Fixed a situation when, sometimes, the scheduler incorrectly placed a pod in the `unschedulable` queue instead of the `backoff` queue. This happened when some plugin previously declared the pod as `unschedulable` and then in a later attempt encounters some other error. Scheduling of that pod then got delayed by up to five minutes, after which periodic flushing moved the pod back into the `active` queue. ([#120334](https://github.com/kubernetes/kubernetes/pull/120334), [@pohly](https://github.com/pohly))...

---

Mais si vous êtes curieux de cet exemple de code spécifique et que vous êtes toujours partant, voici quelques détails supplémentaires.

#### Chaîne avec `value.startswith()` { #string-with-value-startswith }

     * Most Multimap implementations use a List or Set (or even Multiset) for their values, in which
     * case Multimap equality works as expected. Users who use a Collection type that does not
     * implement equals(), such as most Queue implementations, will get the same behavior from our
     * value-collection wrappers (and from Multimap.equals) as from the underlying Collection.
     */
    @SuppressWarnings("UndefinedEquals")

  Now, when unschedulable Pods are updated, the scheduling queue checks with QueueingHint(s) whether the update may make the pods schedulable, and requeues them to activeQ/backoffQ **only when** at least one QueueingHint(s) return Queue. 
  
  Action required for custom scheduler plugin developers:

			}
			t.Log("Client Context canceled. err state:", err)
			clientCanceled <- time.Now()
		}(t)
		start := time.Now()
		if st.Requests != nil {
			defer close(st.Requests)
		}
		// Fill up queue.
		for sendReq {
			select {
			case st.Requests <- []byte("Hello"):
				time.Sleep(10 * time.Millisecond)
			default:
				sendReq = false
			}
		}
		cancel()
		<-serverCanceled

Há muitos casos em que você deseja executar algumas etapas **antes de iniciar** sua aplicação.

Por exemplo, você pode querer executar **migrações de banco de dados**.

Mas na maioria dos casos, você precisará executar essas etapas apenas **uma vez**.

Portanto, você vai querer ter um **processo único** para executar essas **etapas anteriores** antes de iniciar o aplicativo.

Mas você também pode explorar os benefícios do paralelismo e multiprocessamento (tendo múltiplos processadores rodando em paralelo) para trabalhos **limitados por CPU** como aqueles em sistemas de Aprendizado de Máquina.

     * Most Multimap implementations use a List or Set (or even Multiset) for their values, in which
     * case Multimap equality works as expected. Users who use a Collection type that does not
     * implement equals(), such as most Queue implementations, will get the same behavior from our
     * value-collection wrappers (and from Multimap.equals) as from the underlying Collection.
     */
    @SuppressWarnings("UndefinedEquals")

 *  Fix: Handle multiple 1xx responses.

 *  Fix: Address a performance bug in our internal task runner. We had a race condition that could
    result in it OkHttp starting a thread for each queued task, even when a single thread could run
    all of them.

 *  Fix: Address a performance bug in `MultipartReader`. We were scanning the entire input stream

	Name   string
	Prefix string
}

func (db decomBucketInfo) String() string {
	return pathJoin(db.Name, db.Prefix)
}

func (p *poolMeta) QueueBuckets(idx int, buckets []decomBucketInfo) {
	// add new queued buckets
	for _, bucket := range buckets {
		p.Pools[idx].Decommission.bucketPush(bucket)
	}
}

var (
	errDecommissionAlreadyRunning = errors.New("decommission is already in progress")