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  • Book Overview & Buying Optimizing Hadoop for MapReduce
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Optimizing Hadoop for MapReduce

Optimizing Hadoop for MapReduce

By : Khaled Tannir
4.3 (4)
Buy this Book
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Optimizing Hadoop for MapReduce

Optimizing Hadoop for MapReduce

4.3 (4)
By: Khaled Tannir
Buy this Book

Overview of this book

Table of Contents (15 chapters)
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Optimizing Hadoop for MapReduce
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Optimizing Hadoop for MapReduce
Credits
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Credits
About the Author
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About the Author
Acknowledgments
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Acknowledgments
About the Reviewers
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About the Reviewers
www.PacktPub.com
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www.PacktPub.com
Preface
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Preface
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1
Understanding Hadoop MapReduce
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Understanding Hadoop MapReduce
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The MapReduce model
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An overview of Hadoop MapReduce
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Hadoop MapReduce internals
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Factors affecting the performance of MapReduce
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Summary
2
An Overview of the Hadoop Parameters
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An Overview of the Hadoop Parameters
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Investigating the Hadoop parameters
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Hadoop MapReduce metrics
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Performance monitoring tools
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Summary
3
Detecting System Bottlenecks
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Detecting System Bottlenecks
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Performance tuning
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Creating a performance baseline
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Identifying resource bottlenecks
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Summary
4
Identifying Resource Weaknesses
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Identifying Resource Weaknesses
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Identifying cluster weakness
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Sizing your Hadoop cluster
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Configuring your cluster correctly
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Summary
5
Enhancing Map and Reduce Tasks
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Enhancing Map and Reduce Tasks
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Enhancing map tasks
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Enhancing reduce tasks
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Tuning map and reduce parameters
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Summary
6
Optimizing MapReduce Tasks
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Optimizing MapReduce Tasks
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Using Combiners
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Using compression
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Using appropriate Writable types
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Reusing types smartly
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Optimizing mappers and reducers code
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Summary
7
Best Practices and Recommendations
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Best Practices and Recommendations
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Hardware tuning and OS recommendations
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Hadoop best practices and recommendations
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Summary
1
Index
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Index

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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