wForget commented on issue #3596:
URL: 
https://github.com/apache/datafusion-comet/issues/3596#issuecomment-3970232665

   > Thanks [@Shekharrajak](https://github.com/Shekharrajak) it actually sounds 
attractive, if talking about just replacing transport. However IMO the flow 
brings up some challenges:
   > 
   > * less resilient, without disk it would be easier to run out of memory
   > * backpressure, so if the reducer is busy now, what mapper is supposed to 
do? buffer in memory? resend? if so we stumble on problem on step1
   
   And this may break the Spark DRA feature.
   
   > nevertheless it would be nice having separate shuffle manager for 
lightweight jobs
   
   Introducing a spark remote shuffle service like Apache Celeborn/Uniffle is a 
good option.


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