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The cube data model : a conceptual model and algebra for on-line analytical processing in data warehouses

机译:多维数据集数据模型:用于数据仓库中的在线分析处理的概念模型和代数

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摘要

Data warehousing and On-Line Analytical Processing (OLAP) are two of the most significant new technologies in the business data processing arena. A data warehouse can be defined as a “very large” repository of historical data pertaining to an organization. OLAP refers to the technique of performing complex analysis over the information stored in a data warehouse. The complexity of queries required to support OLAP applications makes it difficult to implement using standard relational database technology. Moreover, there is currently no standard conceptual model for OLAP. There is clearly a need for such a model and an algebra as evidenced by the numerous SQL extensions offered by many vendors of OLAP products. In this paper, we address this issue by proposing a model of a data cube and an algebra to support OLAP operations on this cube. The model we present is simple and intuitive, and the algebra provides a means to concisely express complex OLAP queries.
机译:数据仓库和在线分析处理(OLAP)是业务数据处理领域中最重要的两项新技术。数据仓库可以定义为与组织有关的历史数据的“超大型”存储库。 OLAP是指对数据仓库中存储的信息执行复杂分析的技术。支持OLAP应用程序所需的查询非常复杂,因此很难使用标准的关系数据库技术来实现。而且,当前没有用于OLAP的标准概念模型。许多OLAP产品供应商提供的大量SQL扩展证明了这种模型和代数的需求。在本文中,我们通过提出一个数据多维数据集和代数模型来支持此多维数据集上的OLAP操作来解决此问题。我们提供的模型简单直观,并且代数提供了一种简洁表达复杂OLAP查询的方法。

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