[jira] [Updated] (SPARK-19728) PythonUDF with multiple parents shouldn't be pushed down when used as a predicate
[ https://issues.apache.org/jira/browse/SPARK-19728?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Maciej Szymkiewicz updated SPARK-19728: --- Affects Version/s: (was: 2.2.0) > PythonUDF with multiple parents shouldn't be pushed down when used as a > predicate > -- > > Key: SPARK-19728 > URL: https://issues.apache.org/jira/browse/SPARK-19728 > Project: Spark > Issue Type: Bug > Components: PySpark, SQL >Affects Versions: 2.0.0, 2.1.0 >Reporter: Maciej Szymkiewicz > Fix For: 2.2.0 > > > Prior to Spark 2.0 it was possible to use Python UDF output as a predicate: > {code} > from pyspark.sql.functions import udf > from pyspark.sql.types import BooleanType > df1 = sc.parallelize([(1, ), (2, )]).toDF(["col_a"]) > df2 = sc.parallelize([(2, ), (3, )]).toDF(["col_b"]) > pred = udf(lambda x, y: x == y, BooleanType()) > df1.join(df2).where(pred("col_a", "col_b")).show() > {code} > In Spark 2.0 this is no longer possible: > {code} > spark.conf.set("spark.sql.crossJoin.enabled", True) > df1.join(df2).where(pred("col_a", "col_b")).show() > ## ... > ## Py4JJavaError: An error occurred while calling o731.showString. > : java.lang.RuntimeException: Invalid PythonUDF (col_a#132L, > col_b#135L), requires attributes from more than one child. > ## ... > {code} -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-19728) PythonUDF with multiple parents shouldn't be pushed down when used as a predicate
[ https://issues.apache.org/jira/browse/SPARK-19728?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Maciej Szymkiewicz updated SPARK-19728: --- Summary: PythonUDF with multiple parents shouldn't be pushed down when used as a predicate (was: PythonUDF with multiple parents shouldn't be pushed down when used as a predicat) > PythonUDF with multiple parents shouldn't be pushed down when used as a > predicate > -- > > Key: SPARK-19728 > URL: https://issues.apache.org/jira/browse/SPARK-19728 > Project: Spark > Issue Type: Bug > Components: PySpark, SQL >Affects Versions: 2.0.0, 2.1.0, 2.2.0 >Reporter: Maciej Szymkiewicz > > Prior to Spark 2.0 it was possible to use Python UDF output as a predicate: > {code} > from pyspark.sql.functions import udf > from pyspark.sql.types import BooleanType > df1 = sc.parallelize([(1, ), (2, )]).toDF(["col_a"]) > df2 = sc.parallelize([(2, ), (3, )]).toDF(["col_b"]) > pred = udf(lambda x, y: x == y, BooleanType()) > df1.join(df2).where(pred("col_a", "col_b")).show() > {code} > In Spark 2.0 this is no longer possible: > {code} > spark.conf.set("spark.sql.crossJoin.enabled", True) > df1.join(df2).where(pred("col_a", "col_b")).show() > ## ... > ## Py4JJavaError: An error occurred while calling o731.showString. > : java.lang.RuntimeException: Invalid PythonUDF (col_a#132L, > col_b#135L), requires attributes from more than one child. > ## ... > {code} -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org