DEV 300 - Build Hadoop MapReduce Applications

DEV 300 - Build Hadoop MapReduce Applications

Write Hadoop Applications using MapReduce and YARN in Java, including debugging, managing jobs, improving performance, working with custom data, managing workflows, and using other programming languages.

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. First course in the MapReduce series from MapR.

What's Covered

Course Lessons Lab Activities

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

 

Run wordcount
Examine Job Metrics in JobHistoryServer

2: Job Execution Framework - MapReduce v1 and 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

 

Run DistributedShell
Examine 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

 

Modify a MapReduce Program

Get Certified

This course help to prepare you for the MapR Certified Hadoop Developer (MCHD) certification exam.

Prerequisites

  • Completion of ESS 100 - 102
  • Basic Hadoop knowledge
  • Beginner-to-intermediate fluency with Java in an IDE

Curriculum

  • Lesson 1 - Introduction to Developing Hadoop Applications
  • Lesson 2 - Job Execution Framework MapReduce v1 and v2
  • Quiz 2
  • Lesson 3 - Write MapReduce Programs
  • Quiz 3
  • Course Materials
  • Slide Guide (Transcript)
  • Lab Guide

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. First course in the MapReduce series from MapR.

What's Covered

Course Lessons Lab Activities

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

 

Run wordcount
Examine Job Metrics in JobHistoryServer

2: Job Execution Framework - MapReduce v1 and 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

 

Run DistributedShell
Examine 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

 

Modify a MapReduce Program

Get Certified

This course help to prepare you for the MapR Certified Hadoop Developer (MCHD) certification exam.

Prerequisites

  • Completion of ESS 100 - 102
  • Basic Hadoop knowledge
  • Beginner-to-intermediate fluency with Java in an IDE

Curriculum

  • Lesson 1 - Introduction to Developing Hadoop Applications
  • Lesson 2 - Job Execution Framework MapReduce v1 and v2
  • Quiz 2
  • Lesson 3 - Write MapReduce Programs
  • Quiz 3
  • Course Materials
  • Slide Guide (Transcript)
  • Lab Guide