findepi commented on code in PR #13756:
URL: https://github.com/apache/datafusion/pull/13756#discussion_r1888428810


##########
datafusion/functions-nested/src/extract.rs:
##########
@@ -993,3 +993,84 @@ where
     let data = mutable.freeze();
     Ok(arrow::array::make_array(data))
 }
+
+#[cfg(test)]
+mod tests {
+    use super::array_element_udf;
+    use arrow_schema::{DataType, Field};
+    use datafusion_common::{Column, DFSchema, ScalarValue};
+    use datafusion_expr::expr::ScalarFunction;
+    use datafusion_expr::{cast, Expr, ExprSchemable};
+    use std::collections::HashMap;
+
+    #[test]
+    fn test_array_element_return_type() {
+        let complex_type = DataType::FixedSizeList(

Review Comment:
   > How about we compute the `return_type` when the function is created, and 
`get_type` read the value.
   
   I like the idea _in principle_.
   
   It should be combined with a new ScalarUDFImpl sub-trait that doesn't have 
return type-related methods at all, since they are not to be used once the plan 
is constructed.
   
   
   > The reason is because we can't guarantee the input is already coerced.
   
   in a _logical plan_ we can.
   
   My understanding is that coercing analyzer also calls the `get_type` 
functions.
   It can be solved by changing how the coercing analyzer tracks its internal 
state.
   
   But the real problem is that same types, the `LogicalPlan` & `Expr`, have 
two meanings: syntactic and semantic. So in the code we go back and forth about 
what should and what cannot be guaranteed for an `Expr` or `LogicalPlan` 
instance.
   
   
   
   



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