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https://issues.apache.org/jira/browse/SPARK-43156?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17716312#comment-17716312
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Ignite TC Bot commented on SPARK-43156:
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User 'jchen5' has created a pull request for this issue:
https://github.com/apache/spark/pull/40946
> Correctness COUNT bug in correlated scalar subselect with `COUNT(*) is null`
> ----------------------------------------------------------------------------
>
> Key: SPARK-43156
> URL: https://issues.apache.org/jira/browse/SPARK-43156
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 3.4.0
> Reporter: Jack Chen
> Priority: Major
>
> Example query:
> {code:java}
> spark.sql("select *, (select (count(1)) is null from t1 where t0.a = t1.c)
> from t0").collect()
> res6: Array[org.apache.spark.sql.Row] = Array([1,1.0,null], [2,2.0,false])
> {code}
> In this subquery, count(1) always evaluates to a non-null integer value, so
> count(1) is null is always false. The correct evaluation of the subquery is
> always false.
> We incorrectly evaluate it to null for empty groups. The reason is that
> NullPropagation rewrites Aggregate [c] [isnull(count(1))] to Aggregate [c]
> [false] - this rewrite would be correct normally, but in the context of a
> scalar subquery it breaks our count bug handling in
> RewriteCorrelatedScalarSubquery.constructLeftJoins . By the time we get
> there, the query appears to not have the count bug - it looks the same as if
> the original query had a subquery with select any_value(false) from r..., and
> that case is _not_ subject to the count bug.
>
> Postgres comparison show correct always-false result:
> [http://sqlfiddle.com/#!17/67822/5]
> DDL for the example:
> {code:java}
> create or replace temp view t0 (a, b)
> as values
> (1, 1.0),
> (2, 2.0);
> create or replace temp view t1 (c, d)
> as values
> (2, 3.0); {code}
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