andygrove commented on code in PR #6455:
URL: https://github.com/apache/datafusion-comet/pull/6455#discussion_r4149554973
##########
spark/src/test/scala/org/apache/comet/CometCodegenSuite.scala:
##########
@@ -2346,6 +2393,44 @@ object CometCodegenSuite {
class NotSerializableTarget {
def twice(s: UTF8String): UTF8String = UTF8String.fromString(s.toString +
s.toString)
}
+
+ /**
+ * DSv2 function catalog for the #6425 test. `as_money` declares
`DECIMAL(10, 2)` and
+ * `as_wide_money` declares `DECIMAL(20, 12)`.
+ */
+ class DecimalFunctionCatalog extends FunctionCatalog {
+ private val functions = Map(
+ "as_money" -> new ScaleZeroDecimalFunction(10, 2),
+ "as_wide_money" -> new ScaleZeroDecimalFunction(20, 12))
+ private var catalogName: String = _
+
+ override def initialize(name: String, options: CaseInsensitiveStringMap):
Unit =
+ catalogName = name
+
+ override def name(): String = catalogName
+
+ override def listFunctions(namespace: Array[String]): Array[Identifier] =
+ functions.keys.map(Identifier.of(namespace, _)).toArray
+
+ override def loadFunction(ident: Identifier): UnboundFunction =
+ functions.getOrElse(ident.name(), throw new
NoSuchFunctionException(ident))
+ }
+
+ /**
+ * Returns its `INT` argument as `Decimal(v)`, at scale 0, whatever scale it
declares. `invoke`
+ * is an instance method, so Spark lowers a call to `Invoke`. The function
binds to itself.
+ */
+ class ScaleZeroDecimalFunction(precision: Int, scale: Int)
+ extends UnboundFunction
+ with ScalarFunction[Decimal] {
+ override def name(): String = "scale_zero_decimal"
+ override def description(): String = s"int -> decimal($precision, $scale),
at scale 0"
+ override def bind(inputType: StructType): BoundFunction = this
+ override def inputTypes(): Array[DataType] = Array(IntegerType)
+ override def resultType(): DataType = DecimalType(precision, scale)
+ def invoke(v: Int): Decimal = Decimal(v)
Review Comment:
Added in 4cf7c1c6a8. There's now a third function, `mills_as_money`, which
returns its argument as thousandths into a `DECIMAL(10, 2)`, so the rescale has
to round. It gives -1.01 for -1005, 1.00 for 1004 and 0.01 for 5, the same as
Spark. I also added -99999999 and -100000000 rows for the negative side of the
overflow boundary.
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