Building an efficient RDF store over a relational database

Mihaela A. Bornea, Julian T Dolby, Anastasios Kementsietsidis, Kavitha Srinivas, Patrick Dantressangle, O. Udrea, Bishwaranjan Bhattacharjee
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引用次数: 233

Abstract

Efficient storage and querying of RDF data is of increasing importance, due to the increased popularity and widespread acceptance of RDF on the web and in the enterprise. In this paper, we describe a novel storage and query mechanism for RDF which works on top of existing relational representations. Reliance on relational representations of RDF means that one can take advantage of 35+ years of research on efficient storage and querying, industrial-strength transaction support, locking, security, etc. However, there are significant challenges in storing RDF in relational, which include data sparsity and schema variability. We describe novel mechanisms to shred RDF into relational, and novel query translation techniques to maximize the advantages of this shredded representation. We show that these mechanisms result in consistently good performance across multiple RDF benchmarks, even when compared with current state-of-the-art stores. This work provides the basis for RDF support in DB2 v.10.1.
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在关系数据库上构建高效的RDF存储
由于RDF在web和企业中的日益普及和广泛接受,RDF数据的高效存储和查询变得越来越重要。在本文中,我们描述了一种新的RDF存储和查询机制,该机制工作在现有的关系表示之上。对RDF的关系表示的依赖意味着可以利用35年以上在高效存储和查询、行业级事务支持、锁定、安全性等方面的研究成果。然而,在关系中存储RDF存在重大挑战,其中包括数据稀疏性和模式可变性。我们描述了将RDF分解为关系的新机制,以及将这种分解表示的优势最大化的新查询翻译技术。我们展示了这些机制可以在多个RDF基准测试中获得一致的良好性能,即使与当前最先进的存储进行比较也是如此。这项工作为DB2 v.10.1中的RDF支持奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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