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Apache Hadoop 3 Quick Start Guide

You're reading from   Apache Hadoop 3 Quick Start Guide Learn about big data processing and analytics

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788999830
Length 220 pages
Edition 1st Edition
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Author (1):
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Hrishikesh Vijay Karambelkar Hrishikesh Vijay Karambelkar
Author Profile Icon Hrishikesh Vijay Karambelkar
Hrishikesh Vijay Karambelkar
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Table of Contents (10) Chapters Close

Preface 1. Hadoop 3.0 - Background and Introduction FREE CHAPTER 2. Planning and Setting Up Hadoop Clusters 3. Deep Dive into the Hadoop Distributed File System 4. Developing MapReduce Applications 5. Building Rich YARN Applications 6. Monitoring and Administration of a Hadoop Cluster 7. Demystifying Hadoop Ecosystem Components 8. Advanced Topics in Apache Hadoop 9. Other Books You May Enjoy

Summary

In this chapter, we have gone through various topics pertaining to MapReduce with a deeper walk through. We started with understanding the concept of MapReduce and an example of how it works. We started configuring the config files for a MapReduce environment; we also configured Job history server. We then looked at Hadoop application URLs, ports, and so on. Post-configuration, we focused on some hands-on work of setting up a MapReduce project and going through Hadoop packages, and then we did a deeper dive into writing MapReduce programs. We also studied different data formats needed for MapReduce. Later, we looked at job compilation, remote job run, and using utilities such as Tool for a simple life. We then studied unit testing and failure handling.

Now that you are able to write applications in MapReduce, in the next chapter, we will start looking at building applications...

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