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https://issues.apache.org/jira/browse/SPARK-48302?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ian Cook updated SPARK-48302:
-----------------------------
    Description: 
Because of a limitation in PyArrow, when PyArrow Tables are passed to 
{{spark.createDataFrame()}}, null values in MapArray columns are replaced with 
empty lists.

The PySpark function where this happens is 
{{pyspark.sql.pandas.types._check_arrow_array_timestamps_localize}}.

Also see [https://github.com/apache/arrow/issues/41684].

See the skipped tests and the TODO mentioning SPARK-48302.

A possible fix for this will involve adding a {{mask}} argument to 
{{pa.MapArray.from_arrays}}. But since older versions of PyArrow (which PySpark 
will still support for a while) won't have this argument, we will need to do a 
check like:

{{if LooseVersion(pa._{_}version{_}_) >= LooseVersion("1X.0.0"):}}

or

{{from inspect import signature}}
{{"mask" in signature(pa.MapArray.from_arrays).parameters}}

and only passĀ {{mask}} if that's true.

  was:
Because of a limitation in PyArrow, when PyArrow Tables are passed to 
spark.createDataFrame(), null values in MapArray columns are replaced with 
empty lists.

The PySpark function where this happens is pyspark.sql.pandas.types.
_check_arrow_array_timestamps_localize.
Also see [https://github.com/apache/arrow/issues/41684].

See the skipped tests and the TODO mentioning SPARK-48302.


> Null values in map columns of PyArrow tables are replaced with empty lists
> --------------------------------------------------------------------------
>
>                 Key: SPARK-48302
>                 URL: https://issues.apache.org/jira/browse/SPARK-48302
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 4.0.0
>            Reporter: Ian Cook
>            Priority: Major
>
> Because of a limitation in PyArrow, when PyArrow Tables are passed to 
> {{spark.createDataFrame()}}, null values in MapArray columns are replaced 
> with empty lists.
> The PySpark function where this happens is 
> {{pyspark.sql.pandas.types._check_arrow_array_timestamps_localize}}.
> Also see [https://github.com/apache/arrow/issues/41684].
> See the skipped tests and the TODO mentioning SPARK-48302.
> A possible fix for this will involve adding a {{mask}} argument to 
> {{pa.MapArray.from_arrays}}. But since older versions of PyArrow (which 
> PySpark will still support for a while) won't have this argument, we will 
> need to do a check like:
> {{if LooseVersion(pa._{_}version{_}_) >= LooseVersion("1X.0.0"):}}
> or
> {{from inspect import signature}}
> {{"mask" in signature(pa.MapArray.from_arrays).parameters}}
> and only passĀ {{mask}} if that's true.



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