Aggregate-Query Processing in Data Warehousing Environments

In this paper we introduce generalized projections (GP s), an extension of duplicateeliminating projections, that capture aggregations, groupbys, duplicate-eliminating projections (distinct), and duplicate-preserving projections in a common uni ed framework. Using GP s we extend well known and simple algorithms for SQL queries that use distinct projections to derive algorithms for queries using aggregations like sum,max,min, count, and avg. We develop powerful query rewrite rules for aggregate queries that unify and extend rewrite rules previously known in the literature. We then illustrate the power of our approach by solving a very practical and important problem in data warehousing: how to answer an aggregate query on base tables using materialized aggregate views (summary tables).