限流实现-Guava 的RateLimiter(二)

/*
 * Copyright (C) 2012 The Guava Authors
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.google.common.util.concurrent;

import static java.lang.Math.min;
import static java.util.concurrent.TimeUnit.SECONDS;

import java.util.concurrent.TimeUnit;

abstract class SmoothRateLimiter extends RateLimiter {
  /*
   * How is the RateLimiter designed, and why?
   *
   * The primary feature of a RateLimiter is its "stable rate", the maximum rate that
   * is should allow at normal conditions. This is enforced by "throttling" incoming
   * requests as needed, i.e. compute, for an incoming request, the appropriate throttle time,
   * and make the calling thread wait as much.
   *
   * The simplest way to maintain a rate of QPS is to keep the timestamp of the last
   * granted request, and ensure that (1/QPS) seconds have elapsed since then. For example,
   * for a rate of QPS=5 (5 tokens per second), if we ensure that a request isn't granted
   * earlier than 200ms after the last one, then we achieve the intended rate.
   * If a request comes and the last request was granted only 100ms ago, then we wait for
   * another 100ms. At this rate, serving 15 fresh permits (i.e. for an acquire(15) request)
   * naturally takes 3 seconds.
   *
   * It is important to realize that such a RateLimiter has a very superficial memory
   * of the past: it only remembers the last request. What if the RateLimiter was unused for
   * a long period of time, then a request arrived and was immediately granted?
   * This RateLimiter would immediately forget about that past underutilization. This may
   * result in either underutilization or overflow, depending on the real world consequences
   * of not using the expected rate.
   *
   * Past underutilization could mean that excess resources are available. Then, the RateLimiter
   * should speed up for a while, to take advantage of these resources. This is important
   * when the rate is applied to networking (limiting bandwidth), where past underutilization
   * typically translates to "almost empty buffers", which can be filled immediately.
   *
   * On the other hand, past underutilization could mean that "the server responsible for
   * handling the request has become less ready for future requests", i.e. its caches become
   * stale, and requests become more likely to trigger expensive operations (a more extreme
   * case of this example is when a server has just booted, and it is mostly busy with getting
   * itself up to speed).
   *
   * To deal with such scenarios, we add an extra dimension, that of "past underutilization",
   * modeled by "storedPermits" variable. This variable is zero when there is no
   * underutilization, and it can grow up to maxStoredPermits, for sufficiently large
   * underutilization. So, the requested permits, by an invocation acquire(permits),
   * are served from:
   * - stored permits (if available)
   * - fresh permits (for any remaining permits)
   *
   * How this works is best explained with an example:
   *
   * For a RateLimiter that produces 1 token per second, every second
   * that goes by with the RateLimiter being unused, we increase storedPermits by 1.
   * Say we leave the RateLimiter unused for 10 seconds (i.e., we expected a request at time
   * X, but we are at time X + 10 seconds before a request actually arrives; this is
   * also related to the point made in the last paragraph), thus 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 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 permits? As explained above, there is no unique answer. If we are primarily
   * interested to deal with underutilization, then we want stored permits to be given out
   * /faster/ than fresh ones, because underutilization = free resources for the taking.
   * If we are primarily interested to deal with overflow, then stored permits could
   * be given out /slower/ than fresh ones. Thus, we require a (different in each case)
   * function that translates storedPermits to throtting time.
   *
   * This role is played by storedPermitsToWaitTime(double storedPermits, double permitsToTake).
