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Hadoop 2.x Administration Cookbook

You're reading from   Hadoop 2.x Administration Cookbook Administer and maintain large Apache Hadoop clusters

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781787126732
Length 348 pages
Edition 1st Edition
Tools
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Author (1):
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Aman Singh Aman Singh
Author Profile Icon Aman Singh
Aman Singh
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Table of Contents (14) Chapters Close

Preface 1. Hadoop Architecture and Deployment FREE CHAPTER 2. Maintaining Hadoop Cluster HDFS 3. Maintaining Hadoop Cluster – YARN and MapReduce 4. High Availability 5. Schedulers 6. Backup and Recovery 7. Data Ingestion and Workflow 8. Performance Tuning 9. HBase Administration 10. Cluster Planning 11. Troubleshooting, Diagnostics, and Best Practices 12. Security Index

Tuning Datanode


In this recipe, we will look at tuning the Datanode by making some important configuration changes. Datanodes are mostly I/O bound, but can have a varied workload for HBase region servers. The network throughout the disks must be tuned for optimal performance.

We will look at parameters only for the Datanode, which in production will come into effect in conjunction with HDFS and Namenode parameters, discussed earlier in this chapter.

Getting ready

For this recipe, you will again need a running cluster and have at least the HDFS daemons running in the cluster.

How to do it...

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

  2. The hdfs-site.xml file will remain the same in the cluster. Each of the Namenode and Datanode daemons will read its respective parameters, ignoring the others.

  3. Tune the Datanode handler count by using the following configuration in the hdfs-site.xml file:

    <property>
    <name>dfs.datanode.handler.count</name>
    <value>40...
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