Providing Better Support for Quanti

Relational database systems do not eeectively support complex queries containing quantiiers (quantiied queries) that are increasingly becoming important in decision support applications. Generalized quantiiers provide an eeective way of expressing such queries naturally. In this paper, we consider the problem of processing quantiied queries within the generalized quantiier framework. We demonstrate that current relational systems are ill-equipped, both at the language and at the query processing level, to deal with such queries. We also provide insights into the intrinsic diicul-ties associated with processing such queries. We then describe the implementation of a quantiied query processor, Q 2 P, that is based on multidimensional and boolean matrix structures. We provide results of performance experiments run on Q 2 P that demonstrate superior performance on quantiied queries. Our results indicate that it is feasible to augment relational systems with query subsystems like Q 2 P for signiicant performance beneets for quantiied queries in decision support applications.