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

Chapter 7. Writing Your Own YARN Applications

In the first chapter, we talked about the shortcomings of Hadoop 1.x framework. Hadoop 1.x framework was restricted to MapReduce programming only. You had to write data processing logic as map and reduce tasks. With the introduction of YARN in Hadoop 2.x version, you can now execute different data processing algorithms over the data stored in HDFS. YARN separates the resource management and the data processing frameworks into two different components, ResourceManager and ApplicationMaster.

In the last few chapters, you learned about the application execution flow, and how YARN components communicate and manage the life cycle of an application. You executed a MapReduce application over a YARN cluster and worked with MRApplicationMaster component. In this chapter, you will learn to create your own YARN applications using YARN Java APIs. This chapter requires you to have a Java background and basic knowledge of Eclipse IDE. This chapter is helpful...