Title :
Prairie: A rule specification framework for query optimizers
Author :
Das, Dinesh ; Batory, Don
Author_Institution :
Dept. of Comput. Sci., Texas Univ., Austin, TX, USA
Abstract :
From our experience, current rule-based query optimizers do not provide a very intuitive and well-defined framework to define rules and actions. To remedy this situation, we propose an extensible and structured algebraic framework called Prairie for specifying rules. Prairie facilitates rule-writing by enabling a user to write rules and actions more quickly, correctly and in an easy-to-understand and easy-to-debug manner. Query optimizers consist of three major parts: a search space, a cost model and a search strategy. The approach we take is only to develop the algebra which defines the search space and the cost model and use the Volcano optimizer-generator as our search engine. Using Prairie as a front-end we translate Prairie rules to Volcano to validate our claim that Prairie makes it easier to write rules. We describe our algebra and present experimental results which show that using a high-level framework like Prairie to design large-scale optimizers does not sacrifice efficiency
Keywords :
deductive databases; knowledge based systems; optimisation; query processing; Prairie; Volcano optimizer-generator; cost model; high-level framework; large-scale optimizers; rule specification framework; rule-based query optimizers; search engine; search space; search strategy; structured algebraic framework; Algebra; Cost function; Database systems; Design optimization; Information retrieval; Large-scale systems; Query processing; Search engines; Volcanoes; Writing;
Conference_Titel :
Data Engineering, 1995. Proceedings of the Eleventh International Conference on
Conference_Location :
Taipei
Print_ISBN :
0-8186-6910-1
DOI :
10.1109/ICDE.1995.380391