Github user srowen commented on the pull request: https://github.com/apache/spark/pull/9169#issuecomment-149473946 To give you an idea of how prevalent the `@Experimental` tag is ... - Streaming: 6 - Core: 29 - SQL: 42 - ML: 93 - MLlib: 95 Worth cleaning up MLlib I think; does anyone have particular opinions about applying similar logic to ML (anything from <= 1.4.0 is no longer Experimental, in general)? There would be much less to remove there. Or, core and streaming? I could keep going to swat this in one logical change, but don't feel strongly enough to push on it. MLlib is the most important part to update.
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