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

ResourceManager REST APIs

YARN ResourceManager APIs allow the user or administrator to obtain cluster metrics, lists of NodeManager nodes, scheduler information, associated applications, and so on. As mentioned in the previous chapters, the default port for the ResourceManager web application is 8088. An administrator can configure the web application address using the yarn.resourcemanager.webapp.address property in the yarn-site.xml file:


The ResourceManager REST APIs can be grouped as:

  • Cluster summary

  • Scheduler details

  • Nodes

  • Applications

The cluster summary

There are two URIs to fetch cluster meta-information such as the deployed version, available memory, cluster capabilities, nodes available, and so on:

  • Cluster metadata: This API provides overall information about the cluster, including the state and version of ResourceManager and Hadoop:

    • URI: http:/...