Release 6.3.4 - Airflow v3 compatibility

Author: dotinfinity

config/config.json

@@ -195,4 +195,4 @@
             "reporting": "REPORTING_OracleEBS"
         }
     }
-}
+}

docs/deprecated/README.md

@@ -321,7 +321,7 @@ Navigate to [Cloud Storage](https://console.cloud.google.com/storage/create-buck
 **Alternatively**, you can use the following command to create a bucket from the Cloud Shell:
 
 ```bash
-gsutil mb -l <REGION/MULTI-REGION> gs://<BUCKET NAME>
+gcloud storage buckets create --location <REGION/MULTI-REGION> gs://<BUCKET NAME>
 ```
 
 Navigate to the _Permissions_ tab. Grant `Storage Object Creator` to the user executing the Build command or to the Service account you created for impersonation.
@@ -333,7 +333,7 @@ You can create a specific bucket for the Cloud Build process to store the logs.
 **Alternatively**, here is the command line to create this bucket:
 
 ```bash
-gsutil mb -l <REGION/MULTI-REGION> gs://<BUCKET NAME>
+gcloud storage buckets create -l <REGION/MULTI-REGION> gs://<BUCKET NAME>
 ```
 
 You will need to grant `Object Admin` permissions to the Cloud Build service account.
@@ -560,8 +560,8 @@ We recommend pasting the generated SQL into BigQuery to identify and correct the
 If you opted to generate integration or CDC files and have an instance of Cloud Composer (Airflow), you can move them into their final bucket with the following command:
 
 ```bash
-gsutil -m cp -r  gs://<output bucket>/dags/ gs://<composer DAG bucket>/
-gsutil -m cp -r  gs://<output bucket>/data/ gs://<composer DAG bucket>/
+gcloud storage cp --recursive  gs://<output bucket>/dags/ gs://<composer DAG bucket>/
+gcloud storage cp --recursive  gs://<output bucket>/data/ gs://<composer DAG bucket>/
 ```
 
 ## Test, customize and prepare for upgrade

docs/deprecated/RELEASE_NOTES.md

@@ -202,11 +202,11 @@ The following changes are on our roadmap and are planned to happen **no sooner t
 *   Option for `sequential` deployment (TURBO=false) for SFDC incorporated.
 *   Salesforce integration now updates the RAW tables with changes, merging changes on landing. This removes the need for additional CDC processing. Deltas are captured using SystemModstamp provided by Salesforce APIs. See details in README.
 *   `IsArchived` flag is removed from CDC processing for Salesforce.
-*   Errors originating from gsutil steps in cloudbuild.sfdc.yaml not finding files to copy are now caught and surfaced gracefully.
+*   Errors originating from gcloud storage steps in cloudbuild.sfdc.yaml not finding files to copy are now caught and surfaced gracefully.
 *   Removing some `substitution` defaults (e.g., LOCATION) from cloudbuild.yaml file so all configurations are either passed from the command line or read from `config/config.json`. 🚨🔪🚨[TL;DR submit sample call](https://github.com/GoogleCloudPlatform/cortex-data-foundation#tldr-for-setup) was updated to default these flags. These parameters will be removed from subsitution defaults in future releases. 🚨🔪🚨
 *   Detecting version for Airflow in DAG templates to use updated libraries for Airflow v2 in SAP and Salesforce. This remvoes some deprecation warnings but may need additional libraries installed in your Airflow instance.
 *   Fix for test harness data not loading in an intended location when the location is not passed as a substitution.
-*   Checking existence of DAG-generated files before attempting to copy with `gsutil` to avoid errors.
+*   Checking existence of DAG-generated files before attempting to copy with `gcloud storage cp` to avoid errors.
 *   **NOTE**: 🚨🚨Structure of RAW landed tables has changed🚨🚨 to not require additional DAG processing. Please check the documentation on mapping and use of the new extraction process before upgrading to avoid disruption. We recommend pausing the replication, making abackup copy of any loaded tables, modifying the schemata of existing loaded tables and testing the new DAGs work with the new columns. The DAG will start fetching records using the last SystemModstamp present in RAW.
 ## December 2022 - Release 4.0
 *   **🎆Welcome Salesforce.com to Cortex Data Foundation🎆🐈🦄**: New [module for Salesforce](https://github.com/GoogleCloudPlatform/cortex-salesforce), to be implemented alongside the SAP models or on its own. The module includes optional integration and CDC scripts and reporting views for Leads Capture & Conversion, Opportunity Trends & Pipeline, Sales Activity and Engagement, Case Overview and Trends, Case Management & Resolution, Accounts with Cases. See the [entity-relationship diagram](images/erd_sfdc.png) for a list of tables and views. Check the [Looker repository](https://github.com/looker-open-source/block-cortex-salesforce) for sample dashboards.

src/OracleEBS/src/common/materializer/deploy.sh

@@ -220,8 +220,8 @@ echo "generate_dependent_dags.py completed successfully."
 if [[ $(find generated_materializer_dag_files/*/*/task_dep_dags -type f 2> /dev/null | wc -l) -gt 0 ]]
 then
   echo "Copying DAG files to GCS bucket..."
-  echo "gsutil -m cp -r 'generated_materializer_dag_files/*' gs://${GCS_TGT_BUCKET}/dags/"
-  gsutil -m cp -r 'generated_materializer_dag_files/*' "gs://${GCS_TGT_BUCKET}/dags/"
+  echo "gcloud storage cp --recursive 'generated_materializer_dag_files/*' gs://${GCS_TGT_BUCKET}/dags/"
+  gcloud storage cp --recursive 'generated_materializer_dag_files/*' "gs://${GCS_TGT_BUCKET}/dags/"
 else
   echo "No task dependent DAG files to copy to GCS bucket!"
 fi

src/OracleEBS/src/common/materializer/templates/airflow_dag_template_reporting.py

