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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

Summary


We have caused a lot of destruction in this chapter and I hope you never have to deal with this much failure in a single day with an operational Hadoop cluster. There are some key learning points from the experience.

In general, component failures are not something to fear in Hadoop. Particularly with large clusters, failure of some component or host will be pretty commonplace and Hadoop is engineered to handle this situation. HDFS, with its responsibility to store data, actively manages the replication of each block and schedules new copies to be made when the DataNode processes die.

MapReduce has a stateless approach to TaskTracker failure and in general simply schedules duplicate jobs if one fails. It may also do this to prevent the misbehaving hosts from slowing down the whole job.

Failure of the HDFS and MapReduce master nodes is a more significant failure. In particular, the NameNode process holds critical filesystem data and you must actively ensure you have it set up to allow...

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