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

Configure shared cache manager


In YARN, whenever a job is submitted, it sets up a distributed cache for jars and configuration files per job. What this means is that the jars will be cached during the execution life cycle of a job. However, often the jars or the code does not change across different users of the cluster.

To solve the problem of loading jars for every job, which consume network bandwidth, a proposal is in place to implement a shared cache across the cluster for all users to use it.

Getting ready

You will need a running cluster with HDFS and YARN set up properly so that the user can run test jobs such as pi or wordcount examples on it.

Note

This feature is not yet production ready and is scheduled to be a standard feature in Hadoop 2.9.0, but users can still play with it and test it. Users will not see many improvements for small jobs with very few jars or common code.

How to do it...

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

  2. Create a directory on HDFS...