Fix for describe column types

CHANGELOG.md

@@ -8,6 +8,7 @@
 - Update default scope/redirect Url for OAuth U2M, so with default OAuth app user can run python models ([776](https://github.com/databricks/dbt-databricks/pull/776))
 - Fix foreign key constraints by switching from `parent` to `to` and `parent_columns` to `to_columns` ([789](https://github.com/databricks/dbt-databricks/pull/789))
 - Now handles external shallow clones without blowing up ([795](https://github.com/databricks/dbt-databricks/pull/795))
+- Use information_schema to get column types when possible, since describe extended truncates complex types ([796](https://github.com/databricks/dbt-databricks/pull/796))
 
 ## dbt-databricks 1.8.5 (August 6, 2024)
 

dbt/adapters/databricks/impl.py

@@ -73,6 +73,7 @@
 from dbt.adapters.spark.impl import LIST_SCHEMAS_MACRO_NAME
 from dbt.adapters.spark.impl import SparkAdapter
 from dbt.adapters.spark.impl import TABLE_OR_VIEW_NOT_FOUND_MESSAGES
+from dbt_common.behavior_flags import BehaviorFlag
 from dbt_common.exceptions import DbtRuntimeError
 from dbt_common.utils import executor
 from dbt_common.utils.dict import AttrDict
@@ -88,6 +89,7 @@
 SHOW_TABLES_MACRO_NAME = "show_tables"
 SHOW_VIEWS_MACRO_NAME = "show_views"
 GET_COLUMNS_COMMENTS_MACRO_NAME = "get_columns_comments"
+GET_COLUMNS_BY_INFO_MACRO_NAME = "get_columns_comments_via_information_schema"
 
 
 @dataclass
@@ -164,6 +166,12 @@ class DatabricksAdapter(SparkAdapter):
         }
     )
 
+    # This will begin working once we have 1.9 of dbt-core.
+    # For now does nothing
+    @property
+    def _behavior_flags(self) -> List[BehaviorFlag]:
+        return [{"name": "column_types_from_information_schema", "default": False}]  # type: ignore
+
     # override/overload
     def acquire_connection(
         self, name: Optional[str] = None, query_header_context: Any = None
@@ -376,6 +384,36 @@ def parse_describe_extended(  # type: ignore[override]
 
     def get_columns_in_relation(  # type: ignore[override]
         self, relation: DatabricksRelation
+    ) -> List[DatabricksColumn]:
+        if (
+            # We can uncomment this once behavior flags are available to adapters
+            # self.behavior.column_types_from_information_schema and # type: ignore
+            not relation.is_hive_metastore()
+        ):
+            return self._get_columns_in_relation_by_information_schema(relation)
+        else:
+            return self._get_columns_in_relation_by_describe(relation)
+
+    def _get_columns_in_relation_by_information_schema(
+        self, relation: DatabricksRelation
+    ) -> List[DatabricksColumn]:
+        rows = list(
+            handle_missing_objects(
+                lambda: self.execute_macro(
+                    GET_COLUMNS_BY_INFO_MACRO_NAME, kwargs={"relation": relation}
+                ),
+                AttrDict(),
+            )
+        )
+
+        columns = []
+        for row in rows:
+            columns.append(DatabricksColumn(column=row[0], dtype=row[1], comment=row[2]))
+
+        return columns
+
+    def _get_columns_in_relation_by_describe(
+        self, relation: DatabricksRelation
     ) -> List[DatabricksColumn]:
         rows = list(
             handle_missing_objects(

dbt/include/databricks/macros/adapters/persist_docs.sql

@@ -28,6 +28,22 @@
   {% do return(load_result('get_columns_comments').table) %}
 {% endmacro %}
 
+{% macro get_columns_comments_via_information_schema(relation) -%}
+  {% call statement('get_columns_comments_via_information_schema', fetch_result=True) -%}
+    select
+      column_name,
+      full_data_type,
+      comment
+    from `system`.`information_schema`.`columns`
+    where
+      table_catalog = '{{ relation.database|lower }}' and
+      table_schema = '{{ relation.schema|lower }}' and 
+      table_name = '{{ relation.identifier|lower }}'
+  {% endcall %}
+
+  {% do return(load_result('get_columns_comments_via_information_schema').table) %}
+{% endmacro %}
+
 {% macro databricks__persist_docs(relation, model, for_relation, for_columns) -%}
   {%- if for_relation and config.persist_relation_docs() and model.description %}
     {% do alter_table_comment(relation, model) %}

dev-requirements.txt

@@ -15,4 +15,4 @@ types-requests
 types-mock
 pre-commit
 
-dbt-tests-adapter~=1.8.0
+dbt-tests-adapter~=1.9.0

requirements.txt

@@ -1,7 +1,7 @@
 databricks-sql-connector>=3.1.0, <3.2.0
 dbt-spark~=1.8.0
 dbt-core>=1.8.0, <2.0
-dbt-adapters>=1.3.0, <2.0
+dbt-adapters>=1.6.0, <2.0
 databricks-sdk==0.17.0
 keyring>=23.13.0
 pandas<2.2.0

tests/functional/adapter/columns/fixtures.py

@@ -0,0 +1,13 @@
+base_model = """
+select struct('a', 1, 'b', 'b', 'c', ARRAY(1,2,3)) as struct_col, 'hello' as str_col
+"""
+
+schema = """
+version: 2
+
+models:
+  - name: base_model
+    columns:
+      - name: struct_col
+      - name: str_col
+"""

tests/functional/adapter/columns/test_get_columns.py

@@ -0,0 +1,55 @@
+import pytest
+
+from dbt.adapters.databricks.column import DatabricksColumn
+from dbt.adapters.databricks.relation import DatabricksRelation
+from tests.functional.adapter.columns import fixtures
+from dbt.tests import util
+
+
+class ColumnsInRelation:
+
+    @pytest.fixture(scope="class")
+    def models(self):
+        return {"base_model.sql": fixtures.base_model, "schema.yml": fixtures.schema}
+
+    @pytest.fixture(scope="class", autouse=True)
+    def setup(self, project):
+        util.run_dbt(["run"])
+
+    @pytest.fixture(scope="class")
+    def expected_columns(self):
+
+        return [
+            DatabricksColumn(
+                column="struct_col",
+                dtype=(
+                    "struct<col1:string,col2:int,col3:string,"
+                    "col4:string,col5:string,col6:array<int>>"
+                ),
+            ),
+            DatabricksColumn(column="str_col", dtype="string"),
+        ]
+
+    def test_columns_in_relation(self, project, expected_columns):
+        my_relation = DatabricksRelation.create(
+            database=project.database,
+            schema=project.test_schema,
+            identifier="base_model",
+            type=DatabricksRelation.Table,
+        )
+
+        with project.adapter.connection_named("_test"):
+            actual_columns = project.adapter.get_columns_in_relation(my_relation)
+        assert actual_columns == expected_columns
+
+
+class TestColumnsInRelationBehaviorFlagOff(ColumnsInRelation):
+    @pytest.fixture(scope="class")
+    def project_config_update(self):
+        return {"flags": {}}
+
+
+class TestColumnsInRelationBehaviorFlagOn(ColumnsInRelation):
+    @pytest.fixture(scope="class")
+    def project_config_update(self):
+        return {"flags": {"column_types_from_information_schema": True}}