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Similarity queries: their conceptual evaluation, transformations, and processing

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Abstract

Many application scenarios can significantly benefit from the identification and processing of similarities in the data. Even though some work has been done to extend the semantics of some operators, for example join and selection, to be aware of data similarities, there has not been much study on the role and implementation of similarity-aware operations as first-class database operators. Furthermore, very little work has addressed the problem of evaluating and optimizing queries that combine several similarity operations. The focus of this paper is the study of similarity queries that contain one or multiple first-class similarity database operators such as Similarity Selection, Similarity Join, and Similarity Group-by. Particularly, we analyze the implementation techniques of several similarity operators, introduce a consistent and comprehensive conceptual evaluation model for similarity queries, and present a rich set of transformation rules to extend cost-based query optimization to the case of similarity queries.

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Acknowledgments

Walid G. Aref’s research was partially supported by the National Science Foundation under Grants III-1117766, IIS-0964639, and IIS-0811954.

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Authors and Affiliations

  1. Arizona State University, Phoenix, AZ, USA

    Yasin N. Silva & Spencer S. Pearson

  2. Purdue University, West Lafayette, IN, USA

    Walid G. Aref

  3. Microsoft Research, Redmond, WA, USA

    Per-Ake Larson

  4. Microsoft Corporation, Redmond, WA, USA

    Mohamed H. Ali

Authors
  1. Yasin N. Silva
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  2. Walid G. Aref
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  3. Per-Ake Larson
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  4. Spencer S. Pearson
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  5. Mohamed H. Ali
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Corresponding author

Correspondence to Yasin N. Silva.

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Supplementary material 1 (PDF 712 KB)

Appendix: Similarity-aware transformation rules

Appendix: Similarity-aware transformation rules

See Table 4.

Table 4 Transformation rules for similarity-aware operators—instances of generic rules
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Silva, Y.N., Aref, W.G., Larson, PA. et al. Similarity queries: their conceptual evaluation, transformations, and processing. The VLDB Journal 22, 395–420 (2013). https://doi.org/10.1007/s00778-012-0296-4

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