我需要过滤这个 MDX 结果集

I need to filter this MDX result set

我希望过滤下面的结果集,这样我只显示维度 A 值 1 的计数为 1 的结果,而不管维度 A 值 2 的计数值如何

           Dimension A Value 1     Dimension A Value 2
Entity ID   Count                Count
11              1   
78          1   
90          1   
101         1   
114                                1
118         1   
125         1   
134                                    1
140         1   
161         1   
169         1   
186         1                  2

过滤后的集合看起来像

    Dimension A Value 1 Dimension A Value 2
Entity ID   Count               Count
11           1  
78           1  
90           1  
101          1  
118          1  
125          1  
140          1  
161          1  
169          1  
186          1                 2

mdx 是

WITH
SET [~COLUMNS] AS
    {[Dimension A].[Dimension A].[Value 1], [Dimension A].[Dimension A].[Value 2]}
SET [~ROWS] AS
    {[Entity].[Entity].[Entity ID].Members}
SELECT
NON EMPTY CrossJoin([~COLUMNS], {[Measures].[Count]}) ON COLUMNS,
NON EMPTY [~ROWS] ON ROWS
FROM [My Cube]

我一直在玩弄 Filter 和 NonEmpty,但我是 MDX 的新手,我的 sql 脑袋很疼。我想这对于拥有大量 MDX 的人来说可能是微不足道的,但我失败了。温柔一点这是我的第一个问题

您的查询应该像

Select ([Dimension A].[AttributeHierarchy1].[AttributeHierarchy1],{[Measures].[Value1],[Measures].[Value2]}) on columns,

filter([Dimension B].[EntityID].[EntityID],[Measures].[Value1]=0)
on rows 
from yourcube

但是可能会有问题。例如,您的尺寸有两个值 A 和 B,对于特定行,A,value1 = 1 但 B,Value1 = 0,此行将显示为 A qulifyes for it and B gets carried over.

编辑

举个例子,我想查看销售额超过 150 美元的 Bottles and Cages 的 Internet Sales

我的初始查询

select 
([Product].[Subcategory].[Subcategory],[Measures].[Internet Sales Amount]
)
on columns,
[Customer].[City].[City]
on rows 
from 
[Adventure Works]

结果

现在修改查询

select 
([Product].[Subcategory].[Subcategory],[Measures].[Internet Sales Amount]
)
on columns,

filter
(
[Customer].[City].[City], [Measures].[Internet Sales Amount]>150
)
on rows 
from 
(select [Product].[Subcategory].&[28] on 0 from [Adventure Works])

结果

您可以尝试使用 HAVING 子句:

WITH
SET [~COLUMNS] AS
    {
      [Dimension A].[Dimension A].[Value 1], 
      [Dimension A].[Dimension A].[Value 2]
    } 
MEMBER [Measures].[CountValue1] AS   //<<<<this is new <<<<<<<<<<<<<<<<<<<<<<<<<<<<<
    (
       [Measures].[Count],
       [Dimension A].[Dimension A].[Value 1]
    )
SELECT
NON EMPTY 
  CrossJoin(
    [~COLUMNS]
  , {[Measures].[Count]}
  ) ON COLUMNS,
NON EMPTY 
  [Entity].[Entity].[Entity ID].MEMBERS 
  HAVING [Measures].[CountValue1] = 1    //<<CHANGED TO NEW MEASURE
  ON ROWS
FROM [My Cube];

如果您可以使用 HAVING 而不是 FILTER,您可能会看到性能提升 - 特别是当您的脚本变得更复杂时:
https://blog.crossjoin.co.uk/2006/01/04/the-having-clause/

为了完整起见,较慢的 FILTER 版本应该是这样的:

WITH
SET [~COLUMNS] AS
    {
      [Dimension A].[Dimension A].[Value 1], 
      [Dimension A].[Dimension A].[Value 2]
    } 
//>>>>>> following is new >>>>>>>>>>>>>>>>>>>>>
MEMBER [Measures].[CountValueNEW] AS   
    (
       [Measures].[Count],
       [Dimension A].[Dimension A].[Value 1]
    )
SELECT
NON EMPTY 
    [~COLUMNS]
   *{[Measures].[Count]}
ON 0,
NON EMPTY 
FILTER(
  [Entity].[Entity].[Entity ID].MEMBERS,
  [Measures].[CountValueNEW] = 1 
)  
ON 1
FROM [My Cube];