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https://issues.apache.org/jira/browse/SPARK-47525?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wenchen Fan reassigned SPARK-47525:
-----------------------------------
Assignee: Jack Chen
> Support subquery correlation joining on map attributes
> ------------------------------------------------------
>
> Key: SPARK-47525
> URL: https://issues.apache.org/jira/browse/SPARK-47525
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.5.0
> Reporter: Jack Chen
> Assignee: Jack Chen
> Priority: Major
> Labels: pull-request-available
>
> Currently, when a subquery is correlated on a condition like `outer_map[1] =
> inner_map[1]`, DecorrelateInnerQuery generates a join on the map itself,
> which is unsupported, so the query cannot run - for example:
>
> {code:java}
> scala> Seq(Map(0 -> 0)).toDF.createOrReplaceTempView("v")scala> sql("select
> v1.value[0] from v v1 where v1.value[0] > (select avg(v2.value[0]) from v v2
> where v1.value[1] = v2.value[1])").explain
> org.apache.spark.sql.AnalysisException:
> [UNSUPPORTED_SUBQUERY_EXPRESSION_CATEGORY.UNSUPPORTED_CORRELATED_REFERENCE_DATA_TYPE]
> Unsupported subquery expression: Correlated column reference 'v1.value'
> cannot be map type. SQLSTATE: 0A000; line 1 pos 49
> at
> org.apache.spark.sql.errors.QueryCompilationErrors$.unsupportedCorrelatedReferenceDataTypeError(QueryCompilationErrors.scala:2463)
> ... {code}
> However, if we rewrite the query to pull out the map access `outer_map[1]`
> into the outer plan, it succeeds:
>
> {code:java}
> scala> sql("""with tmp as (
> select value[0] as value0, value[1] as value1 from v
> )
> select v1.value0 from tmp v1 where v1.value0 > (select avg(v2.value0) from
> tmp v2 where v1.value1 = v2.value1)""").explain{code}
> Another point that can be improved is that, even if the data type supports
> join, we still don’t need to join on the full attribute, and we can get a
> better plan by doing the same rewrite to pull out the extract expression.
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