气流:ExternalTask Sensor不会触发任务

问题描述 投票:2回答:2

我已经在SO上看到了thisthis的问题并做出了相应的更改。但是,我的依赖DAG仍然处于戳状态。以下是我的主DAG:

from airflow import DAG
from airflow.operators.jdbc_operator import JdbcOperator
from datetime import datetime
from airflow.operators.bash_operator import BashOperator

today = datetime.today()

default_args = {
    'depends_on_past': False,
    'retries': 0,
    'start_date': datetime(today.year, today.month, today.day),
    'schedule_interval': '@once'
}

dag = DAG('call-procedure-and-bash', default_args=default_args)

call_procedure = JdbcOperator(
    task_id='call_procedure',
    jdbc_conn_id='airflow_db2',
    sql='CALL AIRFLOW.TEST_INSERT (20)',
    dag=dag
)

call_procedure

以下是我的依赖DAG:

from airflow import DAG
from airflow.operators.jdbc_operator import JdbcOperator
from datetime import datetime, timedelta
from airflow.sensors.external_task_sensor import ExternalTaskSensor

today = datetime.today()

default_args = {
    'depends_on_past': False,
    'retries': 0,
    'start_date': datetime(today.year, today.month, today.day),
    'schedule_interval': '@once'
}

dag = DAG('external-dag-upstream', default_args=default_args)

task_sensor = ExternalTaskSensor(
    task_id='link_upstream',
    external_dag_id='call-procedure-and-bash',
    external_task_id='call_procedure',
    execution_delta=timedelta(minutes=-2),
    dag=dag
)

count_rows = JdbcOperator(
    task_id='count_rows',
    jdbc_conn_id='airflow_db2',
    sql='SELECT COUNT(*) FROM AIRFLOW.TEST',
    dag=dag
)

count_rows.set_upstream(task_sensor)

以下是主DAG执行后依赖DAG的日志:

[2019-01-10 11:43:52,951] {{external_task_sensor.py:91}} INFO - Poking for call-procedure-and-bash.call_procedure on 2019-01-10T11:45:47.893735+00:00 ... 
[2019-01-10 11:44:52,955] {{external_task_sensor.py:91}} INFO - Poking for call-procedure-and-bash.call_procedure on 2019-01-10T11:45:47.893735+00:00 ... 
[2019-01-10 11:45:52,961] {{external_task_sensor.py:91}} INFO - Poking for call-procedure-and-bash.call_procedure on 2019-01-10T11:45:47.893735+00:00 ... 
[2019-01-10 11:46:52,949] {{external_task_sensor.py:91}} INFO - Poking for call-procedure-and-bash.call_procedure on 2019-01-10T11:45:47.893735+00:00 ... 
[2019-01-10 11:47:52,928] {{external_task_sensor.py:91}} INFO - Poking for call-procedure-and-bash.call_procedure on 2019-01-10T11:45:47.893735+00:00 ... 
[2019-01-10 11:48:52,928] {{external_task_sensor.py:91}} INFO - Poking for call-procedure-and-bash.call_procedure on 2019-01-10T11:45:47.893735+00:00 ... 
[2019-01-10 11:49:52,905] {{external_task_sensor.py:91}} INFO - Poking for call-procedure-and-bash.call_procedure on 2019-01-10T11:45:47.893735+00:00 ... 

以下是主DAG执行的日志:

[2019-01-10 11:45:20,215] {{jdbc_operator.py:56}} INFO - Executing: CALL AIRFLOW.TEST_INSERT (20)
[2019-01-10 11:45:21,477] {{logging_mixin.py:95}} INFO - [2019-01-10 11:45:21,476] {{dbapi_hook.py:166}} INFO - CALL AIRFLOW.TEST_INSERT (20)
[2019-01-10 11:45:24,139] {{logging_mixin.py:95}} INFO - [2019-01-10 11:45:24,137] {{jobs.py:2627}} INFO - Task exited with return code 0

我的假设是,如果主机运行正常,Airflow应该触发相关的DAG?我试过玩execution_delta,但这似乎不起作用。

此外,两个DAG的schedule_intervalstart_date相同,所以不要认为这会造成任何麻烦。

我错过了什么吗?

python airflow directed-acyclic-graphs airflow-scheduler
2个回答
0
投票

可能你应该使用正时间delta:https://airflow.readthedocs.io/en/stable/_modules/airflow/sensors/external_task_sensor.html,因为当减去执行增量时,它最终将寻找在其自身后2分钟运行的任务。

但是,delta实际上不是一个范围,TI必须在日期时间列表中具有匹配的Dag ID,任务ID,成功结果以及执行日期。当你将execution_delta作为delta时,它是一个日期时间列表,它取当前执行日期并减去timedelta。

这可能取决于您要么删除timedelta以便两个执行日期匹配,传感器将等到另一个任务成功,或者您的开始日期和计划间隔基本上设置为今天,而@once的执行日期不是可预测的相互锁定。您可以尝试设置说datetime(2019,1,10)0 1 * * *让它们每天凌晨1点运行(再次没有execution_delta)。


0
投票

确保两个DAG同时启动,并且不要手动启动任一DAG。

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