Don't re-patch pods that are already controlled by current worker (#2…

…6778)

After the scheduler has launched many pods, it keeps trying to
re-adopt them by patching every pod. Each patch-operation
involves a remote API-call which can be be very slow.
In the meantime the scheduler can not do anything else.

By ignoring the pods that already have the expected label,
the list query-result will be shorter and the number of
patch-queries much less.

We had an unlucky moment in our environment, where each
patch-operation started taking 100ms each, with 200 pods in
flight it accumulates into 20 seconds of blocked scheduler.

(cherry picked from commit 27ec562)

airflow/executors/kubernetes_executor.py

@@ -754,14 +754,15 @@ def _adopt_completed_pods(self, kube_client: client.CoreV1Api) -> None:
         """
         if not self.scheduler_job_id:
             raise AirflowException(NOT_STARTED_MESSAGE)
+        new_worker_id_label = pod_generator.make_safe_label_value(self.scheduler_job_id)
         kwargs = {
             'field_selector': "status.phase=Succeeded",
-            'label_selector': 'kubernetes_executor=True',
+            'label_selector': f'kubernetes_executor=True,airflow-worker!={new_worker_id_label}',
         }
         pod_list = kube_client.list_namespaced_pod(namespace=self.kube_config.kube_namespace, **kwargs)
         for pod in pod_list.items:
             self.log.info("Attempting to adopt pod %s", pod.metadata.name)
-            pod.metadata.labels['airflow-worker'] = pod_generator.make_safe_label_value(self.scheduler_job_id)
+            pod.metadata.labels['airflow-worker'] = new_worker_id_label
             try:
                 kube_client.patch_namespaced_pod(
                     name=pod.metadata.name,