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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
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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 2. Getting Hadoop Up and Running FREE CHAPTER 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

Time for action – performing the shape/time analysis from the command line


It may not be immediately obvious how to do this sort of local command-line analysis, so let's look at an example.

With the UFO datafile on the local filesystem, execute the following command:

$ cat ufo.tsv | shapetimemapper.rb | sort| shapetimereducer.rb

What just happened?

With a single Unixcommand line, we produced output identical to our previous full MapReduce job. If you look at what the command line does, this makes sense.

Firstly, the input file is sent—a line at a time—to the mapper. The output of this is passed through the Unix sort utility and this sorted output is passed a line at a time to the reducer. This is of course a very simplified representation of our general MapReduce job workflow.

Then the obvious question is why should we bother with Hadoop if we can do equivalent analysis at the command line. The answer of course is our old friend, scale. This simple approach works fine for a file such as the...

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