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[P] Filtering data in a Pyspark Pipeline without losing all the data?

I have a project where I’m feeding a dataframe into a PipelineModel with two pretrained models inside. The flow goes something like this:

Input DF -> Preprocessing Transformers -> Model1 -> Model2 -> Output DF

The thing is, Model1 and Model2 predict on different values (e.g. Male vs Female). I tried using the SQLTransformer to filter the data on each type, but I drop everything, so the output of Model1 throws away all the data I need to predict in Model2.

Is there a way to filter data to be fed into Model1, then filter data to be fed into Model2, and then concatenate the dataframes to be returned?

Please let me know if I can clarify anything!

submitted by /u/Octosaurus
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.