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Efficient Computation of Iceberg Cubes by Bounding Aggregate Functions
2007
IEEE Transactions on Knowledge and Data Engineering
The iceberg cubing problem is to compute the multidimensional group-by partitions that satisfy given aggregation constraints. Pruning unproductive computation for iceberg cubing when nonantimonotone constraints are present is a great challenge because the aggregate functions do not increase or decrease monotonically along the subset relationship between partitions. In this paper, we propose a novel bound prune cubing (BP-Cubing) approach for iceberg cubing with nonantimonotone aggregation
doi:10.1109/tkde.2007.1053
fatcat:p6owgysnrjb3ngwuksq3vab4pu