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DOLAP
2003
ACM

Exploiting hierarchical clustering in evaluating multidimensional aggregation queries

10 years 5 months ago
Exploiting hierarchical clustering in evaluating multidimensional aggregation queries
Multidimensional aggregation queries constitute the single most important class of queries for data warehousing applications and decision support systems. The bottleneck in the evaluation of these queries is the join of the usually huge fact table with the restricted dimension tables (star-join). Recently, a multidimensional hierarchical clustering schema for star schemas is suggested. Subsequently, query evaluation plans for multidimensional queries appeared that essentially implement a star join as a multidimensional range restriction. We present a number of transformations for such plans. The transformations place grouping/aggregation operations before joins and safely prune aggregated tuples. They can be applied at no or minimal extra I/O cost. We show how these transformations can be used to construct a new evaluation plan for grouping/aggregation queries over multidimensional hierarchically clustered schemas. The new plan improves previous results by grouping and aggregating tup...
Dimitri Theodoratos
Added 05 Jul 2010
Updated 05 Jul 2010
Type Conference
Year 2003
Where DOLAP
Authors Dimitri Theodoratos
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