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

Tuning the operating system


In Hadoop, we mostly use Linux-based operating systems, so the settings we talk about will be restricted to any Linux-based systems.

The first important thing to consider is making sure that the hardware is optimal with latest drivers for motherboard components and the right kind of memory modules with matching bus speed. The BIOS settings are tuned to be optimal like disable power saving mode, VT flag enabled, 64-bit architecture, the right cabling for disk enclosures (Just a bunk of disks (JBOD)). Multiple CPUs with at least a quad core per CPU socket and high bandwidth bonded interface cards. Racks with support for 1U or 2U servers, with rack top switches which can support network traffic from a large Hadoop cluster.

The hardware configuration will vary according to the Hadoop components like whether it is a Namenode, Datanode, HBase master, or region server. Also, whether the work load is I/O intensive or CPU intensive. There will always be a race between right...