• Corpus ID: 218971715

Discovering Domain Orders through Order Dependencies

  title={Discovering Domain Orders through Order Dependencies},
  author={Reza Karegar and Melicaalsadat Mirsafian and Parke Godfrey and Lukasz Golab and Mehdi Kargar and Divesh Srivastava and Jaroslaw Szlichta},
Much real-world data come with explicitly defined domain orders; e.g., lexicographic order for strings, numeric for integers, and chronological for time. Our goal is to discover implicit domain orders that we do not already know; for instance, that the order of months in the Chinese Lunar calendar is Corner < Apricot < Peach. To do so, we enhance data profiling methods by discovering implicit domain orders in data through order dependencies. We enumerate tractable special cases and proceed… 
1 Citations

Discovering Domain Orders via Order Dependencies

This work enhances data profiling methods by discovering implicit domain orders in data through order dependencies, enumerate tractable special cases and show that the general case is NP-complete but can be effectively handled by a SAT solver.



Efficient order dependency detection

This work is the first to describe the discovery problem for order dependencies in a principled manner by characterizing the search space, developing and proving pruning rules, and presenting the algorithm Order, which finds all order dependenciesIn a comprehensive evaluation, it is shown that it is efficient even for various large datasets.

Effective and complete discovery of bidirectional order dependencies via set-based axioms

This work presents an efficient biddirectional OD discovery algorithm enabled by a novel polynomial mapping to a canonical form, and a sound and complete set of axioms for canonical bidirectional ODs to prune the search space, and proves that it produces a complete and minimal set of bidirectionAL ODs.

Effective and Complete Discovery of Order Dependencies via Set-based Axiomatization

This work addresses the limitations of prior work on OD discovery, and develops an efficient set-containment, lattice-driven OD discovery algorithm that uses the inference rules to prune the search space.

Expressiveness and Complexity of Order Dependencies

This work investigates the inference problem for ODs, and shows the usefulness of ODs in query optimization, as by the order-by operator in SQL, because this is the notion of order used in SQL and within query optimization.

Fundamentals of Order Dependencies

It is proved that functional dependencies are subsumed by order dependencies and that the set of axioms for order dependencies is sound and complete.

Efficient Discovery of Approximate Order Dependencies

This work presents an algorithm for validating approximate ODs with significantly improved runtime performance over existing methods for AODs, and proves that it is correct and has optimal runtime.

Fast Incremental Discovery of Pointwise Order Dependencies

This paper proposes a novel indexing technique and presents an effective algorithm for computing ΔΣ, based on Σ and identified violations caused by Δ D, and shows that this approach outperforms the batch approach that computes from scratch, up to orders of magnitude.

Efficient Bidirectional Order Dependency Discovery

This paper presents carefully designed data structures, a host of algorithms and optimizations, for efficient order dependency discovery, and proves that its approach significantly outperforms state-of-the-art techniques, by orders of magnitude.

Erratum for Discovering Order Dependencies through Order Compatibility (EDBT 2019)

The authors claim to prove that their OD discovery algorithm, OCDDISCOVER, is complete, as well as being significantly more efficient in practice than the state-of-the-art, but this rebuttal shows that their claim of completeness is not true.

The Sat 4 j library , release 2 . 2 system description

  • 2010