The Experts below are selected from a list of 291 Experts worldwide ranked by ideXlab platform
Michael A Walter - One of the best experts on this subject based on the ideXlab platform.
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extension of the Relational Algebra to probabilistic complex values
Foundations of Information and Knowledge Systems, 2000Co-Authors: Thomas Eiter, Thomas Lukasiewicz, Michael A WalterAbstract:We present a probabilistic data model for complex values. More precisely, we introduce probabilistic complex value relations, which combine the concept of probabilistic relations with the idea of complex values in a uniform framework. We then define an Algebra for querying database instances, which comprises the operations of selection, projection, renaming, join, Cartesian product, union, intersection, and difference. We finally show that most of the query equivalences of classical Relational Algebra carry over to our Algebra on probabilistic complex value relations. Hence, query optimization techniques for classical Relational Algebra can easily be applied to optimize queries on probabilistic complex value relations.
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FoIKS - Extension of the Relational Algebra to Probabilistic Complex Values
Lecture Notes in Computer Science, 2000Co-Authors: Thomas Eiter, Thomas Lukasiewicz, Michael A WalterAbstract:We present a probabilistic data model for complex values. More precisely, we introduce probabilistic complex value relations, which combine the concept of probabilistic relations with the idea of complex values in a uniform framework. We then define an Algebra for querying database instances, which comprises the operations of selection, projection, renaming, join, Cartesian product, union, intersection, and difference. We finally show that most of the query equivalences of classical Relational Algebra carry over to our Algebra on probabilistic complex value relations. Hence, query optimization techniques for classical Relational Algebra can easily be applied to optimize queries on probabilistic complex value relations.
D. Alton - One of the best experts on this subject based on the ideXlab platform.
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ICDE - A polymorphic Relational Algebra and its optimization
[1991] Proceedings. Seventh International Conference on Data Engineering, 1Co-Authors: David Eichmann, D. AltonAbstract:The notion of a polymorphic database and the optimization of polymorphic queries-specifically, optimization of queries under the Morpheus data model-is addressed. The notion of query optimization through type inference, applicable both to polymorphic databases and traditional monomorphic databases, is introduced. The Morpheus data model and its type inference rules are reviewed and a polymorphic Relational Algebra is characterized. It is shown how the inference rules can be used for static optimization of a few sample queries. It is concluded that type inference provides a formal mechanism for optimizing a very rich extension to the Relational Algebra. The approach retains the basic framework that lead to the wide acceptance of the Relational model, while enriching it with the structural expressiveness of the object-oriented approaches of recent years. >
Jan Van Den Bussche - One of the best experts on this subject based on the ideXlab platform.
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On the complexity of division and set joins in the Relational Algebra
Journal of Computer and System Sciences, 2007Co-Authors: Dirk Leinders, Jan Van Den BusscheAbstract:We show that any expression of the Relational division operator in the Relational Algebra with union, difference, projection, selection, constant-tagging, and joins, must produce intermediate results of quadratic size. To prove this result, we show a dichotomy theorem about intermediate sizes of Relational Algebra expressions (they are either all linear, or at least one is quadratic), and we link linear Relational Algebra expressions to expressions using only semijoins instead of joins.
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on the complexity of division and set joins in the Relational Algebra
Symposium on Principles of Database Systems, 2005Co-Authors: Dirk Leinders, Jan Van Den BusscheAbstract:We show that any expression of the Relational division operator in the Relational Algebra with union, difference, projection, selection, and equijoins, must produce intermediate results of quadratic size. To prove this result, we show a dichotomy theorem about intermediate sizes of Relational Algebra expressions (they are either all linear, or at least one is quadratic); we link linear Relational Algebra expressions to expressions using only semijoins instead of joins; and we link these semijoin Algebra expressions to the guarded fragment of first-order logic.
