milenkovicm commented on issue #1612:
URL: 
https://github.com/apache/datafusion-python/issues/1612#issuecomment-4892430303

   thanks for keeping me in the loop @timsaucer , 
   
   IMHO, option 2 makes more sense for few reasons:
   
   - it would not introduce any overhead on datafusion python, which can keep 
release cadence as it was. currently ballista has release more than 4+ weeks 
after df has been released. I don't want to put us all on pressure. 
   - reading the option 1, it discuss something very specific to df-distributed 
which i don't think it should be concern of df-python, I would suggest to keep 
separation of concerns  
   - keeping small codebase locally is not really a problem, as there is not 
much code. the only issue i see is that each project needs to have release 
process in place. we have all supporting infrastructure in place already, which 
could be reused. Py03 is not issue for ballista and i dont think it would be 
issue for df-distributed, if it is i would be more than happy to help.
   -  should new framework want to distribute df-python there is a supporting 
framework in place, and two implementation already using it, making integration 
framework robust 
   
   also, if we move https://github.com/apache/datafusion/pull/22151 to 
df-python i dont think its would be big effort to get support for `option 2` .
   
   
   
   


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