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https://issues.apache.org/jira/browse/SPARK-45657?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17779281#comment-17779281
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John Zhuge commented on SPARK-45657:
------------------------------------
Root cause:
# SQL UNION of 2 sides with different data types produce a Project of Project
on 1 side to cast the type. When this is cached, the Project of Project is
preserved.
{noformat}
Distinct
+- Union false, false
:- Project [cast(id#153 as string) AS id#155]
: +- Project [1 AS id#153]
: +- OneRowRelation
+- Project [s2 AS id#154]
+- OneRowRelation{noformat}
# Dataset.union applies `CombineUnions` which applies to all unions in the
tree. CombineUnions collapses the 2 Projects into 1. Thus Dataset.union of the
above plan with any plan will not be find a matching cached plan.
> Caching SQL UNION of different column data types does not work inside
> Dataset.union
> -----------------------------------------------------------------------------------
>
> Key: SPARK-45657
> URL: https://issues.apache.org/jira/browse/SPARK-45657
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.4.1
> Reporter: John Zhuge
> Priority: Major
>
>
> Cache SQL UNION of 2 sides with different column data types
> {code:java}
> scala> spark.sql("select 1 id union select 's2' id").cache() {code}
> Dataset.union does not leverage the cache
> {code:java}
> scala> spark.sql("select 1 id union select 's2' id").union(spark.sql("select
> 's3'")).queryExecution.optimizedPlan
> res15: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan =
> Union false, false
> :- Aggregate [id#109], [id#109]
> : +- Union false, false
> : :- Project [1 AS id#109]
> : : +- OneRowRelation
> : +- Project [s2 AS id#108]
> : +- OneRowRelation
> +- Project [s3 AS s3#111]
> +- OneRowRelation {code}
> SQL UNION of the cached SQL UNION does use the cache! Please note
> `InMemoryRelation` used.
> {code:java}
> scala> spark.sql("(select 1 id union select 's2' id) union select
> 's3'").queryExecution.optimizedPlan
> res16: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan =
> Aggregate [id#117], [id#117]
> +- Union false, false
> :- InMemoryRelation [id#117], StorageLevel(disk, memory, deserialized, 1
> replicas)
> : +- *(4) HashAggregate(keys=[id#100], functions=[], output=[id#100])
> : +- Exchange hashpartitioning(id#100, 500), ENSURE_REQUIREMENTS,
> [plan_id=241]
> : +- *(3) HashAggregate(keys=[id#100], functions=[],
> output=[id#100])
> : +- Union
> : :- *(1) Project [1 AS id#100]
> : : +- *(1) Scan OneRowRelation[]
> : +- *(2) Project [s2 AS id#99]
> : +- *(2) Scan OneRowRelation[]
> +- Project [s3 AS s3#116]
> +- OneRowRelation {code}
>
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