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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 β€šΓ„Γ¬ 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 FREE CHAPTER 2. Getting Hadoop Up and Running 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 first run


Let's now perform the initial execution of this algorithm on our starting representation of the graph:

  1. Put the previously created graph.txt file onto HDFS:

    $ hadoop fs -mkdirgraphin
    $ hadoop fs -put graph.txtgraphin/graph.txt
    
  2. Compile the job and create the JAR file:

    $ javac GraphPath.java
    $ jar -cvf graph.jar *.class
    
  3. Execute the MapReduce job:

    $ hadoop jar graph.jarGraphPathgraphingraphout1
    
  4. Examine the output file:

    $ hadoop fs –cat /home/user/hadoop/graphout1/part-r00000
    12,3,40D
    21,41C
    31,5,61C
    41,21C
    53,6-1P
    63,5-1P
    76-1P
    

What just happened?

After putting the source file onto HDFS and creating the job JAR file, we executed the job in Hadoop. The output representation of the graph shows a few changes, as follows:

  • Node 1 is now marked as Done; its distance from itself is obviously 0

  • Nodes 2, 3, and 4 – the neighbors of node 1 β€” are marked as Currently processing

  • All other nodes are Pending

Our graph now looks like the following figure:

Given the algorithm, this...

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