// Update replication upload latency with a new value
func (rl *ReplicationLatency) update(size int64, duration time.Duration) {
	rl.UploadHistogram.Add(size, duration)
}

// ReplicationLastMinute has last minute replication counters
type ReplicationLastMinute struct {
	LastMinute lastMinuteLatency
}

func (rl ReplicationLastMinute) merge(other ReplicationLastMinute) (nl ReplicationLastMinute) {

     *
     * @return true if the problem collector has overflowed and some problems were not preserved
     */
    boolean problemsOverflow();

    /**
     * Reports a problem: always maintains the counters, but whether problem is preserved in memory, depends on
     * implementation and its configuration.
     *
     * @param problem the problem to report
     * @return {@code true} if passed problem is preserved by this call.

    if (occurrences == 0) {
      return count(element);
    }
    int index = e.ordinal();
    int oldCount = counts[index];
    if (oldCount == 0) {
      return 0;
    } else if (oldCount <= occurrences) {
      counts[index] = 0;
      distinctElements--;
      size -= oldCount;
    } else {
      counts[index] = oldCount - occurrences;
      size -= occurrences;
    }
    return oldCount;
  }

     */
    public static SecurityAuditLogger getInstance() {
        return SingletonHolder.INSTANCE;
    }

    private SecurityAuditLogger() {
        // Initialize event counters
        for (EventType type : EventType.values()) {
            eventCounters.put(type, new AtomicLong(0));
            eventTimings.put(type, new AtomicLong(0));
        }

        // Start async logging processor

    final Object[] elements;
    final int[] counts;

    // "extends Object" works around https://github.com/typetools/checker-framework/issues/3013
    SerializedForm(Multiset<? extends Object> multiset) {
      int distinct = multiset.entrySet().size();
      elements = new Object[distinct];
      counts = new int[distinct];
      int i = 0;

    }

    /**
     * Represents a field facet with its name and value counts.
     * Each field facet contains multiple values with their respective document counts.
     */
    public static class Field {
        /**
         * Map containing field values and their document counts.
         * Keys are field values as strings, values are document counts.
         */

        assertNotSame(first, second, "Should create new connection when session limit reached");
    }

    @Test
    @DisplayName("Should access fail counts map correctly")
    void testFailCountsAccess() throws Exception {
        // Given: Access to fail counts via reflection
        Field failCountsField = SmbTransportPoolImpl.class.getDeclaredField("failCounts");
        failCountsField.setAccessible(true);

file: org.apache.spark.rdd.RDD[String] = s3a://testbucket/testdata MapPartitionsRDD[1] at textFile at <console>:24

scala> val counts = file.flatMap(line => line.split(" ")).map(word => (word, 1)).reduceByKey(_ + _)
counts: org.apache.spark.rdd.RDD[(String, Int)] = ShuffledRDD[4] at reduceByKey at <console>:25

scala> counts.saveAsTextFile("s3a://testbucket/wordcount")
```

Use one of the following approaches to view job output:

/**
 * Fess-specific crawler configuration that extends OpenSearchCrawlerConfig.
 * This class provides configuration settings for the Fess crawler including
 * index names, shard counts, and replica counts for queue, data, and filter indices.
 */
public class FessCrawlerConfig extends OpenSearchCrawlerConfig {

    /**
     * Default constructor.
     */
    public FessCrawlerConfig() {
        super();

 * It implements the List interface to provide standard list operations while adding search-specific
 * functionality such as page navigation, record counts, and query execution times.
 */
public class QueryResponseList implements List<Map<String, Object>> {

    /** The underlying list that contains the actual search result documents. */