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

Control block report storm


When Datanodes come up in large clusters with more than 200 nodes, Namenode will be overwhelmed by the block reports and this can cause Namenode to become unresponsive.

Getting ready

This recipe makes more sense for large clusters, not in terms of the number of nodes, but the number of blocks in the cluster.

How to do it...

  1. ssh to Namenode and edit the hdfs-site.xml file to add the following property to it:

    <property>
    <name>dfs.blockreport.initialDelay</name>
    <value>20</value>
    </property>
  2. Copy hdfs-site.xml across all nodes in the cluster.

  3. Restart HDFS daemons across the nodes for the property to take effect:

    $ stop-dfs.sh
    $ start-dfs.sh
    

How it works...

The dfs.blockreport.initialDelay parameter specifies the time in seconds. This is the upper limit of the allotted time, and it is chosen randomly by all Datanodes. What it means is that a few Datanodes can take the value of 1, others may be 2, and a few others 10, but the maximum values...