Query Classification in Multidatabase Systems

Query optimisation is a signiicant unsolved problem in the development of multidatabase systems. The main reason for this is that the query cost functions for the component database systems may not be known to the global query optimiser. In this paper, we describe a method, based on a classical clustering algorithm, for classifying queries which allows us to derive accurate approximations of these query cost functions. The experimental results show that the cost functions derived by the clustering algorithm yield a lower average error as compared to the error produced by a manual classiication.