DEV 302 - Launch Jobs and Advanced Hadoop MapReduce

DEV 302 - Launch Jobs and Advanced Hadoop MapReduce

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

Prerequisites

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

Curriculum

  • Lesson 7: Working with Data
  • Quiz 7
  • Lesson 8: Launch Jobs
  • Quiz 8
  • Lesson 9: Streaming MapReduce
  • Quiz 9
  • Course Materials
  • Slide Guide (Transcript)
  • Lab Guide

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

Prerequisites

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

Curriculum

  • Lesson 7: Working with Data
  • Quiz 7
  • Lesson 8: Launch Jobs
  • Quiz 8
  • Lesson 9: Streaming MapReduce
  • Quiz 9
  • Course Materials
  • Slide Guide (Transcript)
  • Lab Guide