Jack Chen created SPARK-47525:
---------------------------------
Summary: 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
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:
{{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)
...}}
However, if we rewrite the query to pull out the map access `outer_map[1]` into
the outer plan, it succeeds:
{{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}}
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.
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
