Running total poor performance with large date table

Hi Greg_Deckler  & lbendlin ,

thank you, I'm surprised and impressed about this content in relation "CALCUHATE"  🤣😂🤣.

I was not aware that there is an alternative to CALCULATE for running totals and so many other things. 

I tested CALCULATE vs. SUMX for running totals against different sizes of Date and Fact table. SUMX is faster with a very large Date table. However it becomes slower than the solution with CALCULATE with smaller sized Data tables depending on the size of the fact table.

I tested the following:

RT CALC = 
CALCULATE (
    SUM ( TasksBLTP[TaskBaselineCost] ),
    ALL ( 'Date' ),
    'Date'[Date] <= MAX ( TasksBLTP[TimeByDay] )
)

RT SUMX = 
VAR _MaxDate =
    MAX ( TasksBLTP[TimeByDay] )
VAR _T1 =
    FILTER ( ALLSELECTED ( TasksBLTP ), TasksBLTP[TimeByDay] <= _MaxDate )
VAR _Result =
    SUMX ( _T1, TasksBLTP[TaskBaselineCost] )
RETURN
    _Result

Date table with 41 Years: SUMX is faster 1,8x to 46x faster depending on rows in Fact table

Date table with 11 Years: CALCULATE or SUMX is faster depending on rows in Fact table

Date table with 4 Years: CALCULATE or SUMX is faster depending on rows in Fact table

The pbix file can be downloaded under https://we.tl/t-3GUEmfy0fE

Since even SUMX takes 10+sec. for most selections in my real model, I'm thinking of implementing a separate Date table only for the TaskBLTP which only contains the number of rows required for the current selection.

Any other ideas?

Best regards