Github user windpiger commented on a diff in the pull request:
https://github.com/apache/spark/pull/15994#discussion_r89742322
--- 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).")
}
+
+ /**
+ * Returns a new [[DataFrame]] that replaces null or NaN values in
specified
+ * numeric, string columns. If a specified column is not a numeric,
string column,
+ * it is ignored.
+ */
+ private def fill1[T](value: T, cols: Seq[String]): DataFrame = {
+ // the fill[T] which T is Long/Integer/Float/Double,
+ // should apply on all the NumericType Column, for example:
+ // val input = Seq[(java.lang.Integer, java.lang.Double)]((null,
164.3)).toDF("a","b")
+ // input.na.fill(3.1)
+ // the result is (3,164.3), not (null, 164.3)
+ val targetType = value match {
+ case _: jl.Double | _: jl.Integer | _: jl.Float | _: jl.Long =>
NumericType
--- End diff --
fixed it
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