Abstract
Block optimization involves several techniques used to avoid optimizing blocks or parts of a query separately. This process may involve integrating views, derived tables, and subqueries with the rest of the query. For those query blocks that cannot be integrated with the rest of the query, the Teradata optimizer tries to simplify and optimize these blocks. Such optimizations can be achieved using the satisfiability test (checking if a set of conditions are satisfiable) and generating transitive closure, which allows pushing constraints into and out of query blocks. Several new Block Optimization techniques, added to the new release of Teradata DBMS (V2R5), are described.
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References
Blakeley, J.A., Cobum, N., Larson, P.A.: Updating derived relations: Detecting/Irrelevant and autonomously computable updates. In: VLDB, vol. 12, Kyoto, pp. 457–466 (1986)
Chakravarthy, U., Grant, J., Minker, J.: Logic-based approach to semantic query optimization. ACM TOD 15(2), 162–207 (1990)
Cheng, Q., Gryz, J., Koo, F.: Implementation of Two Semantic Query Optimization Techniques in DB2 Universal Database. In: VLDB, vol. 25, Edinburgh (1999)
Chaudhuri, S., Shim, K.: Including Group By in Query Optimization. In: VLDB, vol. 20, Santiago Chile (1994)
Ghazal, A., Ouksel, A.: Termination of Programs in Constraint Query Languages. In: 1994 Symposium on Applied Computing, Special Track on Computational Logic, Phoenix, Arizona (March 1994)
Ghazal, A., Ouksel, A.: Subsumption in Constraint Query Languages Involving Disjunctions of Range Constraints, Fort Lauderdale, Florida (January 1994)
King, J.J.: Query Optimization by semantic reasoning Dept of Computer Science Stanford University (1981)
Larson, P.A., Yang, H.Z.: Computing queries from derived relations. In: VLDB, vol. 11, pp. 259–269 (1985)
Levy, A.Y., Mumick, I., Sagiv, Y.: Query optimization by predicate move-around. In: Proc. of VLDB, pp. 96–108 (1994)
Mumick, I., Pirahesh, H.: Implementation of magic sets in Starburst. In: Proc. SIGMOD (1994)
Paulley, G., Larson, P.: Exploiting uniqueness in query optimization. In: Proceeding of ICDE, pp. 68–79 (1994)
Pirahesh, H., Hellerstein, J.M., Hasan, W.: Extensible/rule based query rewrite optimization in Starburst. In: Proc. SIGMOD, pp. 39–48 (1992)
Rosenkrantz, D., Hunt, H.I.: Processing conjunctive predicates and queries. In: VLDB, vol. 80, pp. 64–72.
Shenoy, S.T., Ozsoyoglu, Z.M.: Design and implementation of a semantic query optimizer. IEEE Transactions on Knowledge and Data Engineering 1(3), 344–361 (1989)
Sun, X.H., Kamel, N., Ni, L.: Processing implications on queries. IEEE Transactions on Software Engineering 15(10), 1168–1175 (1990)
Transaction Processing Performance Council, 777 No. First Street, Suite 600, San Jose, CA 95112 6311. TPC Benchmark H, 1.5.0 edition, July 12 (2002), http://www.tpc.org
Yan, W.P., Larson, P.-A.: Performing Group By Before Join. In: Proceedings of the 10th IEEE International Conference on Data Engineering, Houston, TX, pp. 89–100 (1994)
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Ghazal, A., Bhashyam, R., Crolotte, A. (2003). Block Optimization in the Teradata RDBMS. In: MaÅ™Ãk, V., Retschitzegger, W., Å tÄ›pánková, O. (eds) Database and Expert Systems Applications. DEXA 2003. Lecture Notes in Computer Science, vol 2736. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45227-0_76
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DOI: https://doi.org/10.1007/978-3-540-45227-0_76
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