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https://issues.apache.org/jira/browse/SPARK-57964?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ruifeng Zheng reassigned SPARK-57964:
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Assignee: Anas Khan
> DataFrame.dropna raises AssertionError instead of PySparkValueError on
> invalid 'how'
> ------------------------------------------------------------------------------------
>
> Key: SPARK-57964
> URL: https://issues.apache.org/jira/browse/SPARK-57964
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 4.1.0
> Reporter: Anas Khan
> Assignee: Anas Khan
> Priority: Minor
> Labels: pull-request-available
>
> DataFrame.dropna validates the `how` argument and is meant to raise
> PySparkValueError with error class VALUE_NOT_ANY_OR_ALL on an invalid value.
> The messageParameters passed a key named `arg_type`, but the
> VALUE_NOT_ANY_OR_ALL template interpolates <arg_value>:
> "Value for `<arg_name>` must be 'any' or 'all', got '<arg_value>'."
> ErrorClassesReader.get_error_message (python/pyspark/errors/utils.py) asserts
> that the set of template placeholders equals the set of provided message
> parameters. Since \{arg_name, arg_value} != \{arg_name, arg_type}, the
> assertion
> fires inside PySparkException.__init__, so df.dropna(how="foo") surfaces an
> opaque AssertionError instead of the intended PySparkValueError.
> Fix: rename the messageParameters key `arg_type` -> `arg_value` at that single
> call site (the value, `how`, is unchanged) and add a regression test.
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