I have a ragged user hierarchy,with a custom internal hierarchy within the dimension, called [Dim User].[User Hierarchy] which is based on a denormalised Level1, Level2, Level3, Level4, Level5. What I want is that the user hierarchy is collapsed based on a condition that the user type of a descendant of user type SHOP.
What I have done is created a drill through action, with this condition :
IIF([Dim User Balance].[User Type Key].CurrentMember IS
descendants({[Dim User Type].[UserTypeIdHierarchy].&[9]},0,self), TRUE, FALSE)
However when I try to access the drill through action, I cannot seem to find it anywhere? What am I missing? Or maybe is there anyway better to do this?
When trying to do this with mdx, this query is leaving out members :
SELECT
{
[Measures].[Measure]
} ON 0, non empty {
FILTER (
{[Dim User].[User Hierarchy].[Level1].allmembers }
,[Dim User].[User Hierarchy].CurrentMember.Children.Count > 1
)
} ON 1
from [cube]
And when doing it like this:
SELECT
{
[Measures].[comp money in]
} ON columns,{
descendants( [Dim User].[UserHierarchy].children,0,self) *
descendants([Dim User].[UserTypeIdHierarchy].&[9],0,self)}
on rows
from [activities]
It is excluding the descendants of the user hierarchy in the measures, which is not what I want. I want all figures still to be aggregated. It is what I display on my Y axis that I am concerned of. I want it focused on specific user types, which are descending from 9.
Related
I have the following MDX statement on the $Monitoring cube:
WITH
MEMBER [Measures].[Unique Users] AS distinctcount(([User].[User].[User L].members
, [Measures].[Open Report Count])),format_string="#,#0"
SELECT
NON EMPTY { {[Measures].[Unique Users],[Measures].[Open Report Count]} } ON COLUMNS,
NON EMPTY { [Time].[Time].[Day L] } ON ROWS
FROM ( SELECT
{ lag(strtomember("[Time].[Time].["+right("0"+str(day(SchemaRefreshTime())),2) +"-"+ right("0"+str(month(SchemaRefreshTime())),2) + "-"+str(year(SchemaRefreshTime()))+ "]"), 6):strtomember("[Time].[Time].["+right("0"+str(day(SchemaRefreshTime())),2) +"-"+ right("0"+str(month(SchemaRefreshTime())),2) + "-"+str(year(SchemaRefreshTime()))+ "]") } ON 0 FROM [$Monitoring])
/*ic3navigation*/
axis 1 NON EMPTY order(nonempty(Descendants([Report].[Report], ,leaves),[Open Report Count]),[Open Report Count],desc)
FILTERBY /*ic3*/ {[Time].[Time].[ALL].&[2015].&[2015-11-27].&[27-11-2015]}
FILTERBY /*ic3*/ {[User].[User].[All Users].&[<user>]}
*) change <user> with the actual user name
*) the ...lag.. formula is used to give the last 7 days based on schema refresh time
***) this MDX query can be run on any $Monitoring cube if you have filled in an existing user
I would expect the distinctcount function to take into account the FILTERBY. So the result should be 1 (there is just one user selected). The strange thing is, that it does not. It shows more than one user, so I assume the FILTERBY on users is not taken into account for the distinctcount.
The same thing happens when I move the FILTER BY to the AXIS or to the ROWS or COLUMNS.
Is this a bug or is this something how MDX/ MDX++ works in icCube?
Please advise.
It's the expected behaviour. Welcome to advanced MDX !
A FilterBy is exactly the same as a sub-select.
Members are not filtered by a subselect or a where clause in a calculated members.
In a calculated member, a tuple that defines a hierarchy will 'overwrite' the one defined in a subquery or where clause.
------ UPDATE ------
If you want to filter the set with the where clause/subselect you've the EXISTING operator.
MEMBER [Measures].[Unique Users] AS count( Existing [User].[User].[User L].members),format_string="#,#0"
if you want only users with data for the cell tuple :
MEMBER [Measures].[Unique Users] AS count( nonempty( Existing [User].[User].[User L].members, [Measures].[Open Report Count])),format_string="#,#0"
If you've a large number of users I'd advise adding a measure [Distinct Users] that is a distinct count on the user id. This way you avoid all complexity that we're facing here.
Short question:
Any idea how I can pull the name from one dimension entry and apply it to another as filter?
Long description: My cube has has dimensions for manufacturer and seller, and I only need sales for "themselves". The dimensions are loaded from distinct tables in the source but have entries with the exact same name.
Manufacturer Seller
A A *
A D
B B *
C C *
C A
C D
A, B and C sell their products themselves, A and C also sell through reseller D. C also sells through A. I'd like to filter for the marked rows only (names matching).
In SQL this would be simple, or the cube might be easily enhanced to flag "own sales", but both options are not available. I need to query the cube "as is".
I tried using STRTOMEMBER and CURRENTMEMBER like so (with NAME and MEMBER_NAME):
STRTOMEMBER("[Dim Seller].[Seller].[" + [Dim Producer].[Producer].CURRENTMEMBER.NAME + "]
That actually works, syntactically, but CURRENTMEMBER seems to always evaluate to ALL and delivers the (correct) measure value for the ALL element yet not the one for matching name.
I also tried to create a WHERE setting the two names equal
[Dim Seller].[Seller].CURRENTMEMBER.NAME = [Dim Producer].[Producer].CURRENTMEMBER.NAME
but that is very SQL and not valid in MDX.
