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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 – building a JAR file


Before we run our job in Hadoop, we must collect the required class files into a single JAR file that we will submit to the system.

Create a JAR file from the generated class files.

$ jar cvf wc1.jar WordCount1*class

What just happened?

We must always package our class files into a JAR file before submitting to Hadoop, be it local or on Elastic MapReduce.

Tip

Be careful with the JAR command and file paths. If you include in a JAR file class the files from a subdirectory, the class may not be stored with the path you expect. This is especially common when using a catch-all classes directory where all source data gets compiled. It may be useful to write a script to change into the directory, convert the required files into JAR files, and move the JAR files to the required location.

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