[SPARK-22347] UDF is evaluated when 'F.when' condition is false

• Type: Documentation
• Status: Resolved
• Priority: Minor
• Resolution: Won't Fix
• Affects Version/s: 2.2.0
• Component/s: PySpark
• Assignee: L. C. Hsieh
• Reporter: Nicolas Porter
• Created: 25/Oct/17 00:52
• Updated: 13/Aug/18 17:55
• Resolved: 13/Aug/18 16:28

Description

Here's a simple example on how to reproduce this:

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)

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.

Issue Links

• is duplicated by: SPARK-25060 PySpark UDF in case statement is always run
• links to: [Github] Pull Request #19584 (viirya)
• links to: [Github] Pull Request #19592 (viirya)
• links to: [Github] Pull Request #19617 (viirya)