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]
;
Related
In our MDX Queries, we use a template like the following WITH MEMBER . SELECT SUBSET . FROM (SELECT . FROM .) a lot.
What this particular query should do (and does!) is list all product variants matching a filter, and give the sales amount for it for a month in time. On the same row, we have the sales total of all variants of this product.
We need only a subset of the result (for paging), and the results need to ordered to allow paging of course. Then there is a non empty, so only product variants that were sold in the time period qualify.
This works just fine. Paging also works: putting 30, 60, 90 for Start in SUBSET is gives the correct results.
However, if I put a 1 as Count (SUBSET(..., x, 1)) the result of the "Price all" goes to (null) for each and any row I select with x. If I return two or more rows it works just fine, and all rows have their correct values.
Two results and the correct value in the rightmost column (in case you are wondering how the total of all variants, 67, can be lower than the sales of one particular variant (280): I picked a bad example - there was a return (so a negative sale) for another variant of this product, for 213. The 67 is correct and desired!)
One Row and a (null) result
I do not understand how or why the SUBSET count would interfere with the Tuple I select in the WITH MEMBER. If it does it for 30 rows at a time, why not for one?
*edit
I just tried, what would happen if I filter in a way that only one result matches (and SUBSET paging is set to "working values" of 0, 30): The same as in the 2nd screenshot, for one result row the WITH MEMBER evaluates to (null).
So it is not that SUBSET is the problem, but more general: When there is only one result row!
Could this be a bug in our SQL Server Version? It is SQL 2012 with SP4 and all latest security patches.
WITH
MEMBER [DIM Date].[HI Year_Month_Day].[CURRENT_MONTH] AS
[DIM Date].[HI Year_Month_Day].&[20201215].Parent /* Select Month of December */
MEMBER [MEASURES].[Price all] AS (
(
[DIM Products].[HI Products].Currentmember.Parent
, [DIM Products].[HI Subproduct].[Total]
)
, [MEASURES].[Price]
), FORMAT_STRING = '#,0' /* Get the parent product total next to every subproduct */
SELECT {
([DIM Datum].[HI Year_Month_Day].[CURRENT_MONTH], [MEASURES].[Price])
, ([DIM Datum].[HI Year_Month_Day].[CURRENT_MONTH], [MEASURES].[Price All])
} ON COLUMNS
, {
SUBSET(
ORDER(
NONEMPTY(
([DIM Products].[HI Produt Subproduct].[Subproduct])
, {([DIM Date].[HI Year_Month_Day].[CURRENT_MONTH], [MEASURES].[Price])}
)
, ([DIM Date].[HI Year_Month_Day].[CURRENT_MONTH], [MEASURES].[Price])
, BDESC
)
, 0
, 30
)
} ON ROWS
FROM (
SELECT
{[DIM StoreLocation].[HI Country].[Country].&[US]}
* {[DIM Productgroup].[HI Productgroup].[Productgroup].&[Bikes]}
ON COLUMNS
FROM [Cube]
)
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.
This query gives me sales of one store:
select
[measures].[sales] on 0
from [MyCube]
where [store].[store].[042]
However, if I move the slicer to inside of the subquery, it gives me sales of all stores.
select
[measures].[sales] on 0
from (select
from [MyCube]
where [store].[store].[042]
)
How to understand the mechanisms behind this difference?
This is also noted in this article, but without much explanation.
----EDIT----:
I tried various things and read around for a while. I'd like to add a question: is there a scenario in which the where clause in sub-select does filter the result?
This query gives me sales of all stores in state MI (store [042] belongs to MI):
select
[measures].[sales] on 0
from (select
[store].[state].[MI] on 0
from [myCube]
where [store].[store].[042]
)
Thinking of 'inner query only filters if the filtered dimension is returned on an axis', the theory is proved wrong if I do this:
select
[measures].[sales] on 0
from (select
[store].[state].members on 0
from [myCube]
where [store].[store].[042]
)
The sub-select still returns one state MI, but the outer query returns sales of all stores (of all states).
----EDIT 4/13----:
Re-phrasing the question in AdventureWorks cube with screenshot.
Query 1: sales of one store
Query 2: it returns sales of all stores if where clause is in the sub-select.
