could you help me with someting please. I have an MDX query who slice my cube with a Named Set, these results are great, however I need to create a calculated measure and I have not been able to "rewrite" my where clause in the calculated expression.
This MDX works as I need:
select non empty [Measures].[Demanda Real] on 0,
non empty [Agente Distribuidor].[Nombre Distribuidor].[Nombre Distribuidor].members on 1
from Demanda
where [SkSubmercadoUsuario]
I tried to rewrite the above query and it doesn't work:
with member [Measures].[Demanda Real Nueva]
as
([Measures].[Demanda Real],[SkSubmercadoUsuario])
select [Measures].[Demanda Real Nueva] on 0,
non empty [Agente Distribuidor].[Nombre Distribuidor].[Nombre Distribuidor].members on 1
from Demanda
If I am correct, you want your measure "[Measures].[Demanda Real]" to always have a filter named set "[SkSubmercadoUsuario]". I translated your senario to adventure works. First run the create set part alone. Then the next two parts, with first part commented
create SET [Adventure Works].[testSet] AS ([Geography].[State-Province].&[NY]&[US])
Now comment the above part and run
Select [Measures].[Reseller Sales Amount]
on columns,
non empty
[Product].[Product].[Product]
on rows
from [Adventure Works]
where
[testSet]
Now run the third part
with member [Measures].[Test]
as
'('+(settostr([testSet]) ) + ',[Measures].[Reseller Sales Amount])'
Select (strtoset([Measures].[Test]))
on columns,
non empty
[Product].[Product].[Product]
on rows
from [Adventure Works]
Related
I am facing very strange issue with MDX (SSAS 2014), on which simplest calculated member is taking forever to execute. Could someone please help me to understand why i am facing this issue. If i not use calculated member everything works fast and result comes in seconds. When i remove Producer attribute, query performances well.
Below is the complete query.
WITH
MEMBER Measures.AsOfDate AS ("[Policy Effective Date].[Year-Month].[Date].&[2018-01-04T00:00:00]")
MEMBER Measures.YTDPremium AS AGGREGATE (YTD(STRTOMEMBER(Measures.AsOfDate)), [Measures].[Written Premium])
SELECT NON EMPTY
{
Measures.YTDPremium
} ON COLUMNS, NON EMPTY
{
(
[Program].[Program Name].[Program Name]
,[Insuring Company].[Insuring Company Name].[Insuring Company Name]
,[Line Of Business].[Line Of Business].[Line Of Business]
,[Producer].[Producer Name].[Producer Name]
)
} ON ROWS
FROM [Premium]
Try understand what the following part does in your query
NON EMPTY { ( [Program].[Program Name].[Program Name]
,[Insuring Company].[Insuring Company Name].[Insuring Company Name]
,[Line Of Business].[Line Of Business].[Line Of Business]
,[Producer].[Producer Name].[Producer Name]
) } ON ROWS
In the above MDX you are telling the server to take a cross product of all values of "Programs", "Line Of Business" and "Producer Name". So lets say you have 4 values of programs , 3 values of line of business and 2 values of producer name. The total combinations are 4*3*2=24
Now the "Non empty" removes any combinations that are not present in your dataset. This is done by removing all rows that have "Null" value in column value.
Your measure is returning value irrespective if that combination exists or not. You can modify your Calculatedmeasure to return value only in the case if the combination is valid. This can be achived by checking an actual measure for that combination
Edit: based the below example is based on the comment
In the below example i am trying to get the internet sales amount categories and components
select
{ [Measures].[Internet Sales Amount] }
on columns,
(
[Product].[Category].[Category],
[Customer].[Country].[Country]
)
on rows
from [Adventure Works]
Result
Now add "Non empty" to the query and observe the results.
Results
Now lets add calculted measure that returns "hello". Notice how the non empty clause is ineffective.
Now modify the code make the calculated measure check other measures for null
with member measures.t as
case when [Measures].[Internet Sales Amount] = null then null else "hello" end
select
{ [Measures].[Internet Sales Amount] ,measures.t }
on columns,
non empty
(
[Product].[Category].[Category],
[Customer].[Country].[Country]
)
on rows
from [Adventure Works]
Result
The bottom line: Because of cross product your result is so huge that SSAS is having hard time handling it.
Can any one tell me how to get the record count that is a result of a MDX query?I have tried various methods and I haven't really got a solution for that.I am a beginner in MDX queries.
WITH
MEMBER [Measures].[amount] as
COUNT(
[your_dimension].[your_dimension_property].Members
)
SELECT {[Measures].[amount]} ON COLUMNS
FROM [your_awesome_cube]
A code like this will return to you the amount of members in your dimension, the COUNT method have this syntax
Count(Set_Expression [ , ( EXCLUDEEMPTY | INCLUDEEMPTY ) ] )
so you can do a lot of things, like filter your search
Create a measure in the cube that is a count or distinct count.
