*
   * <p><b>{@code Stream} equivalent:</b> {@code stream.filter(predicate).findFirst()}.
   */
  public final Optional<@NonNull E> firstMatch(Predicate<? super E> predicate) {
    // Unsafe, but we can't do much about it now.
    return Iterables.<@NonNull E>tryFind((Iterable<@NonNull E>) getDelegate(), predicate);
  }

  /**
   * Returns a fluent iterable that applies {@code function} to each element of this fluent

   *
   * <p><b>{@code Stream} equivalent:</b> {@code stream.filter(predicate).findFirst()}.
   */
  public final Optional<@NonNull E> firstMatch(Predicate<? super E> predicate) {
    // Unsafe, but we can't do much about it now.
    return Iterables.<@NonNull E>tryFind((Iterable<@NonNull E>) getDelegate(), predicate);
  }

  /**
   * Returns a fluent iterable that applies {@code function} to each element of this fluent

 *       does it offer a way to batch multiple events from a single producer together.
 *   <li>It doesn't support backpressure and other features needed for resilience.
 *   <li>It doesn't provide much control of threading.
 *   <li>It doesn't offer much monitoring.
 *   <li>It doesn't propagate exceptions, so apps don't have a way to react to them.
 *   <li>It doesn't interoperate well with RxJava, coroutines, and other more commonly used

      // timed out. e.g. if we weren't event able to grab the lock within the timeout we would never
      // even check the guard. I don't think we care too much about this use case but it could lead
      // to a confusing error message.
      throw new TimeoutException("Timed out waiting for " + this + " to reach the RUNNING state.");
    }
  }

  @Override

      // timed out. e.g. if we weren't event able to grab the lock within the timeout we would never
      // even check the guard. I don't think we care too much about this use case but it could lead
      // to a confusing error message.
      throw new TimeoutException("Timed out waiting for " + this + " to reach the RUNNING state.");
    }
  }

  @Override

 *
 * <p>Unlike {@code java.util.HashSet}, iteration is only proportional to the actual {@code size()},
 * which is optimal, and <i>not</i> the size of the internal hashtable, which could be much larger
 * than {@code size()}. Furthermore, this structure only depends on a fixed number of arrays; {@code
 * add(x)} operations <i>do not</i> create objects for the garbage collector to deal with, and for

   * and use that list instead.
   */
  public List<Long> asList() {
    /*
     * Typically we cache this kind of thing, but much repeated use of this view is a performance
     * anti-pattern anyway. If we cache, then everyone pays a price in memory footprint even if
     * they never use this method.
     */
    return new AsList(this);
  }

   * ImmutableList.copyOf} and use that list instead.
   */
  public List<Integer> asList() {
    /*
     * Typically we cache this kind of thing, but much repeated use of this view is a performance
     * anti-pattern anyway. If we cache, then everyone pays a price in memory footprint even if
     * they never use this method.
     */
    return new AsList(this);
  }

   * <p>It should be noted that using a {@code Striped<L>} with relatively few stripes, and {@code
   * bulkGet(keys)} with a relative large number of keys can cause an excessive number of shared
   * stripes (much like the birthday paradox, where much fewer than anticipated birthdays are needed
   * for a pair of them to match). Please consider carefully the implications of the number of

        } catch (Exception e) {
            // Expected
        }
        long duration = System.currentTimeMillis() - startTime;

        // Test should complete in under 1 second (much less than the original 25+ seconds)
        assertTrue("Test should complete quickly (duration: " + duration + "ms)", duration < 1000);
    }

    // Fast mock implementations to minimize overhead