theirix commented on code in PR #21737:
URL: https://github.com/apache/datafusion/pull/21737#discussion_r4117068549
##########
datafusion/catalog/src/information_schema.rs:
##########
@@ -454,26 +454,35 @@ impl InformationSchemaConfig {
}
}
+/// Build the argument field for `information_schema` to provide a return type
+fn resolve_informational_field(idx: usize, t: &NativeType) -> Result<FieldRef>
{
+ // Since a native type maps to several physical types, resolve it against
`Null` data type
+ // to get the canonical `DataType` for the native type
+ let data_type = t.default_cast_for(&DataType::Null)?;
+ Ok(Arc::new(Field::new(format!("arg_{idx}"), data_type, true)))
+}
+
/// get the arguments and return types of a UDF
/// returns a tuple of (arg_types, return_type)
fn get_udf_args_and_return_types(
udf: &Arc<ScalarUDF>,
) -> Result<BTreeSet<(Vec<String>, Option<String>)>> {
let signature = udf.signature();
- let arg_types = signature.type_signature.get_example_types();
+ let arg_types = signature.type_signature.get_representative_types();
if arg_types.is_empty() {
Ok(vec![(vec![], None)].into_iter().collect::<BTreeSet<_>>())
} else {
- Ok(arg_types
+ arg_types
.into_iter()
.map(|arg_types| {
- let arg_fields: Vec<FieldRef> = arg_types
+ let mut arg_fields = arg_types
.iter()
.enumerate()
- .map(|(i, t)| {
- Arc::new(Field::new(format!("arg_{i}"), t.clone(),
true))
- })
- .collect();
+ .map(|(i, t)| resolve_informational_field(i, t))
+ .collect::<Result<Vec<FieldRef>>>()?;
+ // Even with collecting results into a set, drop duplicates
early
+ arg_fields.sort();
+ arg_fields.dedup();
Review Comment:
Thank you, it's a good spot. Removed the dedup to have an expected result
(backed by a unit test)
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