*
 * <p>This interface is now a legacy type. Use {@code java.util.function.Predicate} (or the
 * appropriate primitive specialization such as {@code IntPredicate}) instead whenever possible.
 * Otherwise, at least reduce <i>explicit</i> dependencies on this type by using lambda expressions
 * or method references instead of classes, leaving your code easier to migrate in the future.
 *

 *
 * <p>This interface is now a legacy type. Use {@code java.util.function.Predicate} (or the
 * appropriate primitive specialization such as {@code IntPredicate}) instead whenever possible.
 * Otherwise, at least reduce <i>explicit</i> dependencies on this type by using lambda expressions
 * or method references instead of classes, leaving your code easier to migrate in the future.
 *

 *
 * <p>This interface is now a legacy type. Use {@code java.util.function.Supplier} (or the
 * appropriate primitive specialization such as {@code IntSupplier}) instead whenever possible.
 * Otherwise, at least reduce <i>explicit</i> dependencies on this type by using lambda expressions
 * or method references instead of classes, leaving your code easier to migrate in the future.
 *

   * This test creates a long random sequence of inputs, then a lot of differently configured sinks
   * process it; all should produce the same answer, the only difference should be the number of
   * process()/processRemaining() invocations, due to alignment.
   */
  @AndroidIncompatible // slow. TODO(cpovirk): Maybe just reduce iterations under Android.
  public void testExhaustive() throws Exception {

   * following conditions:
   *
   * <ul>
   *   <li>You want to assign the same fraction of inputs to each bucket.
   *   <li>When you reduce the number of buckets, you can accept that the most recently added
   *       buckets will be removed first. More concretely, if you are dividing traffic among tasks,

   * storedPermits becomes 10.0 (assuming maxStoredPermits >= 10.0). At that point, a request of
   * acquire(3) arrives. We serve this request out of storedPermits, and reduce that to 7.0 (how
   * this is translated to throttling time is discussed later). Immediately after, assume that an
   * acquire(10) request arriving. We serve the request partly from storedPermits, using all the

    }

    @Override
    @ParametricNullness
    public T get() {
      // Another variant of Double Checked Locking.
      //
      // We use two volatile reads. We could reduce this to one by
      // putting our fields into a holder class, but (at least on x86)
      // the extra memory consumption and indirection are more
      // expensive than the extra volatile reads.

 * </ul>
 *
 * <p>The one downside of {@code Stopwatch} relative to {@link System#nanoTime()} is that {@code
 * Stopwatch} requires object allocation and additional method calls, which can reduce the accuracy
 * of the elapsed times reported. {@code Stopwatch} is still suitable for logging and metrics where
 * reasonably accurate values are sufficient. If the uncommon case that you need to maximize

   * This test creates a long random sequence of inputs, then a lot of differently configured sinks
   * process it; all should produce the same answer, the only difference should be the number of
   * process()/processRemaining() invocations, due to alignment.
   */
  @AndroidIncompatible // slow. TODO(cpovirk): Maybe just reduce iterations under Android.
  public void testExhaustive() throws Exception {

   * Nearly all declarations in this class are package-private,
   * accessed directly by subclasses.
   *
   * Table entries are of class Cell; a variant of AtomicLong padded
   * to reduce cache contention on most processors. Padding is
   * overkill for most Atomics because they are usually irregularly
   * scattered in memory and thus don't interfere much with each