Abstract: Methods are provided for efficiently evaluating database queries including a rollup operator and a distinct aggregate function. Using a sequence of sorts, duplicate record elimination performed on previous sorts at lower, or finer, levels of the rollup operator is taken advantage of by performing subsequent sorts on the preceding sort. Hence, when moving from one rollup level to the next higher level, there are fewer data records to sort with respect to the relevant grouping columns for that level, and thus also fewer duplicate data records to eliminate for purposes of computing the distinct aggregate. Using parallel evaluation, processing of aggregate functions is split among different processing slaves, and the measure of an aggregate function is included as a partitioning key when sending data from one data flow operation to the next data flow operation of a query execution plan.

Abstract: Methods are provided for efficiently evaluating database queries that include a grouping sets specification, by reducing the grouping sets specification to one or more combinations of groupings that are computable with simple GROUP BY clauses, with or without a rollup operator, wherein the GROUP BY clauses and rollup operators are efficient operations that can be computed with a single data sort. Computational costs are further minimized by computing a grouping from records generated from computation of a previously computed grouping. An optimization algorithm is described which determines the respective grouping combinations to which the grouping sets specification is reduced and the respective GROUP BY clauses, to minimize computational costs. Furthermore, an intermediate grouping, that is, a grouping that is not specified by the query, is included in a query evaluation plan in some instances, to compute specified groupings when doing so reduces computational costs.