return
		}
	}
}

func (r *ReplicationStats) updateMovingAvg() {
	r.RLock()
	for _, s := range r.Cache {
		for _, st := range s.Stats {
			st.XferRateLrg.measure.updateExponentialMovingAverage(time.Now())
			st.XferRateSml.measure.updateExponentialMovingAverage(time.Now())
		}
	}
	r.RUnlock()
}

// ActiveWorkers returns worker stats
func (r *ReplicationStats) ActiveWorkers() ActiveWorkerStat {

  private void weaklyReferenceQueue() {
    frq = new FinalizableReferenceQueue();
    queueReference = new WeakReference<>(frq.queue);

    /*
     * Queue and clear a reference for good measure. We test later on that
     * the finalizer thread stopped, but we should test that it actually
     * started first.
     */
    reference =
        new FinalizableWeakReference<Object>(new Object(), frq) {

  private void weaklyReferenceQueue() {
    frq = new FinalizableReferenceQueue();
    queueReference = new WeakReference<>(frq.queue);

    /*
     * Queue and clear a reference for good measure. We test later on that
     * the finalizer thread stopped, but we should test that it actually
     * started first.
     */
    reference =
        new FinalizableWeakReference<Object>(new Object(), frq) {

      label: "Orthogonality: How does this change interact or overlap with existing features?"
      description: "Is the goal of this change a performance improvement? If so, what quantifiable improvement should we expect? How would we measure it?"
    validations:
      required: false

  - type: textarea
    id: learning-curve
    attributes:
      label: "Would this change make Go easier or harder to learn, and why?"

  - type: textarea

  // +optional
  optional string holderIdentity = 1;

  // leaseDurationSeconds is a duration that candidates for a lease need
  // to wait to force acquire it. This is measure against time of last
  // observed renewTime.
  // +optional
  optional int32 leaseDurationSeconds = 2;

  // acquireTime is a time when the current lease was acquired.
  // +optional

) : ConnectionListener() {
  val eventSequence: Deque<ConnectionEvent> = ConcurrentLinkedDeque()

  private val forbiddenLocks = mutableSetOf<Any>()

  /** The timestamp of the last taken event, used to measure elapsed time between events. */
  private var lastTimestampNs: Long? = null

  /** Confirm that the thread does not hold a lock on `lock` during the callback. */
  fun forbidLock(lock: Any) {
    forbiddenLocks.add(lock)

) : EventListener() {
  val eventSequence: Deque<CallEvent> = ConcurrentLinkedDeque()

  private val forbiddenLocks = mutableListOf<Any>()

  /** The timestamp of the last taken event, used to measure elapsed time between events. */
  private var lastTimestampNs: Long? = null

  /** Confirm that the thread does not hold a lock on `lock` during the callback. */
  fun forbidLock(lock: Any) {
    forbiddenLocks.add(lock)

   * @param offset the offset into the array at which to start
   * @return the value found in the array in the form of a long
   */
  static int load32(byte[] source, int offset) {
    // TODO(user): Measure the benefit of delegating this to LittleEndianBytes also.
    return (source[offset] & 0xFF)
        | ((source[offset + 1] & 0xFF) << 8)
        | ((source[offset + 2] & 0xFF) << 16)

 *   <li>least-recently-used eviction when a maximum size is exceeded (note that the cache is
 *       divided into segments, each of which does LRU internally)
 *   <li>time-based expiration of entries, measured since last access or last write
 *   <li>keys automatically wrapped in {@code WeakReference}
 *   <li>values automatically wrapped in {@code WeakReference} or {@code SoftReference}

    }

    private static final long serialVersionUID = 1;
  }

  /**
   * Writes this {@code BloomFilter} to an output stream, with a custom format (not Java
   * serialization). This has been measured to save at least 400 bytes compared to regular
   * serialization.
   *
   * <p>Use {@linkplain #readFrom(InputStream, Funnel)} to reconstruct the written BloomFilter.
   */