相似性搜索的标准SQL方法

P. H. B. Siqueira, Paulo H. Oliveira, M. Bedo, D. S. Kaster
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摘要

本文解决了RDBMS中复杂数据的存储和检索问题,该问题依赖于度量距离函数来评估数据不相似性。然而,对于复杂数据存储策略的实证分析和相似查询操作符的合适表示的定义仍然是文献中有待解决的问题。在这里,我们将根据标准SQL中的四种结构,即关系、对象-关系、二进制和半结构化,对复杂数据存储的现有方法进行分类、实现和评估,从而弥补这些差距。此外,我们还讨论了一个复杂数据检索的综合模型,其相似运算符的概念与标准SQL表示一致。因此,提出了一种距离函数表示,使RDBMS查询处理器能够解释和执行物理相似性操作符。实验结果表明:(i)关系和对象关系结构在大多数情况下优于其他两个竞争对手,而(ii)对象关系策略可以使用更广泛的表示。
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Standard SQL Approaches for Similarity Searching
This paper addresses complex data storage and retrieval in RDBMS, which depends on metric distance functions for the assessment of data dissimilarity. However, both the empirical analysis of strategies for complex data storage and the definition of a suitable representation for similarity query operators are still open issues in the literature. Here, we fulfill those gaps through the classification, implementation, and evaluation of existing approaches for complex data storage according to four structures found in standard SQL, namely relational, object-relational, binary and semi-structured. Moreover, we also discuss a comprehensive model for complex data retrieval, whose conception of similarity operators is consistent with standard SQL representations. Accordingly, a distance function representation is presented, which enables the RDBMS query processor to interpret and execute physical similarity operators. Experimental results indicate: (i) relational and object-relational structures outperform the other two competitors in the majority of scenarios, whereas (ii) object-relational strategy enables the use of a broader representation.
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