Static vs Dynamic Techniques for Selectivity Evaluation in Distributed Query Optimization

Abstract

In distributed database query optimization, query optimizers have traditionally relied upon statically estimated table cardinalities when evaluating the cost of the query plans. This paper analyses static vs. dynamic calculation for selectivity of intermediate relations generated in query processing. The objective of this research is to overcome the disadvantages of previously formulated static methods which are relatively inaccurate in a distributed database environment. A Dynamic selectivity evaluation tool (DSET) has been proposed to optimize cost for a distributed database query processing environment. The results have shown that dynamic evaluation of selectivity factor of sub query operation is feasible and can significantly reduced the total query cost than its static estimation.