dongjoon-hyun commented on a change in pull request #32764:
URL: https://github.com/apache/spark/pull/32764#discussion_r645141345
##########
File path:
sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2FunctionSuite.scala
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@@ -466,6 +526,60 @@ class DataSourceV2FunctionSuite extends
DatasourceV2SQLBase {
override def produceResult(state: (Long, Long)): Long = state._1 / state._2
}
+ object UnboundDecimalAverage extends UnboundFunction {
+ override def name(): String = "favg"
+
+ override def bind(inputType: StructType): BoundFunction = {
+ if (inputType.fields.length > 1) {
+ throw new UnsupportedOperationException("Too many arguments")
+ }
+
+ // put interval type here for testing purpose
+ inputType.fields(0).dataType match {
+ case _: NumericType | _: DayTimeIntervalType => DecimalAverage
+ case dataType =>
+ throw new UnsupportedOperationException(s"Unsupported input type:
$dataType")
+ }
+ }
+
+ override def description(): String =
+ """iavg: produces an average using decimal division, ignoring nulls
+ | iavg(integral) -> decimal
+ | iavg(float) -> decimal
+ | iavg(decimal) -> decimal""".stripMargin
+ }
+
+ object DecimalAverage extends AggregateFunction[(Decimal, Int), Decimal] {
+ val PRECISION: Int = 15
+ val SCALE: Int = 5
Review comment:
Sorry, but may I ask where these (precision 15, scale 5) came from? I
might miss the context, but this looks like non-conventional values in Apache
Spark codebase. Is it intentionally chosen for some purpose?
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