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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 third run


Let's validate that assumption by running the algorithm for the third time.

  1. Execute the MapReduce job:

    $ hadoop jar graph.jarGraphPathgraphout2graphout3
    
  2. Examine the output file:

    $ hadoop fs -cat /user/hadoop/graphout3/part-r-00000
    12,3,40D
    21,41D
    31,5,61D
    41,21D
    53,62D
    63,52D
    76-1P
    

What just happened?

We now see nodes 1 through 6 are complete. But node 7 is still pending and no nodes are currently being processed, as shown in the following figure:

The reason for this state is that though node 7 has a link to node 6, there is no edge in the reverse direction. Node 7 is therefore effectively unreachable from node 1. If we run the algorithm one final time, we should expect to see the graph unchanged.

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