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Accelerating Incremental Graph Processing by Layering Graph

Published: 25 September 2023 Publication History

Abstract

By using the memoized previous computation state, incremental graph computation can reduce unnecessary recomputation. However, a small change may propagate over the whole graph and lead to large-scale iterative computations. For this, we propose Layph, a two-layered graph framework. The upper layer is a skeleton of the graph which is much smaller than the original graph, and the lower layer has some disjoint subgraphs. Layph limits costly global iterative computations on the original graph to the small graph skeleton and a few subgraphs updated with the input graph changes. Our experimental results show that Layph outperforms current state-of-the-art incremental graph systems in response time.

References

[1]
Guanyu Feng, Zixuan Ma, Daixuan Li, and et.al.2021. RisGraph: A Real-Time Streaming System for Evolving Graphs to Support Sub-millisecond Per-update Analysis at Millions Ops/s. In In SIGMOD. ACM, 513–527.
[2]
Shufeng Gong, Chao Tian, Qiang Yin, and et.al.2021. Automating Incremental Graph Processing with Flexible Memoization. Proc. VLDB Endow. 14, 9 (2021), 1613–1625.
[3]
Mugilan Mariappan, Joanna Che, and Keval Vora. 2021. DZiG: sparsity-aware incremental processing of streaming graphs. In In EuroSys. ACM, 83–98.
[4]
Mugilan Mariappan and Keval Vora. 2019. GraphBolt: Dependency-Driven Synchronous Processing of Streaming Graphs. In Proceedings of the Fourteenth EuroSys Conference 2019, Dresden, Germany, March 25-28, 2019. ACM, 25:1–25:16.
[5]
Keval Vora, Rajiv Gupta, and Guoqing Xu. 2017. KickStarter: Fast and Accurate Computations on Streaming Graphs via Trimmed Approximations. In In ASPLOS. ACM, 237–251.
[6]
Song Yu, Shufeng Gong, Yanfeng Zhang, and et.al.2023. Layph: Making Change Propagation Constraint in Incremental Graph Processing by Layering Graph. arXiv preprint arXiv:2304.07458 (2023).

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Published In

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ACM TURC '23: Proceedings of the ACM Turing Award Celebration Conference - China 2023
July 2023
173 pages
ISBN:9798400702334
DOI:10.1145/3603165
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 September 2023

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Author Tags

  1. Layph
  2. dynamic graph
  3. incremental graph computation

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  • Poster
  • Research
  • Refereed limited

Funding Sources

  • National Natural Science Foundation of China
  • the Key R&D Program of Liaoning Province
  • the Fun- damental Research Funds for the Central Universities
  • National Social Science Foundation of China

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ACM TURC '23

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