Github user cloud-fan commented on a diff in the pull request: https://github.com/apache/spark/pull/14033#discussion_r69498156 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala --- @@ -94,6 +94,70 @@ 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 = try { + children.head.eval().asInstanceOf[Int] + } catch { + case _: ClassCastException => + throw new AnalysisException("The number of rows must be a positive constant integer.") + } + + private lazy val numFields = ((children.length - 1) + numRows - 1) / numRows + + 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 || + children.head.eval().asInstanceOf[Int] < 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}) != " + --- End diff -- not a big deal, `Argument i` is also fine.
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