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https://issues.apache.org/jira/browse/SPARK-55350?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Takuya Ueshin resolved SPARK-55350.
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Fix Version/s: 4.2.0
Resolution: Fixed
Issue resolved by pull request 54144
[https://github.com/apache/spark/pull/54144]
> Convert from pandas to arrow loses row count when schema has 0 columns
> ----------------------------------------------------------------------
>
> Key: SPARK-55350
> URL: https://issues.apache.org/jira/browse/SPARK-55350
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 4.1.0, 4.2.0
> Reporter: Yicong Huang
> Assignee: Yicong Huang
> Priority: Major
> Labels: pull-request-available
> Fix For: 4.2.0
>
>
> When creating an Arrow RecordBatch with 0 columns, the row count is lost due
> to a PyArrow limitation.
> {code:python}
> import pyarrow as pa
> # Creating batch with 0 columns loses row count
> batch = pa.RecordBatch.from_arrays([], [])
> print(batch.num_rows) # Always 0, regardless of input data
> {code}
> This affects pandas UDF serializers when the return type is an empty struct.
> The row count information is lost during serialization.
> In `ArrowStreamPandasSerializer.load_stream`, there is code to handle
> 0-column batches:
> {code:python}
> if batch.num_columns == 0:
> yield [pd.Series([pyspark._NoValue] * batch.num_rows)]
> {code}
> However, this doesn't help because `batch.num_rows` is already 0 when the
> batch was created.
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