Towards Mining Frequent Queries in Star Schemes

Jen, Tao-Yuan; Laurent, Dominique; Spyratos, Nicolas; Sy, Oumar

doi:10.1007/11733492_7

Cited by 6 publications

(11 citation statements)

References 8 publications

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“…To end this section, we emphasize that, to the best of our knowledge, this work along with that of [11], is the first attempt to consider explicitly constraints on the data set, such as functional dependencies, for optimizing the computation of frequent queries.…”

Section: Related Workmentioning

confidence: 99%

“…In our previous work [11], we consider the particular case of a database in which relations are organized according to a star schema. In this setting, frequent selection-projection queries are mined from the associated weak instance ( [14]).…”

Section: Related Workmentioning

confidence: 99%

“…In this setting, frequent selection-projection queries are mined from the associated weak instance ( [14]). However, in [11], equivalence classes are defined based on projection only, and thus, only projection queries can be mined through one run of the proposed level-wise algorithm. Therefore, the present work can be seen as a generalization of [11], because in the present paper, we consider (i) equivalence classes for projection-selection queries, and (ii) any set of functional dependencies (not only those associated to star schemas).…”

Section: Related Workmentioning

confidence: 99%

“…Regarding possible extensions of the present approach, we plan to investigate the following issues: First, the case of a database consisting of several tables, instead of a single table, will be considered as done in [11], i.e., under the weak instance semantics that allows to represent a database as a single table ([14]). Second, extending the selection conditions to equalities of the form Y = Y ′ where Y and Y ′ are two relation schemas, as done in [8], is another point that we plan to investigate in the context of the present work.…”

Section: Conclusion and Further Workmentioning

confidence: 99%

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Mining all frequent projection-selection queries from a relational table

Jen

Laurent

Spyratos

2008

Proceedings of the 11th International Conference on Extending Database Technology: Advances in Database Technology

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In this paper we study the problem of mining all frequent queries in a given database table, a problem known to be intractable even for conjunctive queries. We restrict our attention to projection-selection queries, and we assume that the table to be mined satisfies a set of functional dependencies. Under these assumptions we define a pre-ordering over queries and we show the following: (a) the support measure is anti-monotonic (with respect to ), and (b) if we define q ≡ q ′ iff q q ′ and q ′ q then all queries of an equivalence class have the same support.With these results at hand, we further restrict our attention to star schemas of data warehouses. In those schemas, the set of functional dependencies satisfies an important property, namely, the union of keys of all dimension tables is a key for the fact table. The main contribution of this paper is the proposal of a level-wise algorithm for mining all frequent projection-selection queries in a data warehouse over a star schema. Moreover, we show that, in the case of a star schema, the complexity in the number of scans of our algorithm is similar to that of the well known Apriori algorithm, i.e., linear with respect to the number of attributes.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Conclusion and Further Workmentioning

confidence: 99%

See 2 more Smart Citations

Mining all frequent projection-selection queries from a relational table

Jen

Laurent

Spyratos

2008

Proceedings of the 11th International Conference on Extending Database Technology: Advances in Database Technology

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“…This problem has attracted significant attention in the last few years [4,5,6,7,8,9,11,12,15]. As argued in [8], mining all frequent conjunctive queries from a given Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.…”

Section: Introductionmentioning

confidence: 99%

Mining frequent conjunctive queries in star schemas

Jen¹,

Laurent²,

Spyratos³

2009

Proceedings of the 2009 International Database Engineering &Amp; Applications Symposium on - IDEAS '09

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An Efficient Computation of Frequent Queries in a Star Schema

Dieng

Jen

Laurent

2010

Lecture Notes in Computer Science

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Although the problem of computing frequent queries in relational databases is known to be intractable, it has been argued in our previous work that using functional and inclusion dependencies, computing frequent conjunctive queries becomes feasible for databases operating over a star schema. However, the implementation considered in this previous work showed severe limitations for large fact tables. The main contribution of this paper is to overcome these limitations using appropriate auxiliary tables. We thus introduce a novel algorithm, called Frequent Query Finder (FQF), and we report on experiments showing that our algorithm allows for an effective and efficient computation of frequent queries.

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Towards Mining Frequent Queries in Star Schemes

Cited by 6 publications

References 8 publications

Mining all frequent projection-selection queries from a relational table

Mining all frequent projection-selection queries from a relational table

Mining frequent conjunctive queries in star schemas

An Efficient Computation of Frequent Queries in a Star Schema

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