Systems for Big Graph Analytics
1st Edition
Published on 31. May 2017
VI, 92 pages
978-3-319-58217-7 (ISBN)
Description
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 details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
VI, 92 p. 10 illus., 2 illus. in color.
File size
1,53 MB
ISBN-13
978-3-319-58217-7 (9783319582177)
DOI
10.1007/978-3-319-58217-7
Schweitzer Classification
Other editions
Additional editions
Da Yan | Yuanyuan Tian | James Cheng
Systems for Big Graph Analytics
Book
06/2017
Springer
€53.49
Shipment within 10-15 days
Content
1 Introduction.- 2 Pregel-Like Systems.- 3 Hands-On Experiences.- 4 Shared Memory Abstraction.- 5 Block-Centric Computation.- 6 Subgraph-Centric Graph Mining.- 7 Matrix-Based Graph Systems.- 8 Conclusions.
