Query Optimization for a Graph Database with Visual Queries

  • Greg Butler
  • Guang Wang
  • Yue Wang
  • Liqian Zou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3882)


We have constructed a graph database system where a query can be expressed intuitively as a diagram. The query result is also visualized as a diagram based on the intrinsic relationship among the returned data. In this database system, CORAL plays the role of a query execution engine to evaluate queries and deduce results. In order to understand the effectiveness of CORAL optimization techniques on visual query processing.We present and analyze the performance and scalability of CORAL’s query rewriting strategies, which include Supplementary Magic Templates, Magic Templates, Context Factoring, Naïve Backtracking, and Without Rewriting method. Our research surprisingly shows that the Without Rewriting method takes the minimum total time to process the benchmark queries. Furthermore, CORAL’s default optimization method Supplementary Magic Templates is not uniformly the best choice for every query. The “optimization” of visual queries is beneficial if one could select the right optimization approach for each query.


Query Language Query Result Query Optimization Graph Database Coral Server 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Butler, G., Wang, G., Wang, Y., Zou, L.: A Graph Database with Visual Queries for Genomics. In: Procs. of the 3rd Asia-Pacific Bioinformatics Conf., pp. 31–40 (2005)Google Scholar
  2. 2.
    Consens, M.P., Eigler, F.C., Hasan, M.Z., Mendelzon, A.O., Noik, E.G., Ryman, A.G., Vista, D.: Architecture & Applications of the Hy+ Visualization System. IBM Systems Journal 33(3), 458–476 (1994)CrossRefGoogle Scholar
  3. 3.
    Ramakrishnan, R., Srivastava, D., Sudarshan, S., Seshadri, P.: The CORAL Deductive System. VLDB Journal 3(2), 161–210 (1994)CrossRefGoogle Scholar
  4. 4.
    Widenjus, M., Axmark, D.: MySQL Reference Manual. O’Reilly, Sebastopol (2002)Google Scholar
  5. 5.
    Chan, K.C., Trinder, P.W., Welland, R.: Evaluating Object-Oriented Query Languages. The Computer Journal 37(10), 858–872 (1994)CrossRefGoogle Scholar
  6. 6.
    Zou, L.: GraphLog: Its Representation in XML & Translation to CORAL. Masters Thesis. Dept. of Computer Science, Concordia University (2003)Google Scholar
  7. 7.
    Beeri, C., Ramakrishnan, R.: On the Power of Magic. In: Procs. of the ACM Symp. on Principles of Database Systems, pp. 269–283 (1987)Google Scholar
  8. 8.
    Ramakrishnam, R.: Magic Templates: A Spellbinding Approach to Logic Programs. In: Procs. of the Intl. Conf. on Logic Programming, pp. 140–159 (1988)Google Scholar
  9. 9.
    Naughton, J.F., Seshadri, S.: Argument Reduction Through Factoring. In: Procs. of the 15th Intl. Conf. on Very Large Databases, pp. 173–182 (1989)Google Scholar
  10. 10.
    Ramakrishnan, R., Srivastava, D., Sudarshan, S.: Rule ordering in bottom-up fixpoint evaluation of logic programs. In: Procs of the 16th Intl. Conf. on Very Large Databases, pp. 359–371 (1990)Google Scholar
  11. 11.
    Wang, G.: Linking CORAL to MySQL & PostgreSQL. Master Thesis. Dept. of Computer Science, Concordia University (2004)Google Scholar
  12. 12.
    Bancilhon, F., Ramakrishnan, R.: An amateur’s introduction to recursive query processing strategies. In: Procs. of ACM SIGMOD, pp. 16–52 (1986)Google Scholar
  13. 13.
    Bancilhon, F., Ramakrishnan, R.: Performance evaluation of data intensive logic programs. In: Minker, J. (ed.) Foundations of Deductive Databases & Logic Programming, pp. 439–517. Morgan Kaufmann, San Francisco (1988)CrossRefGoogle Scholar
  14. 14.
    Ceri, S., Gottlob, G., Tanca, L.: What You Always Wanted to Know About Datalog. IEEE Trans. on Knowledge & Data Eng. 1(1), 146–166 (1989)CrossRefGoogle Scholar
  15. 15.
    Giugno, R., Shasha, D.: A Fast & Universal Method for Querying Graphs. In: Proc. of the Intl. Conf. in Pattern Recognition, pp. 112–115 (2002)Google Scholar
  16. 16.
    Cruz, I.F., Leveille, P.S.: Implementation of a Constraint-Based Visualization System. In: Procs. of IEEE Intl. Symp. on Visual Languages, pp. 13–21 (2000)Google Scholar
  17. 17.
    Gyssens, M., Paredaens, J., Gutch, D.V.: A graph-oriented object model for database end-user interfaces. In: Procs. of ACM SIGMOD, pp. 24–33 (1990)Google Scholar
  18. 18.
    Paredaens, J., Peelman, P., Tanca, L.: G-Log: A Declarative Graphical Query Language. In: Procs. of 2nd Intl. Conf. on Deductive & Object–oriented Databases, pp. 108–128 (1991)Google Scholar
  19. 19.
    Poulovassilis, A., Hild, S.G.: Hyperlog: a graph-based system for database browsing, querying & update. Trans. on Knowledge & Data Eng. 13(2) (2001)Google Scholar
  20. 20.
    Olston, C.: VIQING: Visual Interactive QueryING. In: Procs. of 4th IEEE Symp. on Visual Languages, pp. 162–169 (1998)Google Scholar
  21. 21.
    Erwig, M.: XING: a visual XML query language. Journal of Visual Languages & Computing 14, 5–45 (2003)CrossRefGoogle Scholar
  22. 22.
    Ni, W., Ling, T.W.: GLASS: A Graphical Query Language for Semi-Structured Data. In: Procs. of 8th Intl. Conf. on Database Systems for Advanced Applications, pp. 362–369 (2003)Google Scholar
  23. 23.
    Vista, D., Wood, P.T.: Efficient Evaluation of Visual Queries Using Deductive Databases. In: Workshop on Programming with Logic Databases, pp. 143–161 (1993)Google Scholar
  24. 24.
    Seshadri, S., Naughton, J.F.: On the expected size of recursive Datalog queries. In: Procs. of ACM Symp. on Principles of Database Systems, pp. 268–279 (1991)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Greg Butler
    • 1
  • Guang Wang
    • 1
  • Yue Wang
    • 1
  • Liqian Zou
    • 1
  1. 1.Department of Computer Science and Software EngineeringConcordia UniversityMontréal, QuébecCanada

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