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

ResourceManager Web UI and JMX metrics


In the previous recipe, we presented how to configure parameters for YARN and MapReduce. As stated initially, each daemon runs a Jetty web server, which can be accessed using a web browser.

Users must take note of the fact that their RPC ports are different from HTTP ports and must not be confused with the options we used in the previous recipe. There are default web ports such as Namenode 50070, ResourceManager 8088, Datanode 50075. All these can be configured to custom ports, if needed.

Getting ready

Make sure that the user has a running cluster with YARN and HDFS configured. The user must be able to run MapReduce jobs on it.

How to do it...

  1. Point your web browser to http://master1.cyrus.com/8088, to access the ResourceManager Web UI:

  2. The Web UI gives information on running the application and the resources it uses, as shown in the following screenshot:

  3. The web interface also shows the scheduler used, which is by default capacity scheduler:

  4. The ResourceManager...