Optimizing SPARQL queries over decentralized knowledge graphs

IF 3 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Semantic Web Pub Date : 2023-06-22 DOI:10.3233/sw-233438

Christian Aebeloe, Gabriela Montoya, K. Hose

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引用次数: 1

Abstract

While the Web of Data in principle offers access to a wide range of interlinked data, the architecture of the Semantic Web today relies mostly on the data providers to maintain access to their data through SPARQL endpoints. Several studies, however, have shown that such endpoints often experience downtime, meaning that the data they maintain becomes inaccessible. While decentralized systems based on Peer-to-Peer (P2P) technology have previously shown to increase the availability of knowledge graphs, even when a large proportion of the nodes fail, processing queries in such a setup can be an expensive task since data necessary to answer a single query might be distributed over multiple nodes. In this paper, we therefore propose an approach to optimizing SPARQL queries over decentralized knowledge graphs, called Lothbrok. While there are potentially many aspects to consider when optimizing such queries, we focus on three aspects: cardinality estimation, locality awareness, and data fragmentation. We empirically show that Lothbrok is able to achieve significantly faster query processing performance compared to the state of the art when processing challenging queries as well as when the network is under high load.

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优化分散知识图上的SPARQL查询

虽然数据Web原则上提供了对广泛的互连数据的访问，但语义Web的体系结构目前主要依赖于数据提供者通过SPARQL端点维护对其数据的访问。然而，一些研究表明，这样的端点经常经历停机，这意味着它们维护的数据变得不可访问。虽然基于点对点(P2P)技术的去中心化系统以前已经证明可以提高知识图的可用性，但即使在大部分节点失败的情况下，在这种设置中处理查询可能是一项昂贵的任务，因为回答单个查询所需的数据可能分布在多个节点上。因此，在本文中，我们提出了一种方法来优化分散知识图上的SPARQL查询，称为Lothbrok。虽然在优化此类查询时可能有许多方面需要考虑，但我们主要关注三个方面:基数估计、位置感知和数据碎片。我们的经验表明，在处理具有挑战性的查询以及网络处于高负载状态时，与现有的查询处理性能相比，Lothbrok能够实现更快的查询处理性能。

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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来源期刊

Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

8.30

自引率

6.70%

发文量

期刊介绍： The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.