I have three task in one dag.
Task A run first. Task B runs if task A is successful.
I have Task C which has run after Task B but it is not depend up Task B or Task A success or failure.
Task C needs to no matter what happen to task A and B. However, it needs to run after task A and B is completed.
Any idea ?
To have a task run after other tasks are done, but regardless of the outcome of their execution, set the trigger_rule parameter to all_done like so:
my_task = MyOperator(task_id='my_task',
trigger_rule='all_done'
See the trigger rule documentation for more options
Related
I have two tasks A and B. Task A failed once but the retry succeeded and is marked as a success (green). I would expect Task B to perform normally since Task A retry succeeded but it is marked as upstream_failed and was not triggered. Is this a way to fix this behavior?
The Task B has an ALL_SUCCESS trigger rule.
I am using Airflow 2.0.2 on AWS (MWAA).
Trying to restart the scheduler.
upstream_failed happened from scheduler flow or when depends are seting to failed state, you can check states from Task Instances
in Retry Mode:
Task A will be in up_for_retry state until exceed retries number.
If trigger_rule set with all_success(it's default trigger rule), Task B will not trigger untill Task A finished, If every thing running correctly.
Could you add the DAG implementation?
In Apache Airflow, let's say I want to set up a DAG that has 3 tasks.
Task A
Task B
Task C
When the DAG gets scheduled, I want task A to run, followed by Task B (when A completes).
However, I want task C to only run when some external code triggers it (and it shouldn't poll and wait for an external condition to be satisfied; I want it to wait until it receives an external request to start execution, but only if A and B are completed).
I also don't want to create another DAG for task C.
Is this possible? How to set up please? Will it require another task between B and C?
Thanks for any advice on how this can be achieved.
The best way to achieve this is to have two tasks leading into task C, so for example:
A >> [B, x] >> C
Where x is a new task. Then you can set x to be your other trigger condition from somewhere external.
For example if you're waiting for a certain file to be delivered for C to execute, create x as a BranchOperator, and only return C from it if the file exists.
I'm trying to see whether or not there is a straightforward way to not start the next dag run if the previous dag run has failures. I already set depends_on_past=True, wait_for_downstream=True, max_active_runs=1.
What i have is tasks 1, 2, 3 where they:
create resources
run job
tear down resources
task 3 always runs with trigger_rule=all_done to make sure we always tear down resources. What i'm seeing is that if task 2 fails, and task 3 then succeeds, the next dag run starts and if i have wait_for_downstream=False it runs task 1 since the previous task 1 was a success and if i have wait_for_downstream=true then it doesn't start the dag as i expect which is perfect.
The problem is that if tasks 1 and 2 succeed but task 3 fails for some reason, now my next dag run starts and task 1 runs immediately because both task 1 and task 2 (due to wait_for_downstream) were successful in the previous run. This is the worst case scenario because task 1 creates resources and then the job is never run so the resources just sit there allocated.
What i ultimately want is for any failure to stop the dag from proceeding to the next dag run. If my previous dag run is marked as fail then the next one should not start at all. Is there any mechanism for doing this?
My current 2 best effort ideas are:
Use a sub dag so that there's only 1 task in the parent dag and therefore the next dag run will never start at all if the previous single task dag failed. This seems like it will work but i've seen mixed reviews on the use of sub dag operators.
Do some sort of logic within the dag as a first task that manually queries the DB to see if the dag has previous failures and fails the task if it does. This seems hacky and not ideal but that it could work as well.
Is there any out of the box solution for this? Seems fairly standard to not want to continue on failure and not want step 1 to start of run 2 if not all steps of run 1 were successful or if run 1 itself was marked as failed.
The reason depends_on_past is not helping your is it's a task parameter not a dag parameter.
Essentially what you're asking for is for the dag to be disabled after a failure.
I can imagine valid use cases for this, and maybe we should add an AirflowDisableDagException that would trigger this.
The problem with this is you risk having your dag disabled and not noticing for days or weeks.
A better solution would be to build recovery or abort logic into your pipeline so that you don't need to disable the dag.
One way you can do this is add a cleanup task to the start of your dag, which can check whether resources were left sitting there and tear them down if appropriate, and just fail the dag run immediately if you get an appropriate error. You can consider using airflow Variable or Xcom to store the state of your resources.
The other option, notwithstanding the risks, is the disable dag approach: if your process fails to tear down resources appropriately, disable the dag. Something along these lines should work:
class MyOp(BaseOperator):
def disable_dag(self):
orm_dag = DagModel(dag_id=self.dag_id)
orm_dag.set_is_paused(is_paused=True)
def execute(self, context):
try:
print('something')
except TeardownFailedError:
self.disable_dag()
The ExternalTaskSensor may work, with an execution_delta of datetime.timedelta(days=1). From the docs:
execution_delta (datetime.timedelta) – time difference with the previous execution to look at, the default is the same execution_date as the current task or DAG. For yesterday, use [positive!] datetime.timedelta(days=1). Either execution_delta or execution_date_fn can be passed to ExternalTaskSensor, but not both.
I've only used it to wait for upstream DAG's to finish, but seems like it should work as self-referencing because the dag_id and task_id are arguments for the sensor. But you'll want to test it first of course.
I have a DAG with Task A, Task B, and Task C running one after another.
Is there a way that I can trigger to run just Task B and C from the UI?
From this question: Triggering a task in Airflow with the CLI run command, I know that we can trigger task from CLI.
But I dont know how to do so via the UI
Click on Task B and click CLEAR, this will start running from TASK B and TASK C
Currently I have a task that run every 5 minute.
what I want is to have that task rerun every time it is completed with 1 minute delay.
what I have in mind is to create multiple task, task A and task B. task B will run after task A complete and vice versa. But not sure how to execute that.
I have found a workaround for my situation. what I do is create loop for task A to run followed by task B with delay in between.