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 6. Migrating from MRv1 to MRv2

Hadoop development started in 2005 and in December 2011, it reached version 1.0.0. Enterprises started using Hadoop and implemented data processing algorithms based on the MapReduce programming framework. In 2013, Hadoop version 2.2.0 was released and the MapReduce framework went through a lot of architectural changes. A generic framework for resource management, that is, YARN was introduced and architecture for MapReduce job execution over a Hadoop cluster changed. The old API of the framework is known as MRv1 and the MapReduce APIs associated with YARN framework are termed as MRv2.

In this chapter, we will cover the following:

  • Introduction MRv1 and MRv2

  • Migrating to MRv2

  • Running and monitoring MRv1 apps on YARN