DagFileProcessorManager IPC bottleneck: child processes block on Variable.get() during parsing

### Apache Airflow version 3.0.0+ ### What happened When DAG files call `Variable.get()` during parsing, the forked child process blocks on `socket.recv()` waiting for the parent `DagFileProcessorManager` to service the IPC request. However, IPC is only serviced once per main loop iteration in `_service_processor_sockets()` (manager.py line 398). This means child processes can be blocked for the entire duration of the parent's loop — which includes `_refresh_dag_bundles()`, `_collect_results()`, `_scan_stale_dags()`, etc. With multiple parsing processes running and a non-trivial number of DAG files, the parent loop takes significant time per iteration. During this time, any child process that calls `Variable.get()` is completely blocked, turning a sub-second DAG parse into a multi-minute wait. **Profiling confirms the bottleneck**: cProfile of the dag-processor shows `_parse_file()` time is dominated by a single `socket.recv()` call inside `CommsDecoder._get_response()`, waiting for the parent to respond to the `GetVariable` IPC request. This is a regression from Airflow 2.x where `Variable.get()` was a direct DB query with no IPC dependency. ### What you think should happen instead The dag-processor should continuously service IPC requests from child processes, not just once per main loop iteration. For comparison, `WatchedSubprocess._monitor_subprocess()` in the task execution path has a tight loop that services IPC continuously — the dag-processor should have similar behavior. One approach: run `_service_processor_sockets()` in a dedicated background thread during the phases of the main loop where child processes may be actively parsing (i.e., between `_start_new_processes()` and `_collect_results()`). This ensures child IPC requests are serviced immediately regardless of what the parent's main loop is doing. ### How to reproduce 1. Create multiple DAG files that call `Variable.get()` during module-level or top-level DAG definition 2. Run the standalone dag-proc…