Issue 1:
Apache Airflow version

2.1.3 (latest released)

Operating System

Debian

Versions of Apache Airflow Providers

No response

Deployment

Other Docker-based deployment

Deployment details

Custom docker image on k8s

What happened

New dag version was written in same named dag. The only difference was one of specified tags got changed in case, for ex. "test" to "Test". With huge amount of dags this causes scheduler immediately to crash due to constraint violation.

What you expected to happen

Tags are refreshed correctly without crash of scheduler.

How to reproduce

Create dag with tags in running airflow cluster

Update dag with change of case of one of tags for ex. "test" to "Test"

Watch scheduler crash continuously

Anything else

Alternative option is to make tags case sensitive...

Are you willing to submit PR?

Yes I am willing to submit a PR!

Code of Conduct

I agree to follow this project's Code of Conduct

Issue 2:
Apache Airflow version: v1109

executor: CeleryExecutor

some time the scheduler create many sub scheduler process. When this happens, the CPU usage of these sub schduler process is at 99%, and then i can see web ui appear：The scheduler does not appear to be running. Last heartbeat was received xxx ago.The DAGs list may not update, and new tasks will not be scheduled.

job_heartbeat_sec = 5

scheduler_heartbeat_sec = 5

run_duration = -1

num_runs = -1

processor_poll_interval = 1

min_file_process_interval = 30

here is some log i mark，but the scheduler log had no error

etl 23905 12016 0 Oct17 ? 00:00:00 /bin/bash -c source /usr/soft/anaconda3/bin/activate etl_airflow_v1109 && airflow scheduler

etl 23908 23905 1 Oct17 ? 03:13:04 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 23947 23908 1 Oct17 ? 02:40:24 airflow scheduler -- DagFileProcessorManager

etl 30570 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 30573 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 30574 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 30575 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 30576 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 30577 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 30578 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 30579 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 30580 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 30581 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

etl 30583 23908 99 03:07 ? 00:07:22 /root/etl_airflow_v1109/bin/python /root/etl_airflow_v1109/bin/airflow scheduler

Please help. I would be happy to provide any other information needed