It's an open issue : https://issues.apache.org/jira/browse/SPARK-4587
That's being said, you can workaround the issue by serializing the Model
(simple java serialization) and then restoring it before calling the
predicition job.
Best Regards,
On 22/10/2015 14:33, Sebastian Kuepers wrote:
> Hey,
Hi Sebastian,
You can save models to disk and load them back up. In the snippet below
(copied out of a working Databricks notebook), I train a model, then save
it to disk, then retrieve it back into model2 from disk.
import org.apache.spark.mllib.tree.RandomForest
> import org.apache.spark.mllib.
