Refactor distinct aggregate implementations to use common buffer#18348
Merged
Jefffrey merged 1 commit intoapache:mainfrom Nov 13, 2025
Merged
Refactor distinct aggregate implementations to use common buffer#18348Jefffrey merged 1 commit intoapache:mainfrom
Jefffrey merged 1 commit intoapache:mainfrom
Conversation
Jefffrey
commented
Oct 29, 2025
Contributor
Author
There was a problem hiding this comment.
It would be nice if I can pull in PrimitiveDistinctCountAccumulator to the deduplication as well, however it is specialized for types which don't need to hash through Hashable (aka non-float types) and I think there might be a performance hit if I try force them to use Hashable 🤔
Contributor
There was a problem hiding this comment.
Yeah, we definitely don't want to be hashing if we can avoid taht
| /// `merge_batch` and a `Vec` of `ArrayRef` that are converted to scalar values | ||
| /// in the final evaluation step so that we avoid expensive conversions and | ||
| /// allocations during `update_batch`. | ||
| pub struct GenericDistinctBuffer<T: ArrowPrimitiveType> { |
Contributor
Author
There was a problem hiding this comment.
Main implementation here; I toyed with the idea of making this implement Accumulator and have the different functions (like median and percentile_cont) provide their evaluate logic as a closure but it got a bit messy; so for now they delegate their state/update_batch/merge_batch to this inner struct, which allows them to grab the final set of distinct values for them to do their own evaluate
53 tasks
alamb
approved these changes
Nov 11, 2025
Contributor
alamb
left a comment
alamb
left a comment
There was a problem hiding this comment.
Thank you @Jefffrey -- this is really quite elegant. I am sorry it took so long to review
the only thing I think we need to do is ensure this doesn't have any impact in performance (I don't expect that it will but want to be sure)
Really nice 🏆
Contributor
There was a problem hiding this comment.
Yeah, we definitely don't want to be hashing if we can avoid taht
| self.values.extend(arr.iter().flatten().map(Hashable)); | ||
| } else { | ||
| self.values | ||
| .extend(arr.values().iter().cloned().map(Hashable)); |
Contributor
There was a problem hiding this comment.
nice -- this is an elegant way to special case nulls/non nulls
Contributor
|
🤖 |
Contributor
|
🤖: Benchmark completed Details
|
Contributor
Author
|
The clickbench QQuery0 (I believe it's this query?) that is 1.18x slower doesn't use distinct so I don't think it's an actual slowdown. |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Which issue does this PR close?
distinctusage for aggregate expressions #2406Rationale for this change
Make it easier to write distinct variations of aggregate functions be refactoring some of the common code together; specifically how they handle maintaining the complete set of distinct primitive values, as this code was duplicated across different functions.
What changes are included in this PR?
Introduce new
GenericDistinctBufferwhich has methods similar toAccumulatorto manage an internalHashSetof values, so implementations likepercentile_contandsumcan use it internally and only implement their own evaluate functions.Are these changes tested?
Existing tests.
Are there any user-facing changes?
No.