   * The underlying model is a continuous function mapping storedPermits
   * (from 0.0 to maxStoredPermits) onto the 1/rate (i.e. intervals) that is effective at the given
   * storedPermits. "storedPermits" essentially measure unused time; we spend unused time
   * buying/storing permits. Rate is "permits / time", thus "1 / rate = time / permits".
   * Thus, "1/rate" (time / permits) times "permits" gives time, i.e., integrals on this
   * function (which is what storedPermitsToWaitTime() computes) correspond to minimum intervals
   * between subsequent requests, for the specified number of requested permits.
   *
   * Here is an example of storedPermitsToWaitTime:
   * If storedPermits == 10.0, and we want 3 permits, we take them from storedPermits,
   * reducing them to 7.0, and compute the throttling for these as a call to
   * storedPermitsToWaitTime(storedPermits = 10.0, permitsToTake = 3.0), which will
   * evaluate the integral of the function from 7.0 to 10.0.
   *
   * Using integrals guarantees that the effect of a single acquire(3) is equivalent
   * to { acquire(1); acquire(1); acquire(1); }, or { acquire(2); acquire(1); }, etc,
   * since the integral of the function in [7.0, 10.0] is equivalent to the sum of the
   * integrals of [7.0, 8.0], [8.0, 9.0], [9.0, 10.0] (and so on), no matter
   * what the function is. This guarantees that we handle correctly requests of varying weight
   * (permits), /no matter/ what the actual function is - so we can tweak the latter freely.
   * (The only requirement, obviously, is that we can compute its integrals).
   *
   * Note well that if, for this function, we chose a horizontal line, at height of exactly
   * (1/QPS), then the effect of the function is non-existent: we serve storedPermits at
   * exactly the same cost as fresh ones (1/QPS is the cost for each). We use this trick later.
   *
   * If we pick a function that goes /below/ that horizontal line, it means that we reduce
   * the area of the function, thus time. Thus, the RateLimiter becomes /faster/ after a
   * period of underutilization. If, on the other hand, we pick a function that
   * goes /above/ that horizontal line, then it means that the area (time) is increased,
   * thus storedPermits are more costly than fresh permits, thus the RateLimiter becomes
   * /slower/ after a period of underutilization.
   *
   * Last, but not least: consider a RateLimiter with rate of 1 permit per second, currently
   * completely unused, and an expensive acquire(100) request comes. It would be nonsensical
   * to just wait for 100 seconds, and /then/ start the actual task. Why wait without doing
   * anything? A much better approach is to /allow/ the request right away (as if it was an
   * acquire(1) request instead), and postpone /subsequent/ requests as needed. In this version,
   * we allow starting the task immediately, and postpone by 100 seconds future requests,
   * thus we allow for work to get done in the meantime instead of waiting idly.
   *
   * This has important consequences: it means that the RateLimiter doesn't remember the time
   * of the _last_ request, but it remembers the (expected) time of the _next_ request. This
   * also enables us to tell immediately (see tryAcquire(timeout)) whether a particular
   * timeout is enough to get us to the point of the next scheduling time, since we always
   * maintain that. And what we mean by "an unused RateLimiter" is also defined by that
   * notion: when we observe that the "expected arrival time of the next request" is actually
   * in the past, then the difference (now - past) is the amount of time that the RateLimiter
   * was formally unused, and it is that amount of time which we translate to storedPermits.
   * (We increase storedPermits with the amount of permits that would have been produced
   * in that idle time). So, if rate == 1 permit per second, and arrivals come exactly
   * one second after the previous, then storedPermits is _never_ increased -- we would only
   * increase it for arrivals _later_ than the expected one second.
   */

