Dear

My name is Cederic Bosmans and I am a masters student at the Ghent
University (Belgium).
I am currently working on my masters dissertation which involves Apache
Flink.

I want to make predictions in the streaming environment based on a model
trained in the batch environment.

I trained my SVM-model this way:
val svm2 = SVM()
svm2.setSeed(1)
svm2.fit(trainLV)
val testVD = testLV.map(lv => (lv.vector, lv.label))
val evalSet = svm2.evaluate(testVD)

and saved the model:
val modelSvm = svm2.weightsOption.get

Then I have an incoming datastream in the streaming environment:
dataStream[(Int, Int, Int)]
which should be bininary classified using this trained SVM model.

Since the predict function does only support DataSet and not DataStream, on
stackoverflow a flink contributor mentioned that this should be done using
a map/flatMap function.
Unfortunately I am not able to work this function out.

It would be incredible for me if you could help me a little bit further!

Kind regards and thanks in advance
Cederic Bosmans

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