test: add unit test using concat

Signed-off-by: machichima <nary12321@gmail.com>

Author: machichima

python/ray/data/tests/test_transform_pyarrow.py

@@ -473,6 +473,64 @@ def test_struct_with_arrow_variable_shaped_tensor_type(
             )
 
 
+@pytest.mark.skipif(
+    get_pyarrow_version() < MIN_PYARROW_VERSION_TYPE_PROMOTION,
+    reason="Requires PyArrow >= 14.0.0 for type promotion in nested struct fields",
+)
+def test_struct_with_diverging_primitive_types():
+    """Test concatenating tables with struct fields that have diverging primitive types.
+
+    This tests the scenario where struct fields have the same name but different
+    primitive types (e.g., int64 vs float64), which requires type promotion.
+    """
+    import pyarrow as pa
+
+    # Table 1: struct with (a: int64, b: string)
+    t1 = pa.table(
+        {
+            "data": pa.array(
+                [{"a": 1, "b": "hello"}, {"a": 2, "b": "world"}],
+                type=pa.struct([pa.field("a", pa.int64()), pa.field("b", pa.string())]),
+            )
+        }
+    )
+
+    # Table 2: struct with (a: float64, c: int32)
+    # Field 'a' has different type, field 'b' missing, field 'c' new
+    t2 = pa.table(
+        {
+            "data": pa.array(
+                [{"a": 1.5, "c": 100}, {"a": 2.5, "c": 200}],
+                type=pa.struct(
+                    [pa.field("a", pa.float64()), pa.field("c", pa.int32())]
+                ),
+            )
+        }
+    )
+
+    # Concatenate with type promotion
+    result = concat([t1, t2], promote_types=True)
+
+    # Verify schema: field 'a' should be promoted to float64
+    expected_struct_type = pa.struct(
+        [
+            pa.field("a", pa.float64()),
+            pa.field("b", pa.string()),
+            pa.field("c", pa.int32()),
+        ]
+    )
+    assert result.schema == pa.schema([pa.field("data", expected_struct_type)])
+
+    # Verify data: int64 values should be cast to float64, missing fields filled with None
+    expected_data = [
+        {"a": 1.0, "b": "hello", "c": None},
+        {"a": 2.0, "b": "world", "c": None},
+        {"a": 1.5, "b": None, "c": 100},
+        {"a": 2.5, "b": None, "c": 200},
+    ]
+    assert result.column("data").to_pylist() == expected_data
+
+
 def test_arrow_concat_object_with_tensor_fails(object_with_tensor_fails_blocks):
     with pytest.raises(ArrowConversionError) as exc_info:
         concat(object_with_tensor_fails_blocks)