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https://issues.apache.org/jira/browse/SPARK-55674?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon reassigned SPARK-55674:
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Assignee: Yicong Huang
> Apply consistent 0-column pandas-to-Arrow fix
> ---------------------------------------------
>
> Key: SPARK-55674
> URL: https://issues.apache.org/jira/browse/SPARK-55674
> Project: Spark
> Issue Type: Improvement
> Components: PySpark
> Affects Versions: 4.2.0
> Reporter: Yicong Huang
> Assignee: Yicong Huang
> Priority: Major
> Labels: pull-request-available
>
> Follow-up to SPARK-55600 (PR #54382).
> Reviewer ueshin noted that the 0-column pandas-to-Arrow fix should also be
> applied to similar places:
> * {{python/pyspark/sql/connect/session.py}} around line 626, which uses
> {{pa.Table.from_struct_array(pa.array([{}] * len(data), type=pa.struct([])))}}
> * -{{python/pyspark/sql/conversion.py}} around line 289, which uses
> {{pa.RecordBatch.from_struct_array(pa.array([{}] * len(data), arrow_type))}}-
>
> Here schema may have more fields but data frame is empty. So we need to
> create it out instead of converting it. So this case does not apply.
> These should use the same approach introduced in SPARK-55600 for consistency.
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