Query Optimization for Semistructured Data Using Path Constraints in a Deterministic Data Model

Path constraints have been studied in [4, 11, 12, 13] for semistructured data modeled as a rooted edge-labeled directed graph. They have proven useful in the optimization of path queries. However, in this graph model, the implication problems associated with many natural path constraints are undecidable [11, 13]. A variant of the graph model, called the deterministic data model , was recently proposed in [10]. In this model, data is represented as a graph with deterministic edge relations, i.e., the edges emanating from any node in the graph have distinct labels. The deterministic graph model is more appropriate for representing, for example, ACeDB [27] databases and Web sites. This paper investigates path constraints for the deterministic data model. It demonstrates the application of path constraints to, among other things, query optimization. Three classes of path constraints are considered: the language Pc introduced in [11], an extension of Pc, denoted by P w c , by including wildcards in path expressions, and a generalization of P c , denoted by P c , by representing paths as regular expressions. The implication problems for these constraint languages are studied in the context of the deterministic data model. It shows that in contrast to the undecidability result of [11], the implication and nite implication problems for Pc are decidable in cubic-time and are nitely axiomatizable. Moreover, the implication problems are decidable for P c . However, the implication problems for P c are undecidable.