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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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Khaled Tannir Khaled Tannir
Author Profile Icon Khaled Tannir
Khaled Tannir
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Toc

Identifying resource bottlenecks


Typically, a bottleneck occurs when one resource of the system consumes more time than required to finish its tasks and forces other resources to wait, which decreases the overall system performance.

Prior to any deep-dive action into tuning your Hadoop cluster, it is a good practice to ensure that your cluster is stable and your MapReduce jobs are operational. We suggest you verify that the hardware components of your cluster are configured correctly and if necessary, upgrade any software components of the Hadoop stack to the latest stable version. You may also perform a MapReduce job such as TeraSort or PI Estimator to stress your cluster. This is a very important step to get a healthy and optimized Hadoop cluster.

Once your cluster hardware and software components are well configured and updated, you need to create a baseline performance stress-test. In order to stress your Hadoop cluster, you can use the Hadoop microbenchmarks such as TeraSort, TestDFSIO...

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