Adaptive and Automated Index Selection in RDBMS

We present a novel approach for a tool that assists the database administrator in designing an index connguration for a relational database system. A new methodology for collecting usage statistics at run time is developed which lets the optimizer estimate query execution costs for alternative index conngurations. Deening the workload specii-cation required by existing index design tools may be very complex for a large integrated database system. Our tool automatically derives the workload statistics. These statistics are then used to eeciently compute an index connguration. Execution of a prototype of the tool against a sample database demonstrates that the proposed index connguration is reasonably close to the optimum for test query sets.