szehon-ho commented on PR #58145:
URL: https://github.com/apache/spark/pull/58145#issuecomment-6643902551

   Thanks, I had a chat with @aokolnychyi and the concern it is getting deeper 
in a rabbit hole if we try to fix this undercounting etc.. as we discuss on 
point (2) of  
https://github.com/apache/spark/pull/58145#issuecomment-6542082777   .  
   
   Actually originally the idea for this is Iceberg/ Delta derived partition 
filters for partition transform and generated columns.  In these cases, the 
DSV2 data source connector does _not_ have NDV's for the data columns and so 
the original filter does _not_ contribute to stats adjusmtent , hence the use 
is to put 'partition filters' in the Filter node that do allow it to influence 
stats accurately.  So my vote is the simple solution, and not complexity of 
handling over-counting for now, if there's no easy correct way.  There's 
actually not that much use case, I feel.  I should have explained the 
motivation in the pr earlier, sorry!  
   
   So with simplified solution, removing these from Filter node is the next 
step , thanks @yyanyy .  its also a bit tricky :)   


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