[SPARK-46995][SQL] Allow AQE coalesce final stage in SQL cached plan #45054
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@cloud-fan @maryannxue Please help review this change, thanks! |
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sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
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sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala
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…onf.scala Co-authored-by: Wenchen Fan <[email protected]>
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cc @yaooqinn |
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thanks, merging to master! |
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@liuzqt can you correct the JIRA ticket ID? It seems wrong. |
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What changes were proposed in this pull request?
#43435 and #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):
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
truesemantic of old behavior)Also, to keep the default behavior unchanged, we might want to flip the default value of spark.sql.optimizer.canChangeCachedPlanOutputPartitioning to
falseWhy are the changes needed?
To allow AQE coalesce final stage in SQL cached plan. Also make the semantic of
spark.sql.optimizer.canChangeCachedPlanOutputPartitioningmore reasonable.Does this PR introduce any user-facing change?
How was this patch tested?
Updated UTs.
Was this patch authored or co-authored using generative AI tooling?
No