@inbook{afrati_chirkova_gupta_loftis_2005, title={Designing and using views to improve performance of aggregate queries (extended abstract)}, volume={3453}, ISBN={3540253343}, DOI={10.1007/11408079_48}, abstractNote={Data-intensive systems routinely use derived data (e.g., indexes or materialized views) to improve query-evaluation performance. We present a system architecture for Query-Performance Enhancement by Tuning (QPET), which combines design and use of derived data in an end-to-end approach to automated query-performance tuning. Our focus is on a tradeo. between (1) the amount of system resources spent on designing derived data and on keeping the data up to date, and (2) the degree of the resulting improvement in query performance. From the technical point of view, the novelty that we introduce is that we combine aggregate query rewriting techniques [1, 2] and view selection techniques [3] to achieve our goal.}, booktitle={Database systems for advanced applications: 10th international conference, DASFAA 2005, Beijing, China, April 17-20, 2005: Proceedings (Lecture notes in computer science ; 3454)}, publisher={Berlin; New York: Springer}, author={Afrati, F. and Chirkova, R. and Gupta, S. and Loftis, C.}, editor={L. Zhou, B.C. Ooi and Meng, X.Editors}, year={2005}, pages={548–554} }