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Multi-query optimization for subgraph isomorphism search

Published: 01 November 2016 Publication History

Abstract

Existing work on subgraph isomorphism search mainly focuses on a-query-at-a-time approaches: optimizing and answering each query separately. When multiple queries arrive at the same time, sequential processing is not always the most efficient. In this paper, we study multi-query optimization for subgraph isomorphism search. We first propose a novel method for efficiently detecting useful common sub-graphs and a data structure to organize them. Then we propose a heuristic algorithm based on the data structure to compute a query execution order so that cached intermediate results can be effectively utilized. To balance memory usage and the time for cached results retrieval, we present a novel structure for caching the intermediate results. We provide strategies to revise existing single-query subgraph isomorphism algorithms to seamlessly utilize the cached results, which leads to significant performance improvement. Extensive experiments verified the effectiveness of our solution.

References

[1]
F. Bi, L. Chang, X. Lin, L. Qin, and W. Zhang. Efficient subgraph matching by postponing cartesian products. In SIGMOD, pages 1199--1214, 2016.
[2]
N. Bruno, L. Gravano, N. Koudas, and D. Srivastava. Navigation-vs. index-based XML multi-query processing. In ICDE, pages 139--150, 2003.
[3]
L. P. Cordella, P. Foggia, C. Sansone, and M. Vento. A (sub) graph isomorphism algorithm for matching large graphs. Pattern Anal. Mach. Intell., IEEE Trans, 26(10):1367--1372, 2004.
[4]
A. Edenbrandt. Quotient tree partitioning of undirected graphs. BIT Numerical Mathematics, 26(2):148--155, 1986.
[5]
W. Fan, Z. Fan, C. Tian, and X. L. Dong. Keys for graphs. PVLDB, 8(12):1590--1601, 2015.
[6]
W. Fan, X. Wang, Y. Wu, and J. Xu. Association rules with graph patterns. PVLDB, 8(12):1502--1513, 2015.
[7]
W. Fan, Y. Wu, and J. Xu. Functional dependencies for graphs. In SIGMOD, pages 1843--1857, 2016.
[8]
S. J. Finkelstein. Common subexpression analysis in database applications. In SIGMOD, pages 235--245, 1982.
[9]
W.-S. Han, J. Lee, and J.-H. Lee. TurboIso: towards ultrafast and robust subgraph isomorphism search in large graph databases. In SIGMOD, pages 337--348, 2013.
[10]
H. He and A. K. Singh. Query language and access methods for graph databases. In Manag. and Min. Graph Data, pages 125--160. 2010.
[11]
M. Hong, A. J. Demers, J. E. Gehrke, C. Koch, M. Riedewald, and W. M. White. Massively multi-query join processing in publish/subscribe systems. In SIGMOD, pages 761--772, 2007.
[12]
H. H. Hung, S. S. Bhowmick, B. Q. Truong, B. Choi, and S. Zhou. Quble: towards blending interactive visual subgraph search queries on large networks. VLDB, pages 401--426, 2014.
[13]
W. Le, A. Kementsietsidis, S. Duan, and F. Li. Scalable multi-query optimization for SPARQL. In ICDE, pages 666--677, 2012.
[14]
J. Lee, W.-S. Han, R. Kasperovics, and J.-H. Lee. An in-depth comparison of subgraph isomorphism algorithms in graph databases. In VLDB, pages 133--144, 2012.
[15]
M. Natarajan. Undertsanding the structure of a drug trafficing organization: a converational analysis. Crime Preventon Studies, 11:273--298, 2000.
[16]
Y. Q and S. SH. Path matching and graph matching in biological networks. J Comput Biol, 14(1):56--67, 2007.
[17]
X. Ren and J. Wang. Exploiting vertex relationships in speeding up subgraph isomorphism over large graphs. PVLDB, 8(5):617--628, 2015.
[18]
T. Sellis and S. Ghosh. On the multiple-query optimization problem. TKDE, (2):262--266, 1990.
[19]
T. K. Sellis. Multiple-query optimization. TODS, 13(1):23--52, 1988.
[20]
H. Shang, Y. Zhang, X. Lin, and J. X. Yu. Taming verification hardness: an efficient algorithm for testing subgraph isomorphism. PVLDB, 1(1):364--375, 2008.
[21]
Z. Sun, H. Wang, H. Wang, B. Shao, and J. Li. Efficient subgraph matching on billion node graphs. PVLDB, 5:788--799, 2012.
[22]
J. R. Ullmann. An algorithm for subgraph isomorphism. JACM, 23(1):31--42, 1976.
[23]
P. Zhao and J. Han. On graph query optimization in large networks. PVLDB, 3:340--351, 2010.

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  1. Multi-query optimization for subgraph isomorphism search

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    Published In

    cover image Proceedings of the VLDB Endowment
    Proceedings of the VLDB Endowment  Volume 10, Issue 3
    November 2016
    216 pages
    ISSN:2150-8097
    Issue’s Table of Contents

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    VLDB Endowment

    Publication History

    Published: 01 November 2016
    Published in PVLDB Volume 10, Issue 3

    Author Tags

    1. multi-query optimization
    2. subgraph isomorphism

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