[jira] [Updated] (ARROW-11747) [Python] spark.createDataFrame does not support Pandas StringDtype extension type.

["Nic Crane (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-11747?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Nic Crane updated ARROW-11747:
------------------------------
    Summary: [Python] spark.createDataFrame does not support Pandas StringDtype extension type.  (was: spark.createDataFrame does not support Pandas StringDtype extension type.)

> [Python] spark.createDataFrame does not support Pandas StringDtype extension type.
> ----------------------------------------------------------------------------------
>
>                 Key: ARROW-11747
>                 URL: https://issues.apache.org/jira/browse/ARROW-11747
>             Project: Apache Arrow
>          Issue Type: Bug
>    Affects Versions: 3.0.0
>            Reporter: Pavel Ganelin
>            Priority: Critical
>
> The following test case demonstrates the problem:
> {code:java}
> import pandas as pd
> from pyspark.sql import SparkSession, types
> spark = SparkSession.builder.appName(__file__)\
>     .config("spark.sql.execution.arrow.pyspark.enabled","true") \
>     .getOrCreate()
> good = pd.DataFrame([["abc"]], columns=["col"])
> schema = types.StructType([types.StructField("col", types.StringType(), True)])
> df = spark.createDataFrame(good, schema=schema)
> df.show()
> bad = good.copy()
> bad["col"]=bad["col"].astype("string")
> schema = types.StructType([types.StructField("col", types.StringType(), True)])
> df = spark.createDataFrame(bad, schema=schema)
> df.show()
> {code}
> The error:
> {code:java}
> C:\Python\3.8.3\lib\site-packages\pyspark\sql\pandas\conversion.py:289: UserWarning: createDataFrame attempted Arrow optimization because 'spark.sql.execution.arrow.pyspark.enabled' is set to true; however, failed by the reason below:
>   Cannot specify a mask or a size when passing an object that is converted with the __arrow_array__ protocol.
> Attempting non-optimization as 'spark.sql.execution.arrow.pyspark.fallback.enabled' is set to true.
>   warnings.warn(msg)
> {code}



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