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Accelins
Frequent Visitor

Table Visual timeout across multiple dimensions

Hello, 

I'm having issues adding multiple dimension columns into a table visual - I have built a star schema (shown in the picture), and when I add in a 2nd dimension my table times out. I'm using a series of measures that replicate across different D365 Transaction Types based on the fact tables.

 

Member Gross Premium = 
CALCULATE (
    SUM ( 'F Member Transaction Line Item'[Member Original Currency Amount] ),
    CALCULATETABLE (
        'D365 Transaction Type',
        'D365 Transaction Type'[D365 Transaction Type Name] = "Premium"
    )
) + 0

 

  

 

Member Gross Premium - Unpaid = 
VAR Settled =
    CALCULATE (
        SUM ( 'Member Settlement'[Member Settled Original Amount] ),
        CALCULATETABLE (
            'D365 Transaction Type',
            'D365 Transaction Type'[D365 Transaction Type Name] = "Premium"
        )
    )
RETURN
    ( Settled - [Member Gross Premium] ) * -1

 

 So when I add the measures in it works fine, I add in data from the "Premium Transaction" dimension and this works fine, then If I try to add in a column from the "Currency" Dimension the table runs out of memory and I need to add dimension data from more tables.
It's a medium size model with around 20mil rows (metadata shown below) and this is built using Kimbal - I have even separated out string columns into their own dimension. 

If I have 2 table visuals and select a row Power BI filters the row very quickly and gives the desired result but Ideally I need all the information in one table. 

 Model Meta DataModel Meta DataStar SchemaStar Schemareport pagereport page



1 ACCEPTED SOLUTION
Accelins
Frequent Visitor

Ended up changing some of the model fct and dimensions to achieve optimal performance 

View solution in original post

4 REPLIES 4
Accelins
Frequent Visitor

Ended up changing some of the model fct and dimensions to achieve optimal performance 

lbendlin
Super User
Super User

I always try to avoid any iterators but I also did try FILTER instead of CALCULATETABLE but it returned the same result - table timeout. 

Use DAX Studio to examine the query.

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