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From "Chris Riccomini (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (AIRFLOW-111) DAG concurrency is not honored
Date Thu, 09 Jun 2016 21:12:20 GMT

     [ https://issues.apache.org/jira/browse/AIRFLOW-111?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Chris Riccomini updated AIRFLOW-111:
------------------------------------
    External issue URL: https://github.com/apache/incubator-airflow/pull/1579

> DAG concurrency is not honored
> ------------------------------
>
>                 Key: AIRFLOW-111
>                 URL: https://issues.apache.org/jira/browse/AIRFLOW-111
>             Project: Apache Airflow
>          Issue Type: Sub-task
>          Components: celery, scheduler
>    Affects Versions: Airflow 1.6.2, Airflow 1.7.1.2
>         Environment: Version of Airflow: 1.6.2
> Airflow configuration: Running a Scheduler with LocalExecutor
> Operating System: 3.13.0-74-generic #118-Ubuntu SMP Thu Dec 17 22:52:10 UTC 2015 x86_64
x86_64 x86_64 GNU/Linux
> Python Version: 2.7.6
> Screen shots of your DAG's status:
>            Reporter: Shenghu Yang
>             Fix For: Airflow 2.0
>
>
> Description of Issue
> In our dag, we set the dag_args['concurrency'] = 8, however, when the scheduler starts
to run, we can see this concurrency is not being honored, airflow scheduler will run up to
num of the 'parallelism' (we set as 25) jobs.
> What did you expect to happen?
> dag_args['concurrency'] = 8 is honored, e.g. only run at most 8 jobs concurrently.
> What happened instead?
> when the dag starts to run, we can see the concurrency is not being honored, airflow
scheduler/celery worker will run up to the 'parallelism' (we set as 25) jobs.
> Here is how you can reproduce this issue on your machine:
> create a dag which contains nothing but 25 parallelized jobs.
> set the dag dag_args['concurrency'] = 8
> set the airflow parallelism to 25
> then run: airflow scheduler
> you will see all 25 jobs are scheduled to run, not 8.



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