andygrove commented on code in PR #1667:
URL: https://github.com/apache/datafusion-comet/pull/1667#discussion_r2054613906
##########
spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala:
##########
@@ -161,10 +161,28 @@ class CometSparkSessionExtensions
}
if (!schemaSupported) {
- fallbackReasons += s"Unsupported schema ${scanExec.requiredSchema}
for $scanImpl"
+ val field: Option[StructField] =
+ CometNativeScanExec
+ .findUnsupportedField(scanExec.requiredSchema)
+
.orElse(CometScanExec.findUnsupportedField(scanExec.requiredSchema))
+ assert(field.nonEmpty)
+ fallbackReasons +=
+ s"Unsupported field ${field.get} in schema
${scanExec.requiredSchema} for $scanImpl"
Review Comment:
This PR introduces a two-step process:
1) call `isTypeSupported`
2) call `findUnsupportedField` if `isTypeSupported` returns `false`
I wonder if we should consider a different approach so that we do not have
to duplicate the logic.
One idea would be to pass an accumulator into `isTypeSupported` that can
collect fallback reasons. For example:
```scala
def isTypeSupported(dt: DataType, fallbackReasons:
mutable.ListBuffer[String]): Boolean
```
Another approach would be to rename `isTypeSupported` to
`validateTypeSupported` and have it throw an exception when it encounters the
first unsupported type.
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