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作 者:Mickaël Martin Nevot Sébastien Nedjar Lotfi Lakhal Mickaël Martin Nevot;Sébastien Nedjar;Lotfi Lakhal(Laboratoire d’Informatique et Système CRNS UMR 7020, Aix-Marseille Université, Marseille, France)
机构地区:[1]Laboratoire d’Informatique et Système CRNS UMR 7020, Aix-Marseille Université, Marseille, France
出 处:《Journal of Computer and Communications》2023年第6期43-72,共30页电脑和通信(英文)
摘 要:Many approaches have been proposed to pre-compute data cubes in order to efficiently respond to OLAP queries in data warehouses. However, few have proposed solutions integrating all of the possible outcomes, and it is this idea that leads the integration of hierarchical dimensions into these responses. To meet this need, we propose, in this paper, a complete redefinition of the framework and the formal definition of traditional database analysis through the prism of hierarchical dimensions. After characterizing the hierarchical data cube lattice, we introduce the hierarchical data cube and its most concise reduced representation, the closed hierarchical data cube. It offers compact replication so as to optimize storage space by removing redundancies of strongly correlated data. Such data are typical of data warehouses, and in particular in video games, our field of study and experimentation, where hierarchical dimension attributes are widely represented.Many approaches have been proposed to pre-compute data cubes in order to efficiently respond to OLAP queries in data warehouses. However, few have proposed solutions integrating all of the possible outcomes, and it is this idea that leads the integration of hierarchical dimensions into these responses. To meet this need, we propose, in this paper, a complete redefinition of the framework and the formal definition of traditional database analysis through the prism of hierarchical dimensions. After characterizing the hierarchical data cube lattice, we introduce the hierarchical data cube and its most concise reduced representation, the closed hierarchical data cube. It offers compact replication so as to optimize storage space by removing redundancies of strongly correlated data. Such data are typical of data warehouses, and in particular in video games, our field of study and experimentation, where hierarchical dimension attributes are widely represented.
关 键 词:ROLAP Cubing Data Warehouse Datacube Big Data Business Intelligence Hierarchical Cube Hierarchical Dimensions
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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