Mondrian Olap 钻取算法
我没有找到，但可能有人可以解释一下 - OLAP 立方体是所有可能聚合的组合，因此与蒙德里安相关 - 叶级别是事实表中的数据还是最小聚合（单元格）？ 谢谢。
I didn't found but may be someone could me explain - OLAP cube is a combination of all possible aggregation, so related to Mondrian - leaf level is data in fact table or it is a minimum aggregate (cell) ?
Thanks.
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级别是维度表的属性（单元格聚合度量的特征）。每个维度表都是数据立方体中的一个维度。
因此，要执行 OLAP 操作下钻，您应该增加视图的粒度。而卷起来则相反。
假设你有一个消费者维度。在这个维度中，您具有以下属性：地区、国家和城市。向下钻取操作是查看一个国家，然后查看该国家的城市。以蒙德里安为例。
汇总操作则相反，当您查看国家时，您进行汇总并看到该国家的父母。也就是说，向下钻取是在层次结构中向下进行的，而上卷则是向上进行的。
这些数据总是根据总体衡量标准来看待，在这种情况下，这可能是利润的秘诀。因此，您可以看到国家的秘诀，然后浏览城市的层次结构并查看国家，进行向下钻取和向上滚动。
访问BJIn OLAP。它执行这些 OLAP 操作并包含它们的示例。1
我希望这会有所帮助。
Level are attributes (characteristics of the cells aggregated measures) of dimension tables. Each dimension table is a dimension in the data cube.
So to perform an OLAP operation drill-down, you should increase the granularity of the view. While the roll-up the reverse.
Assuming you have a consumer dimension. In this dimension you have the following attributes: region, country and city. A drill-down operation is view a nation and you then view the cities of this nation. How does the Mondrian, for example.
The roll-up operation is the reverse, as you view the nations, you do a roll-up and see the parents of that nation. That is, the drill-down do levels down the hierarchy, while the roll-up rises.
These data are seen always in accordance with an aggregate measure, which in this case could be a recipe for profit. So you could see the recipe for the nation, and then navigate the hierarchy of cities and seeing the country, making a drill-down and roll up.
Access BJIn OLAP. It performs these OLAP operations and contains examples of them.1
I hope this helps.