New applications - such as automatic knowledge discovery - are making new demands on database systems. The constraints on collaborations between query optimizers and query-plan evaluators in conventional database systems severely limit the use of database systems for these new applications. The award supports research into unconventional kinds of collaborations between query optimizers and query-plan evaluators, including the migration of selected optimization decisions to run-time, the scheduling of multiple-implementation queries, and the migration of the use of prefetch hints from the query-plan evaluator to the query optimizer. The performance of the techniques is being extensively analyzed using an integrated rule-based optimizer and database system simulator. This research is expected to result in more efficient designs for a new generation of more flexible, high-performance database systems.
