1 job execution framework
  • Compare MapReduce v1 to MapReduce v2 (YARN)
  • Describe how jobs execute in YARN
  • Describe how to manage jobs in YARN
Lab Activities
    • Run Distributed
    • ShellExamine Job Results
3: Write a MapReduce Program
  • Summary of the programming problem
  • Design and implement the Mapper class, Reducer class and driver
  • Build and execute the code then examine the output
Lab Activities
    • Modify a MapReduce Program