Fix part of Google system tests (#18494)

* Fix CloudBuildExampleDagsSystemTest

* Fix DataCatalog tests

* Fix Dataprep test

* Fix GCS test

* Fix Dataflow test

* Fix GC Functions test

* Fix Cloud SQL tests

* Fix Data Fusion test

* Change env var in Dataprep system test

* Fix config for dataflow system tests

* Add unit test for datafusion

* Fix Data Fusion utest, add optional parameter to data fusion pipeline state sensor

* Update code with black suggestions

* Fix flake8 issue

* Revert changes to example_cloud_sql.py according to review feedback

Co-authored-by: Lukasz Wyszomirski <[email protected]>

Author: mnojek

airflow/providers/google/cloud/example_dags/example_cloud_build.py

@@ -97,7 +97,7 @@
 
 # [START howto_operator_create_build_from_repo_body]
 create_build_from_repo_body = {
-    "source": {"repo_source": {"repo_name": GCP_SOURCE_REPOSITORY_NAME, "branch_name": "master"}},
+    "source": {"repo_source": {"repo_name": GCP_SOURCE_REPOSITORY_NAME, "branch_name": "main"}},
     "steps": [
         {
             "name": "gcr.io/cloud-builders/docker",

airflow/providers/google/cloud/example_dags/example_cloud_sql_query.py

@@ -46,7 +46,7 @@
 from airflow.utils.dates import days_ago
 
 GCP_PROJECT_ID = os.environ.get('GCP_PROJECT_ID', 'example-project')
-GCP_REGION = os.environ.get('GCP_REGION', 'europe-west-1b')
+GCP_REGION = os.environ.get('GCP_REGION', 'europe-west1')
 
 GCSQL_POSTGRES_INSTANCE_NAME_QUERY = os.environ.get('GCSQL_POSTGRES_INSTANCE_NAME_QUERY', 'testpostgres')
 GCSQL_POSTGRES_DATABASE_NAME = os.environ.get('GCSQL_POSTGRES_DATABASE_NAME', 'postgresdb')

airflow/providers/google/cloud/example_dags/example_datacatalog.py

@@ -19,6 +19,8 @@
 """
 Example Airflow DAG that interacts with Google Data Catalog service
 """
+import os
+
 from google.cloud.datacatalog_v1beta1 import FieldType, TagField, TagTemplateField
 
 from airflow import models
@@ -49,7 +51,8 @@
 )
 from airflow.utils.dates import days_ago
 
-PROJECT_ID = "polidea-airflow"
+PROJECT_ID = os.getenv("GCP_PROJECT_ID")
+BUCKET_ID = os.getenv("GCP_TEST_DATA_BUCKET", "INVALID BUCKET NAME")
 LOCATION = "us-central1"
 ENTRY_GROUP_ID = "important_data_jan_2019"
 ENTRY_ID = "python_files"
@@ -92,7 +95,7 @@
         entry={
             "display_name": "Wizard",
             "type_": "FILESET",
-            "gcs_fileset_spec": {"file_patterns": ["gs://INVALID BUCKET NAME/**"]},
+            "gcs_fileset_spec": {"file_patterns": [f"gs://{BUCKET_ID}/**"]},
         },
     )
     # [END howto_operator_gcp_datacatalog_create_entry_gcs]

airflow/providers/google/cloud/example_dags/example_dataflow.py

@@ -152,6 +152,7 @@
     # [START howto_operator_start_python_job_async]
     start_python_job_async = BeamRunPythonPipelineOperator(
         task_id="start-python-job-async",
+        runner="DataflowRunner",
         py_file=GCS_PYTHON,
         py_options=[],
         pipeline_options={
@@ -160,14 +161,18 @@
         py_requirements=['apache-beam[gcp]==2.25.0'],
         py_interpreter='python3',
         py_system_site_packages=False,
-        dataflow_config={"location": 'europe-west3', "wait_until_finished": False},
+        dataflow_config={
+            "job_name": "start-python-job-async",
+            "location": 'europe-west3',
+            "wait_until_finished": False,
+        },
     )
     # [END howto_operator_start_python_job_async]
 
