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update done and fail detection for workflow

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* Instead of traversing the workflow graph to determine if a workflow is
done or has failed; instead, loop through all the nodes in the graph and
grab only the relevant nodes.
This commit is contained in:
chris meyers
2018-11-13 16:13:12 -05:00
parent 834c49b73c
commit 7c52208627
2 changed files with 23 additions and 41 deletions
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4
awx/main/scheduler/task_manager.py
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@@ -163,6 +163,7 @@ class TaskManager():
dag = WorkflowDAG(workflow_job)
status_changed = False
if workflow_job.cancel_flag:
workflow_job.workflow_nodes.filter(do_not_run=False, job__isnull=True).update(do_not_run=True)
logger.debug('Canceling spawned jobs of %s due to cancel flag.', workflow_job.log_format)
cancel_finished = dag.cancel_node_jobs()
if cancel_finished:
@@ -172,11 +173,12 @@ class TaskManager():
workflow_job.save(update_fields=['status', 'start_args'])
status_changed = True
else:
is_done, has_failed = dag.is_workflow_done()
workflow_nodes = dag.mark_dnr_nodes()
map(lambda n: n.save(update_fields=['do_not_run']), workflow_nodes)
is_done = dag.is_workflow_done()
if not is_done:
continue
has_failed = dag.has_workflow_failed()
logger.info('Marking %s as %s.', workflow_job.log_format, 'failed' if has_failed else 'successful')
result.append(workflow_job.id)
new_status = 'failed' if has_failed else 'successful'