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 – summarizing the UFO data


Now we have the data, let's get an initial summarization of its size and how many records may be incomplete:

  1. With the UFO tab-separated value (TSV) file on HDFS saved as ufo.tsv, save the following file to summarymapper.rb:

    #!/usr/bin/env ruby
    
    while line = gets
        puts "total\t1"
        parts = line.split("\t")
        puts "badline\t1" if parts.size != 6
        puts "sighted\t1" if !parts[0].empty?
        puts "recorded\t1" if !parts[1].empty?
        puts "location\t1" if !parts[2].empty?
        puts "shape\t1" if !parts[3].empty?
        puts "duration\t1" if !parts[4].empty?
        puts "description\t1" if !parts[5].empty?
    end
  2. Make the file executable by executing the following command:

    $ chmod +x summarymapper.rb
    
  3. Execute the job as follows by using Streaming:

    $ hadoop jar hadoop/contrib/streaming/hadoop-streaming-1.0.3.jar 
    -file summarymapper.rb -mapper summarymapper.rb -file wcreducer.rb -reducer wcreducer.rb -input ufo.tsv -output ufosummary
    
  4. Retrieve the summary data...