Graph-based rules and transactions for parallel and active database systems

Abstract

Active database management systems are becoming increasingly popular because of their relevance to several advanced and complex database applications. The need for user-defined execution orders (or control structures) for rules is well recognized by researchers of active database management systems. Priority-based approaches (e.g., numeric priorities) have been used to specify a desired control structure among rules. However, due to the fact that fixed priorities are assigned to rules, independent of different contexts in which they may be triggered, the existing approaches are not able to allow rules to be executed following different control structures when they are triggered by different events. More flexible and expressive control mechanisms are often needed for rules in advanced database applications such as CAD/CAM, CASE, CIM and flexible manufacturing systems. Since rules in database environments are executed in a transaction framework, an expressive transaction model is needed to model complex control structures among rulesuniformly. In this work, we separate the event part from the condition-action parts of a rule and associate it with a rule graph which represents a set of rules (actually a set of condition-action pairs) sharing the same control structure. Different rule graphs can be defined under different event specifications thereby enabling a set of rules to follow different control structures when triggered by different events. We also use an expressive graph-based transaction model to incorporate the control structures of rule graphs uniformly in a transaction framework. The proposed rule and transaction modeling and execution techniques have been implemented and verified on a shared-nothing multiprocessor computer nCUBE2. In this paper, we also describe the client-server architecture and different parallel transaction and rule execution techniques that have been used for the implementation. Finally, we analyze the speedup and scaleup of the implemented system.