共查询到18条相似文献,搜索用时 296 毫秒
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随着语义Web的发展,越来越多的RDF数据发布到Web上,需要一个可以提供存储和查询功能的数据管理系统来对海量的RDF数据进行管理。针对上述问题,设计并实现了一种大规模RDF语义数据的分布式存储方案。该方案通过RDF数据装载和预处理,可以有效地管理海量的RDF数据,并通过构建索引可以有效地对大规模RDF数据进行查询。工作包括底层的RDF存储方案的设计与实现,数据的预处理与装载。同时,设计了一系列实验来评估和对比不同节点数目的Cassandra集群之间的性能,数据采用的是从DBpedia获得的13 million行RDF的数据集。实验结果显示,方案对大规模RDF语义数据的存储和查询具有性能优势。 相似文献
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随着语义网的快速发展,为了实现科学数据的共享,越来越多的科学数据被加工发布为关联数据,进而应用于关联查询和关联发现。针对大规模关联数据的管理,本文通过构建 RDF 数据库集群来存储海量数据,设计了基于 SPARQL 端点的联合查询系统来解决用户跨机器透明查询的问题,分析了存储策略和联合查询系统的查询处理相关技术。实际运行表明,本平台易于集成使用,可以实现大规模 RDF 数据的可扩展性存储和有效查询。 相似文献
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资源描述框架(RDF)/资源描述框架模式(RDFS)是语义互联网架构中的技术。尽管XML/RDF数据库正迅速的发展,关系型数据库仍是目前企业级应用的首选。针对如何有效地把RDFS数据存储在关系数据库中,充分利用现有的数据库资源来管理RDFS数据,提出了一种RDB中基于RDFS的语义本体存储技术,实现了RDFS本体抽取,提出了RDFS本体的存储优化方案,提高了数据存储访问效率。 相似文献
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资源描述框架(RDF)是W3C推荐的元数据标准,它提供了资源表示的通用框架.RDF提出的框架是面向机器可理解的,是实现语义Web的关键技术.如何实现RDF数据的高效存储是Web应用程序间语义互操作的基础.本文研究了基于关系数据库的RDF存储结构,分析比较了三种存储结构的特点,并提出了进一步优化的方案. 相似文献
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模糊本体被广泛用来描述语义Web上的模糊信息。如何对模糊本体进行有效的存储,逐渐成为语义Web领域一个重要的研究课题。鉴于关系数据库在数据组织与管理方面的优势,提出基于关系数据库的模糊本体的存储方法。首先,通过对RDF数据类型进行模糊扩展,给出模糊本体中模糊数据类型的表示方法;然后,提出了基于关系数据库的模糊本体的存储模式以及模糊本体的结构和实例在关系数据库中的存储方法;最后,证明了该存储方法的正确性。基于关系数据库的模糊本体的存储方法为语义Web中模糊数据的存储和管理提供了一个有效的解决方案。 相似文献
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RDF查询语言到SQL语言的转换原理及其实现方法 总被引:2,自引:0,他引:2
RDF查询语言的优点是具有语义性,缺点是对于海量信息的存储和查找的效率都很低.而关系数据库对海量信息的存储和查找的效率皆很高,但是其查询语言SQL却缺乏语义信息.为了使信息查询既有RDF的语义性又有关系数据库的高性能,提出将RDF查询语言到SQL语言的转换原理,并在此基础上实现一个对用户透明的、建立在关系数据库之上的RDF查询引擎.其优点是:可以利用关系数据库来存储和查询RDF信息,提高其海量存储和查找效率;对存储在不同的关系数据库中的关系数据,能够利用RDF的查找特性进行异质数据库之间的信息交换及信息融合. 相似文献
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吕艳辉 《计算机工程与应用》2012,48(20):87-90,111
随着语义Web的快速发展,如何使用RDF来描述万维网上的数据以方便语义Web的应用成为一项重要的研究课题。鉴于大部分数据都保存在关系数据库中,设计并实现了一个面向关系数据库的RDF映射系统。给出了关系数据库到RDF数据模型的映射方法,在此基础上,介绍了映射系统的实现过程。实验结果表明,映射系统能够完整地表示关系数据库的模式、数据以及隐含的语义信息。 相似文献
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The Semantic Web’s promise of web-wide data integration requires the inclusion of legacy relational databases,1 i.e. the execution of SPARQL queries on RDF representation of the legacy relational data. We explore a hypothesis: existing commercial relational databases already subsume the algorithms and optimizations needed to support effective SPARQL execution on existing relationally stored data. The experiment is embodied in a system, Ultrawrap, that encodes a logical representation of the database as an RDF graph using SQL views and a simple syntactic translation of SPARQL queries to SQL queries on those views. Thus, in the course of executing a SPARQL query, the SQL optimizer uses the SQL views that represent a mapping of relational data to RDF, and optimizes its execution. In contrast, related research is predicated on incorporating optimizing transforms as part of the SPARQL to SQL translation, and/or executing some of the queries outside the underlying SQL environment.Ultrawrap is evaluated using two existing benchmark suites that derive their RDF data from relational data through a Relational Database to RDF (RDB2RDF) Direct Mapping and repeated for each of the three major relational database management systems. Empirical analysis reveals two existing relational query optimizations that, if applied to the SQL produced from a simple syntactic translations of SPARQL queries (with bound predicate arguments) to SQL, consistently yield query execution time that is comparable to that of SQL queries written directly for the relational representation of the data. The analysis further reveals the two optimizations are not uniquely required to achieve a successful wrapper system. The evidence suggests effective wrappers will be those that are designed to complement the optimizer of the target database. 相似文献
