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https://issues.apache.org/jira/browse/AIRFLOW-113?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Shenghu Yang closed AIRFLOW-113.
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Resolution: REMIND
> DAG concurrency is not honored
> ------------------------------
>
> Key: AIRFLOW-113
> URL: https://issues.apache.org/jira/browse/AIRFLOW-113
> Project: Apache Airflow
> Issue Type: Improvement
> Components: celery, executor, scheduler
> Affects Versions: Airflow 1.6.2
> Environment: Version of Airflow: 1.6.2
> Airflow configuration: Running a Scheduler with LocalExecutor or
> CeleryExecutor
> 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
> Reporter: Shenghu Yang
>
> This is reported in airflow github also:
> https://github.com/apache/incubator-airflow/issues/1424
> 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 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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