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Posted to issues@spark.apache.org by "Darcy Shen (Jira)" <ji...@apache.org> on 2021/03/31 08:34:00 UTC
[jira] [Updated] (SPARK-34771) Support UDT for Pandas/Spark
convertion with Arrow Optimization
[ https://issues.apache.org/jira/browse/SPARK-34771?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Darcy Shen updated SPARK-34771:
-------------------------------
Summary: Support UDT for Pandas/Spark convertion with Arrow Optimization (was: Support UDT for Pandas with Arrow Optimization)
> Support UDT for Pandas/Spark convertion with Arrow Optimization
> ---------------------------------------------------------------
>
> Key: SPARK-34771
> URL: https://issues.apache.org/jira/browse/SPARK-34771
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark
> Affects Versions: 3.0.2, 3.1.1
> Reporter: Darcy Shen
> Priority: Major
>
> {code:python}
> spark.conf.set("spark.sql.execution.arrow.enabled", "true")
> from pyspark.testing.sqlutils import ExamplePoint
> import pandas as pd
> pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1, 1), ExamplePoint(2, 2)])})
> df = spark.createDataFrame(pdf)
> df.toPandas()
> {code}
> with `spark.sql.execution.arrow.enabled` = false, the above snippet works fine without WARNINGS.
> with `spark.sql.execution.arrow.enabled` = true, the above snippet works fine with WARNINGS. Because of Unsupported type in conversion, the Arrow optimization is actually turned off.
> Detailed steps to reproduce:
> {code:python}
> $ bin/pyspark
> Python 3.8.8 (default, Feb 24 2021, 13:46:16)
> [Clang 10.0.0 ] :: Anaconda, Inc. on darwin
> Type "help", "copyright", "credits" or "license" for more information.
> Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
> Setting default log level to "WARN".
> To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
> 21/03/17 23:13:27 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
> Welcome to
> ____ __
> / __/__ ___ _____/ /__
> _\ \/ _ \/ _ `/ __/ '_/
> /__ / .__/\_,_/_/ /_/\_\ version 3.2.0-SNAPSHOT
> /_/
> Using Python version 3.8.8 (default, Feb 24 2021 13:46:16)
> Spark context Web UI available at http://172.30.0.226:4040
> Spark context available as 'sc' (master = local[*], app id = local-1615994008526).
> SparkSession available as 'spark'.
> >>> spark.conf.set("spark.sql.execution.arrow.enabled", "true")
> 21/03/17 23:13:31 WARN SQLConf: The SQL config 'spark.sql.execution.arrow.enabled' has been deprecated in Spark v3.0 and may be removed in the future. Use 'spark.sql.execution.arrow.pyspark.enabled' instead of it.
> >>> from pyspark.testing.sqlutils import ExamplePoint
> >>> import pandas as pd
> >>> pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1, 1), ExamplePoint(2, 2)])})
> >>> df = spark.createDataFrame(pdf)
> /Users/da/github/apache/spark/python/pyspark/sql/pandas/conversion.py:332: UserWarning: createDataFrame attempted Arrow optimization because 'spark.sql.execution.arrow.pyspark.enabled' is set to true; however, failed by the reason below:
> Could not convert (1,1) with type ExamplePoint: did not recognize Python value type when inferring an Arrow data type
> Attempting non-optimization as 'spark.sql.execution.arrow.pyspark.fallback.enabled' is set to true.
> warnings.warn(msg)
> >>>
> >>> df.show()
> +----------+
> | point|
> +----------+
> |(0.0, 0.0)|
> |(0.0, 0.0)|
> +----------+
> >>> df.schema
> StructType(List(StructField(point,ExamplePointUDT,true)))
> >>> df.toPandas()
> /Users/da/github/apache/spark/python/pyspark/sql/pandas/conversion.py:87: UserWarning: toPandas attempted Arrow optimization because 'spark.sql.execution.arrow.pyspark.enabled' is set to true; however, failed by the reason below:
> Unsupported type in conversion to Arrow: ExamplePointUDT
> Attempting non-optimization as 'spark.sql.execution.arrow.pyspark.fallback.enabled' is set to true.
> warnings.warn(msg)
> point
> 0 (0.0,0.0)
> 1 (0.0,0.0)
> {code}
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