Systems for Big Graph Analytics

Nonfiction, Computers, Application Software, Computer Graphics, General Computing, Internet
Cover of the book Systems for Big Graph Analytics by Da Yan, Yuanyuan Tian, James Cheng, Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Da Yan, Yuanyuan Tian, James Cheng ISBN: 9783319582177
Publisher: Springer International Publishing Publication: May 31, 2017
Imprint: Springer Language: English
Author: Da Yan, Yuanyuan Tian, James Cheng
ISBN: 9783319582177
Publisher: Springer International Publishing
Publication: May 31, 2017
Imprint: Springer
Language: English

There has been a surging interest in developing systems for analyzing big graphs generated by real applications, such as online social networks and knowledge graphs. This book aims to help readers get familiar with the computation models of various graph processing systems with minimal time investment.

This book is organized into three parts, addressing three popular computation models for big graph analytics: think-like-a-vertex, think-likea- graph, and think-like-a-matrix. While vertex-centric systems have gained great popularity, the latter two models are currently being actively studied to solve graph problems that cannot be efficiently solved in vertex-centric model, and are the promising next-generation models for big graph analytics. For each part, the authors introduce the state-of-the-art systems, emphasizing on both their technical novelties and hands-on experiences of using them. The systems introduced include Giraph, Pregel+, Blogel, GraphLab, CraphChi, X-Stream, Quegel, SystemML, etc.

Readers will learn how to design graph algorithms in various graph analytics systems, and how to choose the most appropriate system for a particular application at hand. The target audience for this book include beginners who are interested in using a big graph analytics system, and students, researchers and practitioners who would like to build their own graph analytics systems with new features.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

There has been a surging interest in developing systems for analyzing big graphs generated by real applications, such as online social networks and knowledge graphs. This book aims to help readers get familiar with the computation models of various graph processing systems with minimal time investment.

This book is organized into three parts, addressing three popular computation models for big graph analytics: think-like-a-vertex, think-likea- graph, and think-like-a-matrix. While vertex-centric systems have gained great popularity, the latter two models are currently being actively studied to solve graph problems that cannot be efficiently solved in vertex-centric model, and are the promising next-generation models for big graph analytics. For each part, the authors introduce the state-of-the-art systems, emphasizing on both their technical novelties and hands-on experiences of using them. The systems introduced include Giraph, Pregel+, Blogel, GraphLab, CraphChi, X-Stream, Quegel, SystemML, etc.

Readers will learn how to design graph algorithms in various graph analytics systems, and how to choose the most appropriate system for a particular application at hand. The target audience for this book include beginners who are interested in using a big graph analytics system, and students, researchers and practitioners who would like to build their own graph analytics systems with new features.

More books from Springer International Publishing

Cover of the book Combinatorial Optimization and Applications by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Species Concepts in Biology by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book The EU Accession to the ECHR by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Arctic Summer College Yearbook by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Pedestrian and Evacuation Dynamics 2012 by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Transdisciplinary Systems Engineering by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Current Conveyors by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Generalized Adjoint Systems by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book mGLU Receptors by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Surgical Emergencies in the Cancer Patient by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Muslim Citizenship in Liberal Democracies by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Fundamentals of Friction and Wear on the Nanoscale by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Magnesium Technology 2019 by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book The Monge-Ampère Equation by Da Yan, Yuanyuan Tian, James Cheng
Cover of the book Fundamental Issues of Artificial Intelligence by Da Yan, Yuanyuan Tian, James Cheng
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy