Dynamic parallel query processing for distributed objects

An effective exploitation of distributed computing environments to improve the performance of large advanced database applications requires parallel query processing techniques. This is because parallel query execution can be achieved by operations of pipelining and data partitioning, as well as independent subqueries. In order to develop efficient parallel query services in distributed environments, we present a query optimization, a dynamic parallel query scheduling algorithm, and an implementation mechanism for querying distributed objects. Our proposal has four important features. First, the query schedule dynamically schedules independent subqueries in parallel. Second, distributed processors are allowed to execute independent subqueries in random. Third, it doesn't limit the number of processors to deal with parallel query processing in a network based computing environment. Fourth, it provides simple operations to synchronize parallel query programs. We give the query optimization for parallel processing, show an algorithm of dynamic parallel query scheduling, describe an implementation method for the parallel query processing in a network-based distributed computing environment, and present the design of communication and synchronization for the parallel query processing.