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Improving Query Evaluation with Approximate Functional Dependency Based Decompositions

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Advances in Databases (BNCOD 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2405))

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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.

All authors were supported by NSF Grant IIS-0082407.

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Giannella, C.M., Dalkilic, M.M., Groth, D.P., Robertson, E.L. (2002). Improving Query Evaluation with Approximate Functional Dependency Based Decompositions. In: Eaglestone, B., North, S., Poulovassilis, A. (eds) Advances in Databases. BNCOD 2002. Lecture Notes in Computer Science, vol 2405. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45495-0_3

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  • DOI: https://doi.org/10.1007/3-540-45495-0_3

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