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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.

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Product type Paperback
Published in Feb 2013
Publisher Packt
ISBN-13 9781849517300
Length 398 pages
Edition 1st Edition
Tools
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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 FREE CHAPTER 2. Getting Hadoop Up and Running 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 – running WordCount on EMR


We will now show you how to run this same JAR file on EMR. Remember, as always, that this costs money!

  1. Go to the AWS console at http://aws.amazon.com/console, sign in, and select S3.

  2. You'll need two buckets: one to hold the JAR file and another for the job output. You can use existing buckets or create new ones.

  3. Open the bucket where you will store the job file, click on Upload, and add the wc1.jar file created earlier.

  4. Return to the main console home page, and then go to the EMR portion of the console by selecting Elastic MapReduce.

  5. Click on the Create a New Job Flow button and you'll see a familiar screen as shown in the following screenshot:

  6. Previously, we used a sample application; to run our code, we need to perform different steps. Firstly, select the Run your own application radio button.

  7. In the Select a Job Type combobox, select Custom JAR.

  8. Click on the Continue button and you'll see a new form, as shown in the following screenshot:

We now specify...

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