Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/14033#discussion_r69606332
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala
---
@@ -94,6 +94,59 @@ case class UserDefinedGenerator(
}
/**
+ * Separate v1, ..., vk into n rows. Each row will have k/n columns. n
must be constant.
+ * {{{
+ * SELECT stack(2, 1, 2, 3)) ->
+ * 1 2
+ * 3 NULL
+ * }}}
+ */
+@ExpressionDescription(
+ usage = "_FUNC_(n, v1, ..., vk) - Separate v1, ..., vk into n rows.",
+ extended = "> SELECT _FUNC_(2, 1, 2, 3);\n [1,2]\n [3,null]")
+case class Stack(children: Seq[Expression])
+ extends Expression with Generator with CodegenFallback {
+
+ private lazy val numRows = children.head.eval().asInstanceOf[Int]
+ private lazy val numFields = Math.ceil((children.length - 1.0) /
numRows).toInt
+
+ override def checkInputDataTypes(): TypeCheckResult = {
+ if (children.length <= 1) {
+ TypeCheckResult.TypeCheckFailure(s"$prettyName requires at least 2
arguments.")
+ } else if (children.head.dataType != IntegerType ||
!children.head.foldable || numRows < 1) {
+ TypeCheckResult.TypeCheckFailure("The number of rows must be a
positive constant integer.")
+ } else {
+ for (i <- 1 until children.length) {
+ val j = (i - 1) % numFields
+ if (children(i).dataType != elementSchema.fields(j).dataType) {
+ return TypeCheckResult.TypeCheckFailure(
+ s"Argument ${j + 1} (${elementSchema.fields(j).dataType}) != "
+
+ s"Argument $i (${children(i).dataType})")
+ }
+ }
+ TypeCheckResult.TypeCheckSuccess
+ }
+ }
+
+ override def elementSchema: StructType =
+ StructType(children.tail.take(numFields).zipWithIndex.map {
+ case (e, index) => StructField(s"col$index", e.dataType)
+ })
+
+ override def eval(input: InternalRow): TraversableOnce[InternalRow] = {
+ val values = children.tail.map(_.eval(input))
--- End diff --
It's better to call `toArray` here, as we will access it by index in a loop
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