liuzqt opened a new pull request, #45054: URL: https://github.com/apache/spark/pull/45054
### What changes were proposed in this pull request? https://github.com/apache/spark/pull/43435 and https://github.com/apache/spark/pull/43760 are fixing a correctness issue which will be triggered when AQE applied on cached query plan, specifically, when AQE coalescing the final result stage of the cached plan. The current semantic of `spark.sql.optimizer.canChangeCachedPlanOutputPartitioning` ([source code](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/CacheManager.scala#L403-L411)): when true, we enable AQE, but disable coalescing final stage (default) when false, we disable AQE But let’s revisit the semantic of this config: actually for caller the only thing that matters is whether we change the output partitioning of the cached plan. And we should only try to apply AQE if possible. Thus we want to modify the semantic of spark.sql.optimizer.canChangeCachedPlanOutputPartitioning when true, we enable AQE and allow coalescing final: this might lead to perf regression, because it introduce extra shuffle when false, we enable AQE, but disable coalescing final stage. (this is actually the `true` semantic of old behavior) Also, to keep the default behavior unchanged, we might want to flip the default value of spark.sql.optimizer.canChangeCachedPlanOutputPartitioning to `false` ### Why are the changes needed? To allow AQE coalesce final stage in SQL cached plan. Also make the semantic of `spark.sql.optimizer.canChangeCachedPlanOutputPartitioning` more reasonable. ### Does this PR introduce _any_ user-facing change? <!-- Note that it means *any* user-facing change including all aspects such as the documentation fix. If yes, please clarify the previous behavior and the change this PR proposes - provide the console output, description and/or an example to show the behavior difference if possible. If possible, please also clarify if this is a user-facing change compared to the released Spark versions or within the unreleased branches such as master. If no, write 'No'. --> ### How was this patch tested? Updated UTs. ### Was this patch authored or co-authored using generative AI tooling? No -- 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]
