Parameterizing a Genetic Optimizer
Genetic programming has been proposed as a possible although still intriguing approach for query optimization. There exist two main aspects which are still unclear and need further investigation, namely, the quality of the results and the speed to converge to an optimum solution. In this paper we tackle the first aspect and present and validate a statistical model that, for the first time in the literature, lets us state that the average cost of the best query execution plan (QEP) obtained by a genetic optimizer is predictable. Also, it allows us to analyze the parameters that are most important in order to obtain the best possible costed QEP. As a consequence of this analysis, we demonstrate that it is possible to extract general rules in order to parameterize a genetic optimizer independently from the random effects of the initial population.
KeywordsInitial Population Average Cost Mutation Operation Crossover Operation Database Schema
Unable to display preview. Download preview PDF.
- 1.Bennett, K., Ferris, M.C., Ioannidis, Y.E.: A genetic algorithm for database query optimization. In: Belew, R., Booker, L. (eds.) Proceedings of the Fourth International Conference on Genetic Algorithms, pp. 400–407. Morgan Kaufmann, San Mateo (1991)Google Scholar
- 4.Krishnamurthy, R., Boral, H., Zaniolo, C.: Optimization of nonrecursive queries. In: VLDB, pp. 128–137 (1986)Google Scholar
- 6.Muntes, V., Aguilar, J., Zuzarte, C., Larriba, J.L.: An io-based cost model for the carquinyoli genetic optimizer. Technical Report UPC-DAC-RR-2005-69, Dept. d’Arqu. de Comp. UPC (2005), http://www.dama.upc.edu
- 11.Stillger, M., Spiliopoulou, M.: Genetic programming in database query optimization. In: Koza, J.R., Goldberg, D.E., Fogel, D.B., Riolo, R.L. (eds.) Genetic Programming 1996: Proceedings of the First Annual Conference, Stanford University, CA, USA, July 28-31, 1996, pp. 388–393. MIT Press, Cambridge (1996)Google Scholar
- 13.Tao, Y., Zhu, Q., Zuzarte, C., Lau, W.: Optimizing large star-schema queries with snowflakes via heuristic-based query rewriting. In: CASCON 2003: Proceedings of the 2003 conference of the Centre for Advanced Studies on Collaborative research, pp. 279–293. IBM Press (2003)Google Scholar