I am using latest AirFlow. I ran a dag file which just executes print and sleeps command for 10 seconds.
Once that dag complete 50 successful runs it automatically stoped. When I restart the web server , scheduler and worker then it again runs for another 50. I did this way 2 times and the same result.
There is some issue with the schedule.
Most likely reason is the schedule is made of Catchup or Backfill task with specific start_date and end_date parameters .
for more details https://airflow.apache.org/docs/stable/dag-run.html
Related
I set the schedule like '* 1,5,10,18 * * *' in airflow.
But 18 in yesterday wasn't executed. So I checked the logs.
then I found the job scheduled in 10 executed in 18.
I want to know why and how can I fix.
Note that if you run a DAG on a schedule_interval of one day, the run
stamped 2016-01-01 will be trigger soon after 2016-01-01T23:59. In
other words, the job instance is started once the period it covers has
ended.
~Airflow scheduler docs
So as you can see it will be scheduled after the period - 10->18 is closed, so after 18:00. Check task before, it should be ran just after 10:00.
You don't understand how the airflow scheduler works.
Airflow as DAG Run (data_interval_start) always takes the date of the previous execution, therefore the task performed at your place at 18, has DAG Run at 10. The same as the next task, call at 10 will have a DAG Run at 18 the previous day.
I have a big DAG with around 400 tasks that starts at 8:00 and runs for about 2.5 hours.
There are some smaller DAGs that need to start at 9:00, they are scheduled but are not able to start until the first DAG finishes.
I reduced concurrency=6. The DAG is running only 6 parallel tasks, however this is not solving the issue that the other tasks in other DAGs don't start.
There is no other global configuration to limit the number of running tasks, other smaller dags usually run in parallel.
What can be the issue here?
Ariflow version: 2.1 with Local Executor with Postgres backend running on a 20core server.
Tasks of active DAGs not starting
I don't think it's related to concurrency. This could be related to Airflow using the mini-scheduler.
When a task is finished Task supervisor process perform a "mini scheduler" attempting to schedule more tasks of the same DAG. This means that the DAG will be finished quicker as the downstream tasks are set to Scheduled mode directly however one of it's side effect that it can cause starvation for other DAGs in some circumstances. A case like you present where you have one very big DAG that takes very long time to complete and starts before smaller DAGs may be the exact case where stravation can happen.
Try to set schedule_after_task_execution = False in airflow.cfg and it should solve your issue.
Why don't you use the option to invoke the task after the previous one is finished?
In the first DAG, insert the call to the next one as follows:
trigger_new_dag = TriggerDagRunOperator(
task_id=[task name],
trigger_dag_id=[trigered dag],
dag=dag
)
This operator will start a new DAG after the previous one is executed.
Documentation: https://airflow.apache.org/docs/apache-airflow/stable/_api/airflow/operators/trigger_dagrun/index.html
I am completely new to Airflow and am trying to grasp the concepts of scheduling and default args.
I have a scenario where I would like to schedule my DAG hourly to do some data transfer task between a source and a database. What I am trying to understand is, lets say one of my DAG runs has triggered at 00:00 AM. Now if it takes more than an hour for this run to successfully complete all of its tasks (say 1 hour 30 min), does it mean that the next DAG run that was supposed to be triggered at 01:00 AM will NOT get triggered but the DAG run from 02:00 AM will get triggered?
Yes.
In order to avoid, you need catchup=True for the DAG object.
Reference : https://airflow.apache.org/docs/apache-airflow/stable/dag-run.html
(Search for Catchup)
Airflow Scheduler used to monitor all DAGs and tasks in Airflow.Default Arguments can be used to create tasks with default parameters in DAG.
The first DAG runs based on start_date and runs based on scheduled_interval sequentially. Scheduler doesn’t trigger tasks until the period has ended.For your requirement you can set dag.catchup to true as to run the DAG for each completed interval and scheduler will execute them sequentially.Catchup is used to start the DAG run since the last data interval which has not started for any data interval.
After pausing a dag for 2-3 days, when resuming the dag with catchup=False, will run immediately with the last execution.
For example a dag that sends data to an external system is scheduled to run everyday on 19:00.
Stopping the dag for 4 days and enabling on 11:00 would run the dag immediately with yesterdays execution and then again on 19:00 for that day.
In this case the dag runs two times on the day it's resumed.
Is it possible to resume the dag and the first run will happen actually on 19:00?
With default operators, we cannot achieve what you are expecting. Closest to that, what airflow has is LatestOnlyOperator. This is one of the simplest Operators and needs only following configuration
latest_only = LatestOnlyOperator(task_id='latest_only')
This would let the downstream tasks run only if the current time falls between current execution date and next execution date. So, in your case, it would skip execution of three days, but yesterday's run would trigger the jobs.
Good Day,
we use Airflow to orchestrate runs of our jobs.
The Job in question is usually scheduled for 2:30 and takes quite some time.
Due to a new data source it was expected to run a full day.
Since our jobs don't work parallel we set max_active_runs_per_dag to 1 to ensure that there are no multiple instances of the same job even when it takes more than 24h. In general this seem to work, but not in this case.
What happened:
We triggered a manual run at 13:00
at 2:30 (next day) the scheduled run is triggered and runs simultaneously
Expectation:
The scheduled run should wait for the manual run to finish
More Information:
The Airflow instance did not restart.
Airflow version 1.10.2
I thank you for any advice.
Seems to be an open Issue which will be fixed in 2.1 and 1.15.
A workaround was not provided yet.
https://github.com/apache/airflow/issues/9975