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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

Old and new MapReduce APIs

The new API (which is also known as Context Objects) was primarily designed to make the API easier to evolve in the future and is type incompatible with the old one.

The new API came into the picture from the 1.x release series. However, it was partially supported in this series. So, the old API is recommended for 1.x series:

Feature\Release

1.x

0.23

Old MapReduce API

Yes

Deprecated

New MapReduce API

Partial

Yes

MRv1 runtime (Classic)

Yes

No

MRv2 runtime (YARN)

No

Yes

The old and new API can be compared as follows:

Old API

New API

The old API is in the org.apache.hadoop.mapred package and is still present.

The new API is in the org.apache.hadoop.mapreduce package.

The old API used interfaces for Mapper and Reducer.

The new API uses Abstract Classes for Mapper and Reducer.

The old API used the JobConf, OutputCollector, and Reporter object to communicate with the MapReduce system.

The new API uses the context object to communicate with the MapReduce...

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