Importance

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Abstract

Techniques are provided for executing distinct aggregation operations in a manner that is more scalable and efficient than prior techniques. A three-stage technique is provided to parallelize aggregation operations that involve both grouping and multiple distinct-key columns. Such queries are handled by splitting rows into as many pieces as there are distinct aggregates in the query, and processing the row pieces. During the first-stage, a set of slave processes scans the rows of the base tables and performs partial duplicate elimination. During the second-stage, a set of slave processes completes the duplicate elimination and performs partial set function aggregation. During the third-stage, a third set of slave processes completes the set aggregation to produce the results of the distinct aggregation operation. In addition, two-stage parallelization techniques are provided for parallelizing single-distinct aggregations, and for parallelizing distinct aggregation operations that involve multiple distinct-key columns, but do not require grouping.

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First Claim