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Regular Path Queries on Large Graphs

  • Conference paper
Scientific and Statistical Database Management (SSDBM 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7338))

Abstract

The significance of regular path queries (RPQs) on graph-like data structures has grown steadily over the past decade. RPQs are, often in restricted forms, part of graph-oriented query languages such as XQuery/XPath and SPARQL, and have applications in areas such as semantic, social, and biomedical networks. However, existing systems for evaluating RPQs are restricted either in the type of the graph (e.g., only trees), the type of regular expressions (e.g., only single steps), and/or the size of the graphs they can handle. No method has yet been developed that would be capable of efficiently evaluating general RPQs on large graphs, i.e., with millions of nodes/edges.

We present a novel approach for answering RPQs on large graphs. Our method exploits the fact that not all labels in a graph are equally frequent. We devise an algorithm which decomposes an RPQ into a series of smaller RPQs using rare labels, i.e., elements of the query with few matches, as way-points. A search thereby is decomposed into a set of smaller search problems which are tackled in a bi-directional fashion, supported by a set of graph indexes. Comparison of our algorithm with two approaches following the traditional methods for tackling such problems, i.e., the usage of automata, reveals that (a) the automata-based methods are not able to handle large graphs due to the amount of memory they require, and that (b) our algorithm outperforms the automata-based approach, often by orders of magnitude. Another advantage of our algorithm is that it can be parallelized easily.

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References

  1. Abiteboul, S., Quass, D., McHugh, J., Widom, J., Wiener, J.L.: The lorel query language for semistructured data. Int. Journal on Digital Libraries 1, 68–88 (1997)

    Google Scholar 

  2. Aerts, S., Lambrechts, D., Maity, S., Van Loo, P., et al.: Gene prioritization through genomic data fusion. Nat. Biotechnol. 24(5), 537–544 (2006)

    Article  Google Scholar 

  3. Aho, A.V., Sethi, R., Ullman, J.D.: Compilers: principles, techniques, and tools. Addison-Wesley Longman Publishing Co., Boston (1986)

    Google Scholar 

  4. Alkhateeb, F., Baget, J.-F., Euzenat, J.: Extending SPARQL with regular expression patterns (for querying RDF). Web Semant. 7(2), 57–73 (2009)

    Article  Google Scholar 

  5. Anyanwu, K., Maduko, A., Sheth, A.: Sparq2l: towards support for subgraph extraction queries in rdf databases. In: WWW 2007, Banff, Alberta, Canada, pp. 797–806 (2007)

    Google Scholar 

  6. Chan, C.-Y., Garofalakis, M., Rastogi, R.: Re-tree: an efficient index structure for regular expressions. The VLDB Journal 12(2), 102–119 (2003)

    Article  Google Scholar 

  7. Cheng, J., Yu, J.X., Ding, B., Yu, P.S., Wang, H.: Fast graph pattern matching. In: ICDE 2008, pp. 913–922. IEEE (2008)

    Google Scholar 

  8. Cho, J., Rajagopalan, S.: A fast regular expression indexing engine. In: ICDE 2002, p. 0419 (2002)

    Google Scholar 

  9. Detwiler, L.T., Suciu, D., Brinkley, J.F.: Regular paths in sparql: Querying the nci thesaurus. American Medical Informatics Association, 161–165 (2008)

    Google Scholar 

  10. Dries, A., Nijssen, S., De Raedt, L.: A query language for analyzing networks. In: CIKM 2009, New York, NY, USA, pp. 485–494 (2009)

    Google Scholar 

  11. Fan, W., Li, J., Ma, S., Tang, N., Wu, Y.: Adding regular expressions to graph reachability and pattern queries. In: ICDE, pp. 39–50 (2011)

    Google Scholar 

  12. Fernandez, M.F., Suciu, D.: Optimizing regular path expressions using graph schemas. In: ICDE 1998, pp. 14–23. IEEE, Washington, DC (1998)

    Google Scholar 

  13. Goldman, R., Widom, J.: Dataguides: Enabling query formulation and optimization in semistructured databases. In: VLDB 1997, pp. 436–445 (1997)

    Google Scholar 

  14. Goldman, R., Widom, J.: Approximate dataguides. In: Workshop on Query Processing (1999)

    Google Scholar 

  15. He, H., Singh, A.K.: Graphs-at-a-time: query language and access methods for graph databases. In: SIGMOD 2008, New York, USA, pp. 405–418 (2008)

    Google Scholar 

  16. Hopcroft, J.E., Ullman, J.D.: Introduction to Automata Theory, Languages, and Computation. Addison-Wesley, Reading (1979)

    MATH  Google Scholar 

  17. Jaeger, S., Gaudan, S., Leser, U., Rebholz-Schuhmann, D.: Integrating protein-protein interactions and text mining for protein function prediction. BMC Bioinformatics 9(suppl. 8), S2 (2008)

    Article  Google Scholar 

  18. Jin, R., Hong, H., Wang, H., Ruan, N., Xiang, Y.: Computing label-constraint reachability in graph databases. In: Proceedings of the 2010 International Conference on Management of Data, SIGMOD 2010, New York, NY, USA, pp. 123–134 (2010)

