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Revision Accepted: 2019-09-16

Crosschecked: 2019-11-12

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Ning Liu


Dong-sheng Li


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Frontiers of Information Technology & Electronic Engineering  2020 Vol.21 No.3 P.384-404


Large-scale graph processing systems: a survey

Author(s):  Ning Liu, Dong-sheng Li, Yi-ming Zhang, Xiong-lve Li

Affiliation(s):  Science and Technology on Parallel and Distributed Processing Laboratory, National University of Defense Technology, Changsha 410000, China

Corresponding email(s):   liuning17a@nudt.edu.cn, dsli@nudt.edu.cn, zhangyiming@nudt.edu.cn, lixionglve17@nudt.edu.cn

Key Words:  Graph workloads, Graph applications, Graph processing systems

Ning Liu, Dong-sheng Li, Yi-ming Zhang, Xiong-lve Li. Large-scale graph processing systems: a survey[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(3): 384-404.

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T1 - Large-scale graph processing systems: a survey
A1 - Ning Liu
A1 - Dong-sheng Li
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A1 - Xiong-lve Li
J0 - Frontiers of Information Technology & Electronic Engineering
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Y1 - 2020
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1900127

Graph is a significant data structure that describes the relationship between entries. Many application domains in the real world are heavily dependent on graph data. However, graph applications are vastly different from traditional applications. It is inefficient to use general-purpose platforms for graph applications, thus contributing to the research of specific graph processing platforms. In this survey, we systematically categorize the graph workloads and applications, and provide a detailed review of existing graph processing platforms by dividing them into general-purpose and specialized systems. We thoroughly analyze the implementation technologies including programming models, partitioning strategies, communication models, execution models, and fault tolerance strategies. Finally, we analyze recent advances and present four open problems for future research.





Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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