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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

Sizing the cluster as per SLA

In this recipe, we will look at how service-level agreements can impact our decision to size the clusters. In an organization, there will be multitenant clusters, which are funded differently by business units and ask for a guarantee for their share.

A good thing about YARN is that multiple users can run different jobs such as MapReduce, Hive, Pig, HBase, Spark, and so on. While YARN guarantees what it needs to start a job, it does not control how the job will finish. Users can still step on each other and cause an impact on SLAs.

Getting ready

For this recipe, the users must have completed the Memory requirements and Nodes needed in the cluster recipes. It is good to have a running cluster with HDFS and YARN to run quick commands for reference. It is also good to understand the scheduler recipes covered in Chapter 5, Schedulers.

How to do it...

  1. Connect to the master1.cyrus.com master node and switch to the user hadoop.
  2. Run a teragen and terasort on the cluster using...
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