Github user rdblue commented on the issue:
https://github.com/apache/spark/pull/21306
@felixcheung, we're waiting on more reviews and a community decision about
how to pass partition transforms.
For passing transforms, I think the most reasonable compromise is to go
with a generic function application, so each transform would be passed as a
function/transform name with one or more arguments, where each argument is
either a column reference (by name) or a literal value. That's a fairly small
public API addition but it supports a lot of different partitioning schemes to
be expressed, including the one above for Kudu.
We already have all of this implemented based on the current PR, but I can
update this in the next week or so.
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