I am developing a query builder application that generates MDX and trying to get customer counts from a cube using the following, which works just fine:
WITH MEMBER MEASURES.X AS (
{ [Customer].[Gender].[Female]},
[Customer].[Customer].Children
).Count
SELECT Measures.X ON 0 FROM [Adventure Works]
However, if the user drags in a dimension that is not related to the customer like:
WITH MEMBER MEASURES.X AS (
{ [Customer].[Gender].[Female]},
{ [Employee].[Status].[Active], [Employee].[Status].[Inactive]},
[Customer].[Customer].Children
).Count
SELECT Measures.X ON 0 FROM [Adventure Works]
the count result obviously becomes incorrect.
Is there a way to determine whether a dimension is related to the customer so that I can exclude it from the generated MDX query?
This information can be retrieved from the cube through AMO. The Cube class contains all the cube metadata you'll need.
Solved the problem by using the Exists( Set_Expression1 , Set_Expression2 [, MeasureGroupName] ) function. No need to manually determine which dimensions are related. The Exists function filters out the unrelated tuples, leaving only the
{ [Customer].[Customer].Children, [Customer].[Gender].[Female]} set to do the count over.
Here is the MDX:
WITH MEMBER MEASURES.X AS Exists(
[Customer].[Customer].Children,
{[Customer].[Gender].[Female]}
*
{[Employee].[Status].[Active], [Employee].[Status].[Inactive]}
).Count
SELECT Measures.X ON 0 FROM [Adventure Works]
Related
I've been working on an ExcelDNA C# xll that allows users to enter simple words (under guidance) and I construct the elaborate MDX for them to query against a remote ActivePivot cube.
During testing I've ntoticed that when filtering, the grand total disappears (presumably it's joining tuples together). How do I still get a grand total? Do I need to use SCOPE or create a calculated member?
Thanks to more advanced MDX people:
SELECT
NON EMPTY
{
[Measures].[Notional.SUM]
,[Measures].[Notional.SHORT]
,[Measures].[Notional.LONG]
} ON COLUMNS
,NON EMPTY
Hierarchize
(
Filter
(
(
[CDR].[CDR].MEMBERS
,[Book].[Book].MEMBERS
)
,
Left([Book].[Book].CurrentMember.MemberValue,2) = "22"
)
,POST
) ON ROWS
FROM [TraderCube]
WHERE
[Date].[Date].[2020-01-24];
The following is something similar against AdvWrks cube:
WITH
//>>inside the WITH clause we have moved the set
SET [FilteredSet] AS
{
Filter
(
[Reseller].[Reseller Type].[Business Type].MEMBERS
,
Left([Reseller].[Reseller Type].CurrentMember.MemberValue,2) = "sp"
OR
Left([Reseller].[Reseller Type].CurrentMember.MemberValue,2) = "VA"
)
}
//>>next we create a custom member that is the sum of the filtered set
MEMBER [Reseller].[Reseller Type].[All Visible Resellers] AS
Aggregate([FilteredSet])
SELECT
NON EMPTY
{[Measures].[Reseller Sales Amount]} ON COLUMNS
,NON EMPTY
//>> inside these curly brackets we declare a set that is the filtered set and the Total member
{
[FilteredSet]
,[Reseller].[Reseller Type].[All Visible Resellers]
} ON ROWS
FROM [Adventure Works]
WHERE
[Date].[Calendar].[Calendar Year].&[2013];
The results of the above is the following:
I am trying to learn MDX. I am an experienced SQL Developer.
I am trying to find an example of an MDX query that has more than two dimensions. Every single webpage that talks about MDX provides simple two dimensional examples link this:
select
{[Measures].[Sales Amount]} on columns,
Customer.fullname.members on rows
from [Adventure Works DW2012]
I am looking for examples that use the following aliases: PAGES (third dimension?), section (forth dimension?) and Chapter (fifth dimension?). I have tried this but I do not think it is correct:
select
{[Measures].[Sales Amount]} on columns,
Customer.fullname.members on rows,
customer.Location.[Customer Geography] as pages
from [Adventure Works DW2012]
I am trying to get this output using an MDX query (this is from AdventureWorks DW2012):
That's not a 3-dimensional resultset in your screenshot, unless there's something cropped from it.
