Grahne et al. have presented a graph algorithm for evaluating a subset of recursive queries. This method consists of two phases. In the first phase, the method transforms a linear binary-chain program into a set of eq...Grahne et al. have presented a graph algorithm for evaluating a subset of recursive queries. This method consists of two phases. In the first phase, the method transforms a linear binary-chain program into a set of equations over expressions containing predicate symbols. In the second phase, a graph is constructed from the equations and the answers are produced by traversing the relevant paths. A new algorithm is described which requires less time than Grahne’ s. The key idea of the improvement is to reduce the search space that will be traversed when a query is invoked. Further, the evaluation of cyclic data is speeded up by generating most answers directly in terms of the answers already found and the associated 'path information' instead of traversing the corresponding paths as usual. In this way, this algorithm achieves a linear time complexity for both acyclic and most of cyclic data.展开更多
文摘Grahne et al. have presented a graph algorithm for evaluating a subset of recursive queries. This method consists of two phases. In the first phase, the method transforms a linear binary-chain program into a set of equations over expressions containing predicate symbols. In the second phase, a graph is constructed from the equations and the answers are produced by traversing the relevant paths. A new algorithm is described which requires less time than Grahne’ s. The key idea of the improvement is to reduce the search space that will be traversed when a query is invoked. Further, the evaluation of cyclic data is speeded up by generating most answers directly in terms of the answers already found and the associated 'path information' instead of traversing the corresponding paths as usual. In this way, this algorithm achieves a linear time complexity for both acyclic and most of cyclic data.
