zhengruifeng commented on pull request #32734:
URL: https://github.com/apache/spark/pull/32734#issuecomment-853779208


   > So you mean if the number of zeros is more in a vector column, then 
consider that vector column as sparse, and If all the vector columns are 
sparse, then proceed with the sparse based implementation. right?
   
   This is just an idea. I mean compute average nnz, if nnz_avg < numFeatues * 
factor(0.5?), the proceduce perfer the code path prefer sparse dataset, 
otherwise another path.


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