RFormulaModel always throws Exception on transforming data with NULL or Unseen labels

I have trained ML model and big data table in parquet. I want add new column to this table with predicted values. I can't lose any data, but can having null values in it.

RFormulaModel.fit() method creates new StringIndexer with default (handleInvalid="error") parameter. Also VectorAssembler on NULL values throwing Exception. So I must call df.na.drop() to transform this DataFrame and I don't want to do this.

Need add to RFormula new parameter like handleInvalid in StringIndexer.

Or add transform(Seq<Column>): Vector method which user can use as UDF method in df.withColumn("predicted", functions.callUDF(rFormulaModel::transform, Seq<Column>))