[jira] [Resolved] (SPARK-19947) RFormulaModel always throws Exception on transforming data with NULL or Unseen labels

["Joseph K. Bradley (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-19947?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley resolved SPARK-19947.
---------------------------------------
       Resolution: Fixed
    Fix Version/s: 2.4.0

I'll mark this as complete.  Those earlier PRs fixed some issues, and [SPARK-23562] should fix the rest.

> RFormulaModel always throws Exception on transforming data with NULL or Unseen labels
> -------------------------------------------------------------------------------------
>
>                 Key: SPARK-19947
>                 URL: https://issues.apache.org/jira/browse/SPARK-19947
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 2.1.0
>            Reporter: Andrey Yatsuk
>            Priority: Major
>             Fix For: 2.4.0
>
>
> 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>))



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