    Google Scholar 

  19. Kaushik, R., Bohannon, P., Naughton, J.F., Korth, H.F.: Covering indexes for branching path queries. In: SIGMOD Conference, pp. 133–144 (2002)

    Google Scholar 

  20. Kochut, K.J., Janik, M.: SPARQLeR: Extended Sparql for Semantic Association Discovery. In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. LNCS, vol. 4519, pp. 145–159. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  21. Koschmieder, A., Leser, U.: Regular Path Queries on Large Graphs. In: Ailamaki, A., Bowers, S. (eds.) SSDBM 2012. LNCS, vol. 7338, pp. 177–194. Springer, Heidelberg (2012)

    Google Scholar 

  22. Kuramochi, M., Karypis, G.: An efficient algorithm for discovering frequent subgraphs. IEEE Trans. on Knowl. and Data Eng. 16(9), 1038–1051 (2004)

    Article  Google Scholar 

  23. Leser, U.: A query language for biological networks. Bioinformatics 21(2), 33–39 (2005)

    Article  Google Scholar 

  24. Li, L., Alderson, D., Tanaka, R., Doyle, J.C., Willinger, W.: Towards a theory of scale-free graphs: Definition, properties, and implications (ext. version). Internet Mathematics 2(4), 431–523 (2006)

    Article  Google Scholar 

  25. Li, Q., Moon, B.: Indexing and querying XML data for regular path expressions. In: VLDB 2001, Roma, Italy, pp. 361–370 (2001)

    Google Scholar 

  26. Malewicz, G., et al.: Pregel: a system for large-scale graph processing. In: PODC 2009, New York, NY, USA, p. 6 (2009)

    Google Scholar 

  27. Martínez-Bazan, et al.: Dex: high-performance exploration on large graphs for information retrieval. In: CIKM 2007, New York, NY, USA, pp. 573–582 (2007)

    Google Scholar 

  28. Mendelzon, A.O., Wood, P.T.: Finding regular simple paths in graph databases. SIAM Journal on Computing 24(6), 1235–1258 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  29. Milo, T., Suciu, D.: Index Structures for Path Expressions. In: Beeri, C., Bruneman, P. (eds.) ICDT 1999. LNCS, vol. 1540, pp. 277–295. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  30. Neven, F.: Automata theory for xml researchers. SIGMOD Rec. 31(3), 39–46 (2002)

    Article  Google Scholar 

  31. Palaga, P., Nguyen, L., Leser, U., Hakenberg, J.: High-performance information extraction with alibaba. In: EDBT 2009, New York, USA, pp. 1140–1143 (2009)

    Google Scholar 

  32. Ronen, R., Shmueli, O.: SoQL: A language for querying and creating data in social networks. In: ICDE 2009, Shanghai, China, pp. 1595–1602 (2009)

    Google Scholar 

  33. San Martín, M., Gutierrez, C.: Representing, Querying and Transforming Social Networks with RDF/SPARQL. In: Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvönen, E., Mizoguchi, R., Oren, E., Sabou, M., Simperl, E. (eds.) ESWC 2009. LNCS, vol. 5554, pp. 293–307. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  34. Sevon, P., Eronen, L.: Subgraph queries by context-free grammars. Journal of Integrative Bioinformatics 5(2), 100 (2008)

    Google Scholar 

  35. Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: SIGMOD 2007, New York, NY, USA, pp. 845–856 (2007)

    Google Scholar 

  36. Yan, X., Yu, P.S., Han, J.: Graph indexing: a frequent structure-based approach. In: SIGMOD 2004, New York, NY, USA, pp. 335–346 (2004)

    Google Scholar 

  37. Yeger-Lotem, E., Sattath, S., Kashtan, N., et al.: Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction. Proc. Natl. Acad. Sci. USA 101(16), 5934–5939 (2004)

    Article  Google Scholar 

  38. Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. In: VLDB 2010. VLDB Endowment (2010)

    Google Scholar 

  39. Zauner, H., Linse, B., Furche, T., Bry, F.: A RPL through RDF: Expressive Navigation in RDF Graphs. In: Hitzler, P., Lukasiewicz, T. (eds.) RR 2010. LNCS, vol. 6333, pp. 251–257. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  40. Zou, L., Chen, L., Özsu, M.T.: Distance-join: Pattern match query in a large graph database. PVLDB 2(1), 886–897 (2009)

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science, Humboldt-Universität zu Berlin, Germany

    André Koschmieder & Ulf Leser

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  1. André Koschmieder
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  2. Ulf Leser
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Editors and Affiliations

  1. Computer Science, EPFL IC SIN-GE, Ecole Polytechnique Federale de Lausanne, Batiment BC, Station 14, 1015, Lausanne, Switzerland

    Anastasia Ailamaki

  2. Department of Computer Science, Gonzaga University, 502 E. Boone Avenue, 99258-0026, Spokane, WA, USA

    Shawn Bowers

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Koschmieder, A., Leser, U. (2012). Regular Path Queries on Large Graphs. In: Ailamaki, A., Bowers, S. (eds) Scientific and Statistical Database Management. SSDBM 2012. Lecture Notes in Computer Science, vol 7338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31235-9_12

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  • DOI: https://doi.org/10.1007/978-3-642-31235-9_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31234-2

  • Online ISBN: 978-3-642-31235-9

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