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https://issues.apache.org/jira/browse/SPARK-22347?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16578549#comment-16578549
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Ryan Blue commented on SPARK-22347:
-----------------------------------
[~viirya], [~cloud_fan]: Is there any objection to changing the resolution of
this issue to "Won't Fix" instead of "Fixed"? Just documenting the behavior is
not a fix.
If I don't hear anything in the next day or so, I'll update it.
> UDF is evaluated when 'F.when' condition is false
> -------------------------------------------------
>
> Key: SPARK-22347
> URL: https://issues.apache.org/jira/browse/SPARK-22347
> Project: Spark
> Issue Type: Documentation
> Components: PySpark
> Affects Versions: 2.2.0
> Reporter: Nicolas Porter
> Assignee: Liang-Chi Hsieh
> Priority: Minor
> Fix For: 2.3.0
>
>
> Here's a simple example on how to reproduce this:
> {code}
> from pyspark.sql import functions as F, Row, types
> def Divide10():
> def fn(value): return 10 / int(value)
> return F.udf(fn, types.IntegerType())
> df = sc.parallelize([Row(x=5), Row(x=0)]).toDF()
> x = F.col('x')
> df2 = df.select(F.when((x > 0), Divide10()(x)))
> df2.show(200)
> {code}
> This raises a division by zero error, even if `F.when` is trying to filter
> out all cases where `x <= 0`. I believe the correct behavior should be not to
> evaluate the UDF when the `F.when` condition is false.
> Interestingly enough, when the `F.when` condition is set to `F.lit(False)`,
> then the error is not raised and all rows resolve to `null`, which is the
> expected result.
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