restore testing setup

CONTRIBUTING.md

@@ -70,7 +70,8 @@ To run functional tests we rely on [dagger](https://dagger.io/). This launches a
 
 ```sh
 pip install -r dagger/requirements.txt
-python dagger/run_dbt_spark_tests.py --profile apache_spark --test-path tests/functional/adapter/incremental_strategies/test_microbatch.py
+ython dagger/run_dbt_spark_tests.py --profile databricks_sql_endpoint --test-path tests/functional/adapter/test_basic.py::TestSimpleMaterializationsSpark::test_base
+```
 
 `--profile`: required, this is the kind of spark connection to test against
 

dagger/run_dbt_spark_tests.py

@@ -150,8 +150,6 @@ async def test_spark(test_args):
 
         tst_container = tst_container.with_(env_variables(TESTING_ENV_VARS))
         test_path = test_args.test_path if test_args.test_path else "tests/functional/adapter"
-        # TODO: remove before merging!
-        test_path = "tests/functional/adapter/incremental_strategies/test_microbatch.py"
         result = await tst_container.with_exec(
             ["pytest", "-v", "--profile", test_profile, "-n", "auto", test_path]
         ).stdout()

dbt/include/spark/macros/materializations/incremental/strategies.sql

@@ -79,8 +79,7 @@
     {#-- microbatch wraps insert_overwrite, and requires a partition_by config #}
     {% set missing_partition_key_microbatch_msg -%}
       dbt-spark 'microbatch' incremental strategy requires a `partition_by` config.
-      Ensure you are using a `partition_by` column that is of grain {{ config.get('batch_size') }}
-      for microbatch model {{ model.name }}.
+      Ensure you are using a `partition_by` column that is of grain {{ config.get('batch_size') }}.
     {%- endset %}
 
     {%- if not config.get('partition_by') -%}