[jira] [Commented] (SPARK-34545) PySpark Python UDF return inconsistent results when applying 2 UDFs with different return type to 2 columns together

["Takeshi Yamamuro (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-34545?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17292564#comment-17292564 ] 

Takeshi Yamamuro commented on SPARK-34545:
------------------------------------------

Added `correctness` in the label.

> PySpark Python UDF return inconsistent results when applying 2 UDFs with different return type to 2 columns together
> --------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-34545
>                 URL: https://issues.apache.org/jira/browse/SPARK-34545
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark, SQL
>    Affects Versions: 3.0.0
>            Reporter: Baohe Zhang
>            Priority: Blocker
>              Labels: correctness
>
> Python UDF returns inconsistent results between evaluating 2 columns together and evaluating one by one.
> The issue occurs after we upgrading to spark3, so seems it doesn't exist in spark2.
> How to reproduce it?
> {code:python}
> df = spark.createDataFrame([([(1.0, "1"), (1.0, "2"), (1.0, "3")], [(1, "1"), (1, "2"), (1, "3")]), ([(2.0, "1"), (2.0, "2"), (2.0, "3")], [(2, "1"), (2, "2"), (2, "3")]), ([(3.1, "1"), (3.1, "2"), (3.1, "3")], [(3, "1"), (3, "2"), (3, "3")])], ['c1', 'c2'])
> from pyspark.sql.functions import udf
> from pyspark.sql.types import *
> def getLastElementWithTimeMaster(data_type):
>     def getLastElementWithTime(list_elm):
>         # x should be a list of (val, time)
>         y = sorted(list_elm, key=lambda x: x[1]) # default is ascending
>         return y[-1][0]
>     return udf(getLastElementWithTime, data_type)
> # Add 2 columns whcih apply Python UDF
> df = df.withColumn("c3", getLastElementWithTimeMaster(DoubleType())("c1"))
> df = df.withColumn("c4", getLastElementWithTimeMaster(IntegerType())("c2"))
> # Show the results
> df.select("c3").show()
> df.select("c4").show()
> df.select("c3", "c4").show()
> {code}
> Results:
> {noformat}
> >>> df.select("c3").show()
> +---+                                                                           
> | c3|
> +---+
> |1.0|
> |2.0|
> |3.1|
> +---+
> >>> df.select("c4").show()
> +---+
> | c4|
> +---+
> |  1|
> |  2|
> |  3|
> +---+
> >>> df.select("c3", "c4").show()
> +---+----+
> | c3|  c4|
> +---+----+
> |1.0|null|
> |2.0|null|
> |3.1|   3|
> +---+----+
> {noformat}
> The test was done in branch-3.1 local mode.



--
This message was sent by Atlassian Jira
(v8.3.4#803005)

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