A Strategy for Partial Evaluation of Views

  • Parke Godfrey
  • Jarek Gryz
Part of the Advances in Soft Computing book series (AINSC, volume 4)


Database applications and environments such as mediation over heterogeneous database sources and data warehousing for decision support lead to complex queries. Queries are often nested, defined over views, and may involve unions. In certain cases, one might want to “remove” pieces (sub-queries or sub-views) from such queries. Some sub-views may be effectively cached, or may be materialized views. Some may be known to evaluate empty, through reasoning over the integrity constraints. Some may match protected queries, which for security cannot be evaluated.

We introduce an evaluation strategy called tuple-tagging for queries defined over views that efficiently “removes” marked sub-views. This differs from the approach of rewriting the query so that the sub-views to be removed are effectively gone, and then evaluating the rewritten query. With the tuple tagging evaluation, no rewrite of the original query is necessary.


Complex Query Query Evaluation Query Optimization Original Query Deductive Database 
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.
    Chakravarthy U., Grant J., and Minker J. (1990) Logic-based approach to semantic query optimization. ACM TODS, 15 (2): 162–207CrossRefGoogle Scholar
  2. 2.
    Chaudhuri S., Krishnamurthy R. et al. (1995) Optimizing queries with materialized views. In Proceedings of the 11th ICDE, 190–200Google Scholar
  3. 3.
    Cheng Q., Gryz J. et al. (1999) Implementation of two semantic query optimization techniques in DB2 universal database. In Proceedings of the 25th VLDB,Edinburgh, ScotlandGoogle Scholar
  4. 4.
    Cherniack M. and Zdonik S. (1996) Rule languages and internal algebras for rule_based optimizers. In Proc. SIGMOD, 401–412Google Scholar
  5. 5.
    Dar S., Franklin M. et al. (1996) Semantic data caching and replacement. In Proceedings of 22nd VLDB, 330–341Google Scholar
  6. 6.
    Das D. and Batory D. (1995) Prairie: A rule specification framework for query optimizers. In Proceedings of ICDE, 201–210Google Scholar
  7. 7.
    Freytag J. (1987) A rule-based view of query optimization. In SIGMOD Proceedings, 173–180Google Scholar
  8. 8.
    Godfrey P. and Gryz J. (1996) A framework for intensional query optimization. In Proceedings of DDLP’96, 57–68Google Scholar
  9. 9.
    Godfrey P. and Gryz J. (1999) Answering queries by semantic caches. In Proceedings of 10th DEXA, 485–498Google Scholar
  10. 10.
    Godfrey P. and Gryz J. (1999) View disassembly. In Proceedings of 7th ICDT, 417–434Google Scholar
  11. 11.
    Godfrey P., Gryz J., and Minker J. (1996) Semantic query optimization for bottom-up evaluation. In Ras Z. and Michalewicz M., editors, Proc. of the 9th. ISMIS, 561–571Google Scholar
  12. 12.
    Lakshmanan L.V.S. and Hernandez H.J. (1991) Structural query optimization: a uniform framework for semantic query optimization in deductive databases. In Proc. PODS, 102–114Google Scholar
  13. 13.
    Lakshmanan L.V.S. and Missaoui R. (1995) Pushing semantics inside recursion: A general framework for semantic optimization of recursive queries. In Proc. ICDE, 211–220Google Scholar
  14. 14.
    Larson P.-A. and Yang H. (1985) Computing queries from derived relations. In Proc. of 11th VLDB, 259–269Google Scholar
  15. 15.
    Lee S., Henschen L.J., and Qadah G. (1991) Semantic query reformulation in deductive databases. In Proc. IODE, 232–239Google Scholar
  16. 16.
    Levy A.Y., Mendelzon A.O. et al. (1995) Answering queries using views. In Proc. PODS, 95–104Google Scholar
  17. 17.
    Lloyd J. (1987) Foundations of Logic Programming. Springer-Verlag, second editionGoogle Scholar
  18. 18.
    Melton J. and Simon A.R. (1993) Understanding the New SQL: A Complete Guide. Morgan Kaufmann, San Mateo, CaliforniaGoogle Scholar
  19. 19.
    Pirahesh H., Hellerstein J.M., and Hasan W. (1992) Extensible/rule based query rewrite optimization in Starburst. In Proc. SIGMOD, 39–48Google Scholar
  20. 20.
    Qian X. (1996) Query folding. In Proceedings of the 12th IODE, 48–55Google Scholar
  21. 21.
    Sellis T. and Ghosh S. (1990) On the multiple-query optimization problem. TKDE, 2 (2): 262–266Google Scholar
  22. 22.
    Thuraisingham B. and Ford W. (1995) Security constraint processing in a multilevel secure distributed database management system. TKDE,7(2):274–293Google Scholar
  23. 23.
    Transaction Processing Performance Council. (1998) 777 No. First Street, Suite 600, San Jose, CA 95112–6311, TPC Benchmark TM D,1.3.1 editionGoogle Scholar
  24. 24.
    Ullman J.D. (1988) Principles of Database and Knowledge-Base Systems. Principles of Computer Science Series. Computer Science Press, Rockville, Maryland 20850Google Scholar
  25. 25.
    Yernani R., Papakonstantinou Y. et al. (1998) Fusion queries over internet databases. In Proceedings of the 6th EDBT, 57–71Google Scholar

Copyright information

© Physica-Verlag Heidelberg 2000

Authors and Affiliations

  • Parke Godfrey
    • 1
  • Jarek Gryz
    • 1
  1. 1.York UniversityTorontoCanada

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