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Managing Semantic Heterogeneity in Databases : A Theoretical Perspective, Tutorial at PODS
 ACM SIGMOD Record
, 1997
"... A full version of this tutorial appears at ..."
Modular stratification and magic sets for Datalog programs with negation
 In Proceedings of the ACM Symposium on Principles of Database Systems
, 1990
"... ..."
The Magic of Duplicates and Aggregates
, 1990
"... We present a formal treatment of multisets (that arise when duplicates are not eliminated) and aggregate operators for deductive and relational databases. We define the semantics rigorously and extend the magicsets technique to programs containing multisets and aggregates. The work presented here i ..."
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Cited by 59 (5 self)
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We present a formal treatment of multisets (that arise when duplicates are not eliminated) and aggregate operators for deductive and relational databases. We define the semantics rigorously and extend the magicsets technique to programs containing multisets and aggregates. The work presented here is an important step in demonstrating the applicability of the magicsets technique for optimizing queries in commercial query languages such as SQL. 1 Introduction Previous treatments of Datalog and proposed extensions have treated a program as a collection of definitions of sets of facts (tuples). On the other hand, commercial query languages such as SQL typically support the definition of sets and multisets of tuples, and provide aggregate operators such as SUM and COUNT over sets and multisets. The ability to deal with multisets Part of this work was done at the IBM Almaden Research Center. Work at Stanford was supported by an NSF grant IRI87 22886, an Air Force grant AFOSR880266...
The LyriC Language: Querying Constraint Objects
 In Proceedings of the ACM SIGMOD International Conference on Management of Data
, 1994
"... Proposed in this paper is a novel data model and its language for querying objectoriented databases where objects may hold spatial, temporal or constraint data, conceptually represented by linear equality and inequality constraints. The proposed LyriC language is designed to provide a uniform and f ..."
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Cited by 23 (2 self)
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Proposed in this paper is a novel data model and its language for querying objectoriented databases where objects may hold spatial, temporal or constraint data, conceptually represented by linear equality and inequality constraints. The proposed LyriC language is designed to provide a uniform and flexible framework for diverse application realms such as (1) constraintbased design in two, three, or higherdimensional space, (2) largescale optimization and analysis, based mostly on linear programming techniques, and (3) spatial and geographic databases. LyriC extends flat constraint query languages, especially those for linear constraint databases, to structurally complex objects. The extension is based on the objectoriented paradigm, where constraints are treated as firstclass objects that are organized in classes. The query language is an extension of the language XSQL, and is built around the idea of extended path expressions. Path expressions in a query traverse nested struct...
Implementing incremental view maintenance in nested data models
 In Proceedings of the Workshop on Database Programming Languages
, 1997
"... Abstract. Previous research on materialized views has primarily been in the context of flat relational databasesmaterialized views defined in terms of one or more flat relations. This paper discusses a broader class of view definitionsmaterialized views defined over a nested data model such as t ..."
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Cited by 15 (1 self)
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Abstract. Previous research on materialized views has primarily been in the context of flat relational databasesmaterialized views defined in terms of one or more flat relations. This paper discusses a broader class of view definitionsmaterialized views defined over a nested data model such as the nested relational model or an objectoriented data model. An attribute of a tuple deriving the view can be a reference (i.e., a pointer) to a nested relation, with arbitrary levels of nesting possible. The extended capability of this nested data model, together with materialized views, simplifies data modeling and gives more flexibility. Simple extensions of standard view maintenance techniques to the nested model would do too much work for maintenance: a change in a nested set would reprocess the entire nested set, not just the changed parts. We show how existing incremental maintenance algorithms can be extended to maintain the views without performing this additional work. We describe the implementation of these techniques in the SWORD interface to the Ode database system. The implementation is based on the representation of nested structures by classes and the use of an SQLlike language to define materialized views. We outline the data structures and algorithms used in the implementation and examine performance. This is one of the first pieces of work to explore the applicability of materialized views over complex objects. 1
On Negation in HiLog
 Journal of Logic Programming
, 1994
"... The logic HiLog of Chen, Kifer and Warren has a second order syntax, while its semantics is first order. HiLog programs with negative literals in the body are considered. A stable model semantics and a wellfounded semantics for this class of programs are defined, and it is shown that these semantic ..."