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François Goasdoué Konstantinos Karanasos Yannis Katsis Julien Leblay Ioana Manolescu Stamatis Zampetakis 《The VLDB Journal The International Journal on Very Large Data Bases》2013,22(5):589-613
Since the beginning of the Semantic Web initiative, significant efforts have been invested in finding efficient ways to publish, store, and query metadata on the Web. RDF and SPARQL have become the standard data model and query language, respectively, to describe resources on the Web. Large amounts of RDF data are now available either as stand-alone datasets or as metadata over semi-structured (typically XML) documents. The ability to apply RDF annotations over XML data emphasizes the need to represent and query data and metadata simultaneously. We propose XR, a novel hybrid data model capturing the structural aspects of XML data and the semantics of RDF, also enabling us to reason about XML data. Our model is general enough to describe pure XML or RDF datasets, as well as RDF-annotated XML data, where any XML node can act as a resource. This data model comes with the XRQ query language that combines features of both XQuery and SPARQL. To demonstrate the feasibility of this hybrid XML-RDF data management setting, and to validate its interest, we have developed an XR platform on top of well-known data management systems for XML and RDF. In particular, the platform features several XRQ query processing algorithms, whose performance is experimentally compared. 相似文献
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Daniel J. Abadi Adam Marcus Samuel R. Madden Kate Hollenbach 《The VLDB Journal The International Journal on Very Large Data Bases》2009,18(2):385-406
Efficient management of RDF data is an important prerequisite for realizing the Semantic Web vision. Performance and scalability
issues are becoming increasingly pressing as Semantic Web technology is applied to real-world applications. In this paper,
we examine the reasons why current data management solutions for RDF data scale poorly, and explore the fundamental scalability
limitations of these approaches. We review the state of the art for improving performance of RDF databases and consider a
recent suggestion, “property tables”. We then discuss practically and empirically why this solution has undesirable features.
As an improvement, we propose an alternative solution: vertically partitioning the RDF data. We compare the performance of
vertical partitioning with prior art on queries generated by a Web-based RDF browser over a large-scale (more than 50 million
triples) catalog of library data. Our results show that a vertically partitioned schema achieves similar performance to the
property table technique while being much simpler to design. Further, if a column-oriented DBMS (a database architected specially
for the vertically partitioned case) is used instead of a row-oriented DBMS, another order of magnitude performance improvement
is observed, with query times dropping from minutes to several seconds. Encouraged by these results, we describe the architecture
of SW-Store, a new DBMS we are actively building that implements these techniques to achieve high performance RDF data management. 相似文献