}
    }
  }

  /* Half of a 1-second timeout in nanoseconds */
  private static final long HALF_SECOND_NANOS = NANOSECONDS.convert(1L, SECONDS) / 2;

  public void testShutdownAndAwaitTermination_immediateShutdown() throws Exception {
    ExecutorService service = Executors.newSingleThreadExecutor();
    assertTrue(shutdownAndAwaitTermination(service, 1L, SECONDS));
    assertTrue(service.isTerminated());
  }

				continue
			}

			if h.batchSize > 1 {
				// If we are doing batching, we should wait
				// at least one second before sending.
				// Even if there is nothing in the queue.
				if time.Since(lastBatchProcess).Seconds() < 1 {
					continue
				}
			}
		}

		lastBatchProcess = time.Now()

	retry:
		// If the channel reaches above half capacity

   * second" (commonly referred to as <i>QPS</i>, queries per second).
   *
   * <p>The returned {@code RateLimiter} ensures that on average no more than {@code
   * permitsPerSecond} are issued during any given second, with sustained requests being smoothly
   * spread over each second. When the incoming request rate exceeds {@code permitsPerSecond} the

      }
    }
  }

  /* Half of a 1-second timeout in nanoseconds */
  private static final long HALF_SECOND_NANOS = NANOSECONDS.convert(1L, SECONDS) / 2;

  public void testShutdownAndAwaitTermination_immediateShutdown() throws Exception {
    ExecutorService service = Executors.newSingleThreadExecutor();
    assertTrue(shutdownAndAwaitTermination(service, 1L, SECONDS));
    assertTrue(service.isTerminated());
  }

    assertTrue(limiter.tryAcquire(0, SECONDS));
    assertFalse(limiter.tryAcquire(0, SECONDS));
    assertFalse(limiter.tryAcquire(0, SECONDS));
    stopwatch.sleepMillis(100);
    assertFalse(limiter.tryAcquire(0, SECONDS));
  }

  public void testTryAcquire_someWaitAllowed() {
    RateLimiter limiter = RateLimiter.create(5.0, stopwatch);
    assertTrue(limiter.tryAcquire(0, SECONDS));

    assertTrue(limiter.tryAcquire(0, SECONDS));
    assertFalse(limiter.tryAcquire(0, SECONDS));
    assertFalse(limiter.tryAcquire(0, SECONDS));
    stopwatch.sleepMillis(100);
    assertFalse(limiter.tryAcquire(0, SECONDS));
  }

  public void testTryAcquire_someWaitAllowed() {
    RateLimiter limiter = RateLimiter.create(5.0, stopwatch);
    assertTrue(limiter.tryAcquire(0, SECONDS));

   *
   * How this works is best explained with an example:
   *
   * For a RateLimiter that produces 1 token per second, every second that goes by with the
   * RateLimiter being unused, we increase storedPermits by 1. Say we leave the RateLimiter unused
   * for 10 seconds (i.e., we expected a request at time X, but we are at time X + 10 seconds before
   * a request actually arrives; this is also related to the point made in the last paragraph), thus

		memCache:          "Cache memory on the node",
		memAvailable:      "Available memory on the node",
		readsPerSec:       "Reads per second on a drive",
		writesPerSec:      "Writes per second on a drive",
		readsKBPerSec:     "Kilobytes read per second on a drive",
		writesKBPerSec:    "Kilobytes written per second on a drive",
		readsAwait:        "Average time for read requests to be served on a drive",

  // This signals that the block is removed, and should not be inadvertently
  // reinserted into the cache in UpdateLRU.
  entry->second->timestamp = 0;
  lru_list_.erase(entry->second->lru_iterator);
  lra_list_.erase(entry->second->lra_iterator);
  cache_size_ -= entry->second->data.capacity();
  block_map_.erase(entry);
}

  //   * increase no more than 4 pods per 60 seconds
  //   * double the number of pods per 60 seconds
  // No stabilization is used.
  // +optional
  optional HPAScalingRules scaleUp = 1;

  // scaleDown is scaling policy for scaling Down.
  // If not set, the default value is to allow to scale down to minReplicas pods, with a
  // 300 second stabilization window (i.e., the highest recommendation for