QUIET: Continuous Query-driven Index Tuning Kai-Uwe Sattler, Ingolf Geist, and Eike Schallehn   View Paper (PDF)   Return to Advanced Models and Languages/Architectures for Data Analysis (Session D3) Abstract Index tuning as part of database tuning is the task of selecting and creating indexes with the goal of reducing query processing times. However, in dy- namic environments with various ad-hoc queries it is difficult to identify potential useful indexes in advance. In this demonstration, we present our tool QUIET addressing this problem. This tool "intercepts" queries and - based on a cost model as well as runtime statistics about profits of index configurations - decides about index creation au- tomatically at runtime. In this way, index tuning is driven by queries without explicit actions of the database users. ©2004 Association for Computing Machinery