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


This chapter showcased how an application is executed over a YARN cluster. The chapter started with explaining the phases involved in the execution flow for an application. These phases explicate the coordination and communication happening between the different YARN components during application execution.

We executed a sample application provided by Hadoop over the YARN cluster. For the sample application, we saw how an application is submitted to the ResourceManager and how YARN executes the containers of the application as a YarnChild process over the cluster nodes. We also covered progress reports and resource utilization through the ResourceManager web UI.

We also discussed the different failure scenarios and a brief overview about logging in YARN. This chapter was intended to help the users in debugging and analyzing the flow of applications submitted to the cluster.

In the next chapter, we will discuss the internal life cycle management in YARN. It is an extension of the application...