Query 3: the two answers I got suggested that we select the dimension in an axis - here is the result - we get all cities.
select
[measures].[sales] on 0
from (select
from [MyCube]
where [store].[store].[042]
)
The above query reduces the scope of stores just to the member [042]. Make note that sub-select is executed before the actual select. So, when it comes to the select, the engine just sees a cube which has all the members in all the dimensions; but only the member [store].[store].[042] in the store dimension. It's as if the cube has been kept intact every where else but sliced off on the Store dimension.
If you go a step ahead and add the store on to one of the axes, like
select
[measures].[sales] on 0,
[store].[store].members on 1
from (select
from [MyCube]
where [store].[store].[042]
)
you would see that although the member [All] appears in the output, it actually is just comprised of only one store.
In essence, the [All] is a special member which is calculated with respect to scope of the cube. It reflects the combined effect of all the members in the cube.
In SQL terms, it is similar to:
select sales, store as [All] from
(select sales, store from tbl where store = '042') tbl
Even though you see Sales----All, it is but a reflection of sales for store [042]
Here are some other good references concerning sub-select and slicer debate:
http://bisherryli.com/2013/02/08/mdx-25-slicer-or-sub-cube/
https://cwebbbi.wordpress.com/2014/04/07/free-video-on-subselects-in-mdx/
Chris Webb's video being located here:
https://projectbotticelli.com/knowledge/what-is-a-subselect-mdx-video-tutorial?pk_campaign=tt2014cwb
This should still leave an All member:
SELECT
[measures].[sales] ON 0
FROM
(
SELECT
FROM [MyCube]
WHERE
[store].[store].[042]
);
...but the member [All] of the Store hierarchy will only now be made up of [store].[store].[042].
You can see this by adding the Store hierarchy onto ROWS:
SELECT
[measures].[sales] ON 0,
[store].MEMBERS ON 1
FROM
(
SELECT
FROM [MyCube]
WHERE
[store].[store].[042]
);
This is the AdvWorks version similar to the reference in your question:
SELECT
{[Measures].[Order Count]} ON 0
,[Subcategory].MEMBERS ON 1
FROM
(
SELECT
{
[Subcategory].[Subcategory].&[22]
} ON 0
FROM [Adventure Works]
);
It returns the member from the sub-select and the All member adjusted to take account of the subselect:
In the references article why is the [All] less than the sum of the other two - this is not down to the subselect but is in connection with the measure that he has chosen [Measures].[Order Count] which is a distinct count. If you take away the subselect you see exactly the same behaviour of the All member being less than the sum of the other subcategory members (I've marked the point at which the total of the parts becomes higher than the All member):
SELECT
{[Measures].[Order Count]} ON 0
,Order
(
[Subcategory].MEMBERS
,[Measures].[Order Count]
,bdesc
) ON 1
FROM [Adventure Works];
Order Count: on 1 order there might be several Product Subcategories - hence this behaviour.
Edit
This query of yours:
select
[measures].[sales] on 0
from (select
[store].[state].members on 0
from TestCube //<< added this!
where [store].[store].[042]
)
This inner script is not valid? Using the same dimension on an axes and the WHERE clause is not valid:
select
[store].[state].members on 0
from TestCube
where [store].[store].[042]
Edit2
An mdx script returns a cube, which may be sliced or not sliced, but nevertheless it returns a cube. The WHERE clause is used to slice the cube that is returned. If we were using a third party tool then the dimension added to the WHERE clause would go into a combobox - with say Cliffside selected. BUT the user could effectively select Ballard from that combobox - it is just a slicer. The WHERE clause is not changing the cube that is returned by the mdx script, it is just affecting what is displayed in the cellset.
WHERE is valid within a subselect. It is part of the definition:
https://msdn.microsoft.com/en-us/library/ff487138.aspx
I've never found a use case for a subselect's WHERE clause.
Edit3
This link will explain things:
https://social.msdn.microsoft.com/Forums/sqlserver/en-US/ccb66ac3-0f9a-4261-8ccc-b6ecc51b6f07/is-where-clause-pointless-inside-a-subselect?forum=sqlanalysisservices
As Darren gosbell says in the answer to this question:
https://msdn.microsoft.com/en-us/library/ff487138.aspx it says that:
The WHERE clause does not filter the subspace.
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.
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]