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

Fair Scheduler pools


In this recipe, we look at configuring Fair Scheduler with pools instead of queues. This is for backwards compatibility. In Hadoop 1.X, Fair Scheduler was addressed with pools and it means the same as queues.

It is recommended to use queues, as this is quite standard across the board. But, for the sake of the readers, it is good to cover the concepts of pools.

Getting ready

To go through the recipe, complete the previous recipe and just modify the fair-scheduler.xml file to reflect pools.

How to do it...

  1. Connect to the master1.cyrus.com master node in the cluster and switch as user hadoop.

  2. Edit the allocation file fair-scheduler.xml, as shown in the following screenshot:

  3. Copy the fair-scheduler.xml file to all the nodes in the cluster and restart the YARN daemons.

  4. Check the ResourceManager page to confirm whether the pools are visible or not, as shown in the following screenshot:

  5. Submit a sample job such as wordcount as user hadoop and see the ResourceManager page, as shown in...