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I'm having trouble mentally modelling how set analysis & nested aggregation work together, because I can't find an explanation for the behaviour I'm observing.
My table model is just a single, denormalised table. I have a pivot chart that, in general terms, is like this. It has
* dimensions D1, D2, ... Dn
* an expression like
SUM ({set_expr_1}
AGGR (
if (
SUM ({set_expr_2} expr) > threshold,
1,
0
),
d1, d2, ..., dk // these are a superset of the chart's dimensions
)
As you can tell, I'm basically trying to count how many dimension combinations meet some criterion based on a SUM.
So, question 1: how does each set expression impact the other? My mental model - which isn't working - has been that
The reason this isn't working for me is that both my set expressions are of the form {1< field1={'value1'}, field2={'value2'}, ... >} (so, we're attempting start with the full set of data and explicitly select subsets), and yet the resulting chart is being sensitive to user selections. I thought it could be a Chart Property thing, and tried marking the checkboxes for 'Show All Values' for all the dimensions, but this didn't help. So, I'm thinking my mental model of how set expressions interact is flawed.
Can anyone correct my thinking, here?
Thanks,
Angus.