Distributed query optimization in loosely coupled multidatabase systems

A multidatabase system (MDBS) is a database system which integrates pre-existing databases, called component local database systems (LDBSs), to support global applications accessing data at more than one LDBS. An important research issue in MDBS is query optimization. The query optimization problem in MDBS is quite different from the case of distributed database system (DDBS) since, due to schema heterogeneity and local autonomy of component LDBSs, is not possible to assume that the query optimizer has a complete information on the execution cost and database statistics. In this paper we present a distributed query optimization algorithm that works under very general assumptions for MDBSs with relational global data model. The algorithm is based on the idea of delegating the evaluation of the execution cost of the elementary steps in a query execution plan to the LDBS where the computation is performed. The optimization process is organized as a sequence of steps, in which at each step all LDBSs work in parallel to evaluate the cost of execution plans for partial queries of increasing size, and send their cost estimates to the other LDBS that need them for the next step. The computation is totally distributed, and organized in order to perform no duplicate computation, and to discard as soon as possible the execution plans that may not lead to an optimal solution.