return
	}
	// Single calls do not support pinging.
	if v, ok := c.inStream.Load(m.MuxID); ok {
		pong := v.ping(m.Seq)
		pong.T = ping.T
		gridLogIf(ctx, c.queueMsg(m, &pong))
	} else {
		pong := pongMsg{NotFound: true, T: ping.T}
		gridLogIf(ctx, c.queueMsg(m, &pong))
	}
	return
}

func (c *Connection) handleDisconnectClientMux(m message) {

	m.sendMu.Lock()
	defer m.sendMu.Unlock()
	msg.MuxID = m.ID
	msg.Seq = m.SendSeq
	m.SendSeq++
	if debugPrint {
		fmt.Printf("Mux %d, Sending %+v\n", m.ID, msg)
	}
	gridLogIf(m.ctx, m.parent.queueMsg(msg, nil))
}

func (m *muxServer) close() {
	m.cancel()
	m.recvMu.Lock()
	defer m.recvMu.Unlock()

	if m.inbound != nil {
		xioutil.SafeClose(m.inbound)
		m.inbound = nil
	}

   * through the returned queue.
   *
   * <p>It is imperative that the user manually synchronize on the returned queue when accessing the
   * queue's iterator:
   *
   * <pre>{@code
   * Queue<E> queue = Queues.synchronizedQueue(MinMaxPriorityQueue.<E>create());
   * ...
   * queue.add(element);  // Needn't be in synchronized block
   * ...

   * through the returned queue.
   *
   * <p>It is imperative that the user manually synchronize on the returned queue when accessing the
   * queue's iterator:
   *
   * <pre>{@code
   * Queue<E> queue = Queues.synchronizedQueue(MinMaxPriorityQueue.<E>create());
   * ...
   * queue.add(element);  // Needn't be in synchronized block
   * ...

    //    second thread can then dispatch to the subscriber it took before the first thread does.
    //
    // All this makes me really wonder if there's any value in queueing here at all. A dispatcher
    // that simply loops through the subscribers and dispatches the event to each would actually
    // probably provide a stronger order guarantee, though that order would obviously be different

import okhttp3.internal.assertNotHeld
import okhttp3.internal.okHttpName

/**
 * A set of tasks that are executed in sequential order.
 *
 * Work within queues is not concurrent. This is equivalent to each queue having a dedicated thread
 * for its work; in practice a set of queues may share a set of threads to save resources.
 */
class TaskQueue internal constructor(
  internal val taskRunner: TaskRunner,
  internal val name: String,
) {

 * conventional bounded queues, which either block or reject new elements when full.
 *
 * <p>This implementation is based on the <a
 * href="http://portal.acm.org/citation.cfm?id=6621">min-max heap</a> developed by Atkinson, et al.
 * Unlike many other double-ended priority queues, it stores elements in a single array, as compact

 * conventional bounded queues, which either block or reject new elements when full.
 *
 * <p>This implementation is based on the <a
 * href="http://portal.acm.org/citation.cfm?id=6621">min-max heap</a> developed by Atkinson, et al.
 * Unlike many other double-ended priority queues, it stores elements in a single array, as compact

  repeated PriorityLevelConfigurationCondition conditions = 1;
}

// QueuingConfiguration holds the configuration parameters for queuing
message QueuingConfiguration {
  // `queues` is the number of queues for this priority level. The
  // queues exist independently at each apiserver. The value must be
  // positive.  Setting it to 1 effectively precludes
  // shufflesharding and thus makes the distinguisher method of

   * need. Both fields are guarded by [lock].
   */
  private var executeCallCount = 0
  private var runCallCount = 0

  /** Queues with tasks that are currently executing their [TaskQueue.activeTask]. */
  private val busyQueues = mutableListOf<TaskQueue>()

  /** Queues not in [busyQueues] that have non-empty [TaskQueue.futureTasks]. */
  private val readyQueues = mutableListOf<TaskQueue>()