Hi to all, I'm building a recommendation system to my application. I have a set of logs (that contains the user info, the hour, the button that was clicked ect...) that arrive to my Flink by kafka, then I save every log in a HDFS (HADOOP), but know I have a problem, I want to apply ML to (all) my data.
I think in 2 scenarios: First : Transform my DataStream in a DataSet and perform the ML task. It is possible? Second : Preform a task in flink that get the data from Hadoop and perform the ML task. What is the best way to do it? I already check the IncrementalLearningSkeleton but I didn't understand how to apply that to an actual real case. Is there some complex example that I could look? ( https://github.com/apache/flink/tree/master/flink-examples/flink-examples-streaming/src/main/java/org/apache/flink/streaming/examples/ml ) Another thing that I would like to ask is how to perform the second scenario, where I need to perform this task every hour, what it is the best way to do it? Thanks, Fábio Dias.
