Distributed and Parallel Databases

, Volume 34, Issue 2, pp 119–143 | Cite as

Detecting common subexpressions for multiple query optimization over loosely-coupled heterogeneous data sources



The research presented in this paper supports the identification of common subexpressions as candidates for potential materialized views that form the basis of multiple query optimization in a loosely-coupled distributed system where query expressions access heterogeneous data sources, including relations and data-centric XML. This paper introduces a unifying mixed multigraph formalism to represent SQL, XQuery, and LINQ queries in a common query graph model and a heuristics-based algorithm to detect common subexpressions. The identified common subexpressions represent an opportunity for defining a materialized view to avoid repeating computation. The common subexpressions may access only relations, only XML, or a combination of relations and XML. The mixed multigraph model and the heuristic rules presented in this paper have distinguished advantages over the existing approaches that consider only relational or XML data sources individually. The mixed multigraph model can present SQL, XQuery, and LINQ queries in a single graph model and the heuristic rules are designed to consider the identical and subsumed conditions at the same time. A prototype implementation of the algorithm illustrates the applicability of the approach using various examples from the research literature as well as scenarios over a Criminal Justice enterprise that include common subexpressions across relational and XML data sources.


Distributed databases Common subexpressions LINQ SQL XQuery Event and stream processing Heuristic rules 



This material is based upon work supported by the National Science Foundation under Grant No. 0915325. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.


  1. 1.
    Antlr: Antlr v3 (2010). http://www.antlr.org/
  2. 2.
    Chakravarthy, U.S., Minker, J.: Multiple query processing in deductive databases using query graphs. In: VLDB ’86: Proceedings of the 12th International Conference on Very Large Data Bases, pp. 384–391. Morgan Kaufmann Publishers Inc., San Francisco (1986)Google Scholar
  3. 3.
    Chaudhari, M., Dietrich, S.: Metadata services for distributed event stream processing agents. In: 19th International Conference on Software Engineering and Data Engineering, pp. 307–312. San Francisco (2010)Google Scholar
  4. 4.
    Chaudhari, M.B.: Materialized views over heterogeneous structured data sources in a distributed event stream processing environment. Ph.D. thesis, Arizona State University, Tempe, AZ, USA (2011)Google Scholar
  5. 5.
    Chen, F.C.F., Dunham, M.H.: Common subexpression processing in multiple-query processing. IEEE Trans. Knowl. Data Eng. 10(3), 493–499 (1998)CrossRefGoogle Scholar
  6. 6.
    Diao, Y., Florescu, D., Kossmann, D., Carey, M.J., Franklin, M.J.: Implementing memoization in a streaming xquery processor. In: Bellahsene, Z., Milo, T., Rys, M., Suciu, D., Unland, R. (eds.) XSym. Lecture Notes in Computer Science, vol. 3186, pp. 35–50. Springer, Berlin (2004)Google Scholar
  7. 7.
    Elsayed, I., Brezany, P., Tjoa, A.M.: Towards realization of dataspaces. In: DEXA ’06: Proceedings of the 17th International Conference on Database and Expert Systems Applications, pp. 266–272. IEEE Computer Society, Washington, DC, USA (2006). doi: 10.1109/DEXA.2006.140
  8. 8.
    Franklin, M., Halevy, A., Maier, D.: From databases to dataspaces: a new abstraction for information management. SIGMOD Rec. 34(4), 27–33 (2005). doi: 10.1145/1107499.1107502
  9. 9.
    Gupta, A., Mumick, I.S. (eds.): Materialized Views: Techniques, Implementations, and Applications. MIT Press, Cambridge (1999)Google Scholar
  10. 10.
    Halevy, A., Franklin, M., Maier, D.: Principles of dataspace systems. In: PODS ’06: Proceedings of the Twenty-fifth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, pp. 1–9. ACM, New York, NY, USA (2006). doi: 10.1145/1142351.1142352
  11. 11.
    Halevy, A.Y.: Answering queries using views: a survey. VLDB J. 10, 270–294 (2001). doi: 10.1007/s007780100054
  12. 12.
    Jarke, M.: Common subexpression isolation in multiple query optimization. In: Query Processing in Database Systems, pp. 191–205. Springer (1985)Google Scholar
  13. 13.
    Kossmann, D.: The state of the art in distributed query processing. ACM Comput. Surv. 32, 422–469 (2000). doi: 10.1145/371578.371598
  14. 14.
    Lenzerini, M.: Data integration: a theoretical perspective. In: Proceedings of the Twenty-First ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS ’02, pp. 233–246. ACM, New York, NY, USA (2002). doi: 10.1145/543613.543644
  15. 15.
    Löwy, J.: Programming WCF Services. O’Reilly Media, Inc. (2007)Google Scholar
  16. 16.
    Microsoft Corporation: Linq:net language-integrated query (2009). http://msdn.microsoft.com/en-us/library/bb308959.aspx
  17. 17.
    Park, J., Segev, A.: Using common subexpressions to optimize multiple queries. In: Proceedings of the Fourth International Conference on Data Engineering, pp. 311–319. IEEE Computer Society, Washington, DC, USA (1988)Google Scholar
  18. 18.
    QuickGraph: Quickgraph. http://quickgraph.codeplex.com/ (2011)
  19. 19.
    Roy, P., Seshadri, S., Sudarshan, S., Bhobe, S.: Efficient and extensible algorithms for multi query optimization. SIGMOD Rec. 29, 249–260 (2000). doi: 10.1145/335191.335419
  20. 20.
    Sellis, T.K.: Multiple-query optimization. ACM Trans. Database Syst. 13(1), 23–52 (1988). doi: 10.1145/42201.42203
  21. 21.
  22. 22.
    Urban, S., Dietrich, S., Chen, Y.: An xml framework for integrating continuous queries, composite event detection, and database condition monitoring for multiple data streams. In: Chandy, M., Etzion, O., von Ammon, R. (eds.) Event Processing, no. 07191 in Dagstuhl Seminar Proceedings. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany, Dagstuhl, Germany (2007). http://drops.dagstuhl.de/opus/volltexte/2007/1142
  23. 23.
    Vizing, V.: On incidentor coloring in a partially directed multigraph. J. Appl. Ind. Math. 3, 297–300 (2009). doi: 10.1134/S1990478909020161
  24. 24.
    Xamarin: Mono (2013). http://www.mono-project.com
  25. 25.
    Zhou, J., Larson, P.A., Freytag, J.C., Lehner, W.: Efficient exploitation of similar subexpressions for query processing. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, SIGMOD ’07, pp. 533–544. ACM, New York, NY, USA (2007). doi: 10.1145/1247480.1247540

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© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.School of Mathematical and Natural SciencesArizona State UniversityPhoenixUSA

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