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YARN Essentials
YARN Essentials

YARN Essentials: A comprehensive, hands-on guide to install, administer, and configure settings in YARN

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YARN Essentials

Chapter 2. YARN Architecture

This chapter dives deep into YARN architecture its core components, and how they interact to deliver optimal resource utilization, better performance, and manageability. It also focuses on some important terminology concerning YARN.

In this chapter, we will cover the following topics:

  • Core components of YARN architecture
  • Interaction and flow of YARN components
  • ResourceManager scheduling policies
  • Recent developments in YARN

The motivation behind the YARN architecture is to support more data processing models, such as Apache Spark, Apache Storm, Apache Giraph, Apache HAMA, and so on, than just MapReduce. YARN provides a platform to develop and execute distributed processing applications. It also improves efficiency and resource-sharing capabilities.

The design decision behind YARN architecture is to separate two major functionalities, resource management and job scheduling or monitoring of JobTracker, into separate daemons, that is, a cluster level ResourceManager...

Core components of YARN architecture

Here are some core components of YARN architecture that we need to know:

  • ResourceManager
  • ApplicationMaster
  • NodeManager

ResourceManager

ResourceManager acts as a global resource scheduler that is responsible for resource management and scheduling as per the ApplicationMaster's requests for the resource requirements of the application(s). It is also responsible for the management of hierarchical job queues. The ResourceManager can be seen in the following figure:

ResourceManager

The preceding diagram gives more details about the components of the ResourceManager. The Admin and Client service is responsible for client interactions, such as a job request submission, start, restart, and so on. The ApplicationsManager is responsible for the management of every application. The ApplicationMasterService interacts with every application. ApplicationMaster regarding resource or container negotiation, the ResourceTrackerService coordinates with the NodeManager and ResourceManager...

YARN scheduler policies

As explained in the previous section, the ResourceManager acts as a pluggable global scheduler that manages and controls all the containers (resources). There are three different policies that can be applied over the scheduler, as per requirements and resource availability. They are as follows:

  • The FIFO scheduler
  • The Fair scheduler
  • The Capacity scheduler

The FIFO (First In First Out) scheduler

FIFO means First In First Out. As the name indicates, the job submitted first will get priority to execute; in other words, the job runs in the order of submission. FIFO is a queue-based scheduler. It is a very simple approach to scheduling and it does not guarantee performance efficiency, as each job would use a whole cluster for execution. So other jobs may keep waiting to finish their execution, although a shared cluster has a great capability to offer more-than-enough resources to many users.

The fair scheduler

Fair scheduling is the policy of scheduling that assigns resources...

Recent developments in YARN architecture

The ResourceManager is a single point of failure and restart because of various reasons: bugs, hardware failure, deliberate downtime for upgrading, and so on.

We already saw how crucial the role of the ResourceManager in YARN architecture is. The ResourceManager has become a single point of failure; if the ResourceManager in a cluster goes down, everything on that cluster will be lost.

So in a recent development of YARN, ResourceManager HA became a high priority. This recent development of YARN not only covers ResourceManager HA, but also provides transparency to users and does not require them to monitor such events explicitly and resubmit the jobs.

Overly complex in MRv1 for the fact that JobTracker has to save too much of meta-data: both cluster state and per-application running state. This means that if Job-Tracker dies, then all the applications in a running state will be lost.

The development of ResourceManager recovery will be done in two phases...

Summary

In this chapter, we covered the architectural components of YARN, their responsibilities, and their interoperations. We also focused on some major development work going on in the community to overcome the drawbacks of the current release. In the next chapter, we will cover the installation steps of YARN.

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Description

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.

Who is this book for?

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.

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Feb 24, 2015
Length: 176 pages
Edition : 1st
Language : English
ISBN-13 : 9781784397722
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Publication date : Feb 24, 2015
Length: 176 pages
Edition : 1st
Language : English
ISBN-13 : 9781784397722
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Table of Contents

11 Chapters
1. Need for YARN Chevron down icon Chevron up icon
2. YARN Architecture Chevron down icon Chevron up icon
3. YARN Installation Chevron down icon Chevron up icon
4. YARN and Hadoop Ecosystems Chevron down icon Chevron up icon
5. YARN Administration Chevron down icon Chevron up icon
6. Developing and Running a Simple YARN Application Chevron down icon Chevron up icon
7. YARN Frameworks Chevron down icon Chevron up icon
8. Failures in YARN Chevron down icon Chevron up icon
9. YARN – Alternative Solutions Chevron down icon Chevron up icon
10. YARN – Future and Support Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.2
(5 Ratings)
5 star 20%
4 star 80%
3 star 0%
2 star 0%
1 star 0%
francois dlx Jun 08, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is the book you need to maintain and design your Hadoop architecture.It describe not only the architecture but also how it work. It describe the past for compatibility and the future to prepare enhancement.You found in it a lot of information to install and admin yarn modules.It also cover the failures.For design stage, it give samples and some informations on frameworks to link it with TEZ, KAFKA, STORM...To manage or develop a cluster, you must have this book.
Amazon Verified review Amazon
Sunilkumar Chandran Jun 05, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Yarn essentials books provided more detailed guidelines on YARM framework, the installation for single node and distributed systems in cluster. The explanation on the performance and scalability are very good for understanding and good one for any one to start big data career.The exaples are commendable.
Amazon Verified review Amazon
consultstevenj Jun 05, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Yarn Essentials does an excellent job of answering the big questions about YARN and it's place in the Hadoop stack. The initial chapters on need for Yarn and Architecture do a great job of explaining YARN's function and how it related to the change from Hadoop 1 to Hadoop 2. What every confusion is remaining gets addressed in YARN and the Hadoop Ecosystem. The balance of graphics, code examples and explaining makes this a good YARN introduction. The book covers both practical concern like install and failures , the frameworks that take advantage of YARN and what might be in store in the future for the YARN Apache project. I would say this is a solid addition to your Hadoop library.
Amazon Verified review Amazon
Kumaravel Kandasami Jun 04, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
YARN Essentials - As the book name suggests, is a clear simple to read book on YARN technology.In think at this point, it is the only book that is available in the market on YARN covering to this detail.I would recommend this book to teams planning to migrate from MR1 to MR2, or starting on YARN clusters.
Amazon Verified review Amazon
ssanupindi Jul 15, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I liked this book as it helped me to understand the features of Yarn for Hadoop 2.x version.Chapter 2 & 3 covers with Yarn Architecture and Installing Yarn (in sudo & distributed modes) and covers with important configuration files.The chapter 4 covers the differences of MRV1 & MRV2 and provides MRv1 and MRV2 Example code and helped to clearly understnad the differences in the implementation of MRV1 & MRV2.Next, Chapter5 which covers with Yarn Administration and this chapter is most interesting one in this entire book and it helps understand the container allocation and scheuling polices etc.And other chapters tells the other frameworks Yarn supports and the other interesting chapter in this book is the last chapter @ failures in Yarn which covers with various scenarios when a particualr component of Yarn fails.In overall, this book is worth for the money i paid.
Amazon Verified review Amazon
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