Something like
SELECT [Geography].[Country].Members ON 0,
[Customer].[CustomerName].Members ON 1
FROM [whatever the cube is called]
WHERE [Measures].[Sales Amount]
(dimension/hierarchy/level names may not be exactly right)
would give a resultset like the one in your message.
The beyond 2nd-dimension dimensions and dimension names are not used in any client tool that I know. (Others may know different). They seem to be there in MDX so that MDX can hand >2-dimensional resultsets to clients that can handle them (e.g. an MDX subquery handing its results to the main query).
An often-used trick in MDX is to get the members of two dimensions onto one axis by cross-joining:
SELECT
{[Date].[Calendar Date].[Calendar Year].Members * [Geography].[Country].Members} ON 0,
[something else] ON 1
FROM [Cube]
How about the following - it does not send more than two dimensions back to a flat screen but it uses quite a few dimensions explicitly:
SELECT
[Measures].[Sales Amount] ON O,
[Customer].[fullname].MEMBERS ON 1
FROM
(
SELECT
[Date].[Calendar Month].[Calendar Month].&[February-2012] ON 0,
[Geography].[Country].[Country].&[Canada] ON 1,
[Product].[Product].&[Red Bike] ON 2,
[Customer].[Customer].&[foo bar] ON 3
FROM [Adventure Works DW2012]
)
I've made up the dimension | hierarchy | member combinations as I do not have access to the cube.
Also if we consider implicit dimensions then take the following:
SELECT
[Customer].[Location].[Customer Geography] ON 0,
[Customer].[fullname].[fullname].&[Aaron Flores] ON 1
FROM [Adventure Works DW2012]
WHERE
(
[Measures].[Sales Amount]
);
On the slicer I've used braces (..) which indicate a tuple, but this is actually shorthand for the following:
SELECT
[Customer].[Location].[Customer Geography] ON 0,
[Customer].[fullname].[fullname].&[Aaron Flores] ON 1
FROM [Adventure Works DW2012]
WHERE
(
[Measures].[Sales Amount]
,[Date].[Calendar Month].[Calendar Month].[All],
,[Geography].[Country].[Country].[All],
,[Product].[Product].[All]
,...
,...
....
);
The All member from every dimension in the cube could be included in this slicer without affecting the result.
So the whole nature of mdx is multi-dimensional - yes you do not get more than a 2 dimensional table returned to your screen but the way you get to that cellset could well involve many dimensions.
I want to display levels of the same hierarchy in the same axis separate entities. For example I want [Customer].[State] and [Customer].[County] to be displayed in separate columns.
I tried the following query:
select NON EMPTY
{[Customer].[State].Members * [Customer].[County].Members}
ON ROWS
from [Search]
but get Mondrian Error: Tuple contains more than one member of hierarchy.
Is possible to do what I want to do, essentially flatten the hierarchy?
i don't know if the following will work in mondrian:
SELECT
{[Measures].[Internet Sales Amount]} ON 0
,NON EMPTY
{
(
[Customer].[Gender].[Gender].MEMBERS
,[Customer].[Marital Status].[(All)]
)
,(
[Customer].[Gender].[(All)]
,[Customer].[Marital Status].[Marital Status].MEMBERS
)
} ON 1
FROM [Adventure Works];
Philip,
I am using Performance Point Dashboard Designer 2013 and SharePoint Server 2013 for building dashboards. I am using SSAS2012 for Cube.
I have a scenario similar to the one illustrated by figure below. I am required to find Previous Non-Empty value for purpose of finding Trends.
