Book Image

Learning YARN

By : Akhil Arora, Shrey Mehrotra, Shreyank Gupta
Book Image

Learning YARN

By: Akhil Arora, Shrey Mehrotra, Shreyank Gupta

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.
Table of Contents (20 chapters)
Learning YARN
About the Authors
About the Reviewers

Starting with the basics

The Apache Hadoop 2.x version consists of three key components:

  • Hadoop Distributed File System (HDFS)

  • Yet Another Resource Negotiator (YARN)

  • The MapReduce API (Job execution, MRApplicationMaster, JobHistoryServer, and so on)

There are two master processes that manage the Hadoop 2.x cluster—the NameNode and the ResourceManager. All the slave nodes in the cluster have DataNode and NodeManager processes running as the worker daemons for the cluster. The NameNode and DataNode daemons are part of HDFS, whereas the ResourceManager and NodeManager belong to YARN.

When we configure Hadoop-YARN on a single node, we need to have all four processes running on the same system. Hadoop single node installation is generally used for learning purposes. If you are a beginner and need to understand the Hadoop-YARN concepts, you can use a single node Hadoop-YARN cluster.

In the production environment, a multi-node cluster is used. It is recommended to have separate nodes for NameNode and...