dataUsageJSON, err := json.Marshal(dataUsageInfo)
		if err != nil {
			scannerLogIf(ctx, err)
			continue
		}
		if attempts > 10 {
			saveConfig(ctx, objAPI, dataUsageObjNamePath+".bkp", dataUsageJSON) // Save a backup every 10th update.
			attempts = 1
		}
		if err = saveConfig(ctx, objAPI, dataUsageObjNamePath, dataUsageJSON); err != nil {
			scannerLogOnceIf(ctx, err, dataUsageObjNamePath)
		}
		attempts++
	}
}

        blocker = (Blocker) state;
      }
      spinCount++;
      if (spinCount > MAX_BUSY_WAIT_SPINS) {
        /*
         * If we have spun a lot, just park ourselves. This will save CPU while we wait for a slow
         * interrupting thread. In theory, interruptTask() should be very fast, but due to
         * InterruptibleChannel and JavaLangAccess.blockedOn(Thread, Interruptible), it isn't

  patches should only highlight the actual difference, not being disturbed by any formatting issues:
  + Only use spaces for indentation.
  + Create minimal diffs - disable on save actions like reformat source code or organize imports.
    If you feel the source code should be reformatted, create a separate PR for this change.
  + Check for unnecessary whitespace with `git diff --check` before committing.

	EnvPrefix        = madmin.EnvPrefix
	EnvWordDelimiter = madmin.EnvWordDelimiter
)

// DefaultKVS - default kvs for all sub-systems
var DefaultKVS = map[string]KVS{}

// RegisterDefaultKVS - this function saves input kvsMap
// globally, this should be called only once preferably
// during `init()`.
func RegisterDefaultKVS(kvsMap map[string]KVS) {
	for subSys, kvs := range kvsMap {
		DefaultKVS[subSys] = kvs
	}
}

  internal val plansToCancel = CopyOnWriteArrayList<RoutePlanner.Plan>()

  override fun timeout(): Timeout = timeout

  @SuppressWarnings("CloneDoesntCallSuperClone") // We are a final type & this saves clearing state.
  override fun clone(): Call = RealCall(client, originalRequest, forWebSocket)

  override fun request(): Request = originalRequest

  /**

# Recommended: use a local+remote cache.
#
#   Bazel will cache your builds in tensorflow/build_output/cache,
#   and will also try using public build cache results to speed up
#   your builds. This usually saves a lot of time, especially when
#   re-running tests. However, note that:
#
#    - New environments like new CUDA versions, changes to manylinux,
#      compilers, etc. can cause undefined behavior such as build failures

	m.wg.Add(1)
	defer m.wg.Done()

	if atomic.LoadInt32(&m.closing) == 1 {
		return
	}

	select {
	case m.opCh <- op:
	default:
	}
}

// Do not accept new MRF operations anymore and start to save
// the current heal status in one available disk
func (m *mrfState) shutdown() {
	atomic.StoreInt32(&m.closing, 1)
	m.wg.Wait()
	close(m.opCh)
	atomic.StoreInt32(&m.closed, 1)

	if len(m.opCh) > 0 {

      val residentDuration = maxOf(0, nowMillis - receivedResponseMillis)
      return receivedAge + responseDuration + residentDuration
    }

    /**
     * Returns true if the request contains conditions that save the server from sending a response
     * that the client has locally. When a request is enqueued with its own conditions, the built-in
     * response cache won't be used.
     */

     * the lock to check again. Since an IDLE state was observed inside the preceding synchronized
     * block, and reference field assignment is atomic, this may save reacquiring the lock when
     * another thread or the worker task has cleared the count and set the state.
     *
     * <p>When {@link #executor} is a directExecutor(), the value written to

     * the lock to check again. Since an IDLE state was observed inside the preceding synchronized
     * block, and reference field assignment is atomic, this may save reacquiring the lock when
     * another thread or the worker task has cleared the count and set the state.
     *
     * <p>When {@link #executor} is a directExecutor(), the value written to