*
   * <p>The default implementation of this method in {@code AbstractFuture} does nothing. This is
   * intended for very lightweight cleanup work, for example, timing statistics or clearing fields.
   * If your task does anything heavier consider, just using a listener with an executor.
   *
   * @since 20.0
   */
  @ForOverride
  protected void afterDone() {}

     * cause a concurrent read operation to see inconsistent data. This is made easier by the
     * nature of the read operations in Map. For example, no operation can reveal that the table
     * has grown but the threshold has not yet been updated, so there are no atomicity requirements
     * for this with respect to reads.
     *

   * if the primary input succeeds, it is never invoked. If, during the invocation of {@code
   * fallback}, an exception is thrown, this exception is used as the result of the output {@code
   * Future}.
   *
   * <p>Usage example:
   *
   * <pre>{@code
   * ListenableFuture<Integer> fetchCounterFuture = ...;
   *
   * // Falling back to a zero counter in case an exception happens when
   * // processing the RPC to fetch counters.

      checkNotNull(input);
    }
    return concat(consumingForArray(inputs));
  }

  /**
   * Divides an iterator into unmodifiable sublists of the given size (the final list may be
   * smaller). For example, partitioning an iterator containing {@code [a, b, c, d, e]} with a
   * partition size of 3 yields {@code [[a, b, c], [d, e]]} -- an outer iterator containing two
   * inner lists of three and two elements, all in the original order.

      checkNotNull(input);
    }
    return concat(consumingForArray(inputs));
  }

  /**
   * Divides an iterator into unmodifiable sublists of the given size (the final list may be
   * smaller). For example, partitioning an iterator containing {@code [a, b, c, d, e]} with a
   * partition size of 3 yields {@code [[a, b, c], [d, e]]} -- an outer iterator containing two
   * inner lists of three and two elements, all in the original order.

   * specified supplier. The keys and values of the entries are the result of applying the provided
   * mapping functions to the input elements, accumulated in the encounter order of the stream.
   *
   * <p>Example:
   *
   * <pre>{@code
   * static final ListMultimap<Character, String> FIRST_LETTER_MULTIMAP =
   *     Stream.of("banana", "apple", "carrot", "asparagus", "cherry")
   *         .collect(
   *             toMultimap(

   * specified supplier. The keys and values of the entries are the result of applying the provided
   * mapping functions to the input elements, accumulated in the encounter order of the stream.
   *
   * <p>Example:
   *
   * <pre>{@code
   * static final ListMultimap<Character, String> FIRST_LETTER_MULTIMAP =
   *     Stream.of("banana", "apple", "carrot", "asparagus", "cherry")
   *         .collect(
   *             toMultimap(

    return new Builder<>(Ordering.<K>natural().reverse());
  }

  /**
   * A builder for creating immutable sorted map instances, especially {@code public static final}
   * maps ("constant maps"). Example:
   *
   * <pre>{@code
   * static final ImmutableSortedMap<Integer, String> INT_TO_WORD =
   *     new ImmutableSortedMap.Builder<Integer, String>(Ordering.natural())
   *         .put(1, "one")

     * cause a concurrent read operation to see inconsistent data. This is made easier by the
     * nature of the read operations in Map. For example, no operation can reveal that the table
     * has grown but the threshold has not yet been updated, so there are no atomicity requirements
     * for this with respect to reads.
     *