I want to run constrained linear regression in pyspark. I know that it is not directly supported by ML library. but is there a way to do it? I have looked at other answer which convert pyspark data frame to numpy array and then use scipy.optimize.minimize library but that is slow. Is there a way to do it directly on pyspark dataframe using some UDF which use a distributed computing environment as my dataframe is very big?
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