*       maxPermits is equal to warmupPeriod.
   *   <li>When _used_, the time it takes, as explained in the introductory class note, is equal to
   *       the integral of our function, between X permits and X-K permits, assuming we want to
   *       spend K saved permits.
   * </ol>
   *

   */
  @Deprecated
  public static <V extends @Nullable Object> FluentFuture<V> from(FluentFuture<V> future) {
    return checkNotNull(future);
  }

  /**
   * Returns a {@code Future} whose result is taken from this {@code Future} or, if this {@code
   * Future} fails with the given {@code exceptionType}, from the result provided by the {@code

   * // returns {"foo", "quux"}
   * }</pre>
   *
   * <p>This {@code Collector} uses O(k) memory and takes expected time O(n) (worst-case O(n log
   * k)), as opposed to e.g. {@code Stream.sorted(comparator).limit(k)}, which currently takes O(n
   * log n) time and O(n) space.
   *
   * @throws IllegalArgumentException if {@code k < 0}
   * @since 33.2.0 (available since 22.0 in guava-jre)

 *       values for a particular key, and has <i>partially order-dependent equality</i> as defined
 *       by {@link ListMultimap#equals(Object)}. {@code ListMultimap} takes its name from the fact
 *       that the {@linkplain ListMultimap#get collection of values} associated with a given key
 *       fulfills the {@link java.util.List} contract.
 *   <dt>{@link SetMultimap}

 * ArrayListMultimap}. The GWT supersource for this class contains a field for each type.
 *
 * <p>For details about this hack, see {@code GwtSerializationDependencies}, which takes the same
 * approach but with a subclass rather than a superclass.
 *
 * <p>TODO(cpovirk): Consider applying this subclass approach to our other types.
 */
@GwtCompatible(emulated = true)

 * Benchmarks (as of December 2011) show that:
 *
 * <ul>
 *   <li>for an unnested {@code lock()} and {@code unlock()}, a cycle detecting lock takes 38ns as
 *       opposed to the 24ns taken by a plain lock.
 *   <li>for nested locking, the cost increases with the depth of the nesting:
 *       <ul>
 *         <li>2 levels: average of 64ns per lock()/unlock()

 *
 * <p>The time taken to compute multiple quantiles on the same dataset using {@link Scale#indexes
 * indexes} is generally less than the total time taken to compute each of them separately, and
 * sometimes much less. For example, on a large enough dataset, computing the 90th and 99th
 * percentiles together takes about 55% as long as computing them separately.
 *

   *   <li>Otherwise, return an instance of {@link ClusterException} that wraps the first exception
   *       in the {@code exceptions} collection.
   * </ul>
   *
   * <p>Though this method takes any {@link Collection}, it often makes most sense to pass a {@link
   * java.util.List} or some other collection that preserves the order in which the exceptions got
   * added.
   *

 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *
 * <p>Note that this implementation is not synchronized. If multiple threads access this table

   * by delaying the per-stack-frame work until each element is accessed. Roughly speaking:
   *
   * <ul>
   *   <li>{@code getStackTrace} takes {@code stackSize} time to return but then negligible time to
   *       retrieve each element of the returned list.
   *   <li>{@code lazyStackTrace} takes negligible time to return but then {@code 1/stackSize} time
   *       to retrieve each element of the returned list (probably slightly more than {@code