Apache Hadoop YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 (Addison-Wesley Data & Analytics Series)

Apache Hadoop YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 (Addison-Wesley Data & Analytics Series)

Apache Hadoop YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 (Addison-Wesley Data & Analytics Series)

  • Used Book in Good Condition

“This book is a critically needed resource for the newly released Apache Hadoop 2.0, highlighting YARN as the significant breakthrough that broadens Hadoop beyond the MapReduce paradigm.”
—From the Foreword by Raymie Stata, CEO of Altiscale


The Insider’s Guide to Building Distributed, Big Data Applications with Apache Hadoop™ YARN

 

Apache Hadoop is helping drive the Big Data revolution. Now, its data processing has been completely overhauled: Apache Hadoop YARN provides resource management at data center scale and easier ways to create distributed applications that process petabytes of data. And now in Apache Hadoop™ YARN, two Hadoop technical leaders show you how to develop new applications and adapt existing code to fully leverage these revolutionary advances.

 

YARN project founder Arun Murthy and project lead Vinod Kumar Vavilapalli demonstrate how YARN increases scalability and cluster utilization, enables new programming models and services, and opens new options beyond Java and batch processing. They walk you through the entire YARN project lifecycle, from installation through deployment.

 

You’ll find many examples drawn from the authors’ cutting-edge experience—first as Hadoop’s earliest developers and implementers at Yahoo! and now as Hortonworks developers moving the platform forward and helping customers succeed with it.

 

Coverage includes

  • YARN’s goals, design, architecture, and components—how it expands the Apache Hadoop ecosystem
  • Exploring YARN on a single node 
  • Administering YARN clusters and Capacity Scheduler 
  • Running existing MapReduce applications 
  • Developing a large-scale clustered YARN application 
  • Discovering new open source frameworks that run under YARN

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3 comments

  1. 11 of 14 people found the following review helpful
    1.0 out of 5 stars
    Poorly written., May 6, 2014
    By 

    Verified Purchase(What’s this?)
    This review is from: Apache Hadoop YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 (Addison-Wesley Data & Analytics Series) (Paperback)
    The book has a significant number of typos, poor grammar, and lacks power. It seems as if it was rushed through.

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  2. 5 of 6 people found the following review helpful
    4.0 out of 5 stars
    Typos and grammar issues aside, this is a must read if you’re moving from MRv1 to MRv2/YARN, June 3, 2014
    By 
    JC (SF, CA) –

    Verified Purchase(What’s this?)
    This review is from: Apache Hadoop YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 (Addison-Wesley Data & Analytics Series) (Paperback)
    Yes, this seems to have been rushed to print and, unfortunately, yes the proof-readers were not up to snuff.

    However, once you get over the strange sentences that don’t quite read properly (and you will, by re-reading them multiple times), this is a great text for someone looking to get a grip on the understanding of YARN and how MRv2 (+ graph, Storm, Spark etc) fit into things.

    With the myriad of technologies and stacks now available in the “Big Data” space, Hadoop has finally realized the “grid” dreams of the early 2000’s on commodity, on-demand clusters.

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  3. 3 of 3 people found the following review helpful
    3.0 out of 5 stars
    The Scripts Are So Broken, June 22, 2014
    By 

    This review is from: Apache Hadoop YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 (Addison-Wesley Data & Analytics Series) (Paperback)
    I gave the book 3 stars because it has a good overview of Hadoop Yarn.

    I only gave it 3 stars because the “fast” installation scripts are so broken I gave up running them and just manually did what they are supposed to do. It took about 8 hours to get my first cluster operational.

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