[jira] [Commented] (SPARK-19728) PythonUDF with multiple parents shouldn't be pushed down when used as a predicate

2019-05-15 Thread Krishna Prasanna Sistla (JIRA) 


[ 
https://issues.apache.org/jira/browse/SPARK-19728?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16840488#comment-16840488
 ] 

Krishna Prasanna Sistla commented on SPARK-19728:
-

Is it resolved ? I am still seeing this error in 2.3.1 

>  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
>Priority: Major
> 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
(v7.6.3#76005)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

[jira] [Commented] (SPARK-19728) PythonUDF with multiple parents shouldn't be pushed down when used as a predicate

2018-09-03 Thread Sergey Bahchissaraitsev (JIRA) 


[ 
https://issues.apache.org/jira/browse/SPARK-19728?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16602040#comment-16602040
 ] 

Sergey Bahchissaraitsev commented on SPARK-19728:
-

This is still happening in 2.3.1 when using the UDF inside the join "on" 
condition.
e.g.
{quote}df1.join(df2, pred(df1.col_a, df2.col_b)).show()
{quote}

I have opened for this: SPARK-25314

>  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
>Priority: Major
> 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
(v7.6.3#76005)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org