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Learning YARN

You're reading from   Learning YARN Moving beyond MapReduce - learn resource management and big data processing using YARN

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Product type Paperback
Published in Aug 2015
Publisher
ISBN-13 9781784393960
Length 278 pages
Edition 1st Edition
Tools
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Toc

Table of Contents (14) Chapters Close

Preface 1. Starting with YARN Basics FREE CHAPTER 2. Setting up a Hadoop-YARN Cluster 3. Administering a Hadoop-YARN Cluster 4. Executing Applications Using YARN 5. Understanding YARN Life Cycle Management 6. Migrating from MRv1 to MRv2 7. Writing Your Own YARN Applications 8. Dive Deep into YARN Components 9. Exploring YARN REST Services 10. Scheduling YARN Applications 11. Enabling Security in YARN 12. Real-time Data Analytics Using YARN Index

An introduction to schedulers


The scheduler is responsible for providing resources to different tasks of running applications. It is only responsible for scheduling of tasks and is not concerned with status tracking and monitoring of tasks. The scheduler ensures meeting resource requirements in terms of memory, cores, disk, and network for the application. At granular level, it meets the resource requirement of containers running for the particular application. The default scheduler of Hadoop uses a single queue (root queue) to accept and schedule applications. It means that all the applications are submitted to the root queue.

You can view the details of the configured scheduler through ResourceManager web UI at http://<ResourceManager IP>:8088/cluster/scheduler. This is shown in the following screenshot:

YARN provides interfaces for implementation of pluggable scheduler. The two popular schedulers available with Hadoop are:

  • Fair scheduler

  • Capacity scheduler

Fair scheduler

Fair scheduler...

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