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

Preserving ResourceManager states


It is important to preserve the state of ResourceManager during the restart of RM, so as to keep the application running with minimal interruptions. The concept is that the RM preserves the application state in a store and reloads it on restart. ApplicationMasters (AM) and NodeManagers continuously poll RM for status and re-register with it when available, thus resuming the containers from saved state.

Getting ready

For this recipe, you will again need a running cluster and have completed the previous recipes to make sure the cluster is working fine in terms of HDFS and YARN.

How to do it...

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

  2. Navigate to the directory /opt/cluster/hadoop/etc/hadoop.

  3. Edit the yarn-site.xml configuration file to make the necessary changes as shown in the following steps.

  4. Enable RM recovery by making changes as shown in the following screenshot:

  5. Specify the state-store to be used for this, as shown in the following...