spark-matcher
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Raise clear exception when dataframe(s) contain missing values
Currently, when one of the input dataframes for a Matcher object contain missing values, an unclear and seemingly unrelated error is thrown. Before starting to fit or predict, the dataframe(s) should be checked for missing values and a clear error message should be returned.