Kimahriman commented on code in PR #793:
URL: https://github.com/apache/datafusion-comet/pull/793#discussion_r1710186036
##########
spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala:
##########
@@ -2348,6 +2348,27 @@ object QueryPlanSerde extends Logging with
ShimQueryPlanSerde with CometExprShim
.build()
}
+ // datafusion's make_array only supports nullable element types
+ case array @ CreateArray(children, _) if array.dataType.containsNull =>
+ val childExprs = children.map(exprToProto(_, inputs, binding))
+ val dataType = serializeDataType(array.dataType)
Review Comment:
Probably should be but was waiting to see if this was even the right way to
use a ScalarUDF. Looking at it some more I'm not sure how it could even be
updated with the way it currently works, since `ScalarUDFImpl.return_type` just
has `DataType` and not `Field` to know whether the elements are nullable or
not. Still learning how DataFusion works. Should I somehow be using the other
thing created by `make_udf_expr_and_func`:
```
datafusion_functions_nested::make_array
pub fn make_array(arg: Vec<datafusion_expr::Expr>) -> datafusion_expr::Expr
```
?
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