DEV 301 - Manage and Test Hadoop MapReduce Applications

Register Now

About this Course

This course covers how to write MapReduce applications in Java. Students will learn how to use the MapReduce API, work with counters and the Hadoop CLI, and to debug, manage jobs, improve performance, work with different data sources, manage workflows, and use other programming languages for MapReduce.

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

What’s Covered

Course Lessons Lab Activities
4: Use the MapReduce API
API Overview
Mapper Input Processing and Reducer Output Processing Data Flow
Explore the Mapper, Reducer, and Job Class API
Write a Map
Reduce Program
5: Managing, Monitoring, and Testing MapReduce Jobs
Work with Counters
Use the MCS to Monitor Jobs
Use the Hadoop CLI to Manage Jobs
Display Job History and Logs
Write Unit Tests for MapReduce Programs
Examine Default Job Output
Use Custom Counters
Use Standard Output, Error, and Logging
Use the Hadoop CLI to Manage Jobs
Use MRUnit to Test a MapReduce Application
6: Managing Performance
Review Components of MapReduce Performance
Enhance Performance in MapReduce Jobs
Overview of MapR Performance Enhancements
De-tune a Job and Measure Performance Impact

Get Certified

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

Prerequisites

  • Completion of the MapR Academy on-demand courses: ESS 100 - 102, and DEV 300
  • Beginner-to-intermediate fluency with Java or object-oriented programming in an IDE
  • Basic Hadoop knowledge -- helpful but not required