Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/7320#issuecomment-120512893
@FlytxtRnD I should have realized this before, but I think this may be
fairly difficult to do. ML save/load relies on DataFrame serialization, so
Item needs to be a SQL DataType. I think you will need to use Scala reflection
to see if the Item type is a DataType, and only save if so. Are you familiar
with Scala reflection?
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