Measure: [Quota]
Dimension: [Date].[Calendar Date].[Date]
The script ([Measures].[Quota], [Date].[Calendar Date].PrevMember) gives you a previous date. Lets say for date 27-Jan-13 whose Quota value is 87, it returns 26-Jan-13 which has null value. I want it to return 21-Jan-13 that has some Quota value. And for date 21-Jan-13, I want to return 15-Jan-13.
I wonder if this is possible.
Thanks,
Merin
After long searches and hits & trials and so on, I think I invented a solution of my own for myself.
Following is the script for my Calculated Member.
(
[Quota],
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
).Item(0)
)
Explanation
The number 15 means it will look for non-empty measures up to 15 siblings.
Now we know up to how many siblings to traverse back, in this case 15.
Lets find 15 previous siblings (both empty and non-empty) excluding current member.
(LastPeriods(15, [Date].[Calendar Date].PrevMember)
Since it will yield both empty and non-empty members, lets filter out empty members in terms of measure [Quota]. If we don't specify measure here, it will use default measure whatever it is and we may not get desired result.
Nonempty(LastPeriods(15, [Date].[Calendar Date].PrevMember),[Quota])
We may have several members in the output. And we will choose the last one.
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
)
So far, the script above gives previous non-empty member. Now we want to implement this member for our measure [Quota].
Hence we get the script below ready to create a Calculated Member.
(
[Quota],
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
).Item(0)
)
You can use recursion to define this.
The following query delivers something similar for the Adventure Works cube:
WITH member [Measures].[Prev non empty] AS
IIf(IsEmpty(([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Internet Sales Amount])),
([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Prev non empty]),
([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Internet Sales Amount])
), format_String = '$#,##0.00'
SELECT {[Measures].[Internet Sales Amount], [Measures].[Prev non empty]}
ON COLUMNS,
non empty
Descendants([Date].[Calendar].[Month].&[2007]&[12], [Date].[Calendar].[Date])
ON ROWS
FROM [Adventure Works]
WHERE [Customer].[Customer].&[12650]
You would have to replace the name of the date hierarchy, as well as the measure name from Internet Sales Amount to Quota in the recursive definition of the measure Prev non empty.
with member [Measures].[BoughtDispenser] as
Sum(Descendants([Customer].[Customer].CurrentMember, [Customer].[Customer]),
Iif(
(IsEmpty(([Item].[ItemNumber].&[011074], [Measures].[Sale Amount]))
And IsEmpty(([Item].[ItemNumber].&[011069], [Measures].[Sale Amount]))
)
Or IsEmpty([Measures].[Sale Amount]),
0 , 1
)
)
select
{[Measures].[Sale Amount]} on columns,
non empty filter([Customer].[Customer].children, [Measures].[BoughtDispenser])
* {[Item].[ItemNumber].members}
on rows
from [Sales]
where [EnteredDate].[Quarter].&[2010-01-01T00:00:00]
;
The object is to show all the items purchased by customers who also bought either of the two dispensers (011069 and 011074).
I based the calculated member on a query I found to do basket analysis. I feel like there should be a way to write it with the set {[Item].[ItemNumber].&[011074], [Item].[ItemNumber].&[011069]} instead of the two IsEmpty tests. Everything I've tried ended up having every Customer in the result.
My environment is SQL Server Analysis Services 2005.
Yes I can! It just required a slightly different approach to the calculated member:
with member [Measures].[BoughtDispenser] as
Sum(Descendants([Customer].[Customer].CurrentMember, [Customer].[Customer])
* {[Item].[ItemNumber].&[011069], [Item].[ItemNumber].&[011074]},
[Measures].[Quantity Shipped]
)
select
{[Measures].[Sale Amount]} on columns,
non empty filter([Customer].[Customer].children, [Measures].[BoughtDispenser])
* {[Item].[ItemNumber].members}
on rows
from [Sales]
where [EnteredDate].[Quarter].&[2010-01-01T00:00:00]
;