Apache airflow: setting catchup to False is not working - scheduler

Question

I have a DAG created on Apache airflow. It seems the scheduler is configured to run it from June 2015 (By the way. I do not know why, but it is a new DAG I created and I didn't backfill it, I only backfilled other dags with different DAG IDs with these date intervals, and the scheduler took those dates and backfilled my new dag. I'm starting to work with airflow).
(Update: I realized DAG is backfilled because the start date is set on the DAG default config, although this does not explain the behaviour I expose below)
I'm trying to stop the scheduler to run all the DAG executions from that date. airflow backfill --mark_success tutorial2 -s '2015-06-01' -e '2019-02-27' command is giving me database errors (see below), so I'm trying to set catchup to False.
sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) no such
table: job [SQL: 'INSERT INTO job (dag_id, state, job_type,
start_date, end_date, latest_heartbeat, executor_class, hostname,
unixname) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)'] [parameters:
('tutorial2', 'running', 'BackfillJob', '2019-02-27 10:52:37.281716',
None, '2019-02-27 10:52:37.281733', 'SequentialExecutor',
'08b6eb432df9', 'airflow')] (Background on this error at:
http://sqlalche.me/e/e3q8)
So I'm using another approach. What I've tried:
Setting catchup_by_default = False in airflow.cfg and restarting the
whole docker container.
Setting catchup = False on my python DAG file and launching the file
with python again.
What I'm seeing on the web UI:
DAG's executions are being launched starting in June 2015:
[![DAG's executions are being launched starting in June 2015.][1]][1]
[1]: https://i.stack.imgur.com/7hlL9.png
Catchup is set to False on DAG's configuration:
[![Catchup is set to False on DAG's configuration][2]][2]
[2]: https://i.stack.imgur.com/E01Cc.png
So I don't understand why those DAG's executions are being launched.
Thank you
DAG code:
"""
Code that goes along with the Airflow tutorial is located at:
https://github.com/apache/airflow/blob/master/airflow/example_dags/tutorial.py
"""
from airflow import DAG
from airflow.operators.bash_operator import BashOperator
from datetime import datetime, timedelta
default_args = {
'owner': 'airflow',
'depends_on_past': False,
'start_date': datetime(2015, 6, 1),
'email': ['airflow#example.com'],
'email_on_failure': False,
'email_on_retry': False,
'retries': 1,
'retry_delay': timedelta(minutes=5),
'catchup' : False,
# 'queue': 'bash_queue',
# 'pool': 'backfill',
# 'priority_weight': 10,
# 'end_date': datetime(2016, 1, 1),
}
dag = DAG(
'tutorial2', default_args=default_args, schedule_interval='* * * * *')
# t1, t2 and t3 are examples of tasks created by instantiating operators
t1 = BashOperator(
task_id='print_date',
bash_command='date',
dag=dag)
t2 = BashOperator(
task_id='sleep',
bash_command='sleep 5',
retries=3,
dag=dag)
templated_command = """
{% for i in range(5) %}
echo "{{ ds }}"
echo "{{ macros.ds_add(ds, 7)}}"
echo "{{ params.my_param }}"
{% endfor %}
"""
t3 = BashOperator(
task_id='templated',
bash_command=templated_command,
params={'my_param': 'Parameter I passed in'},
dag=dag)
t2.set_upstream(t1)
t3.set_upstream(t1)

Answer 1

I think you actually need to specify the catchup at the dag level, not pass it in through default_args. (The latter doesn't really make sense anyway, since those are the default args for the tasks. You couldn't have some tasks catch up and others not.)
Try this:
dag = DAG(
'tutorial2', default_args=default_args, schedule_interval='* * * * *', catchup=False)