     # [START howto_sensor_wait_for_job_status]
     wait_for_python_job_async_done = DataflowJobStatusSensor(
         task_id="wait-for-python-job-async-done",
-        job_id="{{task_instance.xcom_pull('start-python-job-async')['job_id']}}",
+        job_id="{{task_instance.xcom_pull('start-python-job-async')['dataflow_job_id']}}",
         expected_statuses={DataflowJobStatus.JOB_STATE_DONE},
         location='europe-west3',
     )
@@ -191,9 +196,10 @@ def callback(metrics: List[Dict]) -> bool:
 
     wait_for_python_job_async_metric = DataflowJobMetricsSensor(
         task_id="wait-for-python-job-async-metric",
-        job_id="{{task_instance.xcom_pull('start-python-job-async')['job_id']}}",
+        job_id="{{task_instance.xcom_pull('start-python-job-async')['dataflow_job_id']}}",
         location='europe-west3',
         callback=check_metric_scalar_gte(metric_name="Service-cpu_num_seconds", value=100),
+        fail_on_terminal_state=False,
     )
     # [END howto_sensor_wait_for_job_metric]
 
@@ -207,9 +213,10 @@ def check_message(messages: List[dict]) -> bool:
 
     wait_for_python_job_async_message = DataflowJobMessagesSensor(
         task_id="wait-for-python-job-async-message",
-        job_id="{{task_instance.xcom_pull('start-python-job-async')['job_id']}}",
+        job_id="{{task_instance.xcom_pull('start-python-job-async')['dataflow_job_id']}}",
         location='europe-west3',
         callback=check_message,
+        fail_on_terminal_state=False,
     )
     # [END howto_sensor_wait_for_job_message]
 
@@ -223,9 +230,10 @@ def check_autoscaling_event(autoscaling_events: List[dict]) -> bool:
 
     wait_for_python_job_async_autoscaling_event = DataflowJobAutoScalingEventsSensor(
         task_id="wait-for-python-job-async-autoscaling-event",
-        job_id="{{task_instance.xcom_pull('start-python-job-async')['job_id']}}",
+        job_id="{{task_instance.xcom_pull('start-python-job-async')['dataflow_job_id']}}",
         location='europe-west3',
         callback=check_autoscaling_event,
+        fail_on_terminal_state=False,
     )
     # [END howto_sensor_wait_for_job_autoscaling_event]
 

airflow/providers/google/cloud/example_dags/example_datafusion.py

@@ -39,21 +39,26 @@
 from airflow.utils.state import State
 
 # [START howto_data_fusion_env_variables]
+SERVICE_ACCOUNT = os.environ.get("GCP_DATAFUSION_SERVICE_ACCOUNT")
 LOCATION = "europe-north1"
 INSTANCE_NAME = "airflow-test-instance"
-INSTANCE = {"type": "BASIC", "displayName": INSTANCE_NAME}
+INSTANCE = {
+    "type": "BASIC",
+    "displayName": INSTANCE_NAME,
+    "dataprocServiceAccount": SERVICE_ACCOUNT,
+}
 
 BUCKET_1 = os.environ.get("GCP_DATAFUSION_BUCKET_1", "test-datafusion-bucket-1")
 BUCKET_2 = os.environ.get("GCP_DATAFUSION_BUCKET_2", "test-datafusion-bucket-2")
 
-BUCKET_1_URI = f"gs//{BUCKET_1}"
-BUCKET_2_URI = f"gs//{BUCKET_2}"
+BUCKET_1_URI = f"gs://{BUCKET_1}"
+BUCKET_2_URI = f"gs://{BUCKET_2}"
 
 PIPELINE_NAME = os.environ.get("GCP_DATAFUSION_PIPELINE_NAME", "airflow_test")
 PIPELINE = {
     "name": "test-pipe",
     "description": "Data Pipeline Application",
-    "artifact": {"name": "cdap-data-pipeline", "version": "6.1.2", "scope": "SYSTEM"},
+    "artifact": {"name": "cdap-data-pipeline", "version": "6.4.1", "scope": "SYSTEM"},
     "config": {
         "resources": {"memoryMB": 2048, "virtualCores": 1},
         "driverResources": {"memoryMB": 2048, "virtualCores": 1},
@@ -72,7 +77,7 @@
                     "label": "GCS",
                     "artifact": {
                         "name": "google-cloud",
-                        "version": "0.14.2",
+                        "version": "0.17.3",
                         "scope": "SYSTEM",
                     },
                     "properties": {
@@ -105,7 +110,7 @@
                     "label": "GCS2",
                     "artifact": {
                         "name": "google-cloud",
-                        "version": "0.14.2",
+                        "version": "0.17.3",
                         "scope": "SYSTEM",
                     },
                     "properties": {
@@ -176,7 +181,7 @@
         location=LOCATION,
         instance_name=INSTANCE_NAME,
         instance=INSTANCE,
-        update_mask="instance.displayName",
+        update_mask="",
         task_id="update_instance",
     )
     # [END howto_cloud_data_fusion_update_instance_operator]
@@ -223,6 +228,7 @@
         pipeline_name=PIPELINE_NAME,
         pipeline_id=start_pipeline_async.output,
         expected_statuses=["COMPLETED"],
+        failure_statuses=["FAILED"],
         instance_name=INSTANCE_NAME,
         location=LOCATION,
     )

