Synthesizing third normal form relations from functional dependencies
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Multivalued dependencies and a new normal form for relational databases
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Independent components of relations
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A relational model of data for large shared data banks
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A complete axiomatization for functional and multivalued dependencies in database relations
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The Design and Analysis of Computer Algorithms
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SYSTEM/U: a database system based on the universal relation assumption
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A Proof Procedure for Data Dependencies
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Notions of dependency satisfaction
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Elimination of intersection anomalies from database schemes
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Normalization of relations and PROLOG
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Dynamic functional dependencies and database aging
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Constant-time-maintainable BCNF database schemes
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Independence-reducible database schemes
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Join processing in relational databases
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Constant-time maintainability: a generalization of independence
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Simple conditions for guaranteeing higher normal forms in relational databases
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Updating relational databases through weak instance interfaces
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On the optimality of strategies for multiple join
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On the optimality of strategies for multiple joins
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Independence-reducible database schemes
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Decomposition of relational schemata into components defined by both projection and restriction
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On the foundations of the universal relation model
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Hierarchical schemata for relational databases
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An improved third normal form for relational databases
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A normal form for relational databases that is based on domains and keys
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A simplied universal relation assumption and its properties
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Determining View dependencies using tableaux
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A new normal form for the design of relational database schemata
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Joined normal form: a storage encoding for relational databasess
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The universal relation revisited (technical correspondence)
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Efficient optimization of a class of relational expressions
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Calculating constraints on relational expression
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Equivalences Among Relational Expressions with the Union and Difference Operators
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Minimum Covers in Relational Database Model
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On the Complexity of Testing Implications of Functional and Join Dependencies
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Subset Dependencies and a Completeness Result for a Subclass of Embedded Multivalued Dependencies
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On the Equivalence of Database Models
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Testing satisfaction of functional dependencies
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Properties of functional-dependency families
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Graph Algorithms for Functional Dependency Manipulation
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Elimination of intersection amomalies from database schemes
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Algebraic aspects of relational database decomposition
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Assumptions in relational database theory
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Compatible attributes in a universal relation
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A universal relation database system implemented via the network model
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Inclusion dependencies and their interaction with functional dependencies
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A theory of data dependencies over relational expressions
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Optimal computation of total projections with unions of simple chase join expressions
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Efficient processing of relational calculus expressions using range query theory
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A Group-Select Operation for Relational Algebra and Implications for Database Machine Design
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Fast In-Place Verification of Data Dependencies
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An Equational Chase for Path-Conjunctive Queries, Constraints, and Views
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A Less Costly Constraints Checking for Join Dependency
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Supporting Flat Relations by a Nested Relational Kernel
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Database Decomposition into Fourth Normal Form
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Unary inclusion dependencies have polynomial time inference problems
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Characterisations of multivalued dependency implication over undetermined universes
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Size and Treewidth Bounds for Conjunctive Queries
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Evaluating multiple join queries in a distributed database system
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Executing join queries in an uncertain distributed environment
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Atomicity and Semantic Normalization
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ACM SIGMOD Record
Hi-index | 0.03 |
Answering queries in a relational database often requires that the natural join of two or more relations be computed. However, the result of a join may not be what one expects. In this paper we give efficient algorithms to determine whether the join of several relations has the intuitively expected value (is lossless) and to determine whether a set of relations has a subset with a lossy join. These algorithms assume that all data dependencies are functional. We then discuss the extension of our techniques to the case where data dependencies are multivalued.