A user on airflow 1.9.0 reports that 'max_active_runs' isn't respected. I remembered having fixed something related to this ages ago and this is here:
https://issues.apache.org/jira/browse/AIRFLOW-137 That however was related to backfills and clearing the dagruns. I watched him in the scenario and he literally creates a new simple dag with the following config: ----- from airflow import DAG from datetime import datetime, timedelta from airflow.contrib.operators.bigquery_operator import BigQueryOperator from airflow.contrib.operators.bigquery_to_gcs import BigQueryToCloudStorageOperator from airflow.contrib.operators.gcs_download_operator import GoogleCloudStorageDownloadOperator from airflow.contrib.operators.file_to_gcs import FileToGoogleCloudStorageOperator from airflow.operators.python_operator import PythonOperator from airflow.models import Variable import time default_args = { 'owner': 'airflow', 'start_date': datetime(2018, 2, 10), 'max_active_runs': 1, 'email_on_failure': False, 'email_on_retry': False, } dag = DAG('analytics6', default_args=default_args, schedule_interval='15 12 * * *') ----- When it gets activated, multiple dagruns are created when there are still tasks running on the first date. His version is 1.9.0 from pypi. Is max_active_runs broken or are there other explanations for this particular behavior? Rgds, Gerard
