Dynamic Argument Reduction for In-memory Data Queries

Recently tuple-at-a-time evaluation strategies have begun receiving renewed attention for in-memory data queries, due to the existence of efficient techniques for their implementation. One such technique, the SLG-WAM, forms the basis of the XSB system[9]; performance tests indicate it to be an order of magnitude faster than current deductive databases for a wide range of in-memory queries. The SLG-WAM is based on SLG resolution [5], [4], a resolution method which uses tabling to evaluate normal logic programs 1 . For any tabling method, be it SLG or Magic, access to tabled subgoals and to their answers is critical for efficiency. Concern with this access time has led to optimization techniques, such as those for removing ground arguments from recursive rules. This paper presents table access methods, which combined with the backtracking of the SLG-WAM's tuple-at-a-time evaluation, allow dynamic reductions in the arguments of inferred predicates at an almost imperceptible cost compare..