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 11. Enabling Security in YARN

A lot of enterprises today use Hadoop and other big data technologies in a production environment. A secured environment has always been a concern for the Hadoop community. A secured environment ensures rightful access to objects in a shared mode by different entities. The objects refer to the data stored in HDFS or local filesystem, applications running on the cluster, and so on. An entity refers to the services within the cluster, clients accessing the cluster, and so on. YARN needs to ensure that the data and logs stored on the local, as well as on the Hadoop filesystem are secured, so that, only authenticated and authorized users can access the information. YARN also exposes data through web applications and REST calls. A perimeter level security should be added in order to secure these applications and calls.

In this chapter, we will cover the following topics:

  • Adding security to a YARN cluster

  • Working with Access Control Lists (ACLs)

  • An overview of...