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Mastering Hadoop

You're reading from   Mastering Hadoop Go beyond the basics and master the next generation of Hadoop data processing platforms

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783983643
Length 374 pages
Edition 1st Edition
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Author (1):
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Sandeep Karanth Sandeep Karanth
Author Profile Icon Sandeep Karanth
Sandeep Karanth
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Table of Contents (15) Chapters Close

Preface 1. Hadoop 2.X FREE CHAPTER 2. Advanced MapReduce 3. Advanced Pig 4. Advanced Hive 5. Serialization and Hadoop I/O 6. YARN – Bringing Other Paradigms to Hadoop 7. Storm on YARN – Low Latency Processing in Hadoop 8. Hadoop on the Cloud 9. HDFS Replacements 10. HDFS Federation 11. Hadoop Security 12. Analytics Using Hadoop A. Hadoop for Microsoft Windows Index

The YARN architecture


The following figure illustrates the architecture of a YARN-based cluster. There are five major component types in a YARN cluster. They are as follows:

  • Resource Manager (RM): This is a per-cluster daemon that is solely responsible for allocating and managing resources available within the cluster.

  • Node Manager (NM): This is a per-node daemon that is responsible for local resource management. It is also the node-local representative of the RM.

  • Application Master (AM): This is a per-application daemon that encapsulates all application-specific logic and libraries. The AM is responsible for negotiating resources from the RM and working with the NM to execute them to completion.

  • Container: This is an abstract representation of a resource set that is given to a particular application. The AM is a specialized container that is used to bootstrap and manage the entire application's life cycle.

  • Client: This is the entity in the cluster that can submit applications to the RM...

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