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Divide-And-Approximate: A Novel Constraint Push Strategy For Iceberg Cube Mining, Ke Wang, Yuelong Jiang, Jeffrey Xu Yu, Guozhu Dong, Jiawei Han
Divide-And-Approximate: A Novel Constraint Push Strategy For Iceberg Cube Mining, Ke Wang, Yuelong Jiang, Jeffrey Xu Yu, Guozhu Dong, Jiawei Han
Kno.e.sis Publications
The iceberg cube mining computes all cells v, corresponding to GROUP BY partitions, that satisfy a given constraint on aggregated behaviors of the tuples in a GROUP BY partition. The number of cells often is so large that the result cannot be realistically searched without pushing the constraint into the search. Previous works have pushed antimonotone and monotone constraints. However, many useful constraints are neither antimonotone nor monotone. We consider a general class of aggregate constraints of the form f(v)θσ, where f is an arithmetic function of SQL-like aggregates and θ is one of <, ≤, ≥, > . We propose a …,>