Jefffrey commented on code in PR #22244:
URL: https://github.com/apache/datafusion/pull/22244#discussion_r3426089468
##########
datafusion/spark/src/function/string/concat.rs:
##########
@@ -71,28 +71,29 @@ impl ScalarUDFImpl for SparkConcat {
}
fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> {
- // Accept any string types, including zero arguments
- Ok(arg_types.to_vec())
+ if arg_types.is_empty() {
+ // Spark semantics: allow concat with zero arguments
+ Ok(vec![])
+ } else {
+ // Use concat coercion rules
+ ConcatFunc::new().coerce_types(arg_types)
+ }
}
fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
datafusion_common::internal_err!(
"return_type should not be called for Spark concat"
)
}
fn return_field_from_args(&self, args: ReturnFieldArgs<'_>) ->
Result<FieldRef> {
- use DataType::*;
-
// Spark semantics: concat returns NULL if ANY input is NULL
let nullable = args.arg_fields.iter().any(|f| f.is_nullable());
- // Determine return type: Utf8View > LargeUtf8 > Utf8
- let mut dt = &Utf8;
- for field in args.arg_fields {
- let data_type = field.data_type();
- if data_type == &Utf8View || (data_type == &LargeUtf8 && dt !=
&Utf8View) {
- dt = data_type;
- }
- }
+ let arg_types: Vec<DataType> = args
+ .arg_fields
+ .iter()
+ .map(|f| f.data_type().clone())
+ .collect();
+ let dt = ConcatFunc::new().return_type(&arg_types)?;
Ok(Arc::new(Field::new("concat", dt.clone(), nullable)))
Review Comment:
```suggestion
let field = ConcatFunc::new().return_field_from_args(args)?;
Ok(Arc::new(Field::new(
"concat",
field.data_type().clone(),
nullable,
)))
```
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