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 – using the Distributed Cache to improve location output


Let's now use the Distributed Cache to share a list of U.S. state names and abbreviations across the cluster:

  1. Create a datafile called states.txt on the local filesystem. It should have the state abbreviation and full name tab separated, one per line. Or retrieve the file from this book's homepage. The file should start like the following:

    AL      Alabama
    AK      Alaska
    AZ      Arizona
    AR      Arkansas
    CA      California
    
    …
  2. Place the file on HDFS:

    $ hadoop fs -put states.txt states.txt
    
  3. Copy the previous UFOLocation.java file to UFOLocation2.java file and make the changes by adding the following import statements:

    import java.io.* ;
    import java.net.* ;
    import java.util.* ;
    import org.apache.hadoop.fs.Path;
    import org.apache.hadoop.filecache.DistributedCache ;
  4. Add the following line to the driver main method after the job name is set:

    DistributedCache.addCacheFile(new URI ("/user/hadoop/states.txt"), conf) ;
  5. Replace the map...