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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 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 – using the Distributed Cache to improve location output


Let's now use the Distributed Cache to share a list of U.S. state names and abbreviations across the cluster:

  1. Create a datafile called states.txt on the local filesystem. It should have the state abbreviation and full name tab separated, one per line. Or retrieve the file from this book's homepage. The file should start like the following:

    AL      Alabama
    AK      Alaska
    AZ      Arizona
    AR      Arkansas
    CA      California
    
    …
  2. Place the file on HDFS:

    $ hadoop fs -put states.txt states.txt
    
  3. Copy the previous UFOLocation.java file to UFOLocation2.java file and make the changes by adding the following import statements:

    import java.io.* ;
    import java.net.* ;
    import java.util.* ;
    import org.apache.hadoop.fs.Path;
    import org.apache.hadoop.filecache.DistributedCache ;
  4. Add the following line to the driver main method after the job name is set:

    DistributedCache.addCacheFile(new URI ("/user/hadoop/states.txt"), conf) ;
  5. Replace the map...

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