Github user MLnick commented on the issue:
https://github.com/apache/spark/pull/14473
@ZunwenYou sorry if I was not clear on the JIRA. I said there that this
should probably be done as a Spark package external to the core initially. That
way you can gather some user feedback and performance numbers etc.
If this is to be implemented within Spark then as Seth mentions it makes
more sense to go into the `ml` API. In this case we need more work and
discussion to see how to add different optimizers and make them available to
the different models with a unified API.
It would also need some performance comparisons to the current optimizer
options.
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