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RMCC: A ROLAP data model of minimal condensed Cube

机译:RMCC:最小冷凝立方体的ROLAP数据模型

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摘要

Data cubes facilitate online analytical processing( OLAP) systems greatly. Ever since the Cube-by operator was introduced by Jim Gray in 1997, techniques for computing, compressing and efficiently accessing data cubes have been substantially studied due to the enormous storage size as the number of dimensions and dimension cardinalities increase. Minimal condensed cube, one of these data cube compressing schemes, was proposed and shown to be very effective especially for the environment of RDBMSs. Although efforts on fast computation and incremental update algorithms of Minimal condensed cube has been made by researchers, a totally RDBMS based data storage model has not been investigated, which is a key issue in data cube implementation. In this paper, we proposed RMCC(relational Minimal condensed cube), a pure ROLAP-based data model for the storage structure of Minimal condensed cube. We model RMCC not only to further reduce the storage cost of Minimal condensed cube, but also that queries can be answered efficiently by mature relational database engines. We proposed a SQL framework for answering OLAP queries over RMCC by the stored procedure/function technique supported by SQL:2003.
机译:数据立方体极大地方便了联机分析处理(OLAP)系统。自1997年Jim Gray引入Cube-by运算符以来,由于随着维数和维数基数的增加,存储空间巨大,因此对计算,压缩和有效访问数据多维数据集的技术也进行了大量研究。提出了最小压缩立方体(这些数据立方体压缩方案之一),并且显示出非常有效的效果,特别是对于RDBMS的环境。尽管研究人员已努力研究最小精简立方体的快速计算和增量更新算法,但尚未研究完全基于RDBMS的数据存储模型,这是实现数据立方体的关键问题。在本文中,我们提出了RMCC(关系最小精简立方体),这是一种基于ROLAP的纯数据模型,用于最小精简立方体的存储结构。我们对RMCC进行建模,不仅可以进一步降低最小精简多维数据集的存储成本,而且可以通过成熟的关系数据库引擎有效地回答查询。我们提出了一个SQL框架,该框架通过SQL:2003支持的存储过程/函数技术来通过RMCC回答OLAP查询。

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