Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hadoop Beginner's Guide

You're reading from   Hadoop Beginner's Guide Get your mountain of data under control with Hadoop. This guide requires no prior knowledge of the software or cloud services ‚Äì just a willingness to learn the basics from this practical step-by-step tutorial.

Arrow left icon
Product type Paperback
Published in Feb 2013
Publisher Packt
ISBN-13 9781849517300
Length 398 pages
Edition 1st Edition
Tools
Arrow right icon
Toc

Table of Contents (19) Chapters Close

Hadoop Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. What It's All About 2. Getting Hadoop Up and Running FREE CHAPTER 3. Understanding MapReduce 4. Developing MapReduce Programs 5. Advanced MapReduce Techniques 6. When Things Break 7. Keeping Things Running 8. A Relational View on Data with Hive 9. Working with Relational Databases 10. Data Collection with Flume 11. Where to Go Next Pop Quiz Answers Index

Time for action – examining the output data with Ruby


Now that we have the output data from the job, let's examine it again using Ruby.

  1. Create the following as read.rb:

    require 'rubygems'
    require 'avro'
    
    file = File.open('res.avro', 'rb')
    reader = Avro::IO::DatumReader.new()
    dr = Avro::DataFile::Reader.new(file, reader)
    
    dr.each {|record|  
    print record["shape"]," ",record["count"],"\n"
    }
    dr.close
  2. Examine the created result file.

    $ ruby read.rb
    blur 1
    cylinder 1
    diamond 2
    formation 1
    light 3
    saucer 1
    

What just happened?

As before, we'll not analyze the Ruby Avro API. The example created a Ruby script that opens an Avro datafile, iterates through each datum, and displays it based on explicitly named fields. Note that the script does not have access to the schema for the datafile; the information in the header provides enough data to allow each field to be retrieved.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime