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YARN Essentials

YARN Essentials

By : Fasale, Nirmal Kumar
4.2 (5)
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YARN Essentials

YARN Essentials

4.2 (5)
By: Fasale, Nirmal Kumar
Buy this Book

Overview of this book

If you have a working knowledge of Hadoop 1.x but want to start afresh with YARN, this book is ideal for you. You will be able to install and administer a YARN cluster and also discover the configuration settings to fine-tune your cluster both in terms of performance and scalability. This book will help you develop, deploy, and run multiple applications/frameworks on the same shared YARN cluster.
Table of Contents (12 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Need for YARN
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1. Need for YARN
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The redesign idea
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Summary
2
2. YARN Architecture
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2. YARN Architecture
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Core components of YARN architecture
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YARN scheduler policies
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Recent developments in YARN architecture
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Summary
3
3. YARN Installation
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3. YARN Installation
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Single-node installation
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The fully-distributed mode
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Operating Hadoop and YARN clusters
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Web interfaces of the Ecosystem
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Summary
4
4. YARN and Hadoop Ecosystems
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4. YARN and Hadoop Ecosystems
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The Hadoop 2 release
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A short introduction to Hadoop 1.x and MRv1
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MRv1 versus MRv2
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Understanding where YARN fits into Hadoop
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Old and new MapReduce APIs
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Backward compatibility of MRv2 APIs
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Practical examples of MRv1 and MRv2
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Summary
5
5. YARN Administration
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5. YARN Administration
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Container allocation
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Container configurations
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YARN scheduling policies
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YARN multitenancy application support
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Administration of YARN
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Summary
6
6. Developing and Running a Simple YARN Application
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6. Developing and Running a Simple YARN Application
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Running sample examples on YARN
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Monitoring YARN applications with web GUI
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YARN's MapReduce support
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The YARN application workflow
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Summary
7
7. YARN Frameworks
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7. YARN Frameworks
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Apache Samza
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Storm-YARN
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Apache Spark
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Apache Tez
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Apache Giraph
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HOYA (HBase on YARN)
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KOYA (Kafka on YARN)
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Summary
8
8. Failures in YARN
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8. Failures in YARN
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ResourceManager failures
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ApplicationMaster failures
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NodeManager failures
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Container failures
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Hardware Failures
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Summary
9
9. YARN – Alternative Solutions
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9. YARN – Alternative Solutions
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Mesos
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Omega
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Corona
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Summary
10
10. YARN – Future and Support
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10. YARN – Future and Support
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What YARN means to the big data industry
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Journey – present and future
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YARN-supported frameworks
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Summary
11
Index
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Index

MRv1 versus MRv2

MRv1 (MapReduce version 1) is part of Apache Hadoop 1.x and is an implementation of the MapReduce programming paradigm.

The MapReduce project itself can be broken into the following parts:

  • End-user MapReduce API: This is the API needed to develop the MapReduce application.

  • MapReduce framework: This is the runtime implementation of various phases, such as the map phase, the sort/shuffle/merge aggregation phase, and the reduce phase.

  • MapReduce system: This is the backend infrastructure required to run MapReduce applications and includes things such as cluster resource management, scheduling of jobs, and so on.

Hadoop 1.x was written solely as an MR engine. Since it runs on a cluster, its cluster management component was also tightly coupled with the MR programming paradigm. The only thing that could be run on Hadoop 1.x was an MR job.

In MRv1, the cluster was managed by a single JobTracker and multiple TaskTrackers running on the DataNodes.

In Hadoop 2.x, the old MRv1 framework...

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