ajaypadwal73 commented on PR #1026:
URL: https://github.com/apache/sedona-db/pull/1026#issuecomment-4975472854

   Thanks, that is the right baseline to compare against.
   
   I ran a local follow-up comparison to separate partition-level parallelism 
from probe-row chunking. This is still a `query_batch()`-level benchmark, not a 
full `ProbeShuffleExec` physical-plan benchmark: it simulates partition-level 
parallelism by running N concurrent `query_batch()` calls over row ranges 
against the same shared index.
   
   For the skewed workload, partitioning alone removes a lot of the original 
gap, but probe-row chunking still adds value once multiple probe partitions are 
already active:
   
   | Probe partitions | Partition only | + chunk 64 | + chunk 256 | Best chunk 
gain |
   | ---: | ---: | ---: | ---: | ---: |
   | 1 | 182.3 ms | 53.3 ms | 47.3 ms | ~3.9x |
   | 2 | 174.8 ms | 52.2 ms | 51.5 ms | ~3.4x |
   | 4 | 61.9 ms | 49.1 ms | 50.8 ms | ~1.3x |
   | 8 | 60.7 ms | 45.9 ms | 60.8 ms | ~1.3x |
   | 16 | 54.1 ms | 38.8 ms | 52.4 ms | ~1.4x |
   
   For the uniform workload, the picture is different: once partition count is 
high enough, partition-level parallelism mostly catches up, and combining both 
can regress from overhead. So I agree this should not be framed as a broad 
replacement for `ProbeShuffleExec` or a default-on speedup.
   
   The narrower case where this still seems useful is when partition-level 
parallelism is present but a probe stream still has expensive row-local 
refinement work. In that case, this gives a second level of parallelism inside 
the remaining hot `query_batch()` work.
   
   I am happy to rework the PR around that narrower framing, add this benchmark 
matrix, or drop the public config knob if you think the added tuning surface is 
not worth the narrower skewed-workload gain.


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