[GitHub] [airflow] jaketf commented on a change in pull request #8954: Wait for pipeline state in Data Fusion operators

[GitBox <gi...@apache.org>]

jaketf commented on a change in pull request #8954:
URL: https://github.com/apache/airflow/pull/8954#discussion_r437578183



##########
File path: airflow/providers/google/cloud/hooks/datafusion.py
##########
@@ -435,20 +435,52 @@ def _get_pipeline(
             "workflows",
             "DataPipelineWorkflow",
             "runs",
+            pipeline_id,
         )
         response = self._cdap_request(url=url, method="GET")
         if response.status != 200:
             raise AirflowException(
-                f"Retrieving a pipeline failed with code {response.status}"
+                f"Retrieving a pipeline state failed with code {response.status}"
             )
+        workflow = json.loads(response.data)
+        return workflow["status"]
 
-        pipelines_list = json.loads(response.data)
-        for pipe in pipelines_list:
-            runtime_args = json.loads(pipe["properties"]["runtimeArgs"])
-            if runtime_args[job_id_key] == faux_pipeline_id:
-                return pipe
+    def _get_pipeline_run_id(
+        self,
+        pipeline_name: str,
+        faux_pipeline_id: str,
+        instance_url: str,
+        namespace: str = "default",
+    ) -> str:
+        url = os.path.join(
+            instance_url,
+            "v3",
+            "namespaces",
+            namespace,
+            "apps",
+            pipeline_name,
+            "workflows",
+            "DataPipelineWorkflow",
+            "runs",
+        )
+        # Try 5 times to get the CDAP runid. We do this because the pipeline
+        # may not be present instantly
+        for _ in range(5):
+            response = self._cdap_request(url=url, method="GET")
+            if response.status != 200:

Review comment:
       I think we should just handle batch pipelines in this PR (as this is implicitly all the current operator does). Also, anecdotally, I think this covers 90% of use cases for airflow. In the field i have not see a lot of streaming orchestration with airflow.




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