  /**
   * This implements the following function:
   *
   *          ^ throttling
   *          |
   * 3*stable +                  /
   * interval |                 /.
   *  (cold)  |                / .
   *          |               /  .   <-- "warmup period" is the area of the trapezoid between
   * 2*stable +              /   .       halfPermits and maxPermits
   * interval |             /    .
   *          |            /     .
   *          |           /      .
   *   stable +----------/  WARM . }
   * interval |          .   UP  . } <-- this rectangle (from 0 to maxPermits, and
   *          |          . PERIOD. }     height == stableInterval) defines the cooldown period,
   *          |          .       . }     and we want cooldownPeriod == warmupPeriod
   *          |---------------------------------> storedPermits
   *              (halfPermits) (maxPermits)
   *
   * Before going into the details of this particular function, let's keep in mind the basics:
   * 1) The state of the RateLimiter (storedPermits) is a vertical line in this figure.
   * 2) When the RateLimiter is not used, this goes right (up to maxPermits)
   * 3) When the RateLimiter is used, this goes left (down to zero), since if we have storedPermits,
   *    we serve from those first
   * 4) When _unused_, we go right at the same speed (rate)! I.e., if our rate is
   *    2 permits per second, and 3 unused seconds pass, we will always save 6 permits
   *    (no matter what our initial position was), up to maxPermits.
   *    If we invert the rate, we get the "stableInterval" (interval between two requests
   *    in a perfectly spaced out sequence of requests of the given rate). Thus, if you
   *    want to see "how much time it will take to go from X storedPermits to X+K storedPermits?",
   *    the answer is always stableInterval * K. In the same example, for 2 permits per second,
   *    stableInterval is 500ms. Thus to go from X storedPermits to X+6 storedPermits, we
   *    require 6 * 500ms = 3 seconds.
   *
   *    In short, the time it takes to move to the right (save K permits) is equal to the
   *    rectangle of width == K and height == stableInterval.
   * 4) 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.
   *
   *    In summary, the time it takes to move to the left (spend K permits), is equal to the
   *    area of the function of width == K.
   *
   * Let's dive into this function now:
   *
   * When we have storedPermits <= halfPermits (the left portion of the function), then
   * we spend them at the exact same rate that
   * fresh permits would be generated anyway (that rate is 1/stableInterval). We size
   * this area to be equal to _half_ the specified warmup period. Why we need this?
   * And why half? We'll explain shortly below (after explaining the second part).
   *
   * Stored permits that are beyond halfPermits, are mapped to an ascending line, that goes
   * from stableInterval to 3 * stableInterval. The average height for that part is
   * 2 * stableInterval, and is sized appropriately to have an area _equal_ to the
   * specified warmup period. Thus, by point (4) above, it takes "warmupPeriod" amount of time
   * to go from maxPermits to halfPermits.
   *
   * BUT, by point (3) above, it only takes "warmupPeriod / 2" amount of time to return back
   * to maxPermits, from halfPermits! (Because the trapezoid has double the area of the rectangle
   * of height stableInterval and equivalent width). We decided that the "cooldown period"
   * time should be equivalent to "warmup period", thus a fully saturated RateLimiter
   * (with zero stored permits, serving only fresh ones) can go to a fully unsaturated
   * (with storedPermits == maxPermits) in the same amount of time it takes for a fully
   * unsaturated RateLimiter to return to the stableInterval -- which happens in halfPermits,
   * since beyond that point, we use a horizontal line of "stableInterval" height, simulating
   * the regular rate.
   *
   * Thus, we have figured all dimensions of this shape, to give all the desired
   * properties:
   * - the width is warmupPeriod / stableInterval, to make cooldownPeriod == warmupPeriod
   * - the slope starts at the middle, and goes from stableInterval to 3*stableInterval so
   *   to have halfPermits being spend in double the usual time (half the rate), while their
   *   respective rate is steadily ramping up
   */
  static final class SmoothWarmingUp extends SmoothRateLimiter {
    private final long warmupPeriodMicros;
    /**
     * The slope of the line from the stable interval (when permits == 0), to the cold interval
     * (when permits == maxPermits)
     */
    private double slope;
    private double halfPermits;
  
