infoankitp commented on code in PR #38865:
URL: https://github.com/apache/spark/pull/38865#discussion_r1037937615
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala:
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@@ -4600,3 +4600,69 @@ case class ArrayExcept(left: Expression, right:
Expression) extends ArrayBinaryL
override protected def withNewChildrenInternal(
newLeft: Expression, newRight: Expression): ArrayExcept = copy(left =
newLeft, right = newRight)
}
+
+/**
+ * Given an array, and another element append the element at the end of the
array.
+ */
+@ExpressionDescription(
+ usage = "_FUNC_(expr, expr) - Prepend the element",
+ examples = """
+ Examples:
+ > SELECT _FUNC_(array('b', 'd', 'c', 'a'), array(1, 2, 3, 4));
+
+ """,
+ since = "3.4.0",
+ group = "collection_funcs")
+case class ArrayAppend(left: Expression, right: Expression)
+ extends BinaryExpression
+ with ImplicitCastInputTypes {
+ override def prettyName: String = "array_append"
+ override def inputTypes: Seq[AbstractDataType] = Seq(ArrayType, AnyDataType)
+
+ override def checkInputDataTypes(): TypeCheckResult = {
+ (left.dataType, right.dataType) match {
+ case (ArrayType(e1, _), (e2)) if e1.sameType(e2) =>
+ TypeCheckResult.TypeCheckSuccess
+ case _ =>
Review Comment:
I think snowflake's arrays are not strongly typed while spark's arrays' are
strongly typed, since it does not allow us to mix multiple types of elements in
one Array. But yes if we want to make it similar to snowflake, we will have to
make spark arrays also loosely typed. Let's wait for everyone else's
suggestions as well. And I think it will be a similar construct for
array_insert, array_prepend as well. :)
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