Static optimization of logical queries is, in substance, to move selections down as far as possible in evaluating logical queries. This paper extends Ullman's RGG (Rule/Goal Graph) and introduces P- graph, with wh...Static optimization of logical queries is, in substance, to move selections down as far as possible in evaluating logical queries. This paper extends Ullman's RGG (Rule/Goal Graph) and introduces P- graph, with which a wide range of recursive logical queries can be statically optimized top-down and evaluated bottom-up, some of which are usually optimized by dynamic approaches. The paper also shows that for some logical queries the complexity of pushing selections down and computing bottom-up is related to the complexity of base relation in the queries.展开更多
In this paper, an optimal method to handle cyclic and acyclic data relations in the linear recursive queries is proposed. High efficiency is achieved by integrating graph traversal mechanisms into a top-down evaluatio...In this paper, an optimal method to handle cyclic and acyclic data relations in the linear recursive queries is proposed. High efficiency is achieved by integrating graph traversal mechanisms into a top-down evaluation. In such a way the subsumption checks and the identification of cyclic data can be done very efficielltly First, based on the subsumption checks, the search space can be reduced drastically by avoiding any redundant expansion operation. In fact, in the case of non-cyclic data, the proposed algorithm requires only linear time for evaluating a linear recursive query. On the other hand, in the case of cyclic data, by using the technique for isolating strongly connected components a lot of answers can be generated directly in terms of the intermediate results and the relevant path information instead of evaluating them by performing algebraic operations. Since the cost of generating an answer is much less than that of evaluating an answer by algebraic operations, the time consumption for cyclic data can be reduced by an order of magnitude or more.展开更多
文摘Static optimization of logical queries is, in substance, to move selections down as far as possible in evaluating logical queries. This paper extends Ullman's RGG (Rule/Goal Graph) and introduces P- graph, with which a wide range of recursive logical queries can be statically optimized top-down and evaluated bottom-up, some of which are usually optimized by dynamic approaches. The paper also shows that for some logical queries the complexity of pushing selections down and computing bottom-up is related to the complexity of base relation in the queries.
文摘In this paper, an optimal method to handle cyclic and acyclic data relations in the linear recursive queries is proposed. High efficiency is achieved by integrating graph traversal mechanisms into a top-down evaluation. In such a way the subsumption checks and the identification of cyclic data can be done very efficielltly First, based on the subsumption checks, the search space can be reduced drastically by avoiding any redundant expansion operation. In fact, in the case of non-cyclic data, the proposed algorithm requires only linear time for evaluating a linear recursive query. On the other hand, in the case of cyclic data, by using the technique for isolating strongly connected components a lot of answers can be generated directly in terms of the intermediate results and the relevant path information instead of evaluating them by performing algebraic operations. Since the cost of generating an answer is much less than that of evaluating an answer by algebraic operations, the time consumption for cyclic data can be reduced by an order of magnitude or more.