1) open the cube
2) Right click on the fact table on which that measure sits
3) Select New Measure...
4) Dropdown the list and select the aggregation
5) In the source column section, select the column you want the aggregation on (if u cant find it, click on show all columns on the bottom- this depends on what you are aggregating)
with member
Measures.Counts as
[your_dimension].[your_dimension_property].Children.COUNT
select Measures.Counts on 0
FROM [your_awesome_cube]
When you say record count, you basicly are saying the valid combinations of your row axis.
Lets take a basic example, the query returns 3637 rows, of which 1 row is parctically the column name row.
select [Measures].[Sales Amount] on columns,
(
[Customer].[Country].[Country],
[Product].[Product].[Product]
) on rows
from [Adventure Works]
Now to get the row count without running the query, lets put the combinations in count function and put the count function in a runtime measure
This Returns 3636 row.
with member [Measures].[rowCount]
as
count(([Customer].[Country].[Country],[Product].[Product].[Product]))
select [Measures].[rowCount] on columns from [Adventure Works]
Notice I have not eleminated the null combinations on rows. Lets do that next
The query returns 2101 rows , again one row from column headers.
select [Measures].[Sales Amount] on columns,
non empty
(
[Customer].[Country].[Country],
[Product].[Product].[Product]
) on rows
from [Adventure Works]
Now lets count the rows
This returns 2100 rows.
with member [Measures].[rowCount]
as
count(nonempty(( [Customer].[Country].[Country],[Product].[Product].[Product])
,{[Measures].[Sales Amount]}
))
select [Measures].[rowCount]
on columns from [Adventure Works]
Till now we had measure from just one measure group, now lets try with multiple measure groups.
select {[Measures].[Sales Amount],[Measures].[Internet Sales Amount]} on columns,
non empty
(
[Customer].[Country].[Country],
[Product].[Product].[Product]
) on rows
from [Adventure Works]
//Cell set consists of 2101 rows and 3 columns.
//Wrong way
with member [Measures].[rowCount]
as
count(nonempty(( [Customer].[Country].[Country],[Product].[Product].[Product])
,{[Measures].[Internet Sales Amount]}
))
select [Measures].[rowCount] on columns from [Adventure Works]
//935
//Right way
with member [Measures].[rowCount]
as
count(nonempty(( [Customer].[Country].[Country],[Product].[Product].[Product])
,{[Measures].[Sales Amount],[Measures].[Internet Sales Amount]}
))
select [Measures].[rowCount]
on columns from [Adventure Works]
///2100
Notice when we use just a single measure the result may not be correct . If the measure we use has a null value then the combination would be removed. Where as in our rows the other measure will ensure that the combination appears.
Now Lets add a filter to the picture.
select {[Measures].[Sales Amount],[Measures].[Internet Sales Amount]} on columns,
non empty
filter(
(
[Customer].[Country].[Country],
[Product].[Product].[Product]
)
,[Measures].[Internet Sales Amount]>5000) on rows
from [Adventure Works]
//Cell set consists of 586 rows and 3 columns.
//Wrong way
with member [Measures].[rowCount]
as
count(nonempty(( [Customer].[Country].[Country],[Product].[Product].[Product])
,{[Measures].[Sales Amount],[Measures].[Internet Sales Amount]}
))
select [Measures].[rowCount]
on columns from [Adventure Works]
//2100
//Right way
with member [Measures].[rowCount]
as
count(nonempty(
filter(([Customer].[Country].[Country],[Product].[Product].[Product]),[Measures].[Internet Sales Amount]>5000)
,{[Measures].[Sales Amount],[Measures].[Internet Sales Amount]}
))
select [Measures].[rowCount]
on columns from [Adventure Works]
///585
Again till i gave the RowCount measure the exact senario that I have on my row axis it fails.
I have a requirement displaying data from same dimension in more than 1 column. For eg. I want to show data Year and Month wise. In my dimension structure, Year and Month belongs to same hierarchy. When I run below query I get error. PFB the query.
Select NON EMPTY {[Measures].[Target Actual Value]} ON 0,
NON EMPTY {[Realization Date].[Hierarchy].[Year Name].Members *
[Realization Date].[Hierarchy].[Month Year]} ON 1
From [Cube_BCG_OLAP]
The error I get is Query (2, 12) The Hierarchy hierarchy is used more than once in the Crossjoin function. I am new to MDX queries. Please help in this regard. Thanks in advance.
Select NON EMPTY {[Measures].[Target Actual Value]} ON 0,
NON EMPTY {[Realization Date].[Hierarchy].[Year Name].Members ,
[Realization Date].[Hierarchy].[Month Year]} ON 1
From [Cube_BCG_OLAP]
Instead of CROSSJOIN have a set as above. In a set, you can put members from same hierarchy
I like Sourav's answer - but it will put the results in one column which is slightly different than the question.
