Sorry for the wrong link, what you should refer is jpmml-sparkml ( https://github.com/jpmml/jpmml-sparkml).
Thanks Yanbo 2016-07-24 4:46 GMT-07:00 Yanbo Liang <yblia...@gmail.com>: > Spark does not support exporting ML models to PMML currently. You can try > the third party jpmml-spark (https://github.com/jpmml/jpmml-spark) > package which supports a part of ML models. > > Thanks > Yanbo > > 2016-07-20 11:14 GMT-07:00 Ajinkya Kale <kaleajin...@gmail.com>: > >> Just found Google dataproc has a preview of spark 2.0. Tried it and >> save/load works! Thanks Shuai. >> Followup question - is there a way to export the pyspark.ml models to >> PMML ? If not, what is the best way to integrate the model for inference in >> a production service ? >> >> On Tue, Jul 19, 2016 at 8:22 PM Ajinkya Kale <kaleajin...@gmail.com> >> wrote: >> >>> I am using google cloud dataproc which comes with spark 1.6.1. So >>> upgrade is not really an option. >>> No way / hack to save the models in spark 1.6.1 ? >>> >>> On Tue, Jul 19, 2016 at 8:13 PM Shuai Lin <linshuai2...@gmail.com> >>> wrote: >>> >>>> It's added in not-released-yet 2.0.0 version. >>>> >>>> https://issues.apache.org/jira/browse/SPARK-13036 >>>> https://github.com/apache/spark/commit/83302c3b >>>> >>>> so i guess you need to wait for 2.0 release (or use the current rc4). >>>> >>>> On Wed, Jul 20, 2016 at 6:54 AM, Ajinkya Kale <kaleajin...@gmail.com> >>>> wrote: >>>> >>>>> Is there a way to save a pyspark.ml.feature.PCA model ? I know mllib >>>>> has that but mllib does not have PCA afaik. How do people do model >>>>> persistence for inference using the pyspark ml models ? Did not find any >>>>> documentation on model persistency for ml. >>>>> >>>>> --ajinkya >>>>> >>>> >>>> >
