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
This paper distinguishes among three kinds of linear recursions: canonical strongly linear recursion (CSLR), non-interdependent linear recursion (NILR) and interdependent linear recurstion (ILR) and presents an optima...This paper distinguishes among three kinds of linear recursions: canonical strongly linear recursion (CSLR), non-interdependent linear recursion (NILR) and interdependent linear recurstion (ILR) and presents an optimal algorithm for each. First, for the CSLRs, the magic-set method is refined in such a way that queries can be evaluated efficiently. Then, for the NILRS and ILRs, the concept of query dependency graphs is introduced to partition the rules of a program into a set of CSLRs and the computation is elaborated so that the oplimization for CSLRs can also be applied.展开更多
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.
文摘This paper distinguishes among three kinds of linear recursions: canonical strongly linear recursion (CSLR), non-interdependent linear recursion (NILR) and interdependent linear recurstion (ILR) and presents an optimal algorithm for each. First, for the CSLRs, the magic-set method is refined in such a way that queries can be evaluated efficiently. Then, for the NILRS and ILRs, the concept of query dependency graphs is introduced to partition the rules of a program into a set of CSLRs and the computation is elaborated so that the oplimization for CSLRs can also be applied.
