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Improving Query Evaluation with Approximate Functional Dependency Based Decompositions

  • Chris M. Giannella
  • Mehmet M. Dalkilic
  • Dennis P. Groth
  • Edward L. Robertson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2405)

Abstract

We investigate how relational restructuring may be used to improve query performance. Our approach parallels recent research extending semantic query optimization (SQO), which uses knowledge about the instance to achieve more efficient query processing. Our approach differs, however, in that the instance does not govern whether the optimization may be applied; rather, the instance governs whether the optimization yields more efficient query processing. It also differs in that it involves an explicit decomposition of the relation instance. We use approximate functional dependencies as the conceptual basis for this decomposition and develop query rewriting techniques to exploit it. We present experimental results leading to a characterization of a well-defined class of queries for which improved processing time is observed.

Keywords

Functional Dependency Soft Constraint Query Evaluation Query Optimization Relation Symbol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Chris M. Giannella
    • 1
  • Mehmet M. Dalkilic
    • 2
  • Dennis P. Groth
    • 2
  • Edward L. Robertson
    • 1
  1. 1.Department of Computer ScienceIndiana University BloomingtonUSA
  2. 2.School of InformaticsIndiana Univeristy BloomingtonUSA

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