[GitHub] [spark] beliefer commented on a change in pull request #32229: [SPARK-34837][SQL] Support ANSI SQL intervals by the aggregate function `avg`

[GitBox <gi...@apache.org>]

beliefer commented on a change in pull request #32229:
URL: https://github.com/apache/spark/pull/32229#discussion_r615678978



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File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Average.scala
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@@ -40,10 +39,15 @@ case class Average(child: Expression) extends DeclarativeAggregate with Implicit
 
   override def prettyName: String = getTagValue(FunctionRegistry.FUNC_ALIAS).getOrElse("avg")
 
-  override def inputTypes: Seq[AbstractDataType] = Seq(NumericType)
+  override def inputTypes: Seq[AbstractDataType] =
+    Seq(TypeCollection(NumericType, YearMonthIntervalType, DayTimeIntervalType))
 
-  override def checkInputDataTypes(): TypeCheckResult =
-    TypeUtils.checkForNumericExpr(child.dataType, "function average")
+  override def checkInputDataTypes(): TypeCheckResult = child.dataType match {
+    case YearMonthIntervalType | DayTimeIntervalType | NullType => TypeCheckResult.TypeCheckSuccess
+    case dt if dt.isInstanceOf[NumericType] => TypeCheckResult.TypeCheckSuccess
+    case other => TypeCheckResult.TypeCheckFailure(
+      s"function average requires numeric or interval types, not ${other.catalogString}")
+  }

Review comment:
       Good idea.




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