I've found myself in a situation where I manually trigger a DAG Run (via airflow trigger_dag datablocks_dag) run, and the Dag Run shows up in the interface, but it then stays "Running" forever without actually doing anything.
When I inspect this DAG Run in the UI, I see the following:
I've got start_date set to datetime(2016, 1, 1), and schedule_interval set to @once. My understanding from reading the docs is that since start_date < now, the DAG will be triggered. The @once makes sure it only happens a single time.
My log file says:
[2017-07-11 21:32:05,359] {jobs.py:343} DagFileProcessor0 INFO - Started process (PID=21217) to work on /home/alex/Desktop/datablocks/tests/.airflow/dags/datablocks_dag.py
[2017-07-11 21:32:05,359] {jobs.py:534} DagFileProcessor0 ERROR - Cannot use more than 1 thread when using sqlite. Setting max_threads to 1
[2017-07-11 21:32:05,365] {jobs.py:1525} DagFileProcessor0 INFO - Processing file /home/alex/Desktop/datablocks/tests/.airflow/dags/datablocks_dag.py for tasks to queue
[2017-07-11 21:32:05,365] {models.py:176} DagFileProcessor0 INFO - Filling up the DagBag from /home/alex/Desktop/datablocks/tests/.airflow/dags/datablocks_dag.py
[2017-07-11 21:32:05,703] {models.py:2048} DagFileProcessor0 WARNING - schedule_interval is used for <Task(BashOperator): foo>, though it has been deprecated as a task parameter, you need to specify it as a DAG parameter instead
[2017-07-11 21:32:05,703] {models.py:2048} DagFileProcessor0 WARNING - schedule_interval is used for <Task(BashOperator): foo2>, though it has been deprecated as a task parameter, you need to specify it as a DAG parameter instead
[2017-07-11 21:32:05,704] {jobs.py:1539} DagFileProcessor0 INFO - DAG(s) dict_keys(['example_branch_dop_operator_v3', 'latest_only', 'tutorial', 'example_http_operator', 'example_python_operator', 'example_bash_operator', 'example_branch_operator', 'example_trigger_target_dag', 'example_short_circuit_operator', 'example_passing_params_via_test_command', 'test_utils', 'example_subdag_operator', 'example_subdag_operator.section-1', 'example_subdag_operator.section-2', 'example_skip_dag', 'example_xcom', 'example_trigger_controller_dag', 'latest_only_with_trigger', 'datablocks_dag']) retrieved from /home/alex/Desktop/datablocks/tests/.airflow/dags/datablocks_dag.py
[2017-07-11 21:32:07,083] {models.py:3529} DagFileProcessor0 INFO - Creating ORM DAG for datablocks_dag
[2017-07-11 21:32:07,234] {models.py:331} DagFileProcessor0 INFO - Finding 'running' jobs without a recent heartbeat
[2017-07-11 21:32:07,234] {models.py:337} DagFileProcessor0 INFO - Failing jobs without heartbeat after 2017-07-11 21:27:07.234388
[2017-07-11 21:32:07,240] {jobs.py:351} DagFileProcessor0 INFO - Processing /home/alex/Desktop/datablocks/tests/.airflow/dags/datablocks_dag.py took 1.881 seconds
What could be causing the issue?
Am I misunderstanding how start_date operates?
Or are the worrisome-seeming schedule_interval WARNING lines in the log file possibly the source of the problem?