Multiple Query Optimization with Depth-First Branch-and-Bound
In certain database applications such as deductive databases, batch query processing, and recursive query processing etc., a single query can be transformed into a set ofclosely related database queries. Great benefits can be obtained by executing a group of related queries all together in a single...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
1993
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| Online Access: | https://ink.library.smu.edu.sg/sis_research/958 https://ink.library.smu.edu.sg/context/sis_research/article/1957/viewcontent/p433_cosar.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | In certain database applications such as deductive databases, batch query processing, and recursive query processing etc., a single query can be transformed into a set ofclosely related database queries. Great benefits can be obtained by executing a group of related queries all together in a single unijied multi-plan instead of executing each query separately. In order to achieve this, Multiple Query Optimization (MQO) identifies common task(s) (e.g. common subezpressions, joins, etc.) among a set of query plans and creates a single unified plan (multiplan) which can be executed to obtain the required outputs forall queries at once. In this paper, anew heuristic function (f=), dynamic query ordering heuristics, and Depth-First Branch-and-Bound (DFBB) are dejined and experimentally evaluated, and compared with existing methods which use A* and static query ordering. Our experiments show that all three of f., DFBB, and dynamic query ordering help to improve the performance of our h4Q0 algorithm. |
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