if (v != 0) {
            done = false;
            if (aa.compareAndSet(i, v, v - 1.0)) {
              ++counts;
            }
          }
        }
        if (done) {
          break;
        }
      }
    }
  }

  /**
   * Multiple threads using same array of counters successfully update a number of times equal to
   * total count
   */

// 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.

     */
    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

        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:

 * 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. */

    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;

"","kibanaSavedObjectMeta":{"searchSourceJSON":"{\"query\":{\"query\":\"\",\"language\":\"kuery\"},\"filter\":[],\"indexRefName\":\"kibanaSavedObjectMeta.searchSourceJSON.index\"}"},"title":"search-query-counts-per-sec","uiStateJSON":"{}","version":1,"visState":"{\"title\":\"search-query-counts-per-sec\",\"type\":\"histogram\",\"params\":{\"type\":\"histogram\",\"grid\":{\"categoryLines\":false},\"categoryAxes\":[{\"id\":\"CategoryAxis-1\",\"type\":\"category\",\"position\":\"bottom\",\"show\":t...

    }

    /**
     * Retrieves a list of session IDs with their document counts from the search engine.
     * Uses aggregation to get session segments and their corresponding document counts.
     *
     * @param searchEngineClient the search engine client to perform the query
     * @return a list of maps containing session IDs and their document counts
     */