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https://issues.apache.org/jira/browse/SPARK-61147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-61147:
---------------------------------
    Fix Version/s: connect-rust-4.3.0

> Refer to the column of withMetadata and pivot through the DataFrame, so a 
> missing column is CANNOT_RESOLVE_DATAFRAME_COLUMN as in PySpark
> -----------------------------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-61147
>                 URL: https://issues.apache.org/jira/browse/SPARK-61147
>             Project: Spark
>          Issue Type: Bug
>          Components: Connect
>    Affects Versions: connect-rust-4.3.0
>            Reporter: Hyukjin Kwon
>            Priority: Major
>             Fix For: connect-rust-4.3.0
>
>
> withMetadata("nope", ...) and groupBy(...).pivot("nope") raise 
> AnalysisException UNRESOLVED_COLUMN.WITH_SUGGESTION, because the Python 
> client resolves the column by name. PySpark refers to it through the 
> DataFrame (self[columnName], self._df[pivot_col]), bound to the plan ID of 
> the DataFrame, so the error is CANNOT_RESOLVE_DATAFRAME_COLUMN. The fix 
> builds those columns with DataFrame::col, as the other DataFrame-bound 
> columns do.



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