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

The Hadoop-YARN multi-node installation

Installing a multi-node Hadoop-YARN cluster is similar to a single node installation. You need to configure the master node, the same as you did during the single node installation. Then, copy the Hadoop installation directory to all the slave nodes and set the Hadoop environment variables for the slave nodes. You can start the Hadoop daemons either directly from the master node, or you can login to each node to run their respective services.


Before starting with the installation steps, make sure that you prepare all the nodes as specified here:

  • All the nodes in the cluster have a unique hostname and IP address. Each node should be able to identify all other nodes through the hostname. If you are not using the DHCP server, you need to make sure that the /etc/hosts file contains the resolution for all nodes used in the cluster. The entries will look similar to the following:    master    slave1