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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

Overview of this book

Table of Contents (15 chapters)
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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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