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

An overview of queues


Queues are the data structures or placeholders for the applications submitted to the YARN cluster. A queue is a logical grouping of applications submitted to the YARN cluster. An application is always submitted to a queue. The scheduler then dequeues the applications based on certain parameters to allocate resources and to initiate application execution.

The basic structure of a queue is defined using an interface org.apache.hadoop.yarn.server.resourcemanager.scheduler.Queue, as shown in the following diagram:

A queue object contains the following information:

  • Queue name: This is a name assigned to the queue. In case of hierarchical queues, the complete path to the queue is the name along with the parent queue name. We'll discuss about the hierarchical queues in detail later.

  • Queue information: YARN defines an abstract class QueueInfo to store information related to a queue. It is defined in the org.apache.hadoop.yarn.api.records package.

    The QueueInfo object contains...