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Posted to github@datafusion.apache.org by "lyne7-sc (via GitHub)" <gi...@apache.org> on 2026/08/20 07:15:51 UTC
[PR] fix: evaluate window aggregate arguments after FILTER [datafusion]
lyne7-sc opened a new pull request, #24508:
URL: https://github.com/apache/datafusion/pull/24508
## Which issue does this PR close?
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- Closes #24507.
## Rationale for this change
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Window aggregates evaluate their arguments before applying `FILTER`, which can cause errors on rows that should not participate in the aggregate.
This is analogous to #24444 for grouped aggregates, window aggregates use a separate evaluation path.
## What changes are included in this PR?
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There is no need to duplicate the description in the issue here, but it is sometimes worth providing a summary of the individual changes in this PR.
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Evaluate the window aggregate filter before evaluating its arguments.
Use the resulting filter mask as a selection when evaluating argument expressions. Selected results are scattered back to the original batch length so that window frame row indices remain aligned.
This applies to both ever-expanding and sliding aggregate window frames.
## Are these changes tested?
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Yes.
## Are there any user-facing changes?
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Window aggregate arguments are no longer evaluated for rows rejected by `FILTER`, no public API changes.
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Re: [PR] fix: evaluate window aggregate arguments after FILTER [datafusion]
Posted by "github-actions[bot] (via GitHub)" <gi...@apache.org>.
github-actions[bot] commented on PR #24508:
URL: https://github.com/apache/datafusion/pull/24508#issuecomment-6406182054
Marked as draft after 14 days without activity: merge conflicts.
Please address these items and mark **Ready for review** when ready.
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Re: [PR] fix: evaluate window aggregate arguments after FILTER [datafusion]
Posted by "lyne7-sc (via GitHub)" <gi...@apache.org>.
lyne7-sc commented on PR #24508:
URL: https://github.com/apache/datafusion/pull/24508#issuecomment-5366423176
Thanks for the review! I think this could cause a performance regression when the window argument is a direct column or another cheap expression. In these cases, the cost of filtering the entire batch and scattering the result back to the original row positions may exceed the expression evaluation cost that we skip.
As a low-risk mitigation, we could bypass `evaluate_selection` for expressions that are known to be safe and cheap to evaluate on the original batch, as follows:
```
let value = if can_evaluate_window_arg_unfiltered(expr) {
// These expressions cannot fail because of values in excluded rows.
expr.evaluate(batch)?
} else {
// Fallible expressions must only see selected rows.
expr.evaluate_selection(batch, selection)?
};
```
This could address the most obvious regressions for direct columns and literals. However, it would only be a temporary mitigation and would not cover other cheap expressions such as `column + 1`.
One possible long-term direction might be to keep the selected argument values in compact form instead of scattering them back. We could maintain a prefix-count array that maps each boundary in the original row space to the corresponding boundary in the compact argument arrays:
```
selection: T F T F
prefix: 0 1 1 2 2
original frame: [start, end)
compact frame: [prefix[start], prefix[end])
```
Window frame calculation and output rows could remain in the original row space, while only the ranges passed to the accumulator would be mapped into the compact arrays. This could allow us to skip evaluating expressions for excluded rows while still producing the correct window results. It could also avoid per-argument scatter and the additional filtering before `update_batch/retract_batch`.
I'm not sure whether this approach would improve performance in practice. does this direction make sense to you?
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Re: [PR] fix: evaluate window aggregate arguments after FILTER [datafusion]
Posted by "codecov-commenter (via GitHub)" <gi...@apache.org>.
codecov-commenter commented on PR #24508:
URL: https://github.com/apache/datafusion/pull/24508#issuecomment-5352996672
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<details><summary>Additional details and impacted files</summary>
```diff
@@ Coverage Diff @@
## main #24508 +/- ##
==========================================
+ Coverage 81.23% 81.27% +0.03%
==========================================
Files 1112 1116 +4
Lines 390635 395026 +4391
Branches 390635 395026 +4391
==========================================
+ Hits 317350 321063 +3713
- Misses 54650 55166 +516
- Partials 18635 18797 +162
```
</details>
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Re: [PR] fix: evaluate window aggregate arguments after FILTER [datafusion]
Posted by "neilconway (via GitHub)" <gi...@apache.org>.
neilconway commented on PR #24508:
URL: https://github.com/apache/datafusion/pull/24508#issuecomment-5370977480
@lyne7-sc Yep, that all makes sense -- both the short-term mitigation and the longer-term optimization possibility. Should we start by adding a micro-benchmark to cover the window agg + FILTER case and then proceed from there?
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Re: [PR] fix: evaluate window aggregate arguments after FILTER [datafusion]
Posted by "lyne7-sc (via GitHub)" <gi...@apache.org>.
lyne7-sc commented on PR #24508:
URL: https://github.com/apache/datafusion/pull/24508#issuecomment-5384455201
@neilconway yes, that makes sense. I've added the microbenchmark separately in #24589.
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