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 – WordCount, the Hello World of MapReduce


Many applications, over time, acquire a canonical example that no beginner's guide should be without. For Hadoop, this is WordCount – an example bundled with Hadoop that counts the frequency of words in an input text file.

  1. First execute the following commands:

    $ hadoop dfs -mkdir data
    $ hadoop dfs -cp test.txt data
    $ hadoop dfs -ls data
    Found 1 items
    -rw-r--r--   1 hadoop supergroup         16 2012-10-26 23:20 /user/hadoop/data/test.txt
    
  2. Now execute these commands:

    $ Hadoop Hadoop/hadoop-examples-1.0.4.jar  wordcount data out
    12/10/26 23:22:49 INFO input.FileInputFormat: Total input paths to process : 1
    12/10/26 23:22:50 INFO mapred.JobClient: Running job: job_201210262315_0002
    12/10/26 23:22:51 INFO mapred.JobClient:  map 0% reduce 0%
    12/10/26 23:23:03 INFO mapred.JobClient:  map 100% reduce 0%
    12/10/26 23:23:15 INFO mapred.JobClient:  map 100% reduce 100%
    12/10/26 23:23:17 INFO mapred.JobClient: Job complete: job_201210262315_0002...