[jira] [Commented] (AIRFLOW-584) Airflow Pool does not limit running tasks

["Estefania Rabadan (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/AIRFLOW-584?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16465741#comment-16465741 ] 

Estefania Rabadan commented on AIRFLOW-584:
-------------------------------------------

Same issue in 1.9.0

> Airflow Pool does not limit running tasks
> -----------------------------------------
>
>                 Key: AIRFLOW-584
>                 URL: https://issues.apache.org/jira/browse/AIRFLOW-584
>             Project: Apache Airflow
>          Issue Type: Bug
>          Components: pools
>    Affects Versions: Airflow 1.7.1.3
>         Environment: Ubuntu 14.04
>            Reporter: David Kegley
>            Priority: Major
>         Attachments: img1.png, img2.png
>
>
> Airflow pools are not limiting the number of running task instances for the following dag in 1.7.1.3
> Steps to recreate:
> Create a pool of size 5 through the UI.
> The following dag has 52 tasks with increasing priority corresponding to the task number. There should only ever be 5 tasks running at a time however I observed 29 'used slots' in a pool with 5 slots
> {code}
> dag_name = 'pools_bug'
> default_args = {
>     'owner': 'airflow',
>     'depends_on_past': False,
>     'start_date': datetime(2016, 10, 20),
>     'email_on_failure': False,
>     'retries': 1
> }
> dag = DAG(dag_name, default_args=default_args, schedule_interval="0 8 * * *")
> start = DummyOperator(task_id='start', dag=dag)
> end = DummyOperator(task_id='end', dag=dag)
> for i in range(50):
>     sleep_command = 'sleep 10'
>     task_name = 'task-{}'.format(i)
>     op = BashOperator(
>         task_id=task_name,
>         bash_command=sleep_command,
>         execution_timeout=timedelta(hours=4),
>         priority_weight=i,
>         pool=dag_name,
>         dag=dag)
>     start.set_downstream(op)
>     end.set_upstream(op)
> {code}
> Relevant configurations from airflow.cfg:
> {code}
> [core]
> # The executor class that airflow should use. Choices include
> # SequentialExecutor, LocalExecutor, CeleryExecutor
> executor = CeleryExecutor
> # The amount of parallelism as a setting to the executor. This defines
> # the max number of task instances that should run simultaneously
> # on this airflow installation
> parallelism = 64
> # The number of task instances allowed to run concurrently by the scheduler
> dag_concurrency = 64
> # The maximum number of active DAG runs per DAG
> max_active_runs_per_dag = 1
> [celery]
> # This section only applies if you are using the CeleryExecutor in
> # [core] section above
> # The app name that will be used by celery
> celery_app_name = airflow.executors.celery_executor
> # The concurrency that will be used when starting workers with the
> # "airflow worker" command. This defines the number of task instances that
> # a worker will take, so size up your workers based on the resources on
> # your worker box and the nature of your tasks
> celeryd_concurrency = 64
> [scheduler]
> # Task instances listen for external kill signal (when you clear tasks
> # from the CLI or the UI), this defines the frequency at which they should
> # listen (in seconds).
> job_heartbeat_sec = 5
> # The scheduler constantly tries to trigger new tasks (look at the
> # scheduler section in the docs for more information). This defines
> # how often the scheduler should run (in seconds).
> scheduler_heartbeat_sec = 5
> {code}
> !img1.png!
> !img2.png!



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