apache airflow scheduler not scheduling jobs

我正在使用apache airflow 1.8.0。apache airflow scheduler not scheduling jobs

这里输出的是当我backfill的工作。

[2017-04-13 09:42:55,857] {models.py:1126} INFO - Dependencies all met for <TaskInstance: example_bash_operator.runme_1 2017-04-13 13:43:00  [scheduled]> 
[2017-04-13 09:42:55,857] {models.py:1126} INFO - Dependencies all met for <TaskInstance: example_bash_operator.runme_1 2017-04-13 13:43:00 [scheduled]> 
[2017-04-13 09:42:55,857] {models.py:1126} INFO - Dependencies all met for <TaskInstance: example_bash_operator.runme_2 2017-04-13 13:45:00 [scheduled]> 
[2017-04-13 09:42:55,858] {models.py:1126} INFO - Dependencies all met for <TaskInstance: example_bash_operator.runme_2 2017-04-13 13:45:00 [scheduled]> 
[2017-04-13 09:42:55,858] {models.py:1126} INFO - Dependencies all met for <TaskInstance: example_bash_operator.runme_2 2017-04-13 13:43:00 [scheduled]> 
[2017-04-13 09:42:55,858] {models.py:1126} INFO - Dependencies all met for <TaskInstance: example_bash_operator.runme_2 2017-04-13 13:43:00 [scheduled]> 
[2017-04-13 09:42:55,858] {models.py:1126} INFO - Dependencies all met for <TaskInstance: example_bash_operator.also_run_this 2017-04-13 13:44:00 [scheduled]> 
[2017-04-13 09:42:55,858] {models.py:1126} INFO - Dependencies all met for <TaskInstance: example_bash_operator.also_run_this 2017-04-13 13:44:00 [scheduled]> 
[2017-04-13 09:42:55,864] {models.py:1120} INFO - Dependencies not met for <TaskInstance: example_bash_operator.run_after_loop 2017-04-13 13:44:00 [scheduled]>, dependency 'Trigger Rule' FAILED: Task's trigger rule 'all_success' requires all upstream tasks to have succeeded, but found 3 non-success(es). upstream_tasks_state={'skipped': Decimal('0'), 'successes': Decimal('0'), 'done': 0, 'upstream_failed': Decimal('0'), 'failed': Decimal('0')}, upstream_task_ids=['runme_0', 'runme_1', 'runme_2']

，当我尝试安排它抛出错误的任何DAG。

Traceback (most recent call last): 
    File "/anaconda3/bin/airflow", line 28, in <module> 
    args.func(args) 
    File "/anaconda3/lib/python3.5/site-packages/airflow/bin/cli.py", line 167, in backfill 
    pool=args.pool) 
    File "/anaconda3/lib/python3.5/site-packages/airflow/models.py", line 3330, in run 
    job.run() 
    File "/anaconda3/lib/python3.5/site-packages/airflow/jobs.py", line 200, in run 
    self._execute() 
    File "/anaconda3/lib/python3.5/site-packages/airflow/jobs.py", line 2021, in _execute 
    raise AirflowException(err) 
airflow.exceptions.AirflowException: ---------------------------------------------------

这是关于任务的输出。

BackfillJob is deadlocked. These tasks have succeeded: 
set() 
These tasks have started: 
{} 
These tasks have failed: 
set() 
These tasks are skipped: 
set() 
These tasks are deadlocked: 
{<TaskInstance: example_bash_operator.runme_0 2017-04-13 13:44:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_1 2017-04-13 13:44:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_0 2017-04-13 13:46:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_2 2017-04-13 13:44:00 [scheduled]>, <TaskInstance: example_bash_operator.also_run_this 2017-04-13 13:46:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_0 2017-04-13 13:45:00 [scheduled]>, <TaskInstance: example_bash_operator.run_this_last 2017-04-13 13:46:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_1 2017-04-13 13:46:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_2 2017-04-13 13:46:00 [scheduled]>, <TaskInstance: example_bash_operator.run_after_loop 2017-04-13 13:46:00 [scheduled]>, <TaskInstance: example_bash_operator.also_run_this 2017-04-13 13:43:00 [scheduled]>, <TaskInstance: example_bash_operator.run_after_loop 2017-04-13 13:43:00 [scheduled]>, <TaskInstance: example_bash_operator.run_this_last 2017-04-13 13:45:00 [scheduled]>, <TaskInstance: example_bash_operator.also_run_this 2017-04-13 13:45:00 [scheduled]>, <TaskInstance: example_bash_operator.run_this_last 2017-04-13 13:43:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_0 2017-04-13 13:43:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_1 2017-04-13 13:45:00 [scheduled]>, <TaskInstance: example_bash_operator.run_after_loop 2017-04-13 13:45:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_1 2017-04-13 13:43:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_2 2017-04-13 13:45:00 [scheduled]>, <TaskInstance: example_bash_operator.runme_2 2017-04-13 13:43:00 [scheduled]>, <TaskInstance: example_bash_operator.also_run_this 2017-04-13 13:44:00 [scheduled]>, <TaskInstance: example_bash_operator.run_after_loop 2017-04-13 13:44:00 [scheduled]>, <TaskInstance: example_bash_operator.run_this_last 2017-04-13 13:44:00 [scheduled]>}

与蟒2.7和蟒3.5

使用SequentialExecutor和LocalExecutor

PS测试。如果我在当前时间回填DAG，它会执行一次，然后针对所有计划的任务抛出上述错误。

来源

2017-04-13 Mubin

您的气流实例处于死锁状态。失败的任务不允许将来执行任务。

气流推出每项任务在运行一个新的过程中的每个DAG和任务的时候上不去，这是不处理死锁的情况出现

要解决此问题，您可以执行下列操作之一：

use **airflow clear** <<dag_id>>这将解决死锁并允许未来DAG /任务的运行
如果以上不能解决问题，则需要use airflow resetdb这将清除气流数据库，从而解决问题

今后，

尝试使用execution_timeout=timedelta(minutes=2)设置一些超时，使你有运营商明确控制
另外，确实提供了on_failure_callback=handle_failure这将干净存在操作上的失败

希望这会有所帮助，

干杯！

来源

2017-04-14 05:37:45

apache airflow scheduler not scheduling jobs

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