Question

我正在使用apache airflow 1.8.0。

这是我backfill工作时的输出。

[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']

当我尝试安排任何DAG时，它会抛出错误。

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]>}

使用 python 2.7 和 python 3.5进行测试

使用 SequentialExecutor 和 LocalExecutor

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

Answer 1

您的气流实例处于死锁状态。失败的任务不允许将来运行任务。

Airflow在每个dag运行中启动每个任务作为一个新进程，当任务停滞不前并且没有处理时，会出现死锁情况

要解决此问题，您可以执行以下操作之一：

使用airflow clear <<dag_id>>这将解决死锁并允许将来运行DAG /任务
如果上述方法无法解决问题，则需要use airflow resetdb这样可以清除气流数据库，从而解决问题

将来，

尝试使用execution_timeout=timedelta(minutes=2)设置一些超时，以便您对运营商
此外，确实提供一个on_failure_callback=handle_failure，它将在运行失败时干净地存在

希望这有帮助，

干杯！

apache airflow scheduler不安排工作

1 个答案: