Referencing Named Sets in Calculations
I was recently involved in an interesting discussion about the negative performance impact of referencing named sets inside calculated members. It’s an issue that’s dealt with in this topic in BOL, along with lots of other useful tips for things to avoid when writing MDX calculations:
Since I see lots of people making this mistake, though, I thought it was nonetheless worth a blog post; it’s certainly very easy to reproduce in Adventure Works. Take the following set of calculations:
CREATE SET ALLCUSTS AS [Customer].[Customer].[Customer].MEMBERS; CREATE MEMBER CURRENTCUBE.MEASURES.TEST1 AS COUNT( NONEMPTY( [Customer].[Customer].[Customer].MEMBERS , [Measures].[Internet Sales Amount]) ); CREATE MEMBER CURRENTCUBE.MEASURES.TEST2 AS COUNT( NONEMPTY( ALLCUSTS , [Measures].[Internet Sales Amount]) ); CREATE MEMBER CURRENTCUBE.MEASURES.TEST3 AS SUM( [Customer].[Customer].[Customer].MEMBERS , [Measures].[Internet Sales Amount]); CREATE MEMBER CURRENTCUBE.MEASURES.TEST4 AS SUM( ALLCUSTS , [Measures].[Internet Sales Amount]);
You’ll notice that TEST1 and TEST2 are essentially the same calculation, as are TEST3 and TEST4; the only difference between them is that the set expressions in TEST1 and TEST3 have been replaced by references to the named set ALLCUSTS in TEST2 and TEST4.
Now run the following query four times on a cold cache, each time putting a different calculated measure from the list above in the WHERE clause:
SELECT [Date].[Calendar Year].MEMBERS ON 0, [Product].[Product].MEMBERS ON 1 FROM [Adventure Works] WHERE(MEASURES.TEST1)
On my machine the query with TEST1 took 874ms to run; the query with TEST2 took 6302ms; the query with TEST3 took 234ms; and the query with TEST4 I ended up killing after a few minutes.
So, clearly, as the article says referencing a named set inside one of the MDX aggregation functions in a calculation is a Very Bad Thing for performance and something to be avoided at all costs. While it might seem an appealing thing to do for readability, the downsides are significant.