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 – 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...