An algorithmic basis for integrating production systems and large databases

Executing a large number of transactions on a large database within a short amount of time is computationally stressful. Main-memory resident production systems have been made computationally feasible by the development of incremental match algorithms that exploit the temporal redundancy of the database by saving results computed in prior cycles. Unfortunately, the worst-case space complexity of these match algorithms is exponential, and space management becomes a dominant issue. A lazy incremental match algorithm with linear worst-case space complexity is presented. Initial empirical results show that Lazy Match can prune 60% of the search for rule instantiations. It is felt that these results provide the first reasonable algorithmic basis upon which one can develop an active database system