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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

MapReduce management


As we saw in the previous chapter, the MapReduce framework is generally more tolerant of problems and failures than HDFS. The JobTracker and TaskTrackers have no persistent data to manage and, consequently, the management of MapReduce is more about the handling of running jobs and tasks than servicing the framework itself.

Command line job management

The hadoop job command-line tool is the primary interface for this job management. As usual, type the following to get a usage summary:

$ hadoop job --help

The options to the command are generally self-explanatory; it allows you to start, stop, list, and modify running jobs in addition to retrieving some elements of job history. Instead of examining each individually, we will explore the use of several of these subcommands together in the next section.

Have a go hero – command line job management

The MapReduce UI also provides access to a subset of these capabilities. Explore the UI and see what you can and cannot do from the...

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