Hyukjin Kwon created SPARK-61147:
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Summary: 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
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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