aplyusnin commented on PR #847:
URL: 
https://github.com/apache/flink-kubernetes-operator/pull/847#issuecomment-2327364352

   Hi, sorry for a big delay. I've tried to simplify the logic of the 
backpropagation.
   
   Every vertex has it's initial target data rate and the one limited by the 
donwstream and potential performance after scaling.
   Potential performance is how much data can an operator process when scaled 
by the maximum scale factor.
   Donwstream limitation is evaluated very close to how we discussed it 
earlier. 
   
   There is a pitfall with negative limited data rate appearance during 
backpropagation (check 
ScalingExecutorBackpropagationTest#testDisconnectedJobMetricsUpdate) because of 
"even" backpropagation of data rate to upstream operators, so it is not still 
very clear how to resolve such situations. 
   
   Also I decided to replace bottleneck-propagation.allow-scale-down option 
with processing.rate.backpropagation.impact, because I think it is very unclear 
how use the previous one properly. The new option represents a "weight" of 
backpropagation: 0 means backpropagation is ignored and 1.0 means new values 
will be used further.


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