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.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
