Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Range queries in OLAP data cubes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Multidimensional divide-and-conquer
Communications of the ACM
Modeling Multidimensional Databases
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Hierarchical Prefix Cubes for Range-Sum Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Hierarchical Compact Cube for Range-Max Queries
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Range Top/Bottom k Queries in OLAP Sparse Data Cubes
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
Adaptive Method for Range Top- k Queries in OLAP Data Cubes
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Variable Sized Partitions for Range Query Algorithms
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
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A range query applies an aggregation operation over all selected cells of an OLAP data cube where the selection is specified by ranges of continuous values for numeric dimensions. Much work has been done with one type of aggregations: SUM. But little work has been done with another type of aggregations: MAX/MIN besides the tree-based algorithm. In this paper, we propose a new method which partitions the given data cube, stores precomputed max/min over partitions and location of the max/min of the partitions. We also use some techniques to reduce the chance of accessing the original data cube when answering ad hoc queries at run time. The experiment results demonstrate that out method outperforms the tree-based algorithm.