Looking forward to the blog post. Thanks for for pointing me to some of the simpler classes. Nick Pentreath <nick.pentre...@gmail.com> schrieb am Fr. 18. Nov. 2016 um 02:53:
> @Holden look forward to the blog post - I think a user guide PR based on > it would also be super useful :) > > > On Fri, 18 Nov 2016 at 05:29 Holden Karau <holden.ka...@gmail.com> wrote: > > I've been working on a blog post around this and hope to have it published > early next month 😀 > > On Nov 17, 2016 10:16 PM, "Joseph Bradley" <jos...@databricks.com> wrote: > > Hi Georg, > > It's true we need better documentation for this. I'd recommend checking > out simple algorithms within Spark for examples: > ml.feature.Tokenizer > ml.regression.IsotonicRegression > > You should not need to put your library in Spark's namespace. The shared > Params in SPARK-7146 are not necessary to create a custom algorithm; they > are just niceties. > > Though there aren't great docs yet, you should be able to follow existing > examples. And I'd like to add more docs in the future! > > Good luck, > Joseph > > On Wed, Nov 16, 2016 at 6:29 AM, Georg Heiler <georg.kf.hei...@gmail.com> > wrote: > > HI, > > I want to develop a library with custom Estimator / Transformers for > spark. So far not a lot of documentation could be found but > http://stackoverflow.com/questions/37270446/how-to-roll-a-custom-estimator-in-pyspark-mllib > > > Suggest that: > Generally speaking, there is no documentation because as for Spark 1.6 / > 2.0 most of the related API is not intended to be public. It should change > in Spark 2.1.0 (see SPARK-7146 > <https://issues.apache.org/jira/browse/SPARK-7146>). > > Where can I already find documentation today? > Is it true that my library would require residing in Sparks`s namespace > similar to https://github.com/collectivemedia/spark-ext to utilize all > the handy functionality? > > Kind Regards, > Georg > > > >
