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
