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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

Memory requirements

In this recipe, we will look at the memory requirements per node in the cluster, especially looking at the memory on Datanodes as a factor of storage.

Despite having large clusters with many Datanodes, it is of not much use if the nodes do not have sufficient memory to serve the requests. A Namenode stores the entire metadata in the memory and also has to take care of the block reports sent by the Datanodes in the cluster. The larger the cluster, the larger will be the block reports, and the more resources a Namenode will require.

The intent of this recipe is not to tune it for memory, but to give an estimate on the memory required per node.

Getting ready

To complete this recipe, the user must have completed the Disk space calculations recipe and the Nodes needed in the cluster recipe. For better understanding, the user must have a running cluster with HDFS and YARN configured and must have played around with Chapter 1, Hadoop Architecture and Deployment and Chapter 2, Maintaining...

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