【文件属性】:
文件名称:Data Cube: A Relational Aggregation Operator
文件大小:153KB
文件格式:PDF
更新时间:2018-03-25 01:27:07
数据库论文
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Abstract: Data analysis applications typically aggregate
data across many dimensions looking for unusual patterns.
The SQL aggregate functions and the GROUP BY operator
produce zero-dimensional or one-dimensional answers.
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
cube 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. Aggregation points are represented by an "infinite
value", ALL. For example, the point (ALL,ALL,ALL,...,ALL, sum(*)) would represent the global sum of all items. Each ALL value actually represents the set of values contributing to that aggregation.