在RDF数据库中更新正则表达式索引的有效算法。

Pub Date : 2015-01-01 DOI:10.1504/ijdmb.2015.066767
Jinsoo Lee, Romans Kasperovics, Wook-Shin Han, Jeong-Hoon Lee, Min Soo Kim, Hune Cho
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引用次数: 1

摘要

资源描述框架(RDF)被广泛用于生物医学数据的共享,如基因本体或在线蛋白质数据库UniProt。SPARQL是RDF的一种本地查询语言,在查询中提供正则表达式,而这些正则表达式的准确值要么是不相关的,要么是未知的。在SPARQL查询处理中使用正则表达式索引可以将包含正则表达式的查询的性能提高两个数量级。在本研究中,我们解决了RDF数据库中正则表达式索引的更新操作。我们确定了直接索引更新算法的主要性能问题,并提出了一种利用正则表达式索引的独特属性来提高性能的新算法。我们的贡献可以总结如下:(1)我们为RDF数据库中的正则表达式索引提出了一种有效的更新算法,(2)我们用c++为所提出的算法构建了一个原型系统,(3)我们进行了大量的实验,证明我们的算法比直接的方法有了数量级的改进。
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An efficient algorithm for updating regular expression indexes in RDF databases.

The Resource Description Framework (RDF) is widely used for sharing biomedical data, such as gene ontology or the online protein database UniProt. SPARQL is a native query language for RDF, featuring regular expressions in queries for which exact values are either irrelevant or unknown. The use of regular expression indexes in SPARQL query processing improves the performance of queries containing regular expressions by up to two orders of magnitude. In this study, we address the update operation for regular expression indexes in RDF databases. We identify major performance problems of straightforward index update algorithms and propose a new algorithm that utilises unique properties of regular expression indexes to increase performance. Our contributions can be summarised as follows: (1) we propose an efficient update algorithm for regular expression indexes in RDF databases, (2) we build a prototype system for the proposed algorithm in C++ and (3) we conduct extensive experiments demonstrating the improvement of our algorithm over the straightforward approaches by an order of magnitude.

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