Fix KEDA Query to Use executor Field Instead of queue for Multiple Executors

[HsiuChuanHsu]

Description:

When multiple executors (e.g., CeleryExecutor,KubernetesExecutor) are configured, the worker default KEDA query uses the queue column in the Airflow metadata database to determine Celery worker scaling.
However, task routing in Airflow is based on the executor attribute, not queue. This causes Celery workers to scale up unnecessarily for tasks explicitly configured with executor='KubernetesExecutor' but using the default queue

Changes:

This PR updates the KEDA query logic in values.yaml to correctly filter tasks based on the executor field when multiple executors are configured:

• For CeleryKubernetesExecutor, the existing logic is retained, using queue != '{{ .Values.config.celery_kubernetes_executor.kubernetes_queue }}'.
• For configurations including KubernetesExecutor (alone or with CeleryExecutor), the query is updated to use executor != 'KubernetesExecutor' ensuring tasks assigned to KubernetesExecutor not trigger Celery worker scaling.

Testing Steps

1. Deploy Airflow using Helm Chart with KEDA enabled and multiple executors:

executor: CeleryExecutor,KubernetesExecutor
workers:
  keda:
    enabled: true

2. Create a DAG with tasks explicitly using KubernetesExecutor and queue='default'
3. Verify that Celery workers do not scale up for tasks with executor='KubernetesExecutor'

Additional Notes:

Related Issues:

Closes: #49001

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[romsharon98]

Tests need to be fixed

[jason810496]

Nice catch!

[bugraoz93]

Thanks for the changes! Could you please rebase it before merging it? The PR has 137 commits

[bugraoz93]

I think you are merging the changes. You need to rebase from master and force push changes to your branch.

[HsiuChuanHsu]

I think I changed it correctly this time! Thanks a lot for the help!

[bugraoz93]

This is it, thanks! :)