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Horizontal fragmentation for fuzzy querying databases

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Abstract

Fuzzy querying is one of the main research topics of database investigators. Several research works to date focused on building fuzzy data models, fuzzy query languages, and fuzzy database systems. However, such systems turn out to be less efficient when it comes to querying very large data. Therefore, improving the performance of such database systems is an important research issue. In this paper, we address this issue by proposing a complete fragmentation methodology. Especially, we propose an horizontal fragmentation algorithm as well as different query execution strategies whose aim is minimizing the number of fragment accesses. Extensive experimental evaluation demonstrates the efficiency of our framework scaling up to millions of tuples.

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Notes

  1. https://github.com/postgresqlf/PostgreSQL_f.

  2. https://archive.ics.uci.edu/ml/datasets/pima+indians+diabetes.

  3. The results of the other frequent and non-frequent queries follow similar trends as the reported ones.

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Authors and Affiliations

  1. Laboratory of LITIO, Université Oran 1 Ahmed Ben Bella, 31000, Oran, Algeria

    Asmaa Drissi & Safia Nait-Bahloul

  2. CNRS, LIRIS, Université Claude Bernard Lyon 1, University of Lyon, 69622, Villeurbanne, France

    Karim Benouaret & Djamal Benslimane

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  1. Asmaa Drissi
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  2. Safia Nait-Bahloul
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Correspondence to Karim Benouaret.

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Drissi, A., Nait-Bahloul, S., Benouaret, K. et al. Horizontal fragmentation for fuzzy querying databases. Distrib Parallel Databases 37, 441–468 (2019). https://doi.org/10.1007/s10619-018-7250-4

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