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The issue started to occur after upgrading airflow from v2.2.5 to v2.3.0. The schedulers are crashing when DAG's SLA is configured. Only occurred when I used CeleryKubernetesExecutor. Tested on CeleryExecutor and it works as expected.
Traceback (most recent call last):
File "/home/airflow/.local/bin/airflow", line 8, in <module>
sys.exit(main())
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/__main__.py", line 38, in main
args.func(args)
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/cli/cli_parser.py", line 51, in command
return func(*args, **kwargs)
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/utils/cli.py", line 99, in wrapper
return f(*args, **kwargs)
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/cli/commands/scheduler_command.py", line 75, in scheduler
_run_scheduler_job(args=args)
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/cli/commands/scheduler_command.py", line 46, in _run_scheduler_job
job.run()
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/base_job.py", line 244, in run
self._execute()
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 736, in _execute
self._run_scheduler_loop()
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 824, in _run_scheduler_loop
num_queued_tis = self._do_scheduling(session)
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 919, in _do_scheduling
self._send_dag_callbacks_to_processor(dag, callback_to_run)
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 1179, in _send_dag_callbacks_to_processor
self._send_sla_callbacks_to_processor(dag)
File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 1195, in _send_sla_callbacks_to_processor
self.executor.send_callback(request)
AttributeError: 'CeleryKubernetesExecutor' object has no attribute 'send_callback'
What you think should happen instead
Work like previous version
How to reproduce
Use CeleryKubernetesExecutor
Configure DAG's SLA
DAG to reproduce:
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""Example DAG demonstrating the usage of the BashOperator."""
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.bash import BashOperator
from airflow.operators.dummy import DummyOperator
DEFAULT_ARGS = {
"sla": timedelta(hours=1),
}
with DAG(
dag_id="example_bash_operator",
default_args=DEFAULT_ARGS,
schedule_interval="0 0 * * *",
start_date=datetime(2021, 1, 1),
catchup=False,
dagrun_timeout=timedelta(minutes=60),
tags=["example", "example2"],
params={"example_key": "example_value"},
) as dag:
run_this_last = DummyOperator(
task_id="run_this_last",
)
# [START howto_operator_bash]
run_this = BashOperator(
task_id="run_after_loop",
bash_command="echo 1",
)
# [END howto_operator_bash]
run_this >> run_this_last
for i in range(3):
task = BashOperator(
task_id="runme_" + str(i),
bash_command='echo "{{ task_instance_key_str }}" && sleep 1',
)
task >> run_this
# [START howto_operator_bash_template]
also_run_this = BashOperator(
task_id="also_run_this",
bash_command='echo "run_id={{ run_id }} | dag_run={{ dag_run }}"',
)
# [END howto_operator_bash_template]
also_run_this >> run_this_last
# [START howto_operator_bash_skip]
this_will_skip = BashOperator(
task_id="this_will_skip",
bash_command='echo "hello world"; exit 99;',
dag=dag,
)
# [END howto_operator_bash_skip]
this_will_skip >> run_this_last
if __name__ == "__main__":
dag.cli()
Apache Airflow version
2.3.0 (latest released)
What happened
The issue started to occur after upgrading airflow from v2.2.5 to v2.3.0. The schedulers are crashing when DAG's SLA is configured. Only occurred when I used
CeleryKubernetesExecutor
. Tested onCeleryExecutor
and it works as expected.What you think should happen instead
Work like previous version
How to reproduce
CeleryKubernetesExecutor
DAG to reproduce:
Operating System
Debian GNU/Linux 11 (bullseye)
Versions of Apache Airflow Providers
No response
Deployment
Official Apache Airflow Helm Chart
Deployment details
No response
Anything else
No response
Are you willing to submit PR?
Code of Conduct
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