BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Histogram-based estimation techniques in database systems
Histogram-based estimation techniques in database systems
On Rectangular Partitionings in Two Dimensions: Algorithms, Complexity, and Applications
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Optimal Histograms with Quality Guarantees
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Selectivity Estimation Without the Attribute Value Independence Assumption
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Fast Approximate Answers to Aggregate Queries on a Data Cube
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
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Data warehouses must be able to process and analyze large amounts of information quickly and efficiently. Small summaries provide a very efficient way to obtain fast approximate answers to complex queries that run for too long. This paper proposes an efficient hierarchical partitioning strategy vmhist achieving a large improvement in the accuracy of the summary while maintaining all scalability. This is achieved by pre-computation, localized updating and additivity of the error measures used in the partitioning process. Evaluation reveals that a significant accuracy improvement is obtained for summaries produced with vmhist without significant increase in histogram construction time cost.