[
https://issues.apache.org/jira/browse/SPARK-61147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon resolved SPARK-61147.
----------------------------------
Resolution: Fixed
Issue resolved by pull request 337
[https://github.com/apache/spark-connect-rust/pull/337]
> 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
> Assignee: Hyukjin Kwon
> Priority: Major
> Labels: pull-request-available
> 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.
--
This message was sent by Atlassian Jira
(v10.3.26#10030026)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
