Analytical and Empirical Tools for Advanced Query Optimizer Engineering

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Database query optimizers are complex systems prone to bugs. The intention is to counter this phenomenon by developing a design process that separates the areas that can be formalized and reasoned about from those that require crafting and experimentation. Formal techniques are applied to the specification of optimizer modules (or rule blocks), which can be constructed by expressing provable rules and rule firing strategies. Rules are expressed declaratively (i.e., without code) to permit theorem prover verification. Rule blocks group related rules and propose an order for firing them and a strategy for deciding when firing is appropriate. Associated tools automate rule verification, and permit the effects of rules and rule blocks on queries to be visualized. Assembly of proven modules into a workable whole requires experimentation and evaluation. Tools to assist in this process permit visualization of the assembled optimizer's flow of control on given query sets, and measurement of the performance improvements as a result of transformations of queries. The aim of the project is to develop a methodology and associated suite of tools for the development of effective, correct and extensible query optimizers. This work contributes to the specification, design, verification and empirical evaluation of query optimizers.