Mining frequent conjunctive queries using functional and inclusion dependencies

  • Authors:
  • Cheikh Tidiane Dieng;Tao-Yuan Jen;Dominique Laurent;Nicolas Spyratos

  • Affiliations:
  • ETIS, CNRS, ENSEA, Université de Cergy Pontoise, Cergy-Pontoise, France 95000 and Laboratoire d'Analyse Numérique et Informatique, Université Gaston-Berger, Saint-Louis, Senegal;ETIS, CNRS, ENSEA, Université de Cergy Pontoise, Cergy-Pontoise, France 95000;ETIS, CNRS, ENSEA, Université de Cergy Pontoise, Cergy-Pontoise, France 95000;LRI, CNRS, Université de Paris Sud, Orsay Cedex, France 91405

  • Venue:
  • The VLDB Journal — The International Journal on Very Large Data Bases
  • Year:
  • 2013

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Abstract

We address the issue of mining frequent conjunctive queries in a relational database, a problem known to be intractable even for conjunctive queries over a single table. In this article, we show that mining frequent projection-selection-join queries becomes tractable if joins are performed along keys and foreign keys, in a database satisfying functional and inclusion dependencies, under certain restrictions. We note that these restrictions cover most practical cases, including databases operating over star schemas, snow-flake schemas and constellation schemas. In our approach, we define an equivalence relation over queries using a pre-ordering with respect to which the support is shown to be anti-monotonic. We propose a level-wise algorithm for computing all frequent queries by exploiting the fact that equivalent queries have the same support. We report on experiments showing that, in our context, mining frequent projection-selection-join queries is indeed tractable, even for large data sets.