Optimizing Summarize in DAX - ssas

Question

I have this DAX formula that gives me a count of id that appear on the fact table in a month, averaged over the year. I can put this measure is a table ad it's unpacked by row with no issues (by adding variables from dimensions)
Measure:= AVERAGEX(
SUMMARIZE(
CALCULATETABLE(fact_table;FILTER('Time_Dimension';'Time_Dimension'[Last_month] <> "LAST"));
Time_Dimension[Month Name];
"Count";DISTINCTCOUNT(fact_table[ID])
);
[Count]
)
But it's terrible slow (I have 3 measures like this on a single table) and the fact table is big (like 300Million rows big)
I was reading that SUMMARIZE perform really bad with aggregations and It should be replaced with SUMMARIZECOLUMNS.
I wrote this formula
Measure_v2:= AVERAGEX(
SUMMARIZECOLUMNS(
Time_Dimension[Month Name];
FILTER(Time_Dimension;
Time_Dimension[Month Name]<>"LAST"
);
"Count";DISTINCTCOUNT(fact_table[ID])
)
[Count]
)
And it works when I visualize the measure as it is, but when I try to put it in a context (like the table above) it gives me the error "Can't use SUMMARIZECOLUMN and ADDMISSINGITEMS() in this context" How can I make a sustainable optimization from the original SUMMARIZE function?

Answer 1

Before optimizing SUMMARIZE, I would re-visit the overall approach. If your goal is to calculate average fact count per year-month, there is a simpler (and faster) way.
[ID Count]:=CALCULATE(COUNT('fact_table'[ID]),'Time_Dimension'[Last_month] <> "LAST")
[Average ID Count]:=AVERAGEX( VALUES('Time_Dimension'[Year_Month]), [ID Count`])
assuming that:
you have year-month attribute in your time dimension;
IDs in your fact table are unique (and therefore, simple count is
enough)
If this solution does not solve your problem, then please post your data model - it's hard to optimize without knowing the data structure.
On a side note, I would remove ID field from the fact table. It adds no value to the model, and consumes huge amounts of memory. Your objective can be achieved by simply counting rows:
[Fact Count]:=CALCULATE(COUNTROWS('fact_table'),'Time_Dimension'[Last_month] <> "LAST")