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https://issues.apache.org/jira/browse/SPARK-60991?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-60991.
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Resolution: Fixed
Issue resolved by pull request 194
[https://github.com/apache/spark-connect-rust/pull/194]
> Show a DataFrame as the server formats it, with truncate and vertical, in
> Spark Connect Rust as PySpark does
> ------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-60991
> URL: https://issues.apache.org/jira/browse/SPARK-60991
> 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
>
>
> In PySpark Connect, {{DataFrame.show(n=20, truncate=True, vertical=False)}}
> sends a {{ShowString}} relation with the number of rows, the truncation and
> the vertical flag, and prints the table that the server formats:
> {noformat}
> +---+
> | id|
> +---+
> | 0|
> | 1|
> +---+
> {noformat}
> It raises {{PySparkTypeError}} {{NOT_EXPECTED_TYPE}} for an {{n}} that is not
> an int, a {{vertical}} that is not a bool, and a {{truncate}} that is
> neither. The Rust-backed Python client collects the first {{n}} rows and
> prints each with Rust's {{println!}}, as {{[0]}} and {{[1]}}, ignoring
> {{truncate}} and {{vertical}} and writing past Python's {{sys.stdout}}, so a
> notebook or {{contextlib.redirect_stdout}} does not get the output. The Rust
> {{DataFrame::show}} prints the same. Show the DataFrame as PySpark does.
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