There are several JIRA's and/or PR's that contain logic the Data Science teams that I work with use in their local models. We are trying to determine if/when these features may gain traction again. In at least one case all of the work were done but the shepherd said that getting it committed were of lower priority than other tasks - one specifically mentioned was the mllib/ml parity that has been ongoing for nearly three years.
In order to prioritize work that the ML platform would do it would be helpful to know at least which if any of those tasks were going to be moved ahead by the community: since we could then focus on other ones instead of duplicating the effort. In addition there are some engineering code jam sessions that happen periodically: knowing which features are actively on the roadmap would *certainly *influence our selection of work. The roadmaps from 2.2.0 and earlier were a very good starting point to understand not just the specific work in progress - but also the current mindset/thinking of the committers in terms of general priorities. So if the same format of document were not available - then what content *is *that gives a picture of where spark.ml were headed? 2017-11-29 6:39 GMT-08:00 Stephen Boesch <java...@gmail.com>: > Any further information/ thoughts? > > > > 2017-11-22 15:07 GMT-08:00 Stephen Boesch <java...@gmail.com>: > >> The roadmaps for prior releases e.g. 1.6 2.0 2.1 2.2 were available: >> >> 2.2.0 https://issues.apache.org/jira/browse/SPARK-18813 >> >> 2.1.0 https://issues.apache.org/jira/browse/SPARK-15581 >> .. >> >> It seems those roadmaps were not available per se' for 2.3.0 and later? >> Is there a different mechanism for that info? >> >> stephenb >> > >
