A MapReduce-Based Architecture for Rule Matching in Production System

Production system which accepts the facts and draws conclusions by repeatedly matching facts with rules plays an important role of improving the business by providing agility and flexibility. However, rule matching in production is badly time-consuming, and single computer limits the improvement for current matching algorithm. To address these problems, we proposed a MapReduce-based architecture to implement the distributed and parallel matching in different computers running with Rete algorithm. The architecture would benefit production system in performance, large scale of rules and facts are for special. This paper firstly formalizes some definitions for an accurate description, then not only discusses the details of implementation for different stages of the architecture but also shows the high efficiency through the experiment. At the end, we mention some complex factors which will be considered in the future for better performance.