[FEA] Drop Obsolete PTX/CUDA Rolling Aggregations by lamarrr · Pull Request #23840 · NVIDIA/cudf

lamarrr · 2026-08-26T14:47:12Z

Follow-up to #23598, which moved Rolling.apply from libcudf PTX aggregations to a Python-layer numba-cuda-mlir implementation.

Rolling.apply now computes window bounds in Python and JIT-compiles a dedicated CUDA kernel for the user-provided callable. As a result, the previous PTX/CUDA rolling aggregation implementation in libcudf is no longer used.

This PR:

Removes the libcudf aggregation::PTX and aggregation::CUDA kinds.
Removes make_udf_aggregation and the associated aggregation implementation.
Removes the legacy rolling RTC/JIT kernels and embedded CUDA sources.
Removes the corresponding pylibcudf aggregation factory and declarations.
Simplifies fixed, variable, and grouped rolling paths by removing UDF-specific dispatch.
Removes C++ tests for the retired implementation; Rolling.apply remains covered by the Python tests introduced in Replace rolling.apply implementation with numba-cuda-mlir #23598.

The public cudf.Series/DataFrame.rolling.apply functionality remains available. This is only a breaking change for low-level libcudf or pylibcudf consumers that directly construct PTX/CUDA rolling aggregations.

Checklist

I am familiar with the Contributing Guidelines.
New or existing tests cover these changes.
The documentation is up to date with these changes.

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📝 Summary

Summary by CodeRabbit

Breaking Changes
- Removed CUDA and PTX user-defined aggregation support, including rolling-window UDF execution.
- Removed the Python udf aggregation factory and CUDA/PTX aggregation options across supported APIs.
- Applications using these aggregation kinds must migrate to supported alternatives.
Available Functionality
- Host-based user-defined aggregations remain supported.
- Built-in aggregations continue to work across fixed, variable, and grouped rolling-window operations.

Walkthrough

The change removes PTX and CUDA rolling UDF aggregation APIs, implementations, JIT integration, Python bindings, Java mappings, and related tests. Host UDF aggregation support remains available.

Changes

Rolling UDF removal

Layer / File(s)	Summary
Aggregation API removal `cpp/include/cudf/aggregation.hpp`, `python/pylibcudf/pylibcudf/aggregation.*`, `python/pylibcudf/pylibcudf/libcudf/aggregation.pxd`, `java/src/main/java/ai/rapids/cudf/Aggregation.java`, `java/src/main/native/src/AggregationJni.cpp`	Removes PTX and CUDA aggregation kinds, UDF factories, Python UDF bindings, and obsolete Java kind slots. Host UDF support remains.
Standard rolling execution `cpp/src/rolling/detail/rolling.cuh`, `cpp/src/rolling/detail/rolling_fixed_window.cu`, `cpp/src/rolling/detail/rolling_variable_window.cu`, `cpp/src/rolling/grouped_rolling.cu`	Routes fixed, variable, grouped, and empty rolling aggregations through standard rolling implementations.
JIT integration cleanup `cpp/CMakeLists.txt`	Removes rolling source embedding from the JIT runtime bundle.
Test updates `cpp/tests/rolling/empty_input_test.cpp`, `cpp/tests/rolling/grouped_rolling_test.cpp`, `cpp/tests/rolling/rolling_test.cpp`	Removes rolling UDF fixtures, invocations, reference cases, and rejection assertions.

Estimated code review effort: 3 (Moderate) | ~25 minutes

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 11.76% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 17 functions across 7 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly and concisely describes the main change: removing obsolete PTX/CUDA rolling aggregations.
Description check	✅ Passed	The description directly explains the removal of the obsolete libcudf PTX/CUDA rolling implementation, its affected APIs and tests, and the retained public rolling.apply functionality.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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Inline comments:
In `@java/src/main/java/ai/rapids/cudf/Aggregation.java`:
- Around line 52-63: Add unit-test coverage for the renumbered aggregation IDs
in Aggregation, exercising the native factory dispatch paths in
AggregationJni.cpp for the changed aggregation types and verifying each ID
creates the intended aggregation. Add the required unit benchmark covering these
factory paths, following the project’s existing test and benchmark patterns.

In `@java/src/main/native/src/AggregationJni.cpp`:
- Line 96: Align the `BITWISE_AGG` comment with the neighboring case-label
comments by removing its two extra leading spaces, then run clang-format on the
affected C++ file.

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java/src/main/java/ai/rapids/cudf/Aggregation.java
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vyasr

Approved, with one request for whoever reviews this on the Java side of things.

lamarrr · 2026-09-04T20:11:06Z

Thanks, all!

lamarrr · 2026-09-04T20:12:08Z

/merge

lamarrr added 2 commits August 26, 2026 14:44

[FEA] Drop PTX/CUDA Rolling Aggregations

2ac7ccc

Merge remote-tracking branch 'upstream/main' into py-udf-drop

a8f82ad

github-actions Bot assigned lamarrr Aug 26, 2026

github-actions Bot added libcudf Affects libcudf (C++/CUDA) code. Python Affects Python cuDF API. CMake CMake build issue pylibcudf Issues specific to the pylibcudf package labels Aug 26, 2026

github-project-automation Bot added this to cuDF Python Aug 26, 2026

github-project-automation Bot moved this to Todo in cuDF Python Aug 26, 2026

lamarrr added this to the libcudf JIT Enhancements milestone Sep 2, 2026

lamarrr added breaking Breaking change feature request New feature or request labels Sep 2, 2026

lamarrr changed the title ~~[FEA] Drop PTX/CUDA Rolling Aggregations~~ [FEA] Drop Obsolete PTX/CUDA Rolling Aggregations Sep 2, 2026

Merge remote-tracking branch 'upstream/main' into py-udf-drop

d30cd48

lamarrr marked this pull request as ready for review September 2, 2026 11:41

lamarrr requested review from a team as code owners September 2, 2026 11:41

lamarrr requested review from vyasr and wence- September 2, 2026 11:41

Merge branch 'main' into py-udf-drop

d65ba47

bdice reviewed Sep 2, 2026

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Comment thread cpp/include/cudf/aggregation.hpp

Refactor aggregation constants and remove unused UDF types

37bb534

lamarrr requested a review from a team as a code owner September 2, 2026 15:00

github-actions Bot added the Java Affects Java cuDF API. label Sep 2, 2026

coderabbitai Bot reviewed Sep 2, 2026

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Comment thread java/src/main/java/ai/rapids/cudf/Aggregation.java

Comment thread java/src/main/native/src/AggregationJni.cpp

lamarrr added 2 commits September 3, 2026 10:57

Fix TDIGEST and MERGE_TDIGEST case values in Aggregation JNI

de06226

Merge branch 'main' into py-udf-drop

472643a

bdice approved these changes Sep 3, 2026

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vyasr approved these changes Sep 3, 2026

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Comment thread java/src/main/java/ai/rapids/cudf/Aggregation.java

lamarrr requested review from mythrocks and revans2 September 4, 2026 17:43

revans2 approved these changes Sep 4, 2026

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Comment thread java/src/main/java/ai/rapids/cudf/Aggregation.java

rapids-bot Bot merged commit 4d48f86 into NVIDIA:main Sep 4, 2026
287 of 290 checks passed

github-project-automation Bot moved this from Todo to Done in cuDF Python Sep 4, 2026

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[FEA] Drop Obsolete PTX/CUDA Rolling Aggregations - #23840

[FEA] Drop Obsolete PTX/CUDA Rolling Aggregations#23840
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