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Systems for Big Graph Analytics (Paperback, 1st ed. 2017)
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Systems for Big Graph Analytics (Paperback, 1st ed. 2017)
Series: SpringerBriefs in Computer Science
Expected to ship within 10 - 15 working days
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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.
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