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https://issues.apache.org/jira/browse/SPARK-13801?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15242436#comment-15242436
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Takeshi Yamamuro commented on SPARK-13801:
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I got this cause; wrong nullability is set in coalesce inputs such as `f("b")`
and `f("b")`.
Outer-join outputs are nullable though, `f("b")` and `f("b")` are not.
As a result, `expressions.BoundReference` generates wrong generated codes for
final outputs.
I fixed this in my pr
(https://github.com/apache/spark/pull/11371/files#diff-fa1d044f9cfe587e27866393fe18fd46R219).
> DataFrame.col should return unresolved attribute
> ------------------------------------------------
>
> Key: SPARK-13801
> URL: https://issues.apache.org/jira/browse/SPARK-13801
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Reporter: Wenchen Fan
>
> Recently I saw some JIRAs complain about wrong result when using DataFrame
> API. After checking their queries, I found it was caused by un-direct
> self-join and they build wrong join conditions. For example:
> {code}
> val df = ...
> val df2 = df.filter(...)
> df.join(df2, (df("key") + 1) === df2("key"))
> {code}
> In this case, the confusing part is: df("key") and df2("key2") reference to
> the same column, while df and df2 are different DataFrames.
> I think the biggest problem is, we give users the resolved attribute.
> However, resolved attribute is not real column, as logical plan's output may
> change. For example, we will generate new output for the right child in
> self-join.
> My proposal is: `DataFrame.col` should always return unresolved attribute. We
> can still do the resolution to make sure the given column name is resolvable,
> but don't return the resolved one, just get the name out and wrap it with
> UnresolvedAttribute.
> Now if users run the example query I gave at the beginning, they will get
> analysis exception, and they will understand they need to alias df and df2
> before join.
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