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Apache Spark commented on SPARK-34771: -------------------------------------- User 'sadhen' has created a pull request for this issue: https://github.com/apache/spark/pull/32321 > Support UDT for Pandas/Spark conversion with Arrow support Enabled > ------------------------------------------------------------------ > > 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} -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org