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Apache Hadoop YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 [Format Kindle]

Arun C. Murthy , Vinod Kumar Vavilapalli , Doug Eadline , Joseph Niemiec , Jeff Markham

Prix conseillé : EUR 24,25 De quoi s'agit-il ?
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Descriptions du produit

Revue de presse

" This book is a desperately needed resource for administrators, developers, and power-users of the Hadoop YARN framework. It does an excellent job of documenting the (often unknown) history that inevitably lead up to YARN from previous versions of Hadoop, which provides a valuable canvas against which to present the remaining pragmatically-oriented text. Moving from the history of YARN, it wisely jumps right into getting the reader up and running with their own YARN setup (on a single machine or on a larger cluster) such that the rest of the text is not merely conjecturing, but real guidance for a real instance of YARN. Chapters 7 and 8 were the ones I was most looking forward to in the text from the start, as those "core" components of YARN are some of the ones which are least understood and yet concurrently most impacting on performance. They did not disappoint."

 - Ellis H. Wilson III, Storage Scientist

Présentation de l'éditeur

“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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Commentaires en ligne

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Commentaires client les plus utiles sur Amazon.com (beta)
Amazon.com: 3.0 étoiles sur 5  14 commentaires
4 internautes sur 4 ont trouvé ce commentaire utile 
2.0 étoiles sur 5 Too many circumlocutions that never get to the point. You will need to augment this text, with internet-based resources. 22 août 2014
Par nyceyes - Publié sur Amazon.com
Format:Broché|Achat vérifié
I can't give this book a great rating. In so many places it took five, six, seven or more sentences to say what could be said in one or two well-written, forceful sentences. To some degree I can look past that, were it not for this: even after an unnecessary circumlocution, the point was never firmly made, if at all. Sadly, I had to take my understanding of YARN back to the internet, post my book purchase.
6 internautes sur 7 ont trouvé ce commentaire utile 
2.0 étoiles sur 5 Could be Hadoop Book primer if source code published 1 juin 2014
Par chitti - Publié sur Amazon.com
Format:Broché|Achat vérifié
This book mostly provides introduction and theory on Hadoop with YARN features with installation guide.

The book severely lacking hands-on examples to get the feeling of working on Hadoop. The books's web page says for last one month "We are in the process of uploading all the code from the book. Please come back again in a while! "
13 internautes sur 17 ont trouvé ce commentaire utile 
1.0 étoiles sur 5 Poorly written. 7 mai 2014
Par ZenBowman - Publié sur Amazon.com
Format:Broché|Achat vérifié
The book has a significant number of typos, poor grammar, and lacks power. It seems as if it was rushed through.
7 internautes sur 9 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Typos and grammar issues aside, this is a must read if you're moving from MRv1 to MRv2/YARN 3 juin 2014
Par JC - Publié sur Amazon.com
Format:Broché|Achat vérifié
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.
5 internautes sur 6 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 The Scripts Are So Broken 22 juin 2014
Par Joshua Horns - Publié sur Amazon.com
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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