cloud-fan commented on a change in pull request #29604:
URL: https://github.com/apache/spark/pull/29604#discussion_r489231123
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala
##########
@@ -549,6 +549,85 @@ case class CumeDist() extends RowNumberLike with
SizeBasedWindowFunction {
override def prettyName: String = "cume_dist"
}
+@ExpressionDescription(
+ usage = """
+ _FUNC_(input[, offset]) - Returns the value of `input` at the row that is
the `offset`th row
+ from beginning of the window frame. Offsets start at 1. If
ignoreNulls=true, we will skip
+ nulls when finding the `offset`th row. Otherwise, every row counts for
the `offset`. If
+ there is no such an offset row (e.g., when the offset is 10, size of the
window frame less
+ than 10), null is returned.
+ """,
+ arguments = """
+ Arguments:
+ * input - the target column or expression that the function operates on.
+ * offset - a positive int literal to indicate the offset in the window
frame. It starts with 1.
+ * ignoreNulls - an optional specification that indicates the NthValue
should skip null
+ values in the determination of which row to use.
+ """,
+ since = "3.1.0",
+ group = "window_funcs")
+case class NthValue(input: Expression, offsetExpr: Expression, ignoreNulls:
Boolean)
+ extends AggregateWindowFunction with ImplicitCastInputTypes {
+
+ def this(child: Expression, offset: Expression) = this(child, offset, false)
+
+ override def children: Seq[Expression] = input :: Nil
+
+ override def frame: WindowFrame = UnspecifiedFrame
+
+ override def dataType: DataType = input.dataType
+
+ override def inputTypes: Seq[AbstractDataType] = Seq(AnyDataType,
IntegerType, BooleanType)
+
+ override def checkInputDataTypes(): TypeCheckResult = {
+ val check = super.checkInputDataTypes()
+ if (check.isFailure) {
+ check
+ } else if (!offsetExpr.foldable) {
+ TypeCheckFailure(s"Offset expression '$offsetExpr' must be a literal.")
+ } else {
+ offsetExpr.dataType match {
Review comment:
This will always be `IntegerType` when we reach here, because it extends
`ImplicitCastInputTypes`. We can just do `offsetExpr.eval().asInstanceOf[Int]
match ...`
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