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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)
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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

Summary

In this chapter, we discussed Hadoop MapReduce performance tuning and learned how application developers and cluster administrators can tune Hadoop in order to enhance the MapReduce job's performance.

We learned about most configuration variables related to CPU, disk I/O, memory and network utilization and discussed how these variables may affect the MapReduce job's performance.

Then, we learned about Hadoop metrics and suggested some open source monitoring tools, which enhance the Hadoop monitoring experience and are very handy to Hadoop cluster administrators and application developers.

In the next chapter, we will learn how to identify resource bottlenecks based on performance indicators and also learn about common performance tuning methods.

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