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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