CLC number: TP391.41
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2019-11-12
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Citations: Bibtex RefMan EndNote GB/T7714
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.
@article{title="Large-scale graph processing systems: a survey",
author="Ning Liu, Dong-sheng Li, Yi-ming Zhang, Xiong-lve Li",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="21",
number="3",
pages="384-404",
year="2020",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1900127"
}
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%DOI 10.1631/FITEE.1900127
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1900127
Abstract: 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.
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