The whole query looks like this:
SELECT
NON EMPTY {
[Measures].[Value]
} ON COLUMNS
, NON EMPTY { (
{
[Dim Producer].[Producer].[A]
, [Dim Producer].[Producer].[B]
, [Dim Producer].[Producer].[C]
}
* [Dim Seller].[Seller].[Seller].ALLMEMBERS
// This line needs to be trimmed to same name as producer
) } ON ROWS
FROM
[Cube]
The producer list is coming from a config file and string-concatenated to the query and subject to change. Having a second seller list to be kept in sync would be a burden but also (when C sells through A) deliver wrong results.
Any idea how I can pull the name from one dimension entry and apply it to another?
The HAVING clause might help you:
SELECT
NON EMPTY {
[Measures].[Value]
} ON COLUMNS
, NON EMPTY {
{
[Dim Producer].[Producer].[A]
, [Dim Producer].[Producer].[B]
, [Dim Producer].[Producer].[C]
}
* [Dim Seller].[Seller].[Seller].ALLMEMBERS
}
HAVING
[Dim Seller].[Seller].CURRENTMEMBER.MEMBER_NAME =
[Dim Producer].[Producer].CURRENTMEMBER.MEMBER_NAME
ON ROWS
FROM
[Cube]
Use the GENERATE function to do the job for you.
with set Producers as
{[Dim Producer].[Producer].[A]
,[Dim Producer].[Producer].[B]
,[Dim Producer].[Producer].[C]}
set Sellers as
[Dim Seller].[Seller].members
//For every producer, get the seller who shares the same name.
set ProducersHavingSameNameAsSellers as
GENERATE(Producers, GENERATE(Sellers, filter
(Sellers,
[Dim Seller].[Seller].CURRENTMEMBER.MEMBER_NAME =
[Dim Producer].[Producer].CURRENTMEMBER.MEMBER_NAME
)
)
)
SELECT
NON EMPTY [Measures].[Value] ON COLUMNS,
ProducersHavingSameNameAsSellers ON ROWS
FROM [Cube]
The following script gives exactly the result I want.
It feels like a hack as I've added the custom members VALUE and VALUE_MTD onto the hierarchy [Customer].[Country]. I've chosen this hierarchy arbitrarily - just not used [Measures] or [Date].[Calendar] as they are already in use.
Is there a more standard approach to returning exactly the same set of cells?
WITH
MEMBER [Customer].[Country].[VALUE] AS
Aggregate([Customer].[Country].[(All)].MEMBERS)
MEMBER [Customer].[Country].[VALUE_MTD] AS
Aggregate
(
PeriodsToDate
(
[Date].[Calendar].[Month]
,[Date].[Calendar].CurrentMember
)
,[Customer].[Country].[VALUE]
)
SELECT
{
[Customer].[Country].[VALUE]
,[Customer].[Country].[VALUE_MTD]
} ON 0
,NON EMPTY
{
[Measures].[Internet Sales Amount]
,[Measures].[Internet Order Quantity]
}
*
Descendants
(
{
[Date].[Calendar].[Month].&[2007]&[12]
:
[Date].[Calendar].[Month].&[2008]&[01]
}
,[Date].[Calendar].[Date]
) ON 1
FROM [Adventure Works];
The standard approach is called utility dimension. If you Google this term, you will find several descriptions of this approach. A "utility dimension" is one which does not reference any data, but is just added to the cube for the purpose of being able to cross join them with all other dimensions for calculations. You can have one or more of them.
Thus, in most cases, physically there is nothing in the dimension. It is just used for calculated members. (Depending on the implementation, you may have the attribute members defined physically, if you want to have some properties for them. But then, only the default member is referenced in the star schema from the fact tables. The attribute member values are then overwritten in the calculation script.)
Typical applications for this are time calculations like YTD, MTD, MAT (Moving Annual Total, i. e. a full year of data ending in the selected date), or comparisons like growth vs. a previous period.
I've faced a issue with MDX query, that I don't know how to workaround. I have following query:
SELECT
{
[Measures].[Cost],
[Measures].[Non additive]
} ON COLUMNS,
NON EMPTY
{
[Organization].[Organization Name].[Organization Name].MEMBERS
*[Time].[Month].[Month].MEMBERS
*[Region].[City].[City].MEMBERS
} ON ROWS
FROM [Cube]
And I would like to display "[Measures].[Non additive]" not at the lowest grouping level, but at the Organization Level. Is it possible?
Thanks for any help.
When I have a measure I don't walways want to display, I make a copy of it and include a test for the level of the current cell.
WITH MEMBER [Measures].[My New Measure Name]
AS 'IIF(IsLeaf([Organization].currentMember), NULL, [Measures].[Non additive])'
SELECT
{
[Measures].[Cost],
[Measures].[My New Measure Name]
} ON COLUMNS,
NON EMPTY
{
[Organization].[Organization Name].[Organization Name].MEMBERS
*[Time].[Month].[Month].MEMBERS
*[Region].[City].[City].MEMBERS
} ON ROWS
FROM [Cube]
The new measure tests whether the Organisation member is at the leaf level (the bottom of the hierarchy). If so it returns blank. If not, it returns the value of the old measure.
If you want more control, test if [Organisation].level = [Organisation].levels(1) and vary the number to detect which level you want (lower levels are higher numbers).
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]