Book Image

Hadoop 2.x Administration Cookbook

By : Aman Singh
Book Image

Hadoop 2.x Administration Cookbook

By: Aman Singh

Overview of this book

Hadoop enables the distributed storage and processing of large datasets across clusters of computers. Learning how to administer Hadoop is crucial to exploit its unique features. With this book, you will be able to overcome common problems encountered in Hadoop administration. The book begins with laying the foundation by showing you the steps needed to set up a Hadoop cluster and its various nodes. You will get a better understanding of how to maintain Hadoop cluster, especially on the HDFS layer and using YARN and MapReduce. Further on, you will explore durability and high availability of a Hadoop cluster. You’ll get a better understanding of the schedulers in Hadoop and how to configure and use them for your tasks. You will also get hands-on experience with the backup and recovery options and the performance tuning aspects of Hadoop. Finally, you will get a better understanding of troubleshooting, diagnostics, and best practices in Hadoop administration. By the end of this book, you will have a proper understanding of working with Hadoop clusters and will also be able to secure, encrypt it, and configure auditing for your Hadoop clusters.
Table of Contents (20 chapters)
Hadoop 2.x Administration Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Chapter 8. Performance Tuning

In this chapter, we will cover the following recipes:

  • Tuning the operating system

  • Tuning the disk

  • Tuning the network

  • Tuning HDFS

  • Tuning Namenode

  • Tuning Datanode

  • Configuring YARN for performance

  • Configuring MapReduce for performance

  • Hive performance tuning

  • Benchmarking Hadoop cluster

In this chapter, we will configure a Hadoop cluster with different parameters and see its effect on performance. There is no one way of doing things and if a particular setting works on one cluster, it does not necessarily mean that it will work for the other cluster with different hardware or work load.

Note

This being a recipe book, we will not be covering a lot of theory, but it is recommended to build a background on the things we are going to do in this chapter, rather than simply changing the values.

As stated initially, the performance may vary from one system to another and in many cases, it is just context. When someone says that the system is slow, what does it mean? Slower than what...