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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

Submitting a sample MapReduce application


When a MapReduce application is submitted to a Hadoop-YARN cluster, a series of events occurs in different components. In this section, we will submit a sample Hadoop-YARN application to a cluster. We will discuss the application flow with the help of snapshots and understand how the series of events occurs.

Submitting an application to the cluster

As discussed in Chapter 3, Administering a Hadoop-YARN Cluster, the yarn jar command is used to submit a MapReduce application to a Hadoop-YARN cluster. An example jar is packaged inside the Hadoop bundle. It contains sample MapReduce programs, such as word count, pi estimator, pattern search, and so on. This is shown in the following figure:

As shown in the preceding diagram, we have submitted a pi job with 5 and 10 as sample arguments. The first argument 5 denotes the number of map tasks and the second argument 10 represents the samples per map as parameters to the job.

yarn jar <jarPath> <JobName...
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