Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/16537
@rdblue i think we're maybe understanding different type checks. My
understanding is in this case the error is already thrown right away. It's also
not that the user needs to pass a callable here, were checking that the UDF is
called with column or strings as arguments.
I agree the current error message is a bit obtuse to new users, but I also
don't want us to go adding type checking to every individual function wrapper
to Py4J in another PR - that just isn't scalable given the level of committer
bandwidth available in Python. I'm think we should prioritize issues that users
have run into or figure out a more scalable way to solve this (either bigger
batches of cleanups, improved explanations of Py4J errors possible causes, or
type hints - although as zero323 points out that's a larger discussion). (And
for this type check I didn't see any posts related to it).
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