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An Approach for Schema Extraction of NoSQL Graph Databases

机译:NoSQL图形数据库的模式提取方法

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Currently, a large volume of heterogeneous data is generated and consumed by several classes of applications, which raise a new family of database models called NoSQL. NoSQL graph databases is a member of this family. They provide high scalability and are schemaless, i.e., they do not require an implicit schema such as relational databases. However, the knowledge of how data is structured may be of great importance for data integration or data analysis processes. There are some works in the literature that extract the schema from graph structures or graph-based data sources. Different from them, this work proposes a comprehensive approach that consider all the common NoSQL database graph data model concepts, and generates a schema in the recent JSON Schema recommendation. Experimental evaluations show that our solution generates a suitable schema representation with a linear complexity.
机译:当前,数种应用程序生成并使用了大量的异构数据,这产生了一个新的数据库模型家族,即NoSQL。 NoSQL图形数据库是该家族的成员。它们提供了高可伸缩性并且是无模式的,即,它们不需要诸如关系数据库之类的隐式模式。但是,有关如何构造数据的知识对于数据集成或数据分析过程可能非常重要。文献中有一些工作可以从图结构或基于图的数据源中提取模式。与它们不同的是,这项工作提出了一种综合方法,该方法考虑了所有常见的NoSQL数据库图数据模型概念,并在最近的JSON Schema建议中生成了一个模式。实验评估表明,我们的解决方案可以生成具有线性复杂度的合适模式表示。

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