The future data systems are likely to be integrated data networks (IDNs) consisting of a mix of general-purpose computer systems and special-purpose functional processors that are produced by different vendors and have quite different computational power and database management capabilities. Data stored in these networks need to be integrated and shared by the network users. It is important to have a query processing strategy in this type of network that can take advantage of the diverse functional capabilities of the component systems and the parallel processing potential of the network. In this paper, we present a query processing strategy which combines three known techniques: 1) query decomposition, 2) pipelined and data-flow processing of queries, and 3) intermediate result sharing among concurrent queries. The strategies for controlling and managing query and data pipelines are presented. Algorithms for the pipelined execution of the relational join operation are also described. Selected results of the evaluation of the query processing strategy, pipeline control strategies, and parallel algorithms are presented.
['Stanley Y. W. Su', 'Krishna P. Mikkilineni', 'Raymond A. Liuzzi', 'Yuan-Chieh Chow']
A distributed query processing strategy using decomposition, pipelining and intermediate result sharing techniques