Query Classification in Multidatabase Systems
Information Science Department,
School of Computer Science and Engineering,
The University of New South Wales,
Sydney 2052, Australia.
Query optimisation is a significant 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 classification.
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