What is Excel doing?

Question

Hello,
We have a simple cube prototype with one fact table and two dimensions (on SQL Server 2008 R2)
When I place two fields, one from each dimension, on the Excel pivot table designer, Excel shows data. In particular, it shows over 6000 rows for the unknown member of the first dimension's field.
When I try to do the same in Visual Studios Cube browser, no data is shown until a measure is added to the pivot area. 
What is Excel doing that is enabling it to show data without a measure from the fact table being included? The MDX generated by Excel is shown below. I can see it is doing a cross join, but can't replicate this in SQL using the data warehouse tables. What
is the equivalent SQL?
Excel generated MDX
SELECT NON EMPTY CrossJoin(Hierarchize({DrilldownLevel({[Dim Event].[EVENT CODE].[All]},,,INCLUDE_CALC_MEMBERS)}), Hierarchize({DrilldownLevel({[Dim Supporter].[Supporter URN].[All]},,,INCLUDE_CALC_MEMBERS)})) DIMENSION PROPERTIES PARENT_UNIQUE_NAME,HIERARCHY_UNIQUE_NAME
ON COLUMNS  FROM [Simple Cube] CELL PROPERTIES VALUE, FORMAT_STRING, LANGUAGE, BACK_COLOR, FORE_COLOR, FONT_FLAGS
Excel output

Answer 1

Thanks for the tip.
My problem is this: the Excel query take a very long time to run. DimEvent has only 700 rows and DimSupporter has 10,000 rows. I get the impression that Excel is doing a cross join resulting in a lot of rows. This is obviously frustrating for the user as
Excel takes a very long time to give control back to the user.
Also, without a fact table measure in the pivot, how does Excel know which Event Code and Supporter URN are related? Because of the star schema design, the only link between the two dimensions.
Hi Amir,
In SQL Server Analysis Services Cube, there is a default measure which you can see on the link below.
Besides, for the performnce issue, used CrossJoin function to join multiple dimensions which might cause the performance issue. If you cross-join medium-sized or large-sized sets (e.g., sets that contain more than 100 items each), you can end up with a result
set that contains many thousands of items—enough to seriously impair performance. For the detail information, please see:
http://sqlmag.com/data-access/cross-join-performance
Regards,
Charlie Liao
TechNet Community Support