jaketf commented on a change in pull request #8954:
URL: https://github.com/apache/airflow/pull/8954#discussion_r437578759
##########
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",
Review comment:
As long as we cover batch pipelines (with spark or MR backend I think we
should be good)
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