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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

Configure shared cache manager


In YARN, whenever a job is submitted, it sets up a distributed cache for jars and configuration files per job. What this means is that the jars will be cached during the execution life cycle of a job. However, often the jars or the code does not change across different users of the cluster.

To solve the problem of loading jars for every job, which consume network bandwidth, a proposal is in place to implement a shared cache across the cluster for all users to use it.

Getting ready

You will need a running cluster with HDFS and YARN set up properly so that the user can run test jobs such as pi or wordcount examples on it.

Note

This feature is not yet production ready and is scheduled to be a standard feature in Hadoop 2.9.0, but users can still play with it and test it. Users will not see many improvements for small jobs with very few jars or common code.

How to do it...

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

  2. Create a directory on HDFS...

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