Hugegraph中RDF到属性图的转换

E. Haihong, Penghao Han, Meina Song
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引用次数: 2

摘要

图数据中的数据形式分为RDF和属性图。RDF出现得更早,但它通常更大,数据也更冗余。在属性图中,图由属性、节点和边定义。在边上设置属性更容易,更有利于图的描述,因此将RDF图转换为属性图具有重要的研究意义。但是,由于RDF和属性图的结构天然不同,将RDF转换为属性图需要在保证节点唯一性的同时解决节点和属性的区分、在单标签图数据库中支持多个标签和空标签等困难。本文通过对各种序列化数据的分析,提出了一种具体的映射机制来解决第一个问题。通过附加字段存储节点标签信息的方法,我们成功解决了第二个问题。最后,通过对特定数据集的实验验证,我们发现转换后的数据量减少了10% ~ 20%左右,能够成功完成不同场景下的查询需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transforming RDF to Property Graph in Hugegraph
The data form in the graph data is divided into RDF and property graph. RDF appeared earlier, but it is generally larger and the data is more redundant. In the property graph, a graph is defined by properties, nodes and edges. It is easier to set property to the edges, which is more helpful for the description of the graph, so it is of great research significance to transform RDF graph to property graph. However, because the structure of RDF and property graph are naturally different, transforming RDF to property graph needs to solve the distinction of nodes and properties while ensuring the uniqueness of the nodes, supporting multiple labels and empty labels in a single-label graph database and other difficulties. In this paper, through analyzing a variety of serialized data, we proposed a specific mapping mechanism to solve the first issue. Through the method of storing the label information of the node with additional fields, we have successfully solved the second issue. Finally, through experimental verification of a specific dataset, we found that the converted data volume was reduced by about 10% to 20%, and it can successfully complete the query requirements in different scenarios.
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