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

Network design


In this recipe, we will be looking at the network design for the Hadoop cluster and what things to consider for planning a Hadoop cluster.

Getting ready

Make sure that the user has a running cluster with HDFS and YARN and has at least two nodes in the cluster.

How to do it...

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

  2. Execute the commands as follows to check for the link speed and other network option modes:

    $ ethtool eth0
    $ iftop
    $ netstat -s
    
  3. Always have a separate network for Hadoop traffic by using VLANs.

  4. Ensure the DNS resolution works for both forward and reverse lookup.

  5. Run a caching-only DNS within the Hadoop network, which caches records for faster resolution.

  6. Consider NIC teaming or binding for better performance.

  7. Use dedicated core switches and rack top switches.

  8. Consider having static IPs per node in the cluster.

  9. Disable IPv6 for all nodes and just use IPv4.

  10. Increasing the size of the cluster will mean more connections and more data across nodes...