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PODS - On the complexity of division and set joins in the Relational Algebra
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems - PODS '05, 2005Co-Authors: Dirk Leinders, Jan Van Den BusscheAbstract:We show that any expression of the Relational division operator in the Relational Algebra with union, difference, projection, selection, and equijoins, must produce intermediate results of quadratic size. To prove this result, we show a dichotomy theorem about intermediate sizes of Relational Algebra expressions (they are either all linear, or at least one is quadratic); we link linear Relational Algebra expressions to expressions using only semijoins instead of joins; and we link these semijoin Algebra expressions to the guarded fragment of first-order logic.
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Solving Equations in the Relational Algebra
SIAM Journal on Computing, 2004Co-Authors: Joachim Biskup, Thomas Schwentick, Jan Paredaens, Jan Van Den BusscheAbstract:Enumerating all solutions of a Relational Algebra equation is a natural and powerful operation which, when added as a query language primitive to the nested Relational Algebra, yields a query language for nested Relational databases, equivalent to the well-known powerset Algebra. We study sparse equations, which are equations with at most polynomially many solutions. We look at their complexity and compare their expressive power with that of similar notions in the powerset Algebra.
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Polymorphic Type Inference for the Relational Algebra
Journal of Computer and System Sciences, 2002Co-Authors: Jan Van Den Bussche, Emmanuel WallerAbstract:We give a polymorphic account of the Relational Algebra. We introduce a formalism of “type formulas” specifically tuned for Relational Algebra expressions, and present an algorithm that computes the “principal” type for a given expression. The principal type of an expression is a formula that specifies, in a clear and concise manner, all assignments of types (sets of attributes) to relation names, under which a given Relational Algebra expression is well-typed, as well as the output type that expression will have under each of these assignments. Topics discussed include complexity and polymorphic expressive power.
Thomas Eiter - One of the best experts on this subject based on the ideXlab platform.
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extension of the Relational Algebra to probabilistic complex values
Foundations of Information and Knowledge Systems, 2000Co-Authors: Thomas Eiter, Thomas Lukasiewicz, Michael A WalterAbstract:We present a probabilistic data model for complex values. More precisely, we introduce probabilistic complex value relations, which combine the concept of probabilistic relations with the idea of complex values in a uniform framework. We then define an Algebra for querying database instances, which comprises the operations of selection, projection, renaming, join, Cartesian product, union, intersection, and difference. We finally show that most of the query equivalences of classical Relational Algebra carry over to our Algebra on probabilistic complex value relations. Hence, query optimization techniques for classical Relational Algebra can easily be applied to optimize queries on probabilistic complex value relations.
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FoIKS - Extension of the Relational Algebra to Probabilistic Complex Values
Lecture Notes in Computer Science, 2000Co-Authors: Thomas Eiter, Thomas Lukasiewicz, Michael A WalterAbstract:We present a probabilistic data model for complex values. More precisely, we introduce probabilistic complex value relations, which combine the concept of probabilistic relations with the idea of complex values in a uniform framework. We then define an Algebra for querying database instances, which comprises the operations of selection, projection, renaming, join, Cartesian product, union, intersection, and difference. We finally show that most of the query equivalences of classical Relational Algebra carry over to our Algebra on probabilistic complex value relations. Hence, query optimization techniques for classical Relational Algebra can easily be applied to optimize queries on probabilistic complex value relations.
David Eichmann - One of the best experts on this subject based on the ideXlab platform.
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ICDE - A polymorphic Relational Algebra and its optimization
[1991] Proceedings. Seventh International Conference on Data Engineering, 1Co-Authors: David Eichmann, D. AltonAbstract:The notion of a polymorphic database and the optimization of polymorphic queries-specifically, optimization of queries under the Morpheus data model-is addressed. The notion of query optimization through type inference, applicable both to polymorphic databases and traditional monomorphic databases, is introduced. The Morpheus data model and its type inference rules are reviewed and a polymorphic Relational Algebra is characterized. It is shown how the inference rules can be used for static optimization of a few sample queries. It is concluded that type inference provides a formal mechanism for optimizing a very rich extension to the Relational Algebra. The approach retains the basic framework that lead to the wide acceptance of the Relational model, while enriching it with the structural expressiveness of the object-oriented approaches of recent years. >
