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Toward Automatic Generation of Column-Oriented NoSQL Databases in Big Data Context

机译:在大数据环境中实现面向列的NoSQL数据库的自动生成

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The growth of application architectures in all areas (e.g. Astrology, Meteorology, E-commerce, social network, etc.) has resulted in an exponential increase in data volumes, now measured in Petabytes. Managing these volumes of data has become a problem that relational databases are no longer able to handle because of the acidity properties. In response to this scaling up, new concepts have emerged such as NoSQL. In this paper, we show how to design and apply transformation rules to migrate from an SQL relational database to a Big Data solution within NoSQL. For this, we use the Model Driven Architecture (MDA) and the transformation languages like as MOF 2.0 QVT (Meta-Object Facility 2.0 Query-View-Transformation) and Acceleo which define the meta-models for the development of transformation model. The transformation rules defined in this work can generate, from the class diagram, a CQL code for creation column-oriented NoSQL database.
机译:在所有领域(例如,占星术,气象学,电子商务,社交网络等)中,应用程序体系结构的增长导致数据量呈指数级增长,目前以PB为单位。由于酸性性质,管理这些数据量已成为关系数据库无法处理的问题。为了应对这种规模扩大,出现了新概念,例如NoSQL。在本文中,我们展示了如何设计和应用转换规则以从SQL关系数据库迁移到NoSQL中的大数据解决方案。为此,我们使用模型驱动的体系结构(MDA)和诸如MOF 2.0 QVT(元对象工具2.0查询-视图-转换)和Acceleo之类的转换语言,它们定义了用于转换模型开发的元模型。这项工作中定义的转换规则可以从类图中生成CQL代码,以创建面向列的NoSQL数据库。

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