Pushing Aggregate Constraints by Divide-and-Approximate

Jeffrey Xu Yu

Chinese University of Hong Kong

Iceberg-cube mining is to compute the GROUP BY partitions, for all GROUP BY dimension lists, that satisfy a given aggregate constraint. Previous works have pushed anti-monotone constraints into iceberg-cube mining. However, many useful constraints are not anti-monotone. In this paper, we propose a novel strategy for pushing general aggregate constraints, called Divide-and-Approximate. This strategy divides the search space and approximates the constraint in subspaces by a pushable constraint. As the strategy is recursively applied, the approximation approaches the given constraint and the pruning tights up. We show that all constraints defined by SQL aggregates, arithmetic operators and comparison operators can be pushed by Divide-and-Approximate. We present an efficient implementation for an important subclass and evaluate it on both synthetic and real life databases.

About the speaker

Jeffrey Xu Yu received his B.E., M.E. and Ph.D. in computer science, from the University of Tsukuba, Japan, in 1985, 1987 and 1990, respectively. Jeffrey Xu Yu was a research fellow (Apr. 1990 --Mar. 1991) and was a faculty member Apr. 1991 -- July 1992) in the Institute of Information Sciences and Electronics, University of Tsukuba. From July 1992 to June 2000, he was a Lecturer in the Department of Computer Science, The Australian National University. Currently, he is an Associate Professor in the Department of Systems Engineering and Engineering Management, the Chinese University of Hong Kong. Jeffrey Xu Yu is a member of ACM, and a society affiliate of IEEE Computer Society.