Chapter 6. Tuning Your MapReduce Jobs

Once you have developed your MapReduce job, you need to be able to run it at scale on your cluster. A number of factors influence how your job scales. This chapter will cover how to recognize that your job is having a problem and how to tune the scaling parameters so that your job performs optimally.

First, we'll look at tunable items. The framework provides several parameters that let you tune how your job will run on the cluster. Most of these take effect at the job level, but a few work at the cluster level.

With large clusters of machines, it becomes important to have a simple monitoring framework that provides a visual indication of how the cluster is and has been performing. Having alerts delivered when ...

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