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
Related
I am a beginner in MDX queries. Can any one tell me how to get the record count that is a result of a MDX query?
The query is following:
select {[Measures].[Employee Department History Count],[Measures].[Rate]} on columns, Non Empty{{Filter([Shift].[Shift ID].[Shift ID].Members, ([Shift].[Shift ID].CurrentMember.name <> "1"))}*{[Employee].[Business Entity ID].[Business Entity ID].Members}} on rows from [Adventure Works2012].
I have tried various methods and I haven't really got a solution for that.
I assume you mean row count when you talk of "record count", as MDX does not know a concept of records, but the result shown from an MDX query is the space built by the tuples on the axes.
I see two possibilities to get the row count:
Just count the rows returned from your above query in the tool from which you call the MDX query.
If you want to count in MDX, then let's state what you want to have:
You want to know the number of members of the set of non empty combinations of [Shift ID]s and [Business Entity ID]s where the Shift ID is not "1" and at least one of the measures [Employee Department History Count] and [Rate] is not null.
To state that different: Let's call the tuples like above for which the first measure is not null "SET1", and the tuples like above for which teh second measure is not null "SET2". Then you you want to know the count of the the tuples which are contained in one of these sets (or in both).
To achieve this, we define these two sets and then a calculated menber (a new measure in our case) containing this calculation in its definition, and then use this calculated member in the select clause to show it:
WITH
SET SET1 AS
NonEmpty({{Filter([Shift].[Shift ID].[Shift ID].Members,
([Shift].[Shift ID].CurrentMember.name <> "1"))}
* {[Employee].[Business Entity ID].[Business Entity ID].Members}},
{[Measures].[Employee Department History Count])
SET SET2 AS
NonEmpty({{Filter([Shift].[Shift ID].[Shift ID].Members,
([Shift].[Shift ID].CurrentMember.name <> "1"))}
* {[Employee].[Business Entity ID].[Business Entity ID].Members}},
{[Measures].[Rate])
MEMBER [Measures].[MyCalculation] AS
COUNT(SET1 + SET 2)
SELECT [Measures].[MyCalculation] ON COLUMNS
FROM [Adventure Works2012]
Please note:
The sets SET1 and SET2 are not absolutely necessary, you could also put the whole calculation in one long and complicated definition of the MyCalculation measure, but splitting it up makes is easier to read. However, the definition of a new member is necessary, as in MDX you can only put members on axes (rows, columns, ...). These members can either already been defined in the cube, or you have to define them in the WITH clause of your query. There is no such thing as putting expressions/calculations on axes in MDX, only members.
The + for sets is a union which removes duplicates, hence this operation gives us the tuples which have an non empty value for at least one of the measures. Alternatively, you could have used the Union function equivalently to the +.
The Nonempty() I used in the definitions of the sets is the NonEmpty function, which is slightly different from the NON EMPTY keyword that you can use on the axes. We use one of the measures as second argument to this function in both set definitions.
I have currently no working SSAS installation available to test my statement, hence there might be a minor error or typo in my above statement, but the idea should work.
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.
Working on a task that required to bring all a dimension’s data to the Pivot Table(Excel Sheet) even if they are not related to the fact.
first I was able to do it by using the option “PivotTable Options” -> “Display” -> “Show items with no data on rows” from Excel. The problem here is that using this option is going to affect the other dimensions and the requirement is to only this work for the Student dimension only and the user doesn’t like to keep changing the option back every time. then I found this solution using SCOPE, below, but just like above I could not find an away to just have the scope ignore the logic if any other dimension added so the data does not get duplicated.
SCOPE ([Program].[Program Hierarchy].MEMBERS, [Measures].[Number of Students]);
THIS = IIF(ISEMPTY([Measures].[Number of Students]), 0, ([Measures].[Number of Students]));
END SCOPE;
So is there something that I can add the SCOPE above to just work in the program dimension and get ignore/ skip and work as normal if any other dimension added to the pivot table?
Any suggestion will be appreciated.
Lets suppose that for Dimension1 ,attribute1, and the attribute "Value 1", you had nothing in Fact, so this is removed from the result, now you forced Excel to display it by selecting the option. When you add another dimension's attribute lets say Dimension2.Attribute1, since "Value 1" had nothing in Fact, therefore Cube will not understand which value of of Dimension2.Attribute1 is to be displayed in front of Dimension1.Attribute1, therefore it will display all its values. So if we have 3 values in Dimension2, attribute 1 then "Value 1" will be repeated three times. Now with Excel you cannot solve the issue, however it might just be possible to write an MDX query that works.
Edit: Query Added.
