Algebraic Optimization Of Grouped Preference Queries

SQL queries containing Group-by are common in data warehouse environments and OLAP. From this the concept of grouped Skyline queries emerged, wherein a Skyline of each group of tuples is requested. Grouped preference queries generalize this kind of Skyline queries. In tins paper we present new algebraic transformation rules for grouped preference queries which are one of the most intuitive and practical type of queries. Our optimization laws reduce intermediate result sizes in the computation of joins, Cartesian products, and the preference selection. We have integrated these new rules into our rule-based Preference SQL query optimizer. Our performance benchmarks, building upon the well-known TPC-H and IMDB datasets, show that significant performance gains can be achieved.