andygrove opened a new issue, #1671:
URL: https://github.com/apache/datafusion-comet/issues/1671

   ### What is the problem the feature request solves?
   
   Spark's join strategy planner chooses between Broadcast Hash Join, Shuffled 
Hash Join, and Sort Merge Join based primarily on the estimated `sizeInBytes` 
of the build-side input.
   
   When using Comet, the input to a join may come from a Comet Exchange, which 
benefits from columnar compression. This often results in a `sizeInBytes` 
estimate that is 2x smaller (or more) than what Spark would compute for the 
same plan using row-based execution.
   
   As a result, Spark may incorrectly choose a Broadcast Hash Join when the 
actual uncompressed size of the data would have triggered a Shuffled Hash Join 
or Sort Merge Join. This can lead to performance regressions or even OOM issues 
on the driver or executor.
   
   Proposal:
   
   We should consider adjusting the reported `sizeInBytes` for Comet's columnar 
exchanges to more accurately reflect the logical uncompressed size of the data. 
This would align better with Spark’s assumptions and avoid unintended join 
strategy changes.
   
   Options might include:
   
   - Applying a fixed multiplier to sizeInBytes in columnar exchange operators 
(e.g., 2x)
   - Using schema-aware size estimates to approximate row-based sizes
   - Providing a config flag to tune this behavior for benchmarking and tuning
   
   Impact:
   
   - More consistent join strategy decisions with and without Comet
   - Reduced risk of performance regressions due to unexpectedly chosen 
broadcast joins
   - Better alignment with Spark’s cost model
   
   ### Describe the potential solution
   
   _No response_
   
   ### Additional context
   
   _No response_


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