mdx - 使用 MDX 查询组合不同的层次结构级别

Question

一、说明

现在我有两个 mdx 查询，唯一的区别是 ON ROWS 设置。这是每个查询及其结果。

查询 1：

SELECT

NON EMPTY
{
  [PLOwner].[PLOwner].Members
}
ON ROWS
,
NON EMPTY
Crossjoin(
  {
    [InfoType].[InfoType].[Risk_RecoveryJTDTable],
    [InfoType].[InfoType].[Equivalent_Notional],
    [InfoType].[InfoType].[Risk_SPC],
    [InfoType].[InfoType].[Risk_PSM],
    [InfoType].[InfoType].[Risk_PV10],
    [InfoType].[InfoType].[Notional],
    [InfoType].[InfoType].[Notional_IMM],
    [InfoType].[InfoType].[PnL],
    [InfoType].[InfoType].[TomorrowPnL],
    [InfoType].[InfoType].[RollPnL],
    [InfoType].[InfoType].[RollDownPnL],
    [InfoType].[InfoType].[Risk_JTD],
    [InfoType].[InfoType].[Risk_Raw_KC],
    [InfoType].[InfoType].[Risk_RR],
    [InfoType].[InfoType].[FundingPnLWCOF],
    [InfoType].[InfoType].[FundingPnLRR],
    [InfoType].[InfoType].[FundingPnLSHW],
    [InfoType].[InfoType].[FundingPnLBox],
    [InfoType].[InfoType].[FundingPnLInterest]
  }
  ,
  {
    DrillDownLevel([Category].[ALL].[AllMember])
  }
  ,
  {
    DrillDownLevel([Label1].[ALL].[AllMember])
  }
  ,
  {
    DrillDownLevel([IsError].[ALL].[AllMember])
  }
)
ON COLUMNS

FROM
  [UnityRiskCube]

WHERE
(
  [Measures].[Risk.SUM],
  [BusinessGroup].[BusinessGroup].[AeJ Flow Credit],
  [Context].[ContextId].[official:Live]
)

结果 1：（我使用 Excel 显示来自 Pivot 的 String[][] 结果）

结果 一键查看图片

查询 2：

SELECT

NON EMPTY
Crossjoin(
  {
    [PLOwner].[PLOwner].Members
  }
  ,
  {
    [PLGroup].[PLGroup].Members
  }
)
ON ROWS
,
NON EMPTY
Crossjoin(
  {
    [InfoType].[InfoType].[Risk_RecoveryJTDTable],
    [InfoType].[InfoType].[Equivalent_Notional],
    [InfoType].[InfoType].[Risk_SPC],
    [InfoType].[InfoType].[Risk_PSM],
    [InfoType].[InfoType].[Risk_PV10],
    [InfoType].[InfoType].[Notional],
    [InfoType].[InfoType].[Notional_IMM],
    [InfoType].[InfoType].[PnL],
    [InfoType].[InfoType].[TomorrowPnL],
    [InfoType].[InfoType].[RollPnL],
    [InfoType].[InfoType].[RollDownPnL],
    [InfoType].[InfoType].[Risk_JTD],
    [InfoType].[InfoType].[Risk_Raw_KC],
    [InfoType].[InfoType].[Risk_RR],
    [InfoType].[InfoType].[FundingPnLWCOF],
    [InfoType].[InfoType].[FundingPnLRR],
    [InfoType].[InfoType].[FundingPnLSHW],
    [InfoType].[InfoType].[FundingPnLBox],
    [InfoType].[InfoType].[FundingPnLInterest]
  }
  ,
  {
    DrillDownLevel([Category].[ALL].[AllMember])
  }
  ,
  {
    DrillDownLevel([Label1].[ALL].[AllMember])
  }
  ,
  {
    DrillDownLevel([IsError].[ALL].[AllMember])
  }
)
ON COLUMNS

FROM
  [UnityRiskCube]

WHERE
(
  [Measures].[Risk.SUM],
  [BusinessGroup].[BusinessGroup].[AeJ Flow Credit],
  [Context].[ContextId].[official:Live]
)

结果 2：（我使用 Excel 显示来自 Pivot 的 String[][] 结果）

结果 2-单击查看图像

2.问题

如何使用一个 Mdx 查询将这些数据汇总在一起？非常感谢。

Answer 1

我认为您可以使用层次结构的ALL成员PLGroup来进行组合-您别无选择，因为两者都需要相同的维度：

SELECT

NON EMPTY
{
  [PLOwner].[PLOwner].Members
 *[PLGroup].[PLGroup].[All] //<< or this may be [PLGroup].[All]
,
  [PLOwner].[PLOwner].Members
 *[PLGroup].[PLGroup].Members
}
ON ROWS
,
NON EMPTY
Crossjoin(
  {
    [InfoType].[InfoType].[Risk_RecoveryJTDTable],
    [InfoType].[InfoType].[Equivalent_Notional],
    [InfoType].[InfoType].[Risk_SPC],
    [InfoType].[InfoType].[Risk_PSM],
    [InfoType].[InfoType].[Risk_PV10],
    [InfoType].[InfoType].[Notional],
    [InfoType].[InfoType].[Notional_IMM],
    [InfoType].[InfoType].[PnL],
    [InfoType].[InfoType].[TomorrowPnL],
    [InfoType].[InfoType].[RollPnL],
    [InfoType].[InfoType].[RollDownPnL],
    [InfoType].[InfoType].[Risk_JTD],
    [InfoType].[InfoType].[Risk_Raw_KC],
    [InfoType].[InfoType].[Risk_RR],
    [InfoType].[InfoType].[FundingPnLWCOF],
    [InfoType].[InfoType].[FundingPnLRR],
    [InfoType].[InfoType].[FundingPnLSHW],
    [InfoType].[InfoType].[FundingPnLBox],
    [InfoType].[InfoType].[FundingPnLInterest]
  }
  ,
  {
    DrillDownLevel([Category].[ALL].[AllMember])
  }
  ,
  {
    DrillDownLevel([Label1].[ALL].[AllMember])
  }
  ,
  {
    DrillDownLevel([IsError].[ALL].[AllMember])
  }
)
ON COLUMNS

FROM
  [UnityRiskCube]

WHERE
(
  [Measures].[Risk.SUM],
  [BusinessGroup].[BusinessGroup].[AeJ Flow Credit],
  [Context].[ContextId].[official:Live]
)