nat-openai opened a new pull request, #25979: URL: https://github.com/apache/datafusion/pull/25979
## 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 #123` indicates that this PR will close issue #123. --> This addresses the major incompatibility described in https://github.com/apache/datafusion-comet/issues/4654 for `CometFromUTCTimestamp`. It does not close that issue. It's a follow-up to #19879. ## 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. --> The timezone spellings accepted by Spark are different than those accepted by Arrow's parser. As a result, `from_utc_timestamp` in comet isn't safe to use, since it would fail on things like Java short IDs, prefixed offsets with second precision, and SystemV-style IDs. Additionally, Arrow will accept offsets beyond the Spark limit of 18 hours. ## 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. --> This change improves compatibility by parsing timezone IDs with the rules implemented by Spark. As part of doing this, I added SparkFromUtcTimestampExpr so that computed timezones evaluated for rows with non-null timestamps, avoiding failing when a timezone is invalid but wouldn't be required anyway. (Full compatibility with spark behaviour seems quite complex and I haven't attempted it here.) It also adds more documentation recording remaining differences: - timezone validation and evaluation order can differ from Spark - chrono accepts a narrower calendar range than Spark implemented range - chrono-tz doesn't currently perform DST transitions past 2099 This does not achieve full compatibility with Spark due to those issues, but it makes the region of incompatibility a lot smaller. If this approach isn't the one that folks would prefer, please let me know if there are different avenues you'd rather I explore! Finally, it's worth mentioning that this change was LLM-assisted. ## 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. --> Added unit tests in `datafusion/spark/src/function/datetime/timezone.rs` covering accepted spelling, the 18 hour boundary, and SystemV custom behaviour around DST transitions and exception. Added SQL logic tests in `datafusion/sqllogictest/test_files/spark/datetime/from_utc_timestamp.slt` covering the accepted spellings. ## 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. --> Yes. The existing Spark `from_utc_timestamp` UDF now accepts additional Spark timezone spellings. It also rejects offsets outside Spark's 18-hour limit. This won't affect most users since they'd need to have opted into the existing incompatible implementation. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
