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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 – running WordCount on a local Hadoop cluster


Now we have generated the class files and collected them into a JAR file, we can run the application by performing the following steps:

  1. Submit the new JAR file to Hadoop for execution.

    $ hadoop jar wc1.jar WordCount1 test.txt output
    
  2. If successful, you should see the output being very similar to the one we obtained when we ran the Hadoop-provided sample WordCount in the previous chapter. Check the output file; it should be as follows:

    $ Hadoop fs –cat output/part-r-00000
    This 1
    yes 1
    a 1
    is 2
    test 1
    this 1
    

What just happened?

This is the first time we have used the Hadoop JAR command with our own code. There are four arguments:

  1. The name of the JAR file.

  2. The name of the driver class within the JAR file.

  3. The location, on HDFS, of the input file (a relative reference to the /user/Hadoop home folder, in this case).

  4. The desired location of the output folder (again, a relative path).

Tip

The name of the driver class is only required if a main...

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