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Using Functional Dependencies in Conversion of Relational Databases to Graph Databases

机译:在关系数据库到图形数据库的转换中使用功能依赖

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Graph database management systems are widely used in scenarios where the data are intensively connected. Handling such connected data in a relational database is not an efficient task. Converting relational databases to graph ones is one of the solutions that can empower users with handling such data using the graph model features. In this paper, we propose a new algorithm to ease such conversion and overcome the limitations of the existing algorithms. The state of the art algorithms cannot handle multiple relationships types such as unary relationships and associative entities with non-foreign key attributes. Our proposed algorithm, FD2G, leverages the existence of functional dependencies information inside the input relational database to automatically perform the conversion to property graph databases. In addition, we updated the state of the art algorithm, named R2G, to handle its limitations and be able to fairly compare both algorithms performance. We evaluated FD2G against the updated R2G algorithm where it efficiently and effectively outperformed the existing one.
机译:图形数据库管理系统广泛用于数据密集连接的场景。处理关系数据库中的此类连接数据并不是一项有效的任务。将关系数据库转换为图形数据库是可以使用户能够使用图形模型功能处理此类数据的解决方案之一。在本文中,我们提出了一种新的算法来缓解这种转换并克服现有算法的局限性。现有技术算法不能处理多种关系类型,例如一元关系和具有非外键属性的关联实体。我们提出的算法FD2G利用输入关系数据库中功能依赖项信息的存在来自动执行到属性图数据库的转换。此外,我们更新了称为R2G的最新算法,以处理其局限性,并能够公平地比较这两种算法的性能。我们根据更新后的R2G算法评估了FD2G,该算法有效地胜过了现有算法。

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