*
   * <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

      // 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

  <name>Guava: Google Core Libraries for Java</name>
  <description>
    Guava is a suite of core and expanded libraries that include
    utility classes, Google's collections, I/O classes, and
    much more.
  </description>
  <url>https://github.com/google/guava</url>
  <dependencies>
    <dependency>
      <groupId>com.google.guava</groupId>
      <artifactId>failureaccess</artifactId>

   * remaining 7.0 permits, and the remaining 3.0, we serve them by fresh permits produced by the
   * rate limiter.
   *
   * We already know how much time it takes to serve 3 fresh permits: if the rate is
   * "1 token per second", then this will take 3 seconds. But what does it mean to serve 7 stored

   * 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);
  }

   * 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);
  }

   * <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

            }
        }

        long elapsed = (System.nanoTime() - time) / 1000000;
        // Different hosts should NOT wait for each other
        assertTrue(elapsed + " should be much less than " + (waittime * numTasks), elapsed < waittime * numTasks / 2);
    }

    /**
     * Test that file:// URLs are not delayed
     */
    public void test_fileUrl_noDelay() {

 *
 * <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