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SIGMOD
2008
ACM

ARCube: supporting ranking aggregate queries in partially materialized data cubes

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ARCube: supporting ranking aggregate queries in partially materialized data cubes
Supporting ranking queries in database systems has been a popular research topic recently. However, there is a lack of study on supporting ranking queries in data warehouses where ranking is on multidimensional aggregates instead of on measures of base facts. To address this problem, we propose a query execution model to answer different types of ranking aggregate queries based on a unified, partial cube structure, ARCube. The query execution model follows a candidate generation and verification framework, where the most promising candidate cells are generated using a set of high-level guiding cells. We also identify a bounding principle for effective pruning: once a guiding cell is pruned, all of its children candidate cells can be pruned. We further address the problem of efficient online candidate aggregation and verification by developing a chunk-based execution model to verify a bulk of candidates within a bounded memory buffer. Our extensive performance study shows that the new ...
Tianyi Wu, Dong Xin, Jiawei Han
Added 08 Dec 2009
Updated 08 Dec 2009
Type Conference
Year 2008
Where SIGMOD
Authors Tianyi Wu, Dong Xin, Jiawei Han
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