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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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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

Data data everywhere...


In discussions concerning integration of Hadoop with other systems, it is easy to think of it as a one-to-one pattern. Data comes out of one system, gets processed in Hadoop, and then is passed onto a third.

Things may be like that on day one, but the reality is more often a series of collaborating components with data flows passing back and forth between them. How we build this complex network in a maintainable fashion is the focus of this chapter.

Types of data

For the sake of the discussion, we will categorize data into two broad categories:

  • Network traffic, where data is generated by a system and sent across a network connection

  • File data, where data is generated by a system and written to files on a filesystem somewhere

We don't assume these data categories are different in any way other than how the data is retrieved.

Getting network traffic into Hadoop

When we say network data, we mean things like information retrieved from a web server via an HTTP connection, database...

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