    SmoothWarmingUp(SleepingStopwatch stopwatch, long warmupPeriod, TimeUnit timeUnit) {
      super(stopwatch);
      this.warmupPeriodMicros = timeUnit.toMicros(warmupPeriod);
    }
  
    @Override
    void doSetRate(double permitsPerSecond, double stableIntervalMicros) {
      double oldMaxPermits = maxPermits;
      maxPermits = warmupPeriodMicros / stableIntervalMicros;
      halfPermits = maxPermits / 2.0;
      // Stable interval is x, cold is 3x, so on average it's 2x. Double the time -> halve the rate
      double coldIntervalMicros = stableIntervalMicros * 3.0;
      slope = (coldIntervalMicros - stableIntervalMicros) / halfPermits;
      if (oldMaxPermits == Double.POSITIVE_INFINITY) {
        // if we don't special-case this, we would get storedPermits == NaN, below
        storedPermits = 0.0;
      } else {
        storedPermits = (oldMaxPermits == 0.0)
            ? maxPermits // initial state is cold
            : storedPermits * maxPermits / oldMaxPermits;
      }
    }
  
    @Override
    long storedPermitsToWaitTime(double storedPermits, double permitsToTake) {
      double availablePermitsAboveHalf = storedPermits - halfPermits;
      long micros = 0;
      // measuring the integral on the right part of the function (the climbing line)
      if (availablePermitsAboveHalf > 0.0) {
        double permitsAboveHalfToTake = min(availablePermitsAboveHalf, permitsToTake);
        micros = (long) (permitsAboveHalfToTake * (permitsToTime(availablePermitsAboveHalf)
            + permitsToTime(availablePermitsAboveHalf - permitsAboveHalfToTake)) / 2.0);
        permitsToTake -= permitsAboveHalfToTake;
      }
      // measuring the integral on the left part of the function (the horizontal line)
      micros += (stableIntervalMicros * permitsToTake);
      return micros;
    }
  
    private double permitsToTime(double permits) {
      return stableIntervalMicros + permits * slope;
    }
  }

  /**
   * This implements a "bursty" RateLimiter, where storedPermits are translated to
   * zero throttling. The maximum number of permits that can be saved (when the RateLimiter is
   * unused) is defined in terms of time, in this sense: if a RateLimiter is 2qps, and this
   * time is specified as 10 seconds, we can save up to 2 * 10 = 20 permits. 
   */
  static final class SmoothBursty extends SmoothRateLimiter {
    /** The work (permits) of how many seconds can be saved up if this RateLimiter is unused? */
    final double maxBurstSeconds; 
    
    SmoothBursty(SleepingStopwatch stopwatch, double maxBurstSeconds) {
      super(stopwatch);
      this.maxBurstSeconds = maxBurstSeconds;
    }
  
    @Override
    void doSetRate(double permitsPerSecond, double stableIntervalMicros) {
      double oldMaxPermits = this.maxPermits;
      maxPermits = maxBurstSeconds * permitsPerSecond;
      if (oldMaxPermits == Double.POSITIVE_INFINITY) {
        // if we don't special-case this, we would get storedPermits == NaN, below
        storedPermits = maxPermits;
      } else {
        storedPermits = (oldMaxPermits == 0.0)
            ? 0.0 // initial state
            : storedPermits * maxPermits / oldMaxPermits;
      }
    }
  
    @Override
    long storedPermitsToWaitTime(double storedPermits, double permitsToTake) {
      return 0L;
    }
  }

  /**
   * The currently stored permits.
   */
  double storedPermits;

  /**
   * The maximum number of stored permits.
   */
  double maxPermits;

  /**
   * The interval between two unit requests, at our stable rate. E.g., a stable rate of 5 permits
   * per second has a stable interval of 200ms.
   */
  double stableIntervalMicros;

  /**
   * The time when the next request (no matter its size) will be granted. After granting a
   * request, this is pushed further in the future. Large requests push this further than small
   * requests.
   */
  private long nextFreeTicketMicros = 0L; // could be either in the past or future

  private SmoothRateLimiter(SleepingStopwatch stopwatch) {
    super(stopwatch);
  }

  @Override
  final void doSetRate(double permitsPerSecond, long nowMicros) {
    resync(nowMicros);
    double stableIntervalMicros = SECONDS.toMicros(1L) / permitsPerSecond;
    this.stableIntervalMicros = stableIntervalMicros;
    doSetRate(permitsPerSecond, stableIntervalMicros);
  }

  abstract void doSetRate(double permitsPerSecond, double stableIntervalMicros);

  @Override
  final double doGetRate() {
    return SECONDS.toMicros(1L) / stableIntervalMicros;
  }

  @Override
  final long queryEarliestAvailable(long nowMicros) {
    return nextFreeTicketMicros;
  }

  @Override
  final long reserveEarliestAvailable(int requiredPermits, long nowMicros) {
    resync(nowMicros);
    long returnValue = nextFreeTicketMicros;
    double storedPermitsToSpend = min(requiredPermits, this.storedPermits);
    double freshPermