Xuguang Ren
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.
- F. Bi, L. Chang, X. Lin, L. Qin, and W. Zhang. Efficient subgraph matching by postponing cartesian products. In SIGMOD, pages 1199--1214, 2016. Google Scholar
Digital Library
- N. Bruno, L. Gravano, N. Koudas, and D. Srivastava. Navigation-vs. index-based XML multi-query processing. In ICDE, pages 139--150, 2003.Google ScholarCross Ref
- 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. Google ScholarDigital Library
- A. Edenbrandt. Quotient tree partitioning of undirected graphs. BIT Numerical Mathematics, 26(2):148--155, 1986. Google ScholarDigital Library
- W. Fan, Z. Fan, C. Tian, and X. L. Dong. Keys for graphs. PVLDB, 8(12):1590--1601, 2015. Google ScholarDigital Library
- W. Fan, X. Wang, Y. Wu, and J. Xu. Association rules with graph patterns. PVLDB, 8(12):1502--1513, 2015. Google ScholarDigital Library
- W. Fan, Y. Wu, and J. Xu. Functional dependencies for graphs. In SIGMOD, pages 1843--1857, 2016. Google ScholarDigital Library
- S. J. Finkelstein. Common subexpression analysis in database applications. In SIGMOD, pages 235--245, 1982. Google ScholarDigital Library
- 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. Google ScholarDigital Library
- H. He and A. K. Singh. Query language and access methods for graph databases. In Manag. and Min. Graph Data, pages 125--160. 2010.Google ScholarCross Ref
- 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. Google ScholarDigital Library
- 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. Google ScholarDigital Library
- W. Le, A. Kementsietsidis, S. Duan, and F. Li. Scalable multi-query optimization for SPARQL. In ICDE, pages 666--677, 2012. Google ScholarDigital Library
- 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. Google ScholarDigital Library
- M. Natarajan. Undertsanding the structure of a drug trafficing organization: a converational analysis. Crime Preventon Studies, 11:273--298, 2000.Google Scholar
- Y. Q and S. SH. Path matching and graph matching in biological networks. J Comput Biol, 14(1):56--67, 2007.Google ScholarCross Ref
- X. Ren and J. Wang. Exploiting vertex relationships in speeding up subgraph isomorphism over large graphs. PVLDB, 8(5):617--628, 2015. Google ScholarDigital Library
- T. Sellis and S. Ghosh. On the multiple-query optimization problem. TKDE, (2):262--266, 1990. Google ScholarDigital Library
- T. K. Sellis. Multiple-query optimization. TODS, 13(1):23--52, 1988. Google ScholarDigital Library
- 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. Google ScholarDigital Library
- Z. Sun, H. Wang, H. Wang, B. Shao, and J. Li. Efficient subgraph matching on billion node graphs. PVLDB, 5:788--799, 2012. Google ScholarDigital Library
- J. R. Ullmann. An algorithm for subgraph isomorphism. JACM, 23(1):31--42, 1976. Google ScholarDigital Library
- P. Zhao and J. Han. On graph query optimization in large networks. PVLDB, 3:340--351, 2010. Google ScholarDigital Library
Index Terms
- Multi-query optimization for subgraph isomorphism search
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