andygrove commented on code in PR #3004:
URL: https://github.com/apache/datafusion-comet/pull/3004#discussion_r2712728394
##########
spark/src/main/scala/org/apache/comet/serde/structs.scala:
##########
@@ -230,3 +232,68 @@ object CometJsonToStructs extends
CometExpressionSerde[JsonToStructs] {
}
}
}
+
+object CometStructsToCsv extends CometExpressionSerde[StructsToCsv] {
+
+ private val incompatibleDataTypes = Seq(DateType, TimestampType,
TimestampNTZType, BinaryType)
+
+ override def getSupportLevel(expr: StructsToCsv): SupportLevel = {
+ val dataTypes = expr.inputSchema.fields.map(_.dataType)
+ val containsComplexType = dataTypes.exists(DataTypeSupport.isComplexType)
+ if (containsComplexType) {
+ return Unsupported(
+ Some(
+ s"The schema ${expr.inputSchema} is not supported because it
includes a complex type"))
+ }
+ val containsIncompatibleDataTypes =
dataTypes.exists(incompatibleDataTypes.contains)
+ if (containsIncompatibleDataTypes) {
+ return Incompatible(
+ Some(
+ s"The schema ${expr.inputSchema} is not supported because " +
+ s"it includes a incompatible data types: $incompatibleDataTypes"))
+ }
+ Compatible()
Review Comment:
Can we guarantee full compatibility with the `UnivocityGenerator` that Spark
uses? Perhaps this should be marked as incompatible for now until we have
sufficient fuzz testing to confirm compatibility?
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