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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 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

Introducing Apache Flume


Flume, found at http://flume.apache.org, is another Apache project with tight Hadoop integration and we will explore it for the remainder of this chapter.

Before we explain what Flume can do, let's make it clear what it is not. Flume is described as a system for the retrieval and distribution of logs, meaning line-oriented textual data. It is not a generic data-distribution platform; in particular, don't look to use it for the retrieval or movement of binary data.

However, since the vast majority of the data processed in Hadoop matches this description, it is likely that Flume will meet many of your data retrieval needs.

Note

Flume is also not a generic data serialization framework like Avro that we used in Chapter 5, Advanced MapReduce Techniques, or similar technologies such as Thrift and Protocol Buffers . As we'll see, Flume makes assumptions about the data format and provides no ways of serializing data outside of these.

Flume provides mechanisms for retrieving...

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