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Moving beyond MapReduce - learn resource management and big data processing using YARN
About This Book- Deep dive into YARN components, schedulers, life cycle management and security architecture
- Create your own Hadoop-YARN applications and integrate big data technologies with YARN
- Step-by-step guide to provision, manage, and monitor Hadoop-YARN clusters with ease
This book is intended for those who want to understand what YARN is and how to efficiently use it for the resource management of large clusters. For cluster administrators, this book gives a detailed explanation of provisioning and managing YARN clusters. If you are a Java developer or an open source contributor, this book will help you to drill down the YARN architecture, write your own YARN applications and understand the application execution phases. This book will also help big data engineers explore YARN integration with real-time analytics technologies such as Spark and Storm.
What You Will Learn- Explore YARN features and offerings
- Manage big data clusters efficiently using the YARN framework
- Create single as well as multi-node Hadoop-YARN clusters on Linux machines
- Understand YARN components and their administration
- Gain insights into application execution flow over a YARN cluster
- Write your own distributed application and execute it over YARN cluster
- Work with schedulers and queues for efficient scheduling of applications
- Integrate big data projects like Spark and Storm with YARN
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.
Style and approachStarting with the basics and covering the core concepts with the practical usage, this tutorial is a complete guide to learn and explore YARN offerings.
- Sales Rank: #591266 in Books
- Published on: 2015-08-31
- Released on: 2015-08-28
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .63" w x 7.50" l, 1.06 pounds
- Binding: Paperback
- 330 pages
About the Author
Akhil Arora
Akhil Arora works as a senior software engineer with Impetus Infotech and has around 5 years of extensive research and development experience. He joined Impetus Infotech in October 2012 and is working with the innovation labs team. He is a technology expert, good learner, and creative thinker. He is also passionate and enthusiastic about application development in Hadoop and other big data technologies. He loves to explore new technologies and is always ready to work on new challenges. Akhil attained a BE degree in computer science from the Apeejay College of Engineering in Sohna, Haryana, India. A beginning for a new voyage, A first step towards my passion and to gain recognition, My first book Learning YARN..!! -- Akhil Arora
Shrey Mehrotra
Shrey Mehrotra has more than 5 years of IT experience, and in the past 4 years, he has gained experience in designing and architecting solutions for cloud and big data domains. Working with big data R&D Labs, he has gained insights into Hadoop, focusing on HDFS, MapReduce, and YARN. His technical strengths also include Hive, PIG, ElasticSearch, Kafka, Sqoop, Flume, and Java. During his free time, he listens to music, watches movies, and enjoys going out with friends.
Most helpful customer reviews
1 of 1 people found the following review helpful.
Great book to learn YARN!!!
By Xiao Zhang
I'm one of the technical reviewers of this book. The book is written in a very simple language and very easy to understand. Even you do not know anything about Big Data, Hadoop and Yarn, you will find this book very easy to follow and you will be surprised how much you can learn after reading the book. This book also has very rich content of technical details and sample code. It is very useful for technical practitioners who want to write their own YARN applications. It also has the latest information on YARN integration with Spark and Storm for real-time analytics.
This book goes great with another YARN book I reviewed – YARN Essentials. Compared to YARN Essentials, this book has more hands on technical details. But the author did a very good job of explaining the concepts at the beginning of each chapter before going into technical details. You will have a comprehensive understanding of the YARN architecture and also be able to do hands on develop&admin work.
I am specifically enjoy the chapter related to YARN integration with Spark and Storm. Hadoop is known for its batch processing power. With the new features such as YARN, Spark, Storm available in Hadoop 2.0, we will be able to solve our challenges related to real-time analytics, which is critical for businesses to be successful in this Big Data era.
I'm happy having gotten the opportunity to work on this book and I'm very well pleased with the result. I believe this book is a great asset to any people who are interested in YARN!
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