vxtals opened a new issue #12823: URL: https://github.com/apache/airflow/issues/12823
<!-- Welcome to Apache Airflow! For a smooth issue process, try to answer the following questions. Don't worry if they're not all applicable; just try to include what you can :-) If you need to include code snippets or logs, please put them in fenced code blocks. If they're super-long, please use the details tag like <details><summary>super-long log</summary> lots of stuff </details> Please delete these comment blocks before submitting the issue. --> <!-- IMPORTANT!!! PLEASE CHECK "SIMILAR TO X EXISTING ISSUES" OPTION IF VISIBLE NEXT TO "SUBMIT NEW ISSUE" BUTTON!!! PLEASE CHECK IF THIS ISSUE HAS BEEN REPORTED PREVIOUSLY USING SEARCH!!! Please complete the next sections or the issue will be closed. These questions are the first thing we need to know to understand the context. --> **Apache Airflow version**: apache-airflow 2.0.0b3 **Environment**: Any environment **What happened**: I have dags triggered at same time for several other Dags through TriggerDagRunOperator (let's say this dags have a minute schedule). Then, on_success_callback is not triggered for some of this dags. **What you expected to happen**: Airflow is working pretty fast and sometimes executions_date for these dags is in the same second, so the execution_date stored in the DB is the same, when it calls _execute_dag_callbacks in scheduler_job.py and retrieve DagRun using this date the dag is not the right one. **How to reproduce it**: Create a dag with any task triggered by two other dags with the same schedule, every minute or every 5 minutes will be the faster way of testing. I'm attaching a file with the 3 dags on it as txt [multi_trigger.txt](https://github.com/apache/airflow/files/5645616/multi_trigger.txt) , starting them and waiting to any two consecutive executions with the same execution_date and checking scheduler logs should be enough to reproduce it. **Anything else we need to know**: It doesn't happen in every execution but happens often, and I guess it's more likely with a better machine. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
