Rule-based query optimization, revisited
Proceedings of the eighth international conference on Information and knowledge management
Design Wizards and Visual Programming Environments for GenVoca Generators
IEEE Transactions on Software Engineering
Journal of Intelligent Information Systems
Design Wizards and Visual Programming Environments for Generators
ICSR '98 Proceedings of the 5th International Conference on Software Reuse
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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.