Dear developers,
I am trying to build a machine learning-based UDF for classification. This involves loading in a model that has been trained offline, which in practice basically is deserialization of a big object. This process of deserialization takes a significant amount of time, but it only "needs" to happen once, and after that the model can do the classification rather rapidly. Therefore, in order to avoid having to load the model every time the UDF is called, I am wondering where in the UDF lifecycle I can do the loading in order to achieve a "load model once, classify infinitely"-scenario, and how to implement it. I am assuming it should be done somewhere inside the factory-function-relationship, but I am not sure where/how and can't seem to find a lot of documentation on it. All help is appreciated, thanks! Best wishes, Torsten
