ulysses-you commented on a change in pull request #29749:
URL: https://github.com/apache/spark/pull/29749#discussion_r490212524
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File path: sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala
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@@ -69,6 +70,23 @@ private[hive] case class HiveSimpleUDF(
udfType != null && udfType.deterministic() && !udfType.stateful()
}
+ override def inputTypes: Seq[AbstractDataType] = {
+ val inTypes = children.map(_.dataType)
Review comment:
The `ScalaUDF` also implicit convert input type to expected type at
`ImplicitTypeCasts`.
Let's say we have a udf `Array[Double] => Double = { data => data.sum }` and
we run `spark.sql("select udf(array(1.0, 1.1, 1.2))")`. Then
`ImplicitTypeCasts` will cast `array<decimal>` to `array<double>`.
But Hive udf can't enjoy it, now we only use Hive `ObjectInspector` to
convert data type at running time. It's the difference.
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