AirFlow: How to set large number of external dependencies in one line?
I am reading this question trying to implement dependencies on tasks of other DAG
s. In this example, dependency is written as:
ExternalTaskSensor(
task_id='wait_for_the_first_task_to_be_completed',
external_dag_id='a',
external_task_id='first_task',
dag=dag) >>
In my data warehouse, one table may depends on hundreds of tasks. Using this format, it will generate 2*number of dependencies
lines of codes. This is really unacceptable, is there any better choice?
For instance, in Azkaban
, I can write multi dependencies like this:
dependencies = dag1.task1, dag2.task4, dag2.task5, DAG3.task2, etc...
Any help is appreciated.
hadoop airflow airflow-scheduler
add a comment |
I am reading this question trying to implement dependencies on tasks of other DAG
s. In this example, dependency is written as:
ExternalTaskSensor(
task_id='wait_for_the_first_task_to_be_completed',
external_dag_id='a',
external_task_id='first_task',
dag=dag) >>
In my data warehouse, one table may depends on hundreds of tasks. Using this format, it will generate 2*number of dependencies
lines of codes. This is really unacceptable, is there any better choice?
For instance, in Azkaban
, I can write multi dependencies like this:
dependencies = dag1.task1, dag2.task4, dag2.task5, DAG3.task2, etc...
Any help is appreciated.
hadoop airflow airflow-scheduler
add a comment |
I am reading this question trying to implement dependencies on tasks of other DAG
s. In this example, dependency is written as:
ExternalTaskSensor(
task_id='wait_for_the_first_task_to_be_completed',
external_dag_id='a',
external_task_id='first_task',
dag=dag) >>
In my data warehouse, one table may depends on hundreds of tasks. Using this format, it will generate 2*number of dependencies
lines of codes. This is really unacceptable, is there any better choice?
For instance, in Azkaban
, I can write multi dependencies like this:
dependencies = dag1.task1, dag2.task4, dag2.task5, DAG3.task2, etc...
Any help is appreciated.
hadoop airflow airflow-scheduler
I am reading this question trying to implement dependencies on tasks of other DAG
s. In this example, dependency is written as:
ExternalTaskSensor(
task_id='wait_for_the_first_task_to_be_completed',
external_dag_id='a',
external_task_id='first_task',
dag=dag) >>
In my data warehouse, one table may depends on hundreds of tasks. Using this format, it will generate 2*number of dependencies
lines of codes. This is really unacceptable, is there any better choice?
For instance, in Azkaban
, I can write multi dependencies like this:
dependencies = dag1.task1, dag2.task4, dag2.task5, DAG3.task2, etc...
Any help is appreciated.
hadoop airflow airflow-scheduler
hadoop airflow airflow-scheduler
edited Nov 15 '18 at 7:11
user2894829
asked Nov 15 '18 at 4:10
user2894829user2894829
978
978
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add a comment |
1 Answer
1
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oldest
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You can create your sensors in a loop and set dependencies within it. I think it's cleaner, but I'm not sure if that meets your requirement regarding amount of code as number of dependencies increase.
Example:
dependencies = [('dag1', 'task1'), ('dag2', 'task4'), ('dag2', 'task5'), ('dag3', 'task2')]
other_task = PythonOperator(...)
for dag_id, task_id in dependencies:
sensor = ExternalTaskSensor(
task_id='wait_for_0.1'.format(dag_id, task_id),
external_dag_id=dag_id,
external_task_id=task_id,
dag=dag)
sensor >> other_task
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You can create your sensors in a loop and set dependencies within it. I think it's cleaner, but I'm not sure if that meets your requirement regarding amount of code as number of dependencies increase.
Example:
dependencies = [('dag1', 'task1'), ('dag2', 'task4'), ('dag2', 'task5'), ('dag3', 'task2')]
other_task = PythonOperator(...)
for dag_id, task_id in dependencies:
sensor = ExternalTaskSensor(
task_id='wait_for_0.1'.format(dag_id, task_id),
external_dag_id=dag_id,
external_task_id=task_id,
dag=dag)
sensor >> other_task
add a comment |
You can create your sensors in a loop and set dependencies within it. I think it's cleaner, but I'm not sure if that meets your requirement regarding amount of code as number of dependencies increase.
Example:
dependencies = [('dag1', 'task1'), ('dag2', 'task4'), ('dag2', 'task5'), ('dag3', 'task2')]
other_task = PythonOperator(...)
for dag_id, task_id in dependencies:
sensor = ExternalTaskSensor(
task_id='wait_for_0.1'.format(dag_id, task_id),
external_dag_id=dag_id,
external_task_id=task_id,
dag=dag)
sensor >> other_task
add a comment |
You can create your sensors in a loop and set dependencies within it. I think it's cleaner, but I'm not sure if that meets your requirement regarding amount of code as number of dependencies increase.
Example:
dependencies = [('dag1', 'task1'), ('dag2', 'task4'), ('dag2', 'task5'), ('dag3', 'task2')]
other_task = PythonOperator(...)
for dag_id, task_id in dependencies:
sensor = ExternalTaskSensor(
task_id='wait_for_0.1'.format(dag_id, task_id),
external_dag_id=dag_id,
external_task_id=task_id,
dag=dag)
sensor >> other_task
You can create your sensors in a loop and set dependencies within it. I think it's cleaner, but I'm not sure if that meets your requirement regarding amount of code as number of dependencies increase.
Example:
dependencies = [('dag1', 'task1'), ('dag2', 'task4'), ('dag2', 'task5'), ('dag3', 'task2')]
other_task = PythonOperator(...)
for dag_id, task_id in dependencies:
sensor = ExternalTaskSensor(
task_id='wait_for_0.1'.format(dag_id, task_id),
external_dag_id=dag_id,
external_task_id=task_id,
dag=dag)
sensor >> other_task
answered Nov 15 '18 at 7:40
Daniel HuangDaniel Huang
2,0021015
2,0021015
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