Least expected cost query optimization: an exercise in utility

We identify two unreasonable, though standard, assumptions made by database query optimizers that can adversely affect the quality of the chosen evaluation plans. One assumption is that it is enough to optimize for the expected case---that is, the case where various parameters (like available memory) take on their expected value. The other assumption is that the parameters are constant throughout the execution of the query. We present an algorithm based on the ``System R''-style query optimization algorithm that does not rely on these assumptions. The algorithm we present chooses the plan of the least expected cost instead of the plan of least cost given some fixed value of the parameters. In execution environments that exhibit a high degree of variability, our techniques should result in better performance.