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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 2. An Overview of the Hadoop Parameters

Once you have your Hadoop job running, it is important to know whether your cluster resources are being fully utilized. Fortunately, the Hadoop framework provides several parameters that enable you to tune your job and specify how it will run on the cluster.

Performance tuning involves four main components: CPU utilization, memory occupation, disk I/O, and network traffic. This chapter describes the most relative parameters to these components and introduces techniques to optimize Hadoop execution and define some configuration parameters.

It is important and essential to have an efficient monitoring tool, with alerts delivered when a problem is developing or occurs, which provides a visual indication of how the Hadoop cluster is and has been performing. This chapter is focused on introducing Hadoop performance tuning using configuration parameters and also introducing several tools for monitoring Hadoop services.

In this chapter, we will cover...

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