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synced 2026-05-24 17:17:45 -02:30
we can do all the work in one loop
more than saving the loop, we save building the WorkflowDag twice which makes LOTS of queries!!! Also, do a bulk update on the WorkflowJobNodes instead of saving in a loop :fear:
This commit is contained in:
Elijah DeLee
committed by
Seth Foster
Seth Foster
parent
ad08eafb9a
commit
29d91da1d2
@@ -30,6 +30,7 @@ from awx.main.models import (
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UnifiedJob,
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WorkflowApproval,
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WorkflowJob,
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WorkflowJobNode,
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WorkflowJobTemplate,
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)
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from awx.main.scheduler.dag_workflow import WorkflowDAG
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@@ -132,12 +133,49 @@ class WorkflowManager(TaskBase):
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@timeit
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def spawn_workflow_graph_jobs(self, workflow_jobs):
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logger.debug(f"=== {workflow_jobs}")
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result = []
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for workflow_job in workflow_jobs:
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if workflow_job.cancel_flag:
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logger.debug('Not spawning jobs for %s because it is pending cancelation.', workflow_job.log_format)
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continue
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dag = WorkflowDAG(workflow_job)
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status_changed = False
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if workflow_job.cancel_flag:
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workflow_job.workflow_nodes.filter(do_not_run=False, job__isnull=True).update(do_not_run=True)
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logger.debug('Canceling spawned jobs of %s due to cancel flag.', workflow_job.log_format)
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cancel_finished = dag.cancel_node_jobs()
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if cancel_finished:
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logger.info('Marking %s as canceled, all spawned jobs have concluded.', workflow_job.log_format)
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workflow_job.status = 'canceled'
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workflow_job.start_args = '' # blank field to remove encrypted passwords
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workflow_job.save(update_fields=['status', 'start_args'])
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status_changed = True
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else:
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workflow_nodes = dag.mark_dnr_nodes()
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WorkflowJobNode.objects.bulk_update(workflow_nodes, ['do_not_run'])
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# If workflow is now done, we do special things to mark it as done.
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is_done = dag.is_workflow_done()
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if is_done:
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has_failed, reason = dag.has_workflow_failed()
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logger.debug('Marking %s as %s.', workflow_job.log_format, 'failed' if has_failed else 'successful')
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result.append(workflow_job.id)
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new_status = 'failed' if has_failed else 'successful'
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logger.debug("Transitioning {} to {} status.".format(workflow_job.log_format, new_status))
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update_fields = ['status', 'start_args']
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workflow_job.status = new_status
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if reason:
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logger.info(f'Workflow job {workflow_job.id} failed due to reason: {reason}')
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workflow_job.job_explanation = gettext_noop("No error handling paths found, marking workflow as failed")
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update_fields.append('job_explanation')
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workflow_job.start_args = '' # blank field to remove encrypted passwords
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workflow_job.save(update_fields=update_fields)
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status_changed = True
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if status_changed:
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if workflow_job.spawned_by_workflow:
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schedule_task_manager()
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workflow_job.websocket_emit_status(workflow_job.status)
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# Operations whose queries rely on modifications made during the atomic scheduling session
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workflow_job.send_notification_templates('succeeded' if workflow_job.status == 'successful' else 'failed')
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if workflow_job.status == 'running':
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spawn_nodes = dag.bfs_nodes_to_run()
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if spawn_nodes:
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logger.debug('Spawning jobs for %s', workflow_job.log_format)
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@@ -163,7 +201,8 @@ class WorkflowManager(TaskBase):
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)
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display_list = [spawn_node.unified_job_template] + workflow_ancestors
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job.job_explanation = gettext_noop(
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"Workflow Job spawned from workflow could not start because it " "would result in recursion (spawn order, most recent first: {})"
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"Workflow Job spawned from workflow could not start because it "
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"would result in recursion (spawn order, most recent first: {})"
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).format(', '.join(['<{}>'.format(tmp) for tmp in display_list]))
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else:
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logger.debug(
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@@ -194,48 +233,6 @@ class WorkflowManager(TaskBase):
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# TODO: should we emit a status on the socket here similar to tasks.py awx_periodic_scheduler() ?
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# emit_websocket_notification('/socket.io/jobs', '', dict(id=))
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def process_finished_workflow_jobs(self, workflow_jobs):
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result = []
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for workflow_job in workflow_jobs:
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dag = WorkflowDAG(workflow_job)
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status_changed = False
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if workflow_job.cancel_flag:
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workflow_job.workflow_nodes.filter(do_not_run=False, job__isnull=True).update(do_not_run=True)
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logger.debug('Canceling spawned jobs of %s due to cancel flag.', workflow_job.log_format)
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cancel_finished = dag.cancel_node_jobs()
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if cancel_finished:
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logger.info('Marking %s as canceled, all spawned jobs have concluded.', workflow_job.log_format)
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workflow_job.status = 'canceled'
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workflow_job.start_args = '' # blank field to remove encrypted passwords
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workflow_job.save(update_fields=['status', 'start_args'])
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status_changed = True
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else:
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workflow_nodes = dag.mark_dnr_nodes()
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for n in workflow_nodes:
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n.save(update_fields=['do_not_run'])
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is_done = dag.is_workflow_done()
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if not is_done:
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continue
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has_failed, reason = dag.has_workflow_failed()
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logger.debug('Marking %s as %s.', workflow_job.log_format, 'failed' if has_failed else 'successful')
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result.append(workflow_job.id)
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new_status = 'failed' if has_failed else 'successful'
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logger.debug("Transitioning {} to {} status.".format(workflow_job.log_format, new_status))
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update_fields = ['status', 'start_args']
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workflow_job.status = new_status
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if reason:
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logger.info(f'Workflow job {workflow_job.id} failed due to reason: {reason}')
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workflow_job.job_explanation = gettext_noop("No error handling paths found, marking workflow as failed")
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update_fields.append('job_explanation')
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workflow_job.start_args = '' # blank field to remove encrypted passwords
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workflow_job.save(update_fields=update_fields)
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status_changed = True
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if status_changed:
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if workflow_job.spawned_by_workflow:
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schedule_task_manager()
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workflow_job.websocket_emit_status(workflow_job.status)
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# Operations whose queries rely on modifications made during the atomic scheduling session
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workflow_job.send_notification_templates('succeeded' if workflow_job.status == 'successful' else 'failed')
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return result
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def timeout_approval_node(self):
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@@ -265,18 +262,7 @@ class WorkflowManager(TaskBase):
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def _schedule(self):
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running_workflow_tasks = self.get_tasks()
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if len(running_workflow_tasks) > 0:
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self.process_finished_workflow_jobs(running_workflow_tasks)
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previously_running_workflow_tasks = running_workflow_tasks
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running_workflow_tasks = []
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for workflow_job in previously_running_workflow_tasks:
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if workflow_job.status == 'running':
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running_workflow_tasks.append(workflow_job)
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else:
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logger.debug('Removed %s from job spawning consideration.', workflow_job.log_format)
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self.spawn_workflow_graph_jobs(running_workflow_tasks)
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self.timeout_approval_node()
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