In AdvWorks this is in one column:
SELECT
[State-Province].MEMBERS ON COLUMNS
,{
[Date].[Calendar].[Calendar Year].MEMBERS
,[Date].[Calendar].[Month].MEMBERS
} ON ROWS
FROM [Adventure Works];
It is possible to switch to two columns and use a cross join but you need to find out the details of your Date dimensions Attribute hierarchies (as opposed to User hierarchies):
SELECT
[State-Province].MEMBERS ON COLUMNS
,
[Calendar Year].[All Periods].Children
* [Month].MEMBERS ON ROWS
FROM [Adventure Works];
In your cube maybe something like this:
SELECT
NON EMPTY
{[Measures].[Target Actual Value]} ON 0
,NON EMPTY
[Year Name].MEMBERS
*
[Month Year].MEMBERS ON 1
FROM [Cube_BCG_OLAP];
I have three queries to filter by a member using the currentmember function. When the filter is applied to the hierarchy that has the member I want to filter by, I can match the members using the IS operator and get the correct result. It does not work though when the filtered set and the member are in different hierarchies. Yet, I can get the filtered results correctly for the second case if instead of objects comparison I just do a caption comparison. The examples use the AdventureWorks database.
This query is working as expected with the IS operator:
select non empty [Measures].[Reseller Sales Amount] on 0,
Filter (NonEmpty({[Geography].[Country].[Country].ALLMEMBERS * [Geography].[City].[City].ALLMEMBERS}), [Geography].[City].Currentmember IS [Geography].[City].&[Seattle]&[WA]) on 1
from [Adventure Works]
This one uses a caption comparison (different result, as expected)
select non empty [Measures].[Reseller Sales Amount] on 0,
Filter (NonEmpty({[Geography].[Country].[Country].ALLMEMBERS}), [Geography].[City].Currentmember.MEMBER_CAPTION = 'Seattle') on 1
from [Adventure Works]
This one though, which should produce the same result as the previous query, does not return anything:
select non empty [Measures].[Reseller Sales Amount] on 0,
Filter (NonEmpty({[Geography].[Country].[Country].ALLMEMBERS }), [Geography].[City].Currentmember IS [Geography].[City].&[Seattle]&[WA]) on 1
from [Adventure Works]
Thanks.
In fact, this is a bit strange. For me, the most surprising result is the second one. No reference in the set to be filtered to the city, and nevertheless, a filter is applied. I would think the reason for the second result is that somehow "implicit overwrite" kicks in.
And probably, the second and third case are treated differently as the optimizer somehow choses different ways to interpret the statement. Normally, string operations like the reference to caption are less efficient than the IS operator which works on object identity.
It looks like most comments confirm that the result of the second query is a bug. Some more comments here in this other thread
I'm trying to write a query to give me the total number of users for each customer per day.
Here is what I have so far, which for each customer/day combination is giving the total number of user dimension entries without splitting them up by customer/day.
WITH MEMBER [Measures].[MyUserCount]
AS COUNT(Descendants([User].CurrentMember, [User].[User Name]), INCLUDEEMPTY)
SELECT
NON EMPTY CrossJoin([Date].[Date].Members, [Customer].[Customer Name].Members) ON ROWS,
{[Measures].[MyUserCount]} on COLUMNS
FROM
[Users]
The problem with your calculated member is that [User].CurrentMember is set to the All member for every row tuple, and thus the count is the total. What you need is a way for the [Customer].CurrentMember and [Date].CurrentMember to effectively filter the [User] dimension.
You need to use a measure that makes sense, i.e. that will have a non-empty value for meaningful joins of the dimension members that you're interested in.
To find this out, you could start by running a query like this:
SELECT
NON EMPTY CrossJoin(
[User].[User Name].Members,
[Measures].[Some measuse]
) ON COLUMNS,
NON EMPTY CrossJoin(
[Date].[Date].Members,
[Customer].[Customer Name].Members
) ON ROWS
FROM [Project]
You would have selected Some measure adequately. The results of that query will be a lot of empty cells, but in a given row, the columns that do have a value correspond to the Users that are related to a given Customer x Date tuple (on the row). You want to count those columns for every row. COUNT and FILTER are what you need, then the query with the calculated member will be
WITH MEMBER [Measures].[User count] AS
COUNT(
FILTER(
[User].[User Name].Members,
NOT ISEMPTY([Measures].[Some measure])
)
)
SELECT
NON EMPTY {[Measures].[User count]} ON COLUMNS,
NON EMPTY CrossJoin(
[Date].[Date].Members,
[Customer].[Customer Name].Members
) ON ROWS
FROM [Users]
I am assuming a fair bit here, but with some experimentation you should be able to work it out.