Advertisement

Evaluating Mixed Patterns on Large Data Graphs Using Bitmap Views

  • Xiaoying WuEmail author
  • Dimitri Theodoratos
  • Dimitrios Skoutas
  • Michael Lan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11446)

Abstract

Developing efficient and scalable techniques for pattern queries over large graphs is crucial for modern applications such as social networks, Web analysis, and bioinformatics. In this paper, we address the problem of efficiently finding the homomorphic matches for tree pattern queries with child and descendant edges (mixed pattern queries) over a large data graph. We propose a novel type of materialized views to accelerate the evaluation. Our materialized views are the sets of occurrence lists of the nodes of the pattern in the data graph. They are stored as compressed bitmaps on the inverted lists of the node labels in the data graph. Reachability information between occurrence list nodes is provided by a node reachability index. This technique not only minimizes the materialization space but also reduces CPU and I/O costs by translating view materialization processing into bitwise operations. We provide conditions for view usability using the concept of pattern node coverage. We design a holistic bottom-up algorithm which efficiently computes pattern query matches in the data graph using bitmap views. An extensive experimental evaluation shows that our method evaluates mixed patterns up to several orders of magnitude faster than existing algorithms.

References

  1. 1.
    Chambi, S., Lemire, D., Kaser, O., Godin, R.: Better bitmap performance with roaring bitmaps. Softw. Pract. Exper. 46(5), 709–719 (2016)CrossRefGoogle Scholar
  2. 2.
    Chen, L., Gupta, A., Kurul, M.E.: Stack-based algorithms for pattern matching on DAGs. In: VLDB (2005)Google Scholar
  3. 3.
    Cheng, J., Yu, J.X., Yu, P.S.: Graph pattern matching: a join/semijoin approach. IEEE Trans. Knowl. Data Eng. 23(7), 1006–1021 (2011)CrossRefGoogle Scholar
  4. 4.
    Fan, W., Li, J., Ma, S., Wang, H., Wu, Y.: Graph homomorphism revisited for graph matching. PVLDB 3(1), 1161–1172 (2010)Google Scholar
  5. 5.
    Fan, W., Wang, X., Wu, Y.: Answering pattern queries using views. IEEE Trans. Knowl. Data Eng. 28(2), 326–341 (2016)CrossRefGoogle Scholar
  6. 6.
    Gallagher, B.: Matching structure and semantics: a survey on graph-based pattern matching. AAAI FS 6, 45–53 (2006)Google Scholar
  7. 7.
    Li, J., Cao, Y., Liu, X.: Approximating graph pattern queries using views. In: CIKM, pp. 449–458 (2016)Google Scholar
  8. 8.
    Liang, R., Zhuge, H., Jiang, X., Zeng, Q., He, X.: Scaling hop-based reachability indexing for fast graph pattern query processing. IEEE Trans. Knowl. Data Eng. 26(11), 2803–2817 (2014)CrossRefGoogle Scholar
  9. 9.
    Olteanu, D., Schleich, M.: Factorized databases. SIGMOD Rec. 45(2), 5–16 (2016)CrossRefGoogle Scholar
  10. 10.
    Shang, H., Zhang, Y., Lin, X., Yu, J.X.: Taming verification hardness: an efficient algorithm for testing subgraph isomorphism. PVLDB 1(1), 364–375 (2008)Google Scholar
  11. 11.
    Su, J., Zhu, Q., Wei, H., Yu, J.X.: Reachability querying: can it be even faster? IEEE Trans. Knowl. Data Eng. 29(3), 683–697 (2017)CrossRefGoogle Scholar
  12. 12.
    Ullmann, J.R.: An algorithm for subgraph isomorphism. J. ACM 23(1), 31–42 (1976)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Wang, H., Li, J., Luo, J., Gao, H.: Hash-base subgraph query processing method for graph-structured XML documents. PVLDB 1, 478–489 (2008)Google Scholar
  14. 14.
    Wang, J., Lin, C., Papakonstantinou, Y., Swanson, S.: An experimental study of bitmap compression vs. inverted list compression. In: SIGMOD, pp. 993–1008 (2017)Google Scholar
  15. 15.
    Wang, J., Ntarmos, N., Triantafillou, P.: Indexing query graphs to speedup graph query processing. In: EDBT, pp. 41–52 (2016)Google Scholar
  16. 16.
    Wang, X.: Answering graph pattern matching using views: a revisit. In: Benslimane, D., Damiani, E., Grosky, W.I., Hameurlain, A., Sheth, A., Wagner, R.R. (eds.) DEXA 2017. LNCS, vol. 10438, pp. 65–80. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-64468-4_5CrossRefGoogle Scholar
  17. 17.
    Wu, X., Souldatos, S., Theodoratos, D., Dalamagas, T., Sellis, T.K.: Efficient evaluation of generalized path pattern queries on XML data. In: WWW (2008)Google Scholar
  18. 18.
    Wu, X., Theodoratos, D., Wang, W.H.: Answering XML queries using materialized views revisited. In: CIKM (2009)Google Scholar
  19. 19.
    Wu, X., Theodoratos, D., Wang, W.H., Sellis, T.: Optimizing XML queries: bitmapped materialized views vs. indexes. Inf. Syst. 38(6), 863–884 (2013)CrossRefGoogle Scholar
  20. 20.
    Zeng, Q., Jiang, X., Zhuge, H.: Adding logical operators to tree pattern queries on graph-structured data. PVLDB 5(8), 728–739 (2012)Google Scholar
  21. 21.
    Zeng, Q., Zhuge, H.: Comments on “stack-based algorithms for pattern matching on dags”. PVLDB 5(7), 668–679 (2012)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Xiaoying Wu
    • 1
    Email author
  • Dimitri Theodoratos
    • 2
  • Dimitrios Skoutas
    • 3
  • Michael Lan
    • 2
  1. 1.School of ComputerWuhan UniversityWuhanChina
  2. 2.New Jersey Institute of TechnologyNewarkUSA
  3. 3.IMSI, R.C. AthenaAthensGreece

Personalised recommendations