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Structural Decomposition Methods: Key Notions and Database Applications

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A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years

Part of the book series: Studies in Big Data ((SBD,volume 31))

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Abstract

Many difficult problems that are tractable when restricted to acyclic instances are good candidates to be solved efficiently whenever their structure is not precisely acyclic, but not far from that. This is the case for fundamental database problems such as answering conjunctive queries or counting the number of answers (without actually computing them). The chapter describes structural decomposition methods that guarantee tractability for all such problem instances whose associated hypergraphs have a small degree of cyclicity, called width. In particular, it focuses on the notion of hypertree width, by describing its properties and its applications to the database field, and covering queries with aggregate operators and some recent parallel and distributed implementations.

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Notes

  1. 1.

    Some notions strongly related to the treewidth appeared even before the 80’s in the literature. For a detailed story, we refer to [16].

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Acknowledgements

The work was supported by project “Ba2Know (Business Analytics to Know) Service Innovation - LAB”, No. PON03PE_00001_1 funded by the Italian Ministry of University and Research (MIUR), and by project “Smarter Solutions in the Big Data World (S2BDW)”, funded by the Italian Ministry for Economic Development (MISE) within the programme PON “Imprese e competitivitá” 2014–2020.

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  1. University of Calabria, 87036, Rende, Italy

    G. Greco, N. Leone, F. Scarcello & G. Terracina

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  1. G. Greco
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Correspondence to G. Greco .

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  1. University of Calabria, Rende, Italy

    Sergio Flesca

  2. University of Calabria, Rende, Italy

    Sergio Greco

  3. ICAR-CNR, Rende, Italy

    Elio Masciari

  4. University of Calabria, Rende, Italy

    Domenico Saccà

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Greco, G., Leone, N., Scarcello, F., Terracina, G. (2018). Structural Decomposition Methods: Key Notions and Database Applications. In: Flesca, S., Greco, S., Masciari, E., Saccà, D. (eds) A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years. Studies in Big Data, vol 31. Springer, Cham. https://doi.org/10.1007/978-3-319-61893-7_15

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