var (
	notificationCurrentSendInProgressMD = NewCounterMD(notificationCurrentSendInProgress, "Number of concurrent async Send calls active to all targets")
	notificationEventsErrorsTotalMD     = NewCounterMD(notificationEventsErrorsTotal, "Events that were failed to be sent to the targets")
	notificationEventsSentTotalMD       = NewCounterMD(notificationEventsSentTotal, "Total number of events sent to the targets")

	webhookFailedMessagesMD = NewCounterMD(webhookFailedMessages,
		"Number of messages that failed to send",
		allWebhookLabels...)
	webhookQueueLengthMD = NewGaugeMD(webhookQueueLength,
		"Webhook queue length",
		allWebhookLabels...)
	webhookTotalMessagesMD = NewCounterMD(webhookTotalMessages,
		"Total number of messages sent to this target",
		allWebhookLabels...)
)

        public void setKkk(final String kkk) {
            this.kkk = kkk;
        }

        /**
         * @param arg1
         * @param arg2
         * @return Number
         */
        public Number add(final Number arg1, final Number arg2) {
            return Integer.valueOf(3);
        }

        /**
         * @return BigDecimal
         */
        public BigDecimal getGgg() {

# Default values for min/max heap memory allocated to fess java process
packaging.fess.heap.min=256m
packaging.fess.heap.max=1g

# Specifies the maximum file descriptor number
packaging.os.max.open.files=65535

# Maximum number of VMA (Virtual Memory Areas) a process can own
packaging.os.max.map.count=262144

# Simple marker to check that properties are correctly overridden
packaging.type=tar.gz

 * @param valueCount the number of values per cache entry. Must be positive.
 * @param maxSize the maximum number of bytes this cache should use to store.
 */
class DiskLruCache(
  fileSystem: FileSystem,
  /** Returns the directory where this cache stores its data. */
  val directory: Path,
  private val appVersion: Int,
  internal val valueCount: Int,

        /**
         *
         */
        public void getIii() {
        }

        /**
         * @param arg1
         * @param arg2
         * @return Number
         */
        public Number add(final Number arg1, final Number arg2) {
            return Integer.valueOf(3);
        }

        /**
         * @param arg1
         * @param arg2
         * @return int
         */

        if (field == null) {
            return null;
        }
        if (clazz.equals(Integer.class)) {
            final Number value = (Number) field;
            return (T) Integer.valueOf(value.intValue());
        }
        if (clazz.equals(Long.class)) {
            final Number value = (Number) field;
            return (T) Long.valueOf(value.longValue());
        }
        return (T) field;
    }

    /**

    this.loadSuccessCount = loadSuccessCount;
    this.loadExceptionCount = loadExceptionCount;
    this.totalLoadTime = totalLoadTime;
    this.evictionCount = evictionCount;
  }

  /**
   * Returns the number of times {@link Cache} lookup methods have returned either a cached or
   * uncached value. This is defined as {@code hitCount + missCount}.
   *

      }
      return array;
    }

    /** Number of bits */
    long bitSize() {
      return (long) data.length() * Long.SIZE;
    }

    /**
     * Number of set bits (1s).
     *
     * <p>Note that because of concurrent set calls and uses of atomics, this bitCount is a (very)
     * close *estimate* of the actual number of bits set. It's not possible to do better than an

with 4 drives we get a total of 256 possible sets. So algorithm automatically chooses 64 sets, which is *16* 64 = 1024* drives in total.

- *If total number of nodes are of odd number then GCD algorithm provides affinity towards odd number erasure sets to provide for uniform distribution across nodes*. This is to ensure that same number of drives are pariticipating in any erasure set. For example if you have 2 nodes with 180 drives then GCD is 15 but this would lead to uneven distribution,...