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Cited by 14 (1 self)
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The logic HiLog of Chen, Kifer and Warren has a second order syntax, while its semantics is first order. HiLog programs with negative literals in the body are considered. A stable model semantics and a wellfounded semantics for this class of programs are defined, and it is shown that these semantics generalize the stable model semantics and the wellfounded semantics, respectively, for rangerestricted normal programs. A second order property called preservation under extensions is proposed and investigated. Preservation under extensions ensures that the semantics of a program is not changed when rules having no symbols in common with the program are appended to the program. It is shown that for normal programs domain independence and preservation under extensions are equivalent, while for HiLog programs preservation under extensions is strictly stronger. Range restrictedness is generalized to HiLog programs in two ways, and it is shown that range restricted HiLog programs are preserv...
Denotational Versus Declarative Semantics For Functional Programming
, 1992
"... Denotational semantics is the usual mathematical semantics for functional programming languages. It is higher order (H.O.) in the sense that the semantic domain D includes [D ! D] as a subdomain. On the other hand, the usual declarative semantics for logic programs is first order (F.O.) and given b ..."
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Denotational semantics is the usual mathematical semantics for functional programming languages. It is higher order (H.O.) in the sense that the semantic domain D includes [D ! D] as a subdomain. On the other hand, the usual declarative semantics for logic programs is first order (F.O.) and given by the least Herbrand model. In this paper, we take a restricted kind of H.O. conditional rewriting systems as computational paradigm for functional programming. For these systems, we define both H.O. denotational and F.O. declarative semantics as two particular instances of algebraic semantics over continuous applicative algebras. For the declarative semantics, we prove soundness and completeness of rewriting, as well as an initiality result. We show that both soundness and completeness fail w.r.t. the denotational semantics and we present a natural restriction of rewriting that avoids unsoundness. We conjecture that this restricted rewriting is complete for computing denotationally valid F....
NAIL (Not Another Implementation of Logic) was a prototype deductive database system developed at Stanford.
"... F14.69> end; ffl Condition is a rule body. ffl Its value is "true" iff the body is nonempty. ffl Similar idea: repeat, loop, ifthenelse statements. Example: (1) module semi; (2) export main(:); (3) edb arc(X,Y), path(X,Y); (4) prog main(:) (5) rels newPath(X,Y); (6) arc(X,Y) := . (7) a ..."
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F14.69> end; ffl Condition is a rule body. ffl Its value is "true" iff the body is nonempty. ffl Similar idea: repeat, loop, ifthenelse statements. Example: (1) module semi; (2) export main(:); (3) edb arc(X,Y), path(X,Y); (4) prog main(:) (5) rels newPath(X,Y); (6) arc(X,Y) := . (7) arc(1,2). (8) arc(2,3). (9) arc(3,4). (10) arc(4,5). (11) arc(2,4). (12) newPath(X,Y) := arc(X,Y). (13) path(X,Y) := . (14) while newPath(X,Y) do (15) path(X,Y) += newPath(X,Y). (16) newPath(X,Y) := newPath(X,Z) & arc(Z,Y). (17) newPath(X,Y) = path(X,Y). (18) end; (19) end (20) end This program performs seminaive
Tail Recursion Elimination in Deductive Databases
"... We consider an optimization technique for deductive and relational databases. The optimization technique is an extension of the magic templates rewriting, and it can improve the performance of query evaluation by not materializing the extension of intermediate views. Standard relational techniques, ..."
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We consider an optimization technique for deductive and relational databases. The optimization technique is an extension of the magic templates rewriting, and it can improve the performance of query evaluation by not materializing the extension of intermediate views. Standard relational techniques, such as unfolding embedded view definitions, do not apply to recursively defined views, and so alternative techniques are necessary. We demonstrate the correctness of our rewriting. We define a class of "nonrepeating" view definitions, and show that for certain queries our rewriting performs at least as well as magic templates on nonrepeating views, and often much better. A syntactically recognizable property, called "weak rightlinearity," is proposed. Weak rightlinearity is a sufficient condition for nonrepetition, and is more general than rightlinearity. Our technique gives the same benefits as rightlinear evaluation of rightlinear views, while applying to a significantly more general ...