Github user cloud-fan commented on a diff in the pull request: https://github.com/apache/spark/pull/15994#discussion_r89721405 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala --- @@ -437,4 +444,38 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) { case v => throw new IllegalArgumentException( s"Unsupported value type ${v.getClass.getName} ($v).") } + + /** + * (Scala-specific) Returns a new [[DataFrame]] that replaces null or NaN values in specified + * numeric, bool, string columns. If a specified column is not a numeric, boolean, string column, + * it is ignored. + * + * @since 2.1.0 + */ + private def fill1[T](value: T, cols: Seq[String]): DataFrame = { + value match { + case _: jl.Double | _: jl.Integer | _: jl.Float | _: jl.Boolean | _: jl.Long | _: String => + case _ => + throw new IllegalArgumentException( + s"Unsupported value type ${value.getClass.getName} ($value).") + } + + val targetColumnType = value match { --- End diff -- nit: we can combine the check here: ``` val targetType = value match { case _: Long => LongType case _: Double => DoubleType case _: String => StringType case _ => throw ... } ```
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