The below sample query is based on AdventureWorks, the first sample shows that the result has some nulls, if i un-comment the "non-empty" all null values will vanish, go ahead try it.
select [Measures].[Internet Sales Amount] on columns,
--non empty
[Product].[Subcategory].[Subcategory]
on rows
from
[Adventure Works]
Result without non empty
Now lets add another dimension to the query. Notice that the null value for the first row(Bib-shorts) is now repeated for all values of the second dimension, Since cube has no way to determine which value to display.
select [Measures].[Internet Sales Amount] on columns,
--non empty
([Product].[Subcategory].[Subcategory],[Date].[Calendar Quarter of Year].[Calendar Quarter of Year])
on rows
from
[Adventure Works]
Result
Now the above result shows the issue you are facing. What we now need to do is whenever there is a null value we dont need the individual members of the second dimension, rather a place holder to satisfy the tuple, will work.
In the query below I have two tuples
1) for the not null data-points. Here we display the actual member of the second dimension.
2) for the null data-points, here we use ".defaultmember" which basically means that the second dimension will behave as it was never selected. Have a close look at the second dimension it says "All Period"
select [Measures].[Internet Sales Amount] on columns,
--non empty
{filter(([Product].[Subcategory].[Subcategory],[Date].[Calendar Quarter of Year].[Calendar Quarter of Year]),[Measures].[Internet Sales Amount]>0),
filter(([Product].[Subcategory].[Subcategory],[Date].[Calendar Quarter of Year].defaultmember),[Measures].[Internet Sales Amount]=null)
}
on rows
from
[Adventure Works]
Result:
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 was wondering which of the following two queries is more performant?
Query 1:
SELECT NONEMPTY(CROSSJOIN({[Product].[Category].children},
{[Scenario].[Scenario].members}
)
) ON COLUMNS
FROM [Analysis Services Tutorial]
Query 2:
SELECT CROSSJOIN(NONEMPTY({[Product].[Category].children}),
NONEMPTY({[Scenario].[Scenario].members})
) ON COLUMNS
FROM [Analysis Services Tutorial]
I would say query 2 is more performant/optimized because first you take out all the unnecessary members and then crossjoin them. The first query you crossjoin everything and then take out the nulls. That would be my guess but I want somebody who can clear me up.
Edit 1 In response of comments of an answer
Lets say I add a measure as a second parameter, so it does not go to the "default measure". How could second query return values with null? I am specifying to crossjoin between nonempty members. And I just really dont see how the can return different results no matter the dimensions involved. To me they seemed pretty equivalent. What am I not seeing?
Query 1:
SELECT NONEMPTY(CROSSJOIN({[Product].[Category].children},
{[Scenario].[Scenario].members}
), [Total Internet Sales]
) ON COLUMNS
FROM [Analysis Services Tutorial]
Query 2:
SELECT CROSSJOIN(NONEMPTY({[Product].[Category].children},[Total Internet Sales]),
NONEMPTY({[Scenario].[Scenario].members},[Total Internet Sales])
) ON COLUMNS
FROM [Analysis Services Tutorial]
Edit 2
As the answer said the queries are not the same. I realized when #GregGalloway presented other scenario.
I did an excel with sample data so maybe someone can find it useful.
They aren't equivalent since both queries we will return different results. For example, against the real Adventure Works (not some tutorial version) these two queries return different results. Notice that the Clothing/Kentucky column shows null on the second query:
SELECT NONEMPTY(CROSSJOIN({[Product].[Category].children},
{[Customer].[State-Province].[State-Province].Members}
), [Measures].[Internet Sales Amount]
) ON COLUMNS
FROM [Adventure Works]
where [Measures].[Internet Sales Amount]
SELECT CROSSJOIN(NONEMPTY({[Product].[Category].children},[Measures].[Internet Sales Amount]),
NONEMPTY({[Customer].[State-Province].[State-Province].Members},[Measures].[Internet Sales Amount])
) ON COLUMNS
FROM [Adventure Works]
where [Measures].[Internet Sales Amount]
Note that the Scenario dimension doesn't relate to the Internet Sales measure group, I don't think. So that may not be a good example. I chose the Product dimension and the Customer dimension for my example.
As discussed (and as you updated in your question) NonEmpty() should always have a second parameter so it is clear what measure you are doing NonEmpty against. Your query should also mention a measure on one axis or the WHERE clause so that you're not returning some vague "default measure". I've included a WHERE clause with a measure in my examples.
Anyway, to answer your question... assuming the measure is a physical measure or a well optimized calculated measure that runs in block mode I wouldn't be surprised if Query 1 is faster. But it depends on the measure and the size of dimensions and the sparsity of the cube. This question is very theoretical and the two queries don't return equivalent results.