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Learning YARN

Learning YARN

By : Akhil Arora, Shrey Mehrotra
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Learning YARN

Learning YARN

4 (2)
By: Akhil Arora, Shrey Mehrotra

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 (14 chapters)
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13
Index

Summary


YARN services expose a set of URIs as REST APIs to fetch information related to clusters, nodes, applications, jobs, and more. The response format for these REST APIs is configurable as JSON or XML. These APIs provide useful information to monitor cluster resources and application execution. In this chapter, we covered the different REST APIs available in YARN and looked at how we can access them through web browsers and tools such as Curl. This chapter also covered the REST APIs defined for MapReduce ApplicationMaster and JobHistoryServer services. In the next chapter, we'll discuss the different scheduling algorithms defined in YARN and understand how these schedulers can easily be configured with your cluster.

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