Selecting and Using Views to Compute Aggregate Queries

(Extended Abstract)
  • Foto Afrati
  • Rada Chirkova
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3363)

Abstract

We consider a workload of aggregate queries and investigate the problem of selecting views that (1) provide equivalent rewritings for all queries, and (2) are optimal, in that the cost of evaluating the query workload is minimized. We consider conjunctive views and rewritings, with or without aggregation; in each rewriting, only one view contributes to computing the aggregated query output. We look at query rewriting using existing views and at view selection. In the query-rewriting problem, we give su.cient and necessary conditions for a rewriting to exist. For view selection, we prove complexity results. Finally, we give algorithms for obtaining rewritings and selecting views.

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References

  1. 1.
    Harinarayan, V., Rajaraman, A., Ullman, J.: Implementing data cubes efficiently. In: Proceedings of SIGMOD, pp. 205–216 (1996)Google Scholar
  2. 2.
    Gupta, H., Harinarayan, V., Rajaraman, A., Ullman, J.: Index selection for OLAP. In: Proceedings of ICDE, pp. 208–219 (1997)Google Scholar
  3. 3.
    Agrawal, S., Chaudhuri, S., Narasayya, V.: Automated selection of materialized views and indexes in SQL databases. In: Proceedings of VLDB, pp. 496–505 (2000)Google Scholar
  4. 4.
    Ullman, J.D.: Efficient implementation of data cubes via materialized views. In: Proceedings of KDD, pp. 386–388 (1996)Google Scholar
  5. 5.
    Chirkova, R., Halevy, A., Suciu, D.: A formal perspective on the view selection problem. VLDB Journal 11, 216–237 (2002)MATHCrossRefGoogle Scholar
  6. 6.
    Gupta, A., Harinarayan, V., Quass, D.: Aggregate-query processing in data warehousing environments. In: Proceedings of VLDB, pp. 358–369 (1995)Google Scholar
  7. 7.
    Gray, J., Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M.: Data cube: A relational aggregation operator generalizing Group-by, Cross-Tab, and Sub Totals. Data Mining and Knowledge Discovery 1, 29–53 (1997)CrossRefGoogle Scholar
  8. 8.
    Cohen, S., Nutt, W., Serebrenik, A.: Rewriting aggregate queries using views. In: Proceedings of PODS, pp. 155–166 (1999)Google Scholar
  9. 9.
    Cohen, S., Nutt, W., Serebrenik, A.: Algorithms for rewriting aggregate queries using views. In: Proceedings of ADBIS-DASFAA, pp. 65–78 (2000)Google Scholar
  10. 10.
    Widom, J.: Research problems in data warehousing. In: Proceedings of CIKM (1995)Google Scholar
  11. 11.
    Srivastava, D., Dar, S., Jagadish, H., Levy, A.: Answering queries with aggregation using views. In: Proceedings of VLDB, pp. 318–329 (1996)Google Scholar
  12. 12.
    Grumbach, S., Tininini, L.: On the content of materialized aggregate views. Journal of Computer and System Sciences 66, 133–168 (2003)MATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Agarwal, S., Agrawal, R., Deshpande, P., Gupta, A., Naughton, J., Ramakrishnan, R., Sarawagi, S.: On the computation of multidimensional aggregates. In: Proceedings of VLDB, pp. 506–521 (1996)Google Scholar
  14. 14.
    Yang, J., Widom, J.: Incremental computation and maintenance of temporal aggregates. In: Proceedings of ICDE, pp. 51–62 (2001)Google Scholar
  15. 15.
    Benedikt, M., Libkin, L.: Aggregate operators in constraint query languages. Journal of Computer and System Sciences 64, 628–654 (2002)MATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    Ross, K., Srivastava, D., Stuckey, P., Sudarshan, S.: Foundations of aggregation constraints. Theoretical Computer Science 193, 149–179 (1998)MATHCrossRefMathSciNetGoogle Scholar
  17. 17.
    Özsoyoglu, G., Özsoyoglu, Z., Matos, V.: Extending relational algebra and relational calculus with set-valued attributes and aggregate functions. ACM Transactions on Database Systems (TODS) 12, 566–592 (1987)CrossRefGoogle Scholar
  18. 18.
    Lechtenbörger, J., Shu, H., Vossen, G.: Aggregate queries over conditional tables. Journal of Intelligent Information Systems 19, 343–362 (2002)CrossRefGoogle Scholar
  19. 19.
    Nutt, W., Sagiv, Y., Shurin, S.: Deciding equivalences among aggregate queries. In: Proceedings of PODS, pp. 214–223 (1998)Google Scholar
  20. 20.
    Chaudhuri, S., Vardi, M.: Optimization of real conjunctive queries. In: Proceedings of PODS, pp. 59–70 (1993)Google Scholar
  21. 21.
    Ullman, J.D.: Information integration using logical views. In: Afrati, F.N., Kolaitis, P.G. (eds.) ICDT 1997. LNCS, vol. 1186. Springer, Heidelberg (1996)Google Scholar
  22. 22.
    Afrati, F., Chirkova, R.: Selecting and using views to compute aggregate queries (2004), http://www4.ncsu.edu/~rychirko/Papers/aggregAquv.pdf
  23. 23.
    Afrati, F., Li, C., Ullman, J.: Generating efficient plans for queries using views. In: Proceedings of SIGMOD (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Foto Afrati
    • 1
  • Rada Chirkova
    • 2
  1. 1.Electrical and Computing Eng.National Technical University of AthensAthensGreece
  2. 2.Computer Science DepartmentNorth Carolina State UniversityRaleighUSA

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