Providing better query-processing support for quantified queries in relational database systems
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| Vydáno v: | ProQuest Dissertations and Theses (1996) |
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ProQuest Dissertations & Theses
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| On-line přístup: | Citation/Abstract Full Text - PDF |
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| Abstrakt: | Relational database systems have succeeded commercially because of their simplicity and strong theoretical background. In recent times, relational database systems have had to undergo changes to process complex and ad-hoc queries called decision support queries, which are so called because they aid an organization in critical decision making. A subclass of these queries, referred to as quantified queries, is becoming important in several critical sectors, such as healthcare, insurance, and many others. These quantified queries are so called because of the presence of natural language quantifiers in their natural language specification. The industry standard query language SQL is inadequate to effectively express quantified queries. Furthermore, query processors in relational database systems are also not well equipped for processing these queries, resulting frequently in a poor performance. This dissertation proposes a unified algebraic and query processing framework for the efficient processing of quantified queries. The design of a quantified query processing system that employs such a framework is described. Contributions are made in each of the query processing areas: a query algebra that expresses quantified queries, novel quantified query translation and optimization techniques. and an algebra on specialized runtime structures. All of these have been incorporated into the quantified query processing system. Results of comparative performance results run on the quantified query processing system and on two commercial relational database systems are presented to demonstrate the superior performance that can be achieved. |
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| ISBN: | 9780591243260 |
| Zdroj: | ProQuest Dissertations & Theses Global |