Filter based on existence in one table and non-existence in another

Question

I have the following data model:

Record: Id, ..., CreateDate

FactA: RecordId, CreateDate

FactB: RecordId, CreateDate

Relationships exist from FactA to Record and FactB to Record.

I've written measures on Records such as this with no issues:

FactA's:=CALCULATE(DISTINCTCOUNT(Records[Id]), FactA)
FactB's:=CALCULATE(DISTINCTCOUNT(Records[Id]), FactB)

Now I'd like a count of Records with FactA but no FactB, in SQL I'd do a LEFT JOIN WHERE FactB.RecordId IS NULL but I can't figure out how to do similar in DAX. I've tried:

 -- this returns blank, presumably because when there is a FactB then RecordId isn't blank, and when there is no Fact B then RecordId a NULL which isn't blank either
FactA_No_FactB:=CALCULATE(DISTINCTCOUNT(Records[Id]), FactA, FILTER(FactB, ISBLANK([RecordId])))

-- this returns the long "The value for columns "RecordId" in table "FactB" cannot be determined in the current context" error.
FactA_No_FactB:=CALCULATE(DISTINCTCOUNT(Records[Id]), FILTER(FactA, ISBLANK(FactB[RecordId])))

I've also tried various ways of using RELATED and RELATEDTABLE but I don't really understand enough about DAX and context to know what I'm doing.

Can someone explain how I can write the calculated measure to count Records with FactA but no FactB?

Thanks in advance.

Edit - Workaround

I've come up with this, it looks correct so far but I'm not sure if it is the generally correct way to do this:

-- Take the count with FactA and subtract the count of (FactA and FactB)
FactA_No_FactB:=CALCULATE(DISTINCTCOUNT(Records[Id]), FactA) - CALCULATE(DISTINCTCOUNT(Records[Id]), FactA, FactB)

Answer 1

Here's an alternative, that might still not be the best way of doing it:

FactA_No_FactB:=CALCULATE(DISTINCTCOUNT(Records[ID]), FILTER(Records,CONTAINS(FactA, FactA[RecordID],Records[ID]) && NOT(CONTAINS(FactB,FactB[RecordID],Records[ID]))))

The difference between my version and yours is that mine returns a value of 1 for those items in and A but not B and BLANK for everything else. Your version returns 1 for those items in A but not B, 0 for those in both A and B and BLANK for everything else. Depending on your use case, one outcome may be prefereable over the other.