分布式RDF數(shù)據(jù)管理綜述
[Abstract]:Resource description Framework (resource description framework,RDF), as a model for displaying, sharing and connecting data on the network, has been widely used in a variety of applications. At the same time, as a structured query language, SPARQL (simple protocol and RDF query language) is used to support query retrieval of RDF data. With the increasing scale of RDF data, SPARQL query processing on the existing RDF database has exceeded the ability of single machine processing. Therefore, people need to design a high-performance distributed RDF database to support efficient processing of SPARQL queries. At present, a lot of work has been done to discuss how to build a distributed RDF data management system. This paper summarizes these different distributed RDF data management methods, and divides the existing distributed RDF data management methods into three categories: distributed RDF data management methods based on cloud computing platform, and distributed RDF data management methods based on cloud computing platform. Distributed RDF data management method and federated system based on data partition. The distributed RDF data management method based on cloud computing platform makes use of the existing cloud platform to manage the RDF data. The distributed RDF data management method based on data partition firstly divides the RDF data graph into several sub-graphs and then allocates these sub-graphs to different computing nodes. The characteristic of federated system is that the data is distributed on different nodes, and the data management system can not control the distribution of data. In the introduction of each kind of distributed RDF data management methods, it will be discussed in depth to help readers understand the characteristics of various methods.
【作者單位】: 北京大學(xué)計算機(jī)科學(xué)技術(shù)研究所;湖南大學(xué)信息科學(xué)與工程學(xué)院;
【基金】:國家自然科學(xué)基金優(yōu)秀青年科學(xué)基金項目(61622201)~~
【分類號】:TP311.13
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