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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2021/11/08 02:46:00 UTC
[jira] [Assigned] (SPARK-34521) spark.createDataFrame does not
support Pandas StringDtype extension type
[ https://issues.apache.org/jira/browse/SPARK-34521?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-34521:
------------------------------------
Assignee: (was: Apache Spark)
> spark.createDataFrame does not support Pandas StringDtype extension type
> ------------------------------------------------------------------------
>
> Key: SPARK-34521
> URL: https://issues.apache.org/jira/browse/SPARK-34521
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 3.0.1
> Reporter: Pavel Ganelin
> Priority: Major
>
> 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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