Incorporating Stratified Negation into Query-Subquery Nets for Evaluating Queries to Stratified Deductive Databases

keywords: Deductive databases, datalog with negation, query processing
Most of the previously known evaluation methods for deductive databases are either breadth-first or depth-first (and recursive). There are cases when these strategies are not the best ones. It is desirable to have an evaluation framework for stratified DatalogN that is goal-driven, set-at-a-time (as opposed to tuple-at-a-time) and adjustable w.r.t. flow-of-control strategies. These properties are important for efficient query evaluation on large and complex deductive databases. In this paper, by incorporating stratified negation into so-called query-subquery nets, we develop an evaluation framework, called QSQNSTR, with such properties for evaluating queries to stratified DatalogN databases. A variety of flow-of-control strategies can be used for QSQNSTR. The generic evaluation method QSQNSTR for stratified DatalogN is sound, complete and has a PTIME data complexity.
mathematics subject classification 2000: 68N17
reference: Vol. 38, 2019, No. 1, pp. 19–56