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.
Table of Contents (20 chapters)
Learning YARN
Credits
About the Authors
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Index

About the Reviewers

P. Tomas Delvechio is an IT programmer with nearly 10 years of experience. He completed his graduation at Luján University, Argentina. For his thesis, he started to research big data trends and gained a lot of deep knowledge of the MapReduce approach and the Hadoop environment. He participated in many projects as a web developer and software designing, with PHP and Python as the main languages. In his university, he worked as an assistant for the subject computer networks and taught courses on Hadoop and MapReduce for distributed systems subjects and academic conferences. Also, he is a regular member of the staff of programmers in the same institution. In his free time, he is an enthusiastic user of free software and assists in the organization of conferences of diffusion on it.

Swapnil Salunkhe is a passionate software developer who works on big data. He has a keen interest in learning and implementing new technologies. He also has a passion for functional programming, machine learning, and working with complex datasets. He can be contacted via his Twitter handle at @swapnils10.

Parambir Singh is a JVM/frontend programmer who has worked on a variety of applications in his 10 years of experience. He's currently employed as a senior developer with Atlassian and is working on building their cloud infrastructure.

Jenny (Xiao) Zhang is a technology professional in business analytics, KPIs, and big data. She helps businesses better manage, measure, report, and analyze big data to answer critical business questions and give better experiences to customers. She has written a number of blog posts at jennyxiaozhang.com on big data, Hadoop, and YARN. She constantly shares insights on big data on Twitter at @smallnaruto. She previously reviewed another YARN book called YARN Essentials.