Calculate using OR from Dimensions

[russds]

I have a fairly simple model with 1 Fact table and 2 Dimensions. 

Fact Table Sales:

       SalesID, ProductID, StoreID

ProductDim

       ProductID, ProductName

StoreDim

       StoreID, StoreName

What I need to do is write a dax that will calculate the number of distinct SaleIDs, when either dimension is selected. e.g. If I seled ProductName="Gym Paints" and StoreName="Walmart", I'll get the count of SalesIDs that contain either Gym Paints ProductName or Walmart StoreName. 

I have so far tried:

SalesTotal := 

     CALCULATE(DISTINCTCOUNT(Sales[SalesId])

      -- various forms of FILTER, but none have worked. 

)

I know this is not ideal solution, we are forced into this because other solutions have been performing slowly. 

Thanks!

[MattAllington]

You don’t need calculate. Just write this

DISTINCTCOUNT(Sales[SalesId])

[russds]

Thanks @MattAllington , 

Note I want to apply two dimensions to the calculation though.  If I simply do: 

measure := distinctcount(Sales[SaleId]) and apply two dimension filters, it will count only rows where the two dimension rows are applied. 

I want to acheive an OR condition where either of the two dimensions are applied. I.e. distinctcount of salesid when ProductA OR storeB is selected in the dimensions. 

Thanks! 

[MattAllington · Accepted solution]

Sorry, I missunderstood. You can’t do what you want if you have 2 active relationships. Relationships from 2 dim tables are logical AND. So either remove the relationships or make them inactive. Then write something like

measure =
VAR prod =
    MAX ( prod[id] )
VAR Store =
    MAX ( store[ID] )
VAR prodsales =
    FILTER ( sales, sales[prod id] = prod )
VAR Storesales =
    FILTER ( sales, sales[store id] = store )
VAR allsales =
    UNION ( prodsales, storesales ) // includes 2 copies of rows that are both 
VAR alldistinctsales =
    DISTINCT ( allsales ) // removes double count of rows that are both
RETURN
    CALCULATE ( [total sales], Alldistinctsales)

I think this will work. I haven’t tested it.