@@ -24,6 +24,8 @@
 from datetime import timedelta
 
 import airflow
+from airflow import __version__ as airflow_version
+from packaging.version import Version
 from airflow.operators.empty import EmptyOperator
 from airflow.providers.google.cloud.operators.bigquery import \
     BigQueryInsertJobOperator
@@ -34,18 +36,23 @@
 
 default_dag_args = {
    "depends_on_past": False,
-   "start_date": datetime(${year}, ${month}, ${day}),
+   "start_date": datetime(int("${year}"), int("${month}"), int("${day}")),
    "catchup": False,
    "retries": 1,
    "retry_delay": timedelta(minutes=30),
 }
 
+if Version(airflow_version) >= Version("2.4.0"):
+    schedule_kwarg = {"schedule": "${load_frequency}"}
+else:
+    schedule_kwarg = {"schedule_interval": "${load_frequency}"}
+
 with airflow.DAG("${dag_full_name}",
                  default_args=default_dag_args,
                  catchup=False,
                  max_active_runs=1,
-                 schedule_interval="${load_frequency}",
-                 tags=${tags}) as dag:
+                 tags=ast.literal_eval("${tags}"),
+                 **schedule_kwarg) as dag:
     start_task = EmptyOperator(task_id="start")
     refresh_table = BigQueryInsertJobOperator(
             task_id="refresh_table",

src/OracleEBS/src/common/materializer/templates/airflow_task_dep_dag_template_reporting.py

@@ -24,6 +24,8 @@
 from datetime import timedelta
 
 import airflow
+from airflow import __version__ as airflow_version
+from packaging.version import Version
 from airflow.operators.empty import EmptyOperator
 from airflow.providers.google.cloud.operators.bigquery import \
     BigQueryInsertJobOperator
@@ -36,18 +38,23 @@
 
 default_dag_args = {
    "depends_on_past": False,
-   "start_date": datetime(${year}, ${month}, ${day}),
+   "start_date": datetime(int("${year}"), int("${month}"), int("${day}")),
    "catchup": False,
    "retries": 1,
    "retry_delay": timedelta(minutes=30),
 }
 
+if Version(airflow_version) >= Version("2.4.0"):
+    schedule_kwarg = {"schedule": "${load_frequency}"}
+else:
+    schedule_kwarg = {"schedule_interval": "${load_frequency}"}
+
 with airflow.DAG("${dag_full_name}",
                  default_args=default_dag_args,
                  catchup=False,
                  max_active_runs=1,
-                 schedule_interval="${load_frequency}",
-                 tags=${tags}) as dag:
+                 tags=ast.literal_eval("${tags}"),
+                 **schedule_kwarg) as dag:
 
     start_task = EmptyOperator(task_id="start")
 

src/OracleEBS/src/common/materializer/templates/cloudbuild_materializer.yaml.jinja

@@ -88,8 +88,8 @@ steps:
       if [[ $(find generated_materializer_dag_files -type f 2> /dev/null | wc -l) -gt 0 ]]
       then
         echo "Copying DAG files to GCS bucket..."
-        echo "gsutil -m cp -r 'generated_materializer_dag_files/*' gs://${_GCS_TGT_BUCKET}/dags/"
-        gsutil -m cp -r 'generated_materializer_dag_files/*' gs://${_GCS_TGT_BUCKET}/dags/
+        echo "gcloud storage cp --recursive 'generated_materializer_dag_files/*' gs://${_GCS_TGT_BUCKET}/dags/"
+        gcloud storage cp --recursive 'generated_materializer_dag_files/*' gs://${_GCS_TGT_BUCKET}/dags/
       else
         echo "No files to copy to GCS bucket!"
       fi

src/OracleEBS/src/common/py_libs/k9_deployer.py

@@ -82,10 +82,10 @@ def _simple_process_and_upload(k9_id: str, k9_dir: str, jinja_dict: dict,
         if "__init__.py" not in [str(p.relative_to(k9_dir)) for p in k9_files]:
             with open(f"{tmp_dir}/__init__.py", "w", encoding="utf-8") as f:
                 f.writelines([
-                    "import os",
-                    "import sys",
+                    "import os\n",
+                    "import sys\n",
                     ("sys.path.append("
-                     "os.path.dirname(os.path.realpath(__file__)))")
+                     "os.path.dirname(os.path.realpath(__file__)))\n")
                 ])
 
         if data_source == "k9":

src/OracleEBS/src/common/py_libs/resource_validation_helper.py

@@ -128,7 +128,7 @@ def validate_resources(
             if isinstance(ex, NotFound):
                 logging.error("🛑 Storage bucket `%s` doesn't exist. 🛑",
                               bucket.name)
-            elif isinstance(ex, Unauthorized, Forbidden):
+            elif isinstance(ex, (Unauthorized, Forbidden)):
                 if checking_on_writing:
                     logging.error("🛑 Storage bucket `%s` "
                                 "is not writable. 🛑", bucket.name)

src/SAP/SAP_CDC/cdc_settings.yaml

@@ -312,3 +312,7 @@ data_to_replicate:
     load_frequency: "@weekly"
   - base_table: mkol
     load_frequency: "@weekly"
+## CORTEX-CUSTOMER: Uncomment if you need optional address notes/remarks in AddressMD view.
+#  - base_table: adrt
+#    load_frequency: "@daily"
+