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The efficiency of query processing strategies is critical for system performance in any distributed database management system. Many query processing strategies have been proposed to minimize either the response time or the total cost, or both. In this thesis, we introduce the concept of multi-attribute semijoin (MASJ)--a new database operation to reduce the communication cost (ignoring the local cost of total cost) in distributed query processing. The objective of this investigation is to find out whether this operation gives significant improvements in the communication cost to process distributed queries. We explore some useful properties of this operation and develop a heuristic to identify situations where this operation is useful. Based on these results, we propose a query processing strategy called the MJ Algorithm to minimize the communication cost for query optimization. The MJ Algorithm combines the AHY Algorithm (total time version) and the multi-attribute semijoin operation. Our aim is to find out whether the new algorithm can construct better reducers than the AHY Algorithm. Finally, we use simulation studies with a large number of queries and our experiments indicate that the performance of the MJ Algorithm is significantly better than that of the AHY Algorithm. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1996 .F8. Source: Masters Abstracts International, Volume: 37-01, page: 0284. Adviser: Subir Bandyopadhyay. Thesis (M.Sc.)--University of Windsor (Canada), 1996.
Fu, Qiuling., "Distributed query optimization using multi-attribute semijoin operations." (1996). Electronic Theses and Dissertations. 1763.