airflow/providers/google/cloud/example_dags/example_functions.py

@@ -67,7 +67,7 @@
 )
 GCF_ZIP_PATH = os.environ.get('GCF_ZIP_PATH', '')
 GCF_ENTRYPOINT = os.environ.get('GCF_ENTRYPOINT', 'helloWorld')
-GCF_RUNTIME = 'nodejs6'
+GCF_RUNTIME = 'nodejs14'
 GCP_VALIDATE_BODY = os.environ.get('GCP_VALIDATE_BODY', "True") == "True"
 
 # [START howto_operator_gcf_deploy_body]

airflow/providers/google/cloud/hooks/datafusion.py

@@ -333,7 +333,9 @@ def create_pipeline(
         url = os.path.join(self._base_url(instance_url, namespace), quote(pipeline_name))
         response = self._cdap_request(url=url, method="PUT", body=pipeline)
         if response.status != 200:
-            raise AirflowException(f"Creating a pipeline failed with code {response.status}")
+            raise AirflowException(
+                f"Creating a pipeline failed with code {response.status} while calling {url}"
+            )
 
     def delete_pipeline(
         self,

airflow/providers/google/cloud/sensors/datafusion.py

@@ -33,6 +33,8 @@ class CloudDataFusionPipelineStateSensor(BaseSensorOperator):
     :type pipeline_name: str
     :param expected_statuses: State that is expected
     :type expected_statuses: set[str]
+    :param failure_statuses: State that will terminate the sensor with an exception
+    :type failure_statuses: set[str]
     :param instance_name: The name of the instance.
     :type instance_name: str
     :param location: The Cloud Data Fusion location in which to handle the request.
@@ -70,6 +72,7 @@ def __init__(
         expected_statuses: Set[str],
         instance_name: str,
         location: str,
+        failure_statuses: Set[str] = None,
         project_id: Optional[str] = None,
         namespace: str = "default",
         gcp_conn_id: str = 'google_cloud_default',
@@ -81,6 +84,7 @@ def __init__(
         self.pipeline_name = pipeline_name
         self.pipeline_id = pipeline_id
         self.expected_statuses = expected_statuses
+        self.failure_statuses = failure_statuses
         self.instance_name = instance_name
         self.location = location
         self.project_id = project_id
@@ -119,6 +123,12 @@ def poke(self, context: dict) -> bool:
         except AirflowException:
             pass  # Because the pipeline may not be visible in system yet
 
+        if self.failure_statuses and pipeline_status in self.failure_statuses:
+            raise AirflowException(
+                f"Pipeline with id '{self.pipeline_id}' state is: {pipeline_status}. "
+                f"Terminating sensor..."
+            )
+
         self.log.debug(
             "Current status of the pipeline workflow for %s: %s.", self.pipeline_id, pipeline_status
         )

tests/providers/google/cloud/operators/test_cloud_build_system_helper.py

@@ -79,7 +79,7 @@ def create_repository_and_bucket(self):
                 GCP_PROJECT_ID, GCP_REPOSITORY_NAME
             )
             self.execute_cmd(["git", "remote", "add", "origin", repo_url], cwd=tmp_dir)
-            self.execute_cmd(["git", "push", "--force", "origin", "main"], cwd=tmp_dir)
+            self.execute_cmd(["git", "push", "--force", "origin", "master"], cwd=tmp_dir)
 
     def delete_repo(self):
         """Delete repository in Google Cloud Source Repository service"""

tests/providers/google/cloud/operators/test_dataprep_system.py

@@ -25,11 +25,11 @@
 from tests.test_utils.db import clear_db_connections
 from tests.test_utils.gcp_system_helpers import CLOUD_DAG_FOLDER, GoogleSystemTest
 
-TOKEN = environ.get("DATAPREP_TOKEN", "dataprep-system-test-token")
+TOKEN = environ.get("DATAPREP_TOKEN")
 EXTRA = {"extra__dataprep__token": TOKEN}
 
 
-@pytest.mark.skipif(environ.get("DATAPREP_TOKEN") is None, reason='Dataprep token not present')
+@pytest.mark.skipif(TOKEN is None, reason='Dataprep token not present')
 class DataprepExampleDagsTest(GoogleSystemTest):
     """
     System tests for Dataprep operators.