Deductive query processing with an object-oriented semantic network in a massively parallel environment

Most of researches related to parallel query processing have concentrated on how to partition and schedule operation-by-operation and tuple-by-tuple query processing jobs to available processors. As a result, complex query optimizations should be performed, which cause tremendous overhead especially in a massively parallel system with thousands of processors. This paper proposes an effective parallel query processing method in a massively parallel environment. For this, the facts and deductive rules of a deductive database are partitioned into fine-grain semantic elements based on the concept of the object-oriented model. These semantic elements are used to construct an object-oriented semantic network (OOSN). Since all facts and deductive rules are mapped to the OOSN statically, a query can be evaluated effectively in a distributed manner without any complex query optimization.