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

HDFS balancer


In a long-running cluster, there might be unequal distribution of data across Datanodes. This could be due to failures of nodes or the addition of nodes to the cluster.

To make sure that the data is equally distributed across Datanodes, it is important to use Hadoop balancer to redistribute the blocks.

Getting ready

For this recipe, you will again use the same node on which we have already configured Namenode.

All operations will be done by user hadoop.

How to do it...

  1. Log in the nn1.cluster1.com node and change to user hadoop.

  2. Execute the balancer command as shown in the following screenshot:

  3. By default, the balancer threshold is set to 10%, but we can change it, as shown in the following screenshot:

How it works...

The balancer threshold defines the percentage of cluster disk space utilized, compared to the nodes in the cluster. For example, let's say we have 10 Datanodes in the cluster, with each having 100 GB of disk storage totaling to about 1 TB.

So, when we say the threshold is...