arXiv cs/07011552007-01-25cs.DB

数据立方体：一种通用分组、交叉制表和子合计的关系聚合运算符

Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals

Jim Gray, Surajit Chaudhuri, Adam Bosworth, Andrew Layman, Don Reichart, Murali Venkatrao, Frank Pellow, Hamid Pirahesh

发表信息：: Data Mining and Knowledge Discovery 1(1): 29-53 (1997)

摘要：

数据分析应用程序通常跨多个维度聚合数据，以寻找异常或不寻常的模式。SQL聚合函数和GROUP BY运算符生成零维或一维聚合。应用需要这些算子的N维推广。本文定义了该操作符，称为数据立方体或简单的立方体。cube运算符概括了大多数报表编写器中的直方图、交叉制表、上滚、下钻和小计结构。新颖之处在于立方体是关系。因此，立方体运算符可以嵌入到更复杂的非过程数据分析程序中。立方体运算符将N个聚合属性中的每一个都视为N空间的一个维度。一组特定属性值的集合就是这个空间中的一个点。点的集合形成N维立方体。通过将N-立方体聚合到低维空间来计算超聚集。本文（1）解释了立方体和上滚运算符，（2）说明了它们在SQL中的适用性，（3）解释了用户如何为立方体定义新的聚合函数，（4）讨论了计算立方体的有效技术。这些特性中的许多正在被添加到SQL标准中。

英文摘要：

Data analysis applications typically aggregate data across many dimensions looking for anomalies or unusual patterns. The SQL aggregate functions and the GROUP BY operator produce zero-dimensional or one-dimensional aggregates. Applications need the N-dimensional generalization of these operators. This paper defines that operator, called the data cube or simply cube. The cube operator generalizes the histogram, cross-tabulation, roll-up, drill-down, and sub-total constructs found in most report writers. The novelty is that cubes are relations. Consequently, the cube operator can be imbedded in more complex non-procedural data analysis programs. The cube operator treats each of the N aggregation attributes as a dimension of N-space. The aggregate of a particular set of attribute values is a point in this space. The set of points forms an N-dimensional cube. Super-aggregates are computed by aggregating the N-cube to lower dimensional spaces. This paper (1) explains the cube and roll-up operators, (2) shows how they fit in SQL, (3) explains how users can define new aggregate functions for cubes, and (4) discusses efficient techniques to compute the cube. Many of these features are being added to the SQL Standard.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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