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 >>>> >>> >>>
