摘要
随着语义网的发展,Web上越来越多的开放数据以RDF格式发布,对海量RDF的有效管理是实现语义网的一个重要条件。文中讨论并分析了现有的几种RDF数据存储方法,针对垂直划分的方法,基于列数据库MonetDB,实现了一个RDF数据管理方案。该方案将RDF和RDFS信息分开存储,并在Barton数据集上,设计了包含几种连接的基准查询,对比RDF管理系统Sesame的三元组模式,分别进行了存储空间和查询效率测试。实验结果验证了基于列数据库的垂直划分方案的有效性。
With the development of the semantic Web,the amount of RDF data published on Web is steadily growing,efficient management of RDF data is an important prerequisite for realizing the semantic Web vision. In this paper, discuss and analyze three storage modes,and implement an RDF data management uses the vertically partitioned approach for colunm-oriented database of MonetDB. The approach stores separately from RDF and RDFS, and devises four benchmark queries that cover important RDF join patterns on dataset of Barton. At last compare the performance of the data-size and query speed with Sesame using triple storing. The simulation results show the effectiveness of the proposed approach.
出处
《计算机技术与发展》
2012年第6期53-56,60,共5页
Computer Technology and Development
基金
国家高技术研究发展计划"863"项目(2009AA01Z40)
