Guide to High Performance Distributed Computing: Case Studies With Hadoop, Scalding and Spark

Srinivasa, K. G./ Muppalla, Anil Kumar

ISBN 10: 3319383477 ISBN 13: 9783319383477

Edit� par Springer-Verlag New York Inc, 2016

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reprint edition. 324 pages. 9.25x6.10x0.73 inches. In Stock. N� de r�f. du vendeur __3319383477

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Synopsis :

This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies. Comprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks. Features: describes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing; presents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution; Reviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding; Provides detailed case studies on approaches to clustering, data classification and regression analysis; Explains the process of creating a working recommender system using Scalding and Spark.

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Titre : Guide to High Performance Distributed ...
�diteur : Springer-Verlag New York Inc
Date d'�dition : 2016
Reliure : Paperback
Etat : Brand New

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Guide to High Performance Distributed Computing

K.G. Srinivasa|Anil Kumar Muppalla

Edit� par Springer International Publishing, 2016

ISBN 10 : 3319383477 ISBN 13 : 9783319383477

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a guide to the distributed computing technologies of Hadoop and Spark, from the perspective of industry practitionersSupports the theory with case studies taken from a range of disciplines, including data mining, machine learning, graph p. N� de r�f. du vendeur 448749044

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Guide to High Performance Distributed Computing | Case Studies with Hadoop, Scalding and Spark

Anil Kumar Muppalla (u. a.)

Edit� par Springer International Publishing, 2016

ISBN 10 : 3319383477 ISBN 13 : 9783319383477

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Guide to High Performance Distributed Computing

Anil Kumar Muppalla

Edit� par Springer International Publishing Okt 2016, 2016

ISBN 10 : 3319383477 ISBN 13 : 9783319383477

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies. Comprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks. Features: describes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing; presents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution; Reviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding; Provides detailed case studies on approaches to clustering, data classification and regression analysis; Explains the process of creating a working recommender system using Scalding and Spark. 324 pp. Englisch. N� de r�f. du vendeur 9783319383477

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Guide to High Performance Distributed Computing

Anil Kumar Muppalla

Edit� par Springer International Publishing, Springer International Publishing Okt 2016, 2016

ISBN 10 : 3319383477 ISBN 13 : 9783319383477

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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

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Taschenbuch. Etat : Neu. Neuware -This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies. Comprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks. Features: describes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing; presents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution; Reviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding; Provides detailed case studies on approaches to clustering, data classification and regression analysis; Explains the process of creating a working recommender system using Scalding and Spark.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 324 pp. Englisch. N� de r�f. du vendeur 9783319383477

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Guide to High Performance Distributed Computing : Case Studies with Hadoop, Scalding and Spark

Anil Kumar Muppalla

Edit� par Springer International Publishing, 2016

ISBN 10 : 3319383477 ISBN 13 : 9783319383477

Neuf Taschenbuch

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies. Comprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks. Features: describes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing; presents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution; Reviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding; Provides detailed case studies on approaches to clustering, data classification and regression analysis; Explains the process of creating a working recommender system using Scalding and Spark. N� de r�f. du vendeur 9783319383477

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