Book Image

Learning YARN

Book Image

Learning YARN

Overview of this book

Today enterprises generate huge volumes of data. In order to provide effective services and to make smarter and more intelligent decisions from these huge volumes of data, enterprises use big-data analytics. In recent years, Hadoop has been used for massive data storage and efficient distributed processing of data. The Yet Another Resource Negotiator (YARN) framework solves the design problems related to resource management faced by the Hadoop 1.x framework by providing a more scalable, efficient, flexible, and highly available resource management framework for distributed data processing. This book starts with an overview of the YARN features and explains how YARN provides a business solution for growing big data needs. You will learn to provision and manage single, as well as multi-node, Hadoop-YARN clusters in the easiest way. You will walk through the YARN administration, life cycle management, application execution, REST APIs, schedulers, security framework and so on. You will gain insights about the YARN components and features such as ResourceManager, NodeManager, ApplicationMaster, Container, Timeline Server, High Availability, Resource Localisation and so on. The book explains Hadoop-YARN commands and the configurations of components and explores topics such as High Availability, Resource Localization and Log aggregation. You will then be ready to develop your own ApplicationMaster and execute it over a Hadoop-YARN cluster. Towards the end of the book, you will learn about the security architecture and integration of YARN with big data technologies like Spark and Storm. This book promises conceptual as well as practical knowledge of resource management using YARN.

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Learning YARN
Aug, 2015 | 278 pages
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Table of Contents (20 chapters)
Learning YARN
Learning YARN
Credits
Credits
About the Authors
About the Authors
Acknowledgments
Acknowledgments
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Starting with YARN Basics
Starting with YARN Basics
Introduction to MapReduce v1
Shortcomings of MapReducev1
An overview of YARN components
The YARN architecture
How YARN satisfies big data needs
Projects powered by YARN
Summary
2
Setting up a Hadoop-YARN Cluster
Setting up a Hadoop-YARN Cluster
Starting with the basics
The Hadoop-YARN single node installation
An overview of web user interfaces
The Hadoop-YARN multi-node installation
An overview of the Hortonworks and Cloudera installations
Summary
3
Administering a Hadoop-YARN Cluster
Administering a Hadoop-YARN Cluster
Using the Hadoop-YARN commands
Configuring the Hadoop-YARN services
Managing the Hadoop-YARN services
Monitoring the YARN services
Understanding ResourceManager's High Availability
Monitoring NodeManager's health
Summary
4
Executing Applications Using YARN
Executing Applications Using YARN
Understanding application execution flow
Submitting a sample MapReduce application
Handling failures in YARN
YARN application logging
Summary
5
Understanding YARN Life Cycle Management
Understanding YARN Life Cycle Management
An introduction to state management analogy
The ResourceManager's view
The NodeManager's view
Analyzing transitions through logs
Summary
6
Migrating from MRv1 to MRv2
Migrating from MRv1 to MRv2
Introducing MRv1 and MRv2
High-level changes from MRv1 to MRv2
The migration steps from MRv1 to MRv2
Running and monitoring MRv1 apps on YARN
Summary
7
Writing Your Own YARN Applications
Writing Your Own YARN Applications
An introduction to the YARN API
Writing your own application
Summary
8
Dive Deep into YARN Components
Dive Deep into YARN Components
Understanding ResourceManager
Understanding NodeManager
The YARN Timeline server
The web application proxy server
YARN Scheduler Load Simulator (SLS)
Handling resource localization in YARN
Summary
9
Exploring YARN REST Services
Exploring YARN REST Services
Introduction to YARN REST services
ResourceManager REST APIs
NodeManager REST APIs
MapReduce ApplicationMaster REST APIs
MapReduce HistoryServer REST APIs
How to access REST services
Summary
10
Scheduling YARN Applications
Scheduling YARN Applications
An introduction to scheduling in YARN
An overview of queues
Types of queues
An introduction to schedulers
Summary
11
Enabling Security in YARN
Enabling Security in YARN
Adding security to a YARN cluster
Working with ACLs
Other security frameworks
Summary
12
Real-time Data Analytics Using YARN
Real-time Data Analytics Using YARN
The integration of Spark with YARN
The integration of Storm with YARN
The integration of HAMA and Giraph with YARN
Summary
Index
Index

The YARN architecture

In the previous topic, we discussed the YARN components. Here we'll discuss the high-level architecture of YARN and look at how the components interact with each other.

The ResourceManager service runs on the master node of the cluster. A YARN client submits an application to the ResourceManager. An application can be a single MapReduce job, a directed acyclic graph of jobs, a java application, or any shell script. The client also defines an ApplicationMaster and a command to start the ApplicationMaster on a node.

The ApplicationManager service of resource manager will validate and accept the application request from the client. The scheduler service of resource manager will allocate a container for the ApplicationMaster on a node and the NodeManager service on that node will use the command to start the ApplicationMaster service. Each YARN application has a special container called ApplicationMaster. The ApplicationMaster container is the first container of an application.

The ApplicationMaster requests resources from the ResourceManager. The RequestRequest will have the location of the node, memory, and CPU cores required. The ResourceManager will allocate the resources as containers on a set of nodes. The ApplicationMaster will connect to the NodeManager services and request NodeManager to start containers. The ApplicationMaster manages the execution of the containers and will notify the ResourceManager once the application execution is over. Application execution and progress monitoring is the responsibility of ApplicationMaster rather than ResourceManager.

The NodeManager service runs on each slave of the YARN cluster. It is responsible for running application's containers. The resources specified for a container are taken from the NodeManager resources. Each NodeManager periodically updates ResourceManager for the set of available resources. The ResourceManager scheduler service uses this resource matrix to allocate new containers to ApplicationMaster or to start execution of a new application.

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