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[FEAT]: shuffle_join_default_partitions param #2844

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universalmind303
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addresses #2817

@github-actions github-actions bot added the enhancement New feature or request label Sep 13, 2024
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codspeed-hq bot commented Sep 13, 2024

CodSpeed Performance Report

Merging #2844 will degrade performances by 77.08%

Comparing universalmind303:default_join_partitions (22a0720) with main (78a92a2)

Summary

❌ 1 regressions
✅ 15 untouched benchmarks

⚠️ Please fix the performance issues or acknowledge them on CodSpeed.

Benchmarks breakdown

Benchmark main universalmind303:default_join_partitions Change
test_explain[100 Small Files] 33 ms 143.9 ms -77.08%

@jaychia jaychia requested a review from colin-ho September 15, 2024 21:32
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LGTM, we should see if this affects our local TPC-H benchmarks too

src/daft-plan/src/physical_planner/translate.rs Outdated Show resolved Hide resolved
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@universalmind303 universalmind303 merged commit 688150f into Eventual-Inc:main Sep 20, 2024
35 of 36 checks passed
@universalmind303 universalmind303 deleted the default_join_partitions branch September 20, 2024 19:42
@jaychia
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jaychia commented Sep 20, 2024

Just chatted with @samster25

We should revert this PR since this quite negatively impacts all of our benchmarks:

  • It's not possible a priori to know what a good default here would be, since a user could have a query that may, in fact, benefit from having a smaller partitioning than 200 (as in the case of our benchmarks).
  • The best way to solve this would be through AQE, but we don't yet have support for that.

cc @samster25 for thoughts.

I'll create a PR for the revert? LMK what you all think @universalmind303 @colin-ho

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jaychia commented Sep 20, 2024

To be clear, we probably need a more sophisticated mechanism here for determining the number of partitions. This includes:

  • Statistics which can tell us estimated cardinality/partition sizes at planning-time
  • AQE which can give us the actual cardinality/partition sizes at runtime

Both of which we don't currently have in Daft... And thus this approach might be too naive for us to use right now 😭

Sorry @universalmind303 I know this was quite a bit of wasted effort on your end.

jaychia added a commit that referenced this pull request Sep 20, 2024
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3 participants