Solving Implication Problems in Database Applications.
Xian-He Sun, Nabil Kamel, Lionel M. Ni:
Solving Implication Problems in Database Applications.
SIGMOD Conference 1989: 185-192@inproceedings{DBLP:conf/sigmod/SunKN89,
author = {Xian-He Sun and
Nabil Kamel and
Lionel M. Ni},
editor = {James Clifford and
Bruce G. Lindsay and
David Maier},
title = {Solving Implication Problems in Database Applications},
booktitle = {Proceedings of the 1989 ACM SIGMOD International Conference on
Management of Data, Portland, Oregon, May 31 - June 2, 1989},
publisher = {ACM Press},
year = {1989},
pages = {185-192},
ee = {http://doi.acm.org/10.1145/67544.66943, db/conf/sigmod/SunKN89.html},
crossref = {DBLP:conf/sigmod/89},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
Computing queries from derived relations,
optimizing queries from a group of queries, and updating materialized views are important database problems and have attracted much attention. One thing common to these problems is their demand to quickly solve the implication problem - given two predicates sigmaQ and sigmaT, can sigmaQ imply sigmaT (sigmaQ->sigmaT)? The implication problem has been solved by converting it into a satisfiability problem. Based on a graph representation, a detailed study of the general implication
problem on its own is presented in this paper. We proved that the general implication problem, in which all six comparison operators: =, #, <, >, <=, >=, as well as conjunctions and disjunctions are allowed, is NP-hard. In the case when
"#" operators are not allowed in sigmaQ and disjunctions are not allowed in sigmaT, a polynomial time algorithm is proposed to solve this restricted implication problem. The influence of the "#" operator and disjunctions are studied. Our theoretical results show that for some special cases the polynomial complexity algorithm can solve the implication problem which allows the "#" operator or disjunctions in the predicates. Necessary conditions for detecting when the "#" operator and disjunctions are allowed are also given. These results are very useful in creating heuristic methods.
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BibTeX
Printed Edition
James Clifford, Bruce G. Lindsay, David Maier (Eds.):
Proceedings of the 1989 ACM SIGMOD International Conference on Management of Data, Portland, Oregon, May 31 - June 2, 1989.
ACM Press 1989 BibTeX
,
SIGMOD Record 18(2), June 1989
Contents
References
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SIGMOD Conference 1982: 235-245 BibTeX
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VLDB 1986: 457-466 BibTeX
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Efficiently Updating Materialized Views.
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BibTeX
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Referenced by
- Peter Scheuermann, Junho Shim, Radek Vingralek:
WATCHMAN : A Data Warehouse Intelligent Cache Manager.
VLDB 1996: 51-62
- Nick Roussopoulos, Chung-Min Chen, Stephen Kelley, Alex Delis, Yannis Papakonstantinou:
The ADMS Project: View R Us.
IEEE Data Eng. Bull. 18(2): 19-28(1995)
- Wei Sun, Mark Allen Weiss:
An Improved Algorithm for Implication Testing Involving Arithmetic Inequalities.
IEEE Trans. Knowl. Data Eng. 6(6): 997-1001(1994)
- Arantza Illarramendi, José Miguel Blanco, Alfredo Goñi:
Making the Knowledge Base System More Efficient: A Method to Detect Inconsistent Queries.
IEEE Trans. Knowl. Data Eng. 6(4): 634-639(1994)
- Nabil Kamel, Roger King:
Intelligent Database Caching Through the Use of Page-Answers and Page-Traces.
ACM Trans. Database Syst. 17(4): 601-646(1992)
- T. Y. Cliff Leung, Richard R. Muntz:
Temporal Query Processing and Optimization in Multiprocessor Database Machines.
VLDB 1992: 383-394
- Amit P. Sheth, Anthony B. O'Hare:
The Architecture of BrAID: A System for Bridging AI/DB Systems.
ICDE 1991: 570-581
- Michael V. Mannino, Injun Choi:
Object-Oriented Modelling and Reasoning.
ER 1990: 455-464
- Sreekumar T. Shenoy, Z. Meral Özsoyoglu:
Design and Implementation of a Semantic Query Optimizer.
IEEE Trans. Knowl. Data Eng. 1(3): 344-361(1989)
BibTeX
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