support strucy

Signed-off-by: jayzhan211 <[email protected]>

datafusion/expr-common/src/type_coercion/binary.rs

@@ -370,6 +370,8 @@ impl From<&DataType> for TypeCategory {
 /// align with the behavior of Postgres. Therefore, we've made slight adjustments to the rules
 /// to better match the behavior of both Postgres and DuckDB. For example, we expect adjusted
 /// decimal precision and scale when coercing decimal types.
+///
+/// This function doesn't preserve correct field name and nullability for the nested data type, we only care about data type.
 pub fn type_union_resolution(data_types: &[DataType]) -> Option<DataType> {
     if data_types.is_empty() {
         return None;
@@ -476,6 +478,26 @@ fn type_union_resolution_coercion(
                 type_union_resolution_coercion(lhs.data_type(), rhs.data_type());
             new_item_type.map(|t| DataType::List(Arc::new(Field::new("item", t, true))))
         }
+        (DataType::Struct(lhs), DataType::Struct(rhs)) => {
+            if lhs.len() != rhs.len() {
+                return None;
+            }
+
+            let types = std::iter::zip(lhs.iter(), rhs.iter())
+                .map(|(lhs, rhs)| {
+                    type_union_resolution_coercion(lhs.data_type(), rhs.data_type())
+                })
+                .collect::<Option<Vec<DataType>>>()?;
+
+            let fields = types
+                .into_iter()
+                .enumerate()
+                .map(|(i, datatype)| {
+                    Arc::new(Field::new(format!("c{i}"), datatype, true))
+                })
+                .collect::<Vec<FieldRef>>();
+            Some(DataType::Struct(fields.into()))
+        }
         _ => {
             // numeric coercion is the same as comparison coercion, both find the narrowest type
             // that can accommodate both types

datafusion/sqllogictest/test_files/struct.slt

@@ -373,3 +373,19 @@ You reached the bottom!
 
 statement ok
 drop view complex_view;
+
+statement ok
+create table t(a struct<r1 varchar, c int>, b struct<r2 varchar, c float>) as values (struct('red', 1), struct('blue', 2.3));
+
+query T
+select arrow_typeof([a, b]) from t;
+----
+List(Field { name: "item", data_type: Struct([Field { name: "c0", data_type: Utf8, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "c1", data_type: Float32, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }]), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} })
+
+query ?
+select [a, b] from t;
+----
+[{c0: red, c1: 1.0}, {c0: blue, c1: 2.3}]
+
+statement ok
+drop table t;