FedQPL:一种基于RDF数据源异构联合的逻辑查询计划语言

Sijin Cheng, O. Hartig
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引用次数: 8

摘要

在查询无法单独从一个数据源获得的答案和见解时,RDF数据源的联合提供了巨大的潜力。规划在这样一个联合上执行查询的一个挑战是,就联合成员提供的数据访问接口的类型而言,联合可能是异构的。这一挑战在文献中没有得到太多关注。本文为旨在解决这一挑战的未来方法提供了坚实的正式基础。我们的主要概念贡献是一种表示查询执行计划的形式化语言;此外,我们还确定了该语言的一个片段,该片段可用于捕获为给定查询的不同部分选择相关数据源的结果。作为技术贡献,我们展示了这个片段比现有的源选择方法所支持的更具表现力,这有效地突出了这些方法的固有局限性。此外,我们证明了源选择问题是np困难的,并且在σP2范围内,我们提供了一套广泛的重写规则,可以作为查询优化的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FedQPL: A Language for Logical Query Plans over Heterogeneous Federations of RDF Data Sources
Federations of RDF data sources provide great potential when queried for answers and insights that cannot be obtained from one data source alone. A challenge for planning the execution of queries over such a federation is that the federation may be heterogeneous in terms of the types of data access interfaces provided by the federation members. This challenge has not received much attention in the literature. This paper provides a solid formal foundation for future approaches that aim to address this challenge. Our main conceptual contribution is a formal language for representing query execution plans; additionally, we identify a fragment of this language that can be used to capture the result of selecting relevant data sources for different parts of a given query. As technical contributions, we show that this fragment is more expressive than what is supported by existing source selection approaches, which effectively highlights an inherent limitation of these approaches. Moreover, we show that the source selection problem is NP-hard and in σP2, and we provide an extensive set of rewriting rules that can be used as a basis for query optimization.
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