MaxGekk commented on code in PR #48004:
URL: https://github.com/apache/spark/pull/48004#discussion_r1754532183
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/randomExpressions.scala:
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@@ -181,3 +189,215 @@ case class Randn(child: Expression, hideSeed: Boolean =
false) extends RDG {
object Randn {
def apply(seed: Long): Randn = Randn(Literal(seed, LongType))
}
+
+@ExpressionDescription(
+ usage = """
+ _FUNC_(min, max[, seed]) - Returns a random value with independent and
identically
+ distributed (i.i.d.) values with the specified range of numbers. The
random seed is optional.
+ The provided numbers specifying the minimum and maximum values of the
range must be constant.
+ If both of these numbers are integers, then the result will also be an
integer. Otherwise if
+ one or both of these are floating-point numbers, then the result will
also be a floating-point
+ number.
+ """,
+ examples = """
+ Examples:
+ > SELECT _FUNC_(10, 20) > 0;
+ true
+ """,
+ since = "4.0.0",
+ group = "math_funcs")
+case class Uniform(min: Expression, max: Expression, seed: Expression)
+ extends RuntimeReplaceable with TernaryLike[Expression] with
ExpressionWithRandomSeed {
+ def this(min: Expression, max: Expression) =
+ this(min, max, Literal(Uniform.random.nextLong(), LongType))
+
+ final override lazy val deterministic: Boolean = false
+ override val nodePatterns: Seq[TreePattern] =
+ Seq(RUNTIME_REPLACEABLE, EXPRESSION_WITH_RANDOM_SEED)
+
+ override val dataType: DataType = {
+ val first = min.dataType
+ val second = max.dataType
+ (min.dataType, max.dataType) match {
+ case _ if !valid(min) || !valid(max) => NullType
+ case (_, LongType) | (LongType, _) if Seq(first, second).forall(integer)
=> LongType
+ case (_, IntegerType) | (IntegerType, _) if Seq(first,
second).forall(integer) => IntegerType
+ case (_, ShortType) | (ShortType, _) if Seq(first,
second).forall(integer) => ShortType
+ case (_, DoubleType) | (DoubleType, _) => DoubleType
+ case (_, FloatType) | (FloatType, _) => FloatType
+ case _ => NullType
+ }
+ }
+
+ private def valid(e: Expression): Boolean = e.dataType match {
+ case _ if !e.foldable => false
+ case _: ShortType | _: IntegerType | _: LongType | _: FloatType | _:
DoubleType => true
+ case _ => false
+ }
+
+ private def integer(t: DataType): Boolean = t match {
+ case _: ShortType | _: IntegerType | _: LongType => true
Review Comment:
You could check either it is `IntegralType` or not if you would support
`ByteType`.
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