fenglu-g commented on a change in pull request #4083: [AIRFLOW-3211] Reattach
to GCP Dataproc jobs upon Airflow restart
URL: https://github.com/apache/incubator-airflow/pull/4083#discussion_r227528926
##########
File path: airflow/contrib/hooks/gcp_dataproc_hook.py
##########
@@ -33,12 +33,82 @@ def __init__(self, dataproc_api, project_id, job,
region='global',
self.dataproc_api = dataproc_api
self.project_id = project_id
self.region = region
+
+ # Check if the job to submit is already running on the cluster.
+ # If so, don't resubmit the job.
+ try:
+ cluster_name = job['job']['placement']['clusterName']
+ except KeyError:
+ self.log.error('Job to submit is incorrectly configured.')
+ raise
+
+ jobs_on_cluster_response =
dataproc_api.projects().regions().jobs().list(
+ projectId=self.project_id,
+ region=self.region,
+ clusterName=cluster_name).execute()
+
+ UUID_LENGTH = 9
Review comment:
This seems to be a bit error prone. How about the following? Let's modify
the submit job operator interface by taking a new parameter job_dedupe_regex,
when set, the hook will match existing jobs with this job_dedupe_regex and skip
a new submission if a new match is found and other conditions are met.
This way, the hook implementation is entirely decoupled from the operator
implementation re: job-name and open to other ways of deduping dataproc jobs.
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