Book Image

Hadoop Beginner's Guide

Book Image

Hadoop Beginner's Guide

Overview of this book

Data is arriving faster than you can process it and the overall volumes keep growing at a rate that keeps you awake at night. Hadoop can help you tame the data beast. Effective use of Hadoop however requires a mixture of programming, design, and system administration skills."Hadoop Beginner's Guide" removes the mystery from Hadoop, presenting Hadoop and related technologies with a focus on building working systems and getting the job done, using cloud services to do so when it makes sense. From basic concepts and initial setup through developing applications and keeping the system running as the data grows, the book gives the understanding needed to effectively use Hadoop to solve real world problems.Starting with the basics of installing and configuring Hadoop, the book explains how to develop applications, maintain the system, and how to use additional products to integrate with other systems.While learning different ways to develop applications to run on Hadoop the book also covers tools such as Hive, Sqoop, and Flume that show how Hadoop can be integrated with relational databases and log collection.In addition to examples on Hadoop clusters on Ubuntu uses of cloud services such as Amazon, EC2 and Elastic MapReduce are covered.
Table of Contents (19 chapters)
Hadoop Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
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.