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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 – the second run


If we take this representation as the input to another run of the job, we would expect nodes 2, 3, and 4 to now be complete, and for their neighbors to now be in the Current state. Let's see; execute the following steps:

  1. Execute the MapReduce job by executing the following command:

    $ hadoop jar graph.jarGraphPathgraphout1graphout2
    
  2. Examine the output file:

    $ hadoop fs -cat /home/user/hadoop/graphout2/part-r000000
    12,3,40D
    21,41D
    31,5,61D
    41,21D
    53,62C
    63,52C
    76-1P
    

What just happened?

As expected, nodes 1 through 4 are complete, nodes 5 and 6 are in progress, and node 7 is still pending, as seen in the following figure:

If we run the job again, we should expect nodes 5 and 6 to be Done and any unprocessed neighbors to become Current.

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