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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

Deep diving into MapReduce APIs

Let's start looking at different types of data structures and classes that you will be using while writing MapReduce programs. We will be looking data structures of input and output to MapReduce, and different classes that you can use for Mapper, Combiner, Shuffle, and Reducer.

Configuring MapReduce jobs

Usually, when you write programs in MapReduce, you start with configuration APIs first. In our programs that we have run in previous chapters, the following code represents the configuration part:

The Configuration class (part of the org.apache.Hadoop.conf package) provides access to different configuration parameters. The API reads properties from the supplied file. The configuration...

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