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Hadoop Beginner's Guide

You're reading from   Hadoop Beginner's Guide Get your mountain of data under control with Hadoop. This guide requires no prior knowledge of the software or cloud services ‚Äì just a willingness to learn the basics from this practical step-by-step tutorial.

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Product type Paperback
Published in Feb 2013
Publisher Packt
ISBN-13 9781849517300
Length 398 pages
Edition 1st Edition
Tools
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Toc

Table of Contents (19) Chapters Close

Hadoop Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. What It's All About FREE CHAPTER 2. Getting Hadoop Up and Running 3. Understanding MapReduce 4. Developing MapReduce Programs 5. Advanced MapReduce Techniques 6. When Things Break 7. Keeping Things Running 8. A Relational View on Data with Hive 9. Working with Relational Databases 10. Data Collection with Flume 11. Where to Go Next Pop Quiz Answers Index

Chapter 4. Developing MapReduce Programs

Now that we have explored the technology of MapReduce, we will spend this chapter looking at how to put it to use. In particular, we will take a more substantial dataset and look at ways to approach its analysis by using the tools provided by MapReduce.

In this chapter we will cover the following topics:

  • Hadoop Streaming and its uses

  • The UFO sighting dataset

  • Using Streaming as a development/debugging tool

  • Using multiple mappers in a single job

  • Efficiently sharing utility files and data across the cluster

  • Reporting job and task status and log information useful for debugging

Throughout this chapter, the goal is to introduce both concrete tools and ideas about how to approach the analysis of a new data set. We shall start by looking at how to use scripting programming languages to aid MapReduce prototyping and initial analysis. Though it may seem strange to learn the Java API in the previous chapter and immediately move to different languages, our goal here...

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