executor_config: "limits_memory" option for operators

<!-- 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. --> **Description** <!-- A short description of your feature --> Currently, if you want to change the kubernetes resources allocated to an operator you need to something like ``` from kubernetes.client import models as k8s task1 = PythonOperator( task_id="id1", python_callable=mycallable, dag=dag1, executor_config={ "pod_override": k8s.V1Pod( spec=k8s.V1PodSpec( containers=[ k8s.V1Container( name="base", resources=k8s.V1ResourceRequirements( limits={ "memory": "6Gi", "cpu": "1", } ) ) ] ) ) }, ``` which works, but I think that is very verbose and for a (in my opinion) common case. I would prefer a more direct syntax like ``` task1 = PythonOperator( task_id="id1", python_callable=mycallable, dag=dag1, executor_config={ "pod_limits_memory": "6Gi", "pod_limits_cpu": "1", } ``` Alternatively, maybe a documentation change to * https://github.com/apache/airflow/blob/main/docs/apache-airflow/executor/kubernetes.rst * https://github.com/apache/airflow/blob/main/airflow/example_dags/example_kubernetes_executor_config.py would make this (IMHO common) task easier **Use case / motivation** <!-- What do you want to happen? Rather than telling us how you might implement this solution, try to take a step back and describe what you are trying to a…