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fix(spark): derive concat_ws nullability from separator - #26205
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@Jefffrey @neilconway maybe one of you can take a look? |
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #26205 +/- ##
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- Coverage 82.80% 82.80% -0.01%
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Files 1149 1149
Lines 452205 452213 +8
Branches 452205 452213 +8
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+ Hits 374458 374459 +1
- Misses 54950 54956 +6
- Partials 22797 22798 +1 ☔ View full report in Codecov by Harness. 🚀 New features to boost your workflow:
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neilconway
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Oct 11, 2026
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Thanks @VVKot , lgtm.
Btw, Spark's soundex and space, and core's concat_ws, might benefit from a similar change.
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## Which issue does this PR close? <!-- We generally require a GitHub issue to be filed for all bug fixes and enhancements and this helps us generate change logs for our releases. You can link an issue to this PR using the GitHub syntax. For example `Closes apache#123` indicates that this PR will close issue apache#123. --> Part of the work towards apache#15914 ## Rationale for this change <!-- Why are you proposing this change? If this is already explained clearly in the issue then this section is not needed. Explaining clearly why changes are proposed helps reviewers understand your changes and offer better suggestions for fixes. Please explain the problem you are trying to solve in terms of the user-visible behavior, rather than the implementation. For example, "The code in `foo.rs` doesn't handle nulls" is a symptom of the implementation. "COUNT(DISTINCT) returns wrong results when the column contains nulls" is the user-visible problem. --> `concat_ws` return value is always nullable in DF, which is incorrect. Per upstream Spark implementation, this is only true when separator itself is null. ## What changes are included in this PR? <!-- 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. --> Derive the nullability based on the separator nullability. ## What is the testing strategy for this PR? <!-- We typically require tests for all PRs in order to: 1. Prevent the code from being accidentally broken by subsequent changes 2. Serve as another way to document the expected behavior of the code Briefly describe how this PR is tested, and point to the specific tests you added. For example: 'This new feature is covered by the `sqllogictest` cases added in `foo.slt`'. If this PR does not add tests, explain why. For example, if the change is already covered by existing tests, please mention it. You should also check the `codecov` bot reply on this PR to confirm the changed code is exercised. --> Add SLT tests for schema. ## Are there any user-facing changes? <!-- If there are user-facing changes then we may require documentation to be updated before approving the PR. If there are any breaking changes to public APIs, please add the `api change` label. --> I believe this doesn't count as an API change but would like guidance from a committer.
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Which issue does this PR close?
Part of the work towards #15914
Rationale for this change
concat_wsreturn value is always nullable in DF, which is incorrect. Per upstream Spark implementation, this is only true when separator itself is null.What changes are included in this PR?
Derive the nullability based on the separator nullability.
What is the testing strategy for this PR?
Add SLT tests for schema.
Are there any user-facing changes?
I believe this doesn't count as an API change but would like guidance from a committer.