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Optimizing Hadoop for MapReduce

You're reading from   Optimizing Hadoop for MapReduce This book is the perfect introduction to sophisticated concepts in MapReduce and will ensure you have the knowledge to optimize job performance. This is not an academic treatise; it's an example-driven tutorial for the real world.

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Product type Paperback
Published in Feb 2014
Publisher
ISBN-13 9781783285655
Length 120 pages
Edition Edition
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Author (1):
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Khaled Tannir Khaled Tannir
Author Profile Icon Khaled Tannir
Khaled Tannir
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Toc

Chapter 6. Optimizing MapReduce Tasks

Most MapReduce programs are written for data analysis and they usually take a lot of time to finish. Many companies are embracing Hadoop for advanced data analytics over large datasets that require completion-time guarantees. Efficiency, especially the I/O costs of MapReduce, still need to be addressed for successful implications.

In this chapter, we will discuss some optimization techniques such as using compression and using Combiners in order to improve job execution. Also in this chapter, you will learn basic guidelines and rules to optimize your mappers and reducers code, and techniques to use and reuse the object's instances.

The following topics will be covered in this chapter:

  • The benefits of using Combiners

  • The importance of using compression

  • Learning to use appropriate Writable types

  • How to reuse types smartly

  • How to optimize your mappers and reducers' code

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