A Semantic Query Optimization Approach to Optimize Linear Datalog Programs

After two decades of research in Deductive Databases, SQL99 brings deductive databases again to the foreground given that SQL99 in- cludes queries with linear recursion. However, the execution of recursive queries may result in slow response time, thus the research in query op- timization is very important to provide the suitable algorithms that will be included in the query optimizers of the database management systems in order to speed up the execution of recursive queries. We use a seman- tic query optimization approach in order to improve the efficiency of the evaluation of datalog programs. Our main contribution is an algorithm that builds a program P’ equivalent to a given program P, when both are applied over a database d satisfying a set of functional dependencies. The input program P is a linear recursive datalog program. The new program P’ has less number of different variables and, sometimes, less number of atoms in the recursive rules, thus it is cheaper to evaluate.