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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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Toc

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

Fair Scheduler configuration


Getting ready

To go through the recipe in this section, we need Hadoop Cluster setup and running. By default, Apache Hadoop 1.x distribution uses FIFO scheduler and Hadoop 2.x uses Capacity Scheduler. In a cluster with multiple jobs, it is not good to use FIFO scheduler, as it will starve the jobs for resources and only the very first job in the queue is executed; all other jobs have to wait.

To address the preceding issue, there are two commonly used Schedulers: Fair Scheduler, and Capacity Scheduler, to allocate the cluster resources in a fair manner. In this recipe, we will see how to configure Fair Scheduler. Simply put, Fair Scheduler shares resources fairly among running jobs based on queues and weights assigned.

How to do it...

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

  2. Edit the yarn-site.xml as follows:

    <property>
        <name>yarn.resourcemanager.scheduler.class</name>
        <value>org.apache...
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