Hi everyone.
I have a requirement to run prediction for random forest model locally on a
web-service without touching spark at all in some specific cases. I've
achieved that with previous mllib API (java 8 syntax):
public List<Tuple2<Double, Double>> predictLocally(RandomForestModel
model, List<LabeledPoint> data) {
return data.stream()
.map(point -> new Tuple2<>(model.predict(point.features()),
point.label()))
.collect(Collectors.toList());
}
So I have instance of trained model and can use it any way I want.
The question is whether it's possible to run this on the driver itself with
the following:
DataFrame predictions = model.transform(test);
because AFAIU test has to be a DataFrame, which means it's going to be run
on the cluster.
The use case to run it on driver is very small amount of data for
prediction - much faster to handle it this way, than using spark cluster.
Thank you.
--
Be well!
Jean Morozov
