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Practical graph analytics with Apache Giraph[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	511.5
書名/作者:	Practical graph analytics with Apache Giraph/ by Claudio Martella, Roman Shaposhnik, Dionysios Logothetis.
作者:	Martella, Claudio.
其他作者:	Shaposhnik, Roman.
出版者:	Berkeley, CA : : Apress :, 2015.
面頁冊數:	xix, 315 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Graph theory - Data processing.
標題:	Big data.
標題:	Computer Science.
標題:	Computer Science, general.
標題:	Computational Biology/Bioinformatics.
ISBN:	9781484212516
ISBN:	9781484212523
摘要、提要註:	Practical Graph Analytics with Apache Giraph helps you build data mining and machine learning applications using the Apache Foundation's Giraph framework for graph processing. This is the same framework as used by Facebook, Google, and other social media analytics operations to derive business value from vast amounts of interconnected data points. Graphs arise in a wealth of data scenarios and describe the connections that are naturally formed in both digital and real worlds. Examples of such connections abound in online social networks such as Facebook and Twitter, among users who rate movies from services like Netflix and Amazon Prime, and are useful even in the context of biological networks for scientific research. Whether in the context of business or science, viewing data as connected adds value by increasing the amount of information available to be drawn from that data and put to use in generating new revenue or scientific opportunities. Apache Giraph offers a simple yet flexible programming model targeted to graph algorithms and designed to scale easily to accommodate massive amounts of data. Originally developed at Yahoo!, Giraph is now a top top-level project at the Apache Foundation, and it enlists contributors from companies such as Facebook, LinkedIn, and Twitter. Practical Graph Analytics with Apache Giraph brings the power of Apache Giraph to you, showing how to harness the power of graph processing for your own data by building sophisticated graph analytics applications using the very same framework that is relied upon by some of the largest players in the industry today.
電子資源:	http://dx.doi.org/10.1007/978-1-4842-1251-6

Practical graph analytics with Apache Giraph[electronic resource] /
Martella, Claudio.

Practical graph analytics with Apache Giraph[electronic resource] /by Claudio Martella, Roman Shaposhnik, Dionysios Logothetis. - Berkeley, CA :Apress :2015. - xix, 315 p. :ill., digital ;24 cm.

Practical Graph Analytics with Apache Giraph helps you build data mining and machine learning applications using the Apache Foundation's Giraph framework for graph processing. This is the same framework as used by Facebook, Google, and other social media analytics operations to derive business value from vast amounts of interconnected data points. Graphs arise in a wealth of data scenarios and describe the connections that are naturally formed in both digital and real worlds. Examples of such connections abound in online social networks such as Facebook and Twitter, among users who rate movies from services like Netflix and Amazon Prime, and are useful even in the context of biological networks for scientific research. Whether in the context of business or science, viewing data as connected adds value by increasing the amount of information available to be drawn from that data and put to use in generating new revenue or scientific opportunities. Apache Giraph offers a simple yet flexible programming model targeted to graph algorithms and designed to scale easily to accommodate massive amounts of data. Originally developed at Yahoo!, Giraph is now a top top-level project at the Apache Foundation, and it enlists contributors from companies such as Facebook, LinkedIn, and Twitter. Practical Graph Analytics with Apache Giraph brings the power of Apache Giraph to you, showing how to harness the power of graph processing for your own data by building sophisticated graph analytics applications using the very same framework that is relied upon by some of the largest players in the industry today.

ISBN: 9781484212516

Standard No.: 10.1007/978-1-4842-1251-6doiSubjects--Topical Terms:

561823
Graph theory
--Data processing.

LC Class. No.: QA166

Dewey Class. No.: 511.5

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