The SparkR callJMethod can only invoke methods as they show up in the
Java byte code. So in this case you'll need to check the SparkContext
byte code (with javap or something like that) to see how that method
looks. My guess is the type is passed in as a class tag argument, so
you'll need to do something like create a class tag for the
LinearRegressionModel and pass that in as the first or last argument
etc.
Thanks
Shivaram
On Wed, Dec 9, 2015 at 10:11 AM, Chris Freeman <cfree...@alteryx.com> wrote:
> Hey everyone,
>
> I’m currently looking at ways to save out SparkML model objects from SparkR
> and I’ve had some luck putting the model into an RDD and then saving the RDD
> as an Object File. Once it’s saved, I’m able to load it back in with
> something like:
>
> sc.objectFile[LinearRegressionModel](“path/to/model”)
>
> I’d like to try and replicate this same process from SparkR using the JVM
> backend APIs (e.g. “callJMethod”), but so far I haven’t been able to
> replicate my success and I’m guessing that it’s (at least in part) due to
> the necessity of specifying the type when calling the objectFile method.
>
> Does anyone know if this is actually possible? For example, here’s what I’ve
> come up with so far:
>
> loadModel <- function(sc, modelPath) {
> modelRDD <- SparkR:::callJMethod(sc,
>
> "objectFile[PipelineModel]",
> modelPath,
> SparkR:::getMinPartitions(sc, NULL))
> return(modelRDD)
> }
>
> Any help is appreciated!
>
> --
> Chris Freeman
>
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