In this thesis we address the problem of providing efficient processing of queries in the extensible environment induced by object-oriented databases. We define a framework for query processing in an object-oriented database and develop designs for major components of this framework. The framework encompasses an object-oriented data model, an algebra to query over that model, transformation rules for the algebra, an internal representation for queries expressed in the algebra, a cost model for analyzing query expressions, and an architecture for an extensible query optimizer. The major contributions of this thesis are an algebra and transformation rules, a representation, and an architecture for extensible query optimization. We show how these components fit into the framework and interact with each other. The EQUAL query algebra presented in this thesis is the first query algebra for object-oriented database systems to be completely consistent with data abstraction, and one of the few...

Query optimizers for persistent object systems should be extensible to react to user-supplied abstract types. Current architectures support only a single, non-extensible technique for controlling the optimization process. We propose an alternative to the current extensible architectures that will support multiple optimizer control strategies and the addition of new control strategies. The optimizer consists of a collection of optimization regions, each of which can transform queries according to a particular control strategy, set of transformations and cost model. A global optimizer control coordinates the movement of a query between these regions. This architecture provides extensibility in the optimizer's repertoire of control strategies through the addition of new regions. In this paper we describe our approach and demonstrate its utility by following the optimizer as it works on an example query. The optimizer will move the query between three distinct regions. The different region...