diff --git a/dbt/adapters/spark/impl.py b/dbt/adapters/spark/impl.py
index 01b151686..bbd1a140b 100644
--- a/dbt/adapters/spark/impl.py
+++ b/dbt/adapters/spark/impl.py
@@ -28,6 +28,7 @@
 
 logger = AdapterLogger("Spark")
 
+GET_COLUMNS_IN_RELATION_RAW_MACRO_NAME = "get_columns_in_relation_raw"
 LIST_SCHEMAS_MACRO_NAME = "list_schemas"
 LIST_RELATIONS_MACRO_NAME = "list_relations_without_caching"
 LIST_RELATIONS_SHOW_TABLES_MACRO_NAME = "list_relations_show_tables_without_caching"
@@ -155,7 +156,7 @@ def _get_relation_information(self, row: agate.Row) -> RelationInfo:
 
         return RelationInfo(_schema, name, columns, table_properties)
 
-    def _parse_describe_table(
+    def _parse_describe_table_extended(
         self, table_results: agate.Table
     ) -> Tuple[List[Tuple[str, str]], Dict[str, str]]:
         # Wrap it in an iter, so we continue reading the properties from where we stopped reading columns
@@ -195,7 +196,7 @@ def _get_relation_information_using_describe(self, row: agate.Row) -> RelationIn
             logger.debug(f"Error while retrieving information about {table_name}: {e.msg}")
             table_results = AttrDict()
 
-        columns, table_properties = self._parse_describe_table(table_results)
+        columns, table_properties = self._parse_describe_table_extended(table_results)
         return RelationInfo(_schema, name, columns, table_properties)
 
     def _build_spark_relation_list(
@@ -276,9 +277,29 @@ def get_relation(self, database: str, schema: str, identifier: str) -> Optional[
         return super().get_relation(database, schema, identifier)
 
     def get_columns_in_relation(self, relation: BaseRelation) -> List[SparkColumn]:
-        assert isinstance(relation, SparkRelation), f"Expected SparkRelation, got: {relation}"
+        assert isinstance(relation, SparkRelation)
+        if rel_columns := relation.columns:
+            columns = rel_columns
+            properties = relation.properties
+        else:
+            try:
+                describe_extended_result = self.execute_macro(
+                    GET_COLUMNS_IN_RELATION_RAW_MACRO_NAME, kwargs={"relation": relation}
+                )
+                columns, properties = self._parse_describe_table_extended(describe_extended_result)
+            except dbt.exceptions.DbtRuntimeError as e:
+                # spark would throw error when table doesn't exist, where other
+                # CDW would just return and empty list, normalizing the behavior here
+                errmsg = getattr(e, "msg", "")
+                found_msgs = (msg in errmsg for msg in TABLE_OR_VIEW_NOT_FOUND_MESSAGES)
+                if any(found_msgs):
+                    columns = []
+                    properties = {}
+                else:
+                    raise e
+
         # Convert the Row to a dict
-        raw_table_stats = relation.properties.get(KEY_TABLE_STATISTICS)
+        raw_table_stats = properties.get(KEY_TABLE_STATISTICS)
         table_stats = SparkColumn.convert_table_stats(raw_table_stats)
         return [
             SparkColumn(
@@ -286,13 +307,13 @@ def get_columns_in_relation(self, relation: BaseRelation) -> List[SparkColumn]:
                 table_schema=relation.schema,
                 table_name=relation.name,
                 table_type=relation.type,
-                table_owner=relation.properties.get(KEY_TABLE_OWNER, ""),
+                table_owner=properties.get(KEY_TABLE_OWNER, ""),
                 table_stats=table_stats,
                 column=column_name,
                 column_index=idx,
                 dtype=column_type,
             )
-            for idx, (column_name, column_type) in enumerate(relation.columns)
+            for idx, (column_name, column_type) in enumerate(columns)
             if column_name not in self.HUDI_METADATA_COLUMNS
         ]
 
@@ -385,19 +406,21 @@ def get_rows_different_sql(
         column_names: Optional[List[str]] = None,
         except_operator: str = "EXCEPT",
     ) -> str:
-        """Generate SQL for a query that returns a single row with a two
+        """Generate SQL for a query that returns a single row with two
         columns: the number of rows that are different between the two
         relations and the number of mismatched rows.
         """
         # This method only really exists for test reasons.
         names: List[str]
-        if column_names is None:
+        if not column_names:
             columns = self.get_columns_in_relation(relation_a)
             names = sorted((self.quote(c.name) for c in columns))
         else:
             names = sorted((self.quote(n) for n in column_names))
         columns_csv = ", ".join(names)
 
+        assert columns_csv, f"Could not determine columns for: {relation_a}"
+
         sql = COLUMNS_EQUAL_SQL.format(
             columns=columns_csv,
             relation_a=str(relation_a),
diff --git a/tests/unit/test_adapter.py b/tests/unit/test_adapter.py
index 3bec3df33..aa972913e 100644
--- a/tests/unit/test_adapter.py
+++ b/tests/unit/test_adapter.py
@@ -323,7 +323,7 @@ def test_parse_relation(self):
 
         config = self._get_target_http(self.project_cfg)
         adapter = SparkAdapter(config)
-        columns, properties = adapter._parse_describe_table(input_cols)
+        columns, properties = adapter._parse_describe_table_extended(input_cols)
         relation_info = adapter._build_spark_relation_list(
             columns, lambda a: RelationInfo(relation.schema, relation.name, columns, properties)
         )
@@ -414,7 +414,7 @@ def test_parse_relation_with_integer_owner(self):
         ]
 
         config = self._get_target_http(self.project_cfg)
-        _, properties = SparkAdapter(config)._parse_describe_table(plain_rows)
+        _, properties = SparkAdapter(config)._parse_describe_table_extended(plain_rows)
 
         self.assertEqual(properties.get(KEY_TABLE_OWNER), "1234")
 
@@ -448,7 +448,7 @@ def test_parse_relation_with_statistics(self):
         ]
 
         config = self._get_target_http(self.project_cfg)
-        columns, properties = SparkAdapter(config)._parse_describe_table(plain_rows)
+        columns, properties = SparkAdapter(config)._parse_describe_table_extended(plain_rows)
         spark_relation = SparkRelation.create(
             schema=relation.schema,
             identifier=relation.name,