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Dive into the research topics where Jarek Gryz is active.

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Featured researches published by Jarek Gryz.


international conference on data engineering | 2003

Skyline with presorting

Jan Chomicki; Parke Godfrey; Jarek Gryz; Dongming Liang

The skyline, or Pareto, operator selects those tuples that are not dominated by any others. Extending relational systems with the skyline operator would offer a basis for handling preference queries. Good algorithms are needed for skyline, however, to make this efficient in a relational setting. We propose a skyline algorithm, SFS, based on presorting that is general, for use with any skyline query, efficient, and well behaved in a relational setting.


very large data bases | 2007

Algorithms and analyses for maximal vector computation

Parke Godfrey; Ryan Shipley; Jarek Gryz

AbstractThe maximal vector problem is to identify the maximals over a collection of vectors. This arises in many contexts and, as such, has been well studied.The problem recently gained renewed attention with skyline queries for relational databases and with work to develop skyline algorithms that are external and relationally well behaved. While many algorithms have been proposed, how they perform has been unclear. We study the performance of, and design choices behind, these algorithms. We prove runtime bounds based on the number of vectors N and the dimensionality K. Early algorithms based on divide and conquer established seemingly good average and worst-case asymptotic runtimes. In fact, the problem can be solved in


intelligent information systems | 2005

Skyline with Presorting: Theory and Optimizations

Jan Chomicki; Parke Godfrey; Jarek Gryz; Dongming Liang


Logics for databases and information systems | 1998

Integrity constraints: semantics and applications

Parke Godfrey; John Grant; Jarek Gryz; Jack Minker

\mathcal{O}(KN)


database and expert systems applications | 1999

Answering Queries by Semantic Caches

Parke Godfrey; Jarek Gryz


international conference on data engineering | 1998

Query folding with inclusion dependencies

Jarek Gryz

average-case (holding K as fixed). We prove, however, that the performance is quite bad with respect to K. We demonstrate that the more recent skyline algorithms are better behaved, and can also achieve


Theoretical Computer Science | 2003

Mining for empty spaces in large data sets

Jeff Edmonds; Jarek Gryz; Dongming Liang; Renée J. Miller


Information Systems | 1999

Query rewriting using views in the presence of functional and inclusion dependencies

Jarek Gryz

\mathcal{O}(KN)


international conference on database theory | 2001

Mining for Empty Rectangles in Large Data Sets

Jeff Edmonds; Jarek Gryz; Dongming Liang; Renée J. Miller


international conference on management of data | 2001

Exploiting constraint-like data characterizations in query optimization

Parke Godfrey; Jarek Gryz; Calisto Zuzarte

average-case. While K matters for these, in practice, its effect vanishes in the asymptotic. We introduce a new external algorithm, LESS, that is more efficient and better behaved. We evaluate LESS’s effectiveness and improvement over the field, and prove that its average-case running time is

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Jaroslaw Szlichta

University of Ontario Institute of Technology

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