Github user srowen commented on the issue:
https://github.com/apache/spark/pull/15422
@mridulm for the scenario you're imagining, maybe the data is OK, sure.
That doesn't mean it's true in all cases. Yeah, this is really to work around
bad input, which you can to some degree do at the user level. Other parts of
Spark don't work this way. I'm neutral on whether this is a good idea at all,
but would prefer consistency more than anything.
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