research-article

Incrementalization of graph partitioning algorithms

Authors:

Jingren ZhouAuthors Info & Claims

Proceedings of the VLDB Endowment, Volume 13, Issue 8

Pages 1261 - 1274

https://doi.org/10.14778/3389133.3389142

Published: 01 April 2020 Publication History

Abstract

This paper studies incremental graph partitioning. Given a (vertex-cut or edge-cut) partition C(G) of a graph G and updates ΔG to G, it is to compute changes ΔO to C(G), yielding a partition of the updated graph such that (a) the new partition is load-balanced, (b) its cut size is minimum, and (c) the changes ΔO are also minimum. We show that this tri-criteria optimization problem is NP-complete, even when ΔG has a constant size. Worse yet, it is unbounded, i.e., there exists no algorithm that computes such ΔO with a cost that is determined only by the changes ΔG and ΔO. We approach this by proposing to incrementalize widely-used graph partitioners A into heuristically-bounded incremental algorithms A_Δ. Given graph G, updates ΔG to G and a partition A(G) of G by A, AΔ computes changes ΔO to A(G) such that (1) applying ΔO to A(G) produces a new partition of the updated graph although it may not be exactly the one derived by A, (2) it retains the same bounds on balance and cut sizes as A, and (3) ΔO is decided by ΔG alone. We show that we can deduce A_Δ from both vertex-cut and edge-cut partitioners A, retaining their bounds. Using real-life and synthetic data, we verify the efficiency and partition quality of our incremental partitioners.

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Cited By

Gan XWu GQiu SXiong FSi JFang JDong DGong CLi TWang ZLee IChabbi MSteuwer M(2024)GraphCube: Interconnection Hierarchy-aware Graph ProcessingProceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming10.1145/3627535.3638498(160-174)Online publication date: 2-Mar-2024
https://dl.acm.org/doi/10.1145/3627535.3638498
Yao FTao QYu WZhang YGong SWang QYu GZhou J(2023)RAGraph: A Region-Aware Framework for Geo-Distributed Graph ProcessingProceedings of the VLDB Endowment10.14778/3632093.363209417:3(264-277)Online publication date: 1-Nov-2023
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cover image Proceedings of the VLDB Endowment

Proceedings of the VLDB Endowment Volume 13, Issue 8

April 2020

172 pages

ISSN:2150-8097

Editors:
Magdalena Balazinska
University of Washington
,
Xiaofang Zhou
University of Queensland, Australia

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VLDB Endowment

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Published: 01 April 2020

Published in PVLDB Volume 13, Issue 8

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Cited By

Gan XWu GQiu SXiong FSi JFang JDong DGong CLi TWang ZLee IChabbi MSteuwer M(2024)GraphCube: Interconnection Hierarchy-aware Graph ProcessingProceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming10.1145/3627535.3638498(160-174)Online publication date: 2-Mar-2024
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Yao FTao QYu WZhang YGong SWang QYu GZhou J(2023)RAGraph: A Region-Aware Framework for Geo-Distributed Graph ProcessingProceedings of the VLDB Endowment10.14778/3632093.363209417:3(264-277)Online publication date: 1-Nov-2023
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Qiao YWu KKhabbazian M(2023)Non-intrusive Balance Tomography Using Reinforcement Learning in the Lightning NetworkACM Transactions on Privacy and Security10.1145/363936627:1(1-32)Online publication date: 29-Dec-2023
https://dl.acm.org/doi/10.1145/3639366
Huang ZYuan LSui HChen ZYang SYang J(2023)Edge Coloring on Dynamic GraphsDatabase Systems for Advanced Applications10.1007/978-3-031-30675-4_10(137-153)Online publication date: 17-Apr-2023
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Fan W(2022)Big graphsProceedings of the VLDB Endowment10.14778/3554821.355489915:12(3782-3797)Online publication date: 29-Sep-2022
https://dl.acm.org/doi/10.14778/3554821.3554899
Çatalyürek ÜDevine KFaraj MGottesbüren LHeuer TMeyerhenke HSanders PSchlag SSchulz CSeemaier DWagner D(2022)More Recent Advances in (Hyper)Graph PartitioningACM Computing Surveys10.1145/357180855:12(1-38)Online publication date: 23-Nov-2022
https://dl.acm.org/doi/10.1145/3571808
Hanauer KHenzinger MSchulz C(2022)Recent Advances in Fully Dynamic Graph Algorithms – A Quick Reference GuideACM Journal of Experimental Algorithmics10.1145/355580627(1-45)Online publication date: 12-Aug-2022
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Zhang YYu JIves ZBonifati AEl Abbadi A(2022)Relative Subboundedness of Contraction Hierarchy and Hierarchical 2-Hop Index in Dynamic Road NetworksProceedings of the 2022 International Conference on Management of Data10.1145/3514221.3517875(1992-2005)Online publication date: 10-Jun-2022
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