A Decision Theoretic Cost Model for Dynamic Plans

Since the classic optimization work in System R, query optimization has completely preceded query evaluation. Unfortunately, errors in cost model parameters such as selectivity estimation compromise the optimality of query evaluation plans optimized at compile time. The only promising remedy is to interleave strategy selection and data access using run-time-dynamic plans. Based on the principles of decision theory, our cost model enables careful query analysis and prepares alternative query evaluation plans at compile time, delaying relatively few, selected decisions until run time. In our prototype optimizer, these run-time decisions are based only on those materialized intermediate results for which materialization costs are expected to be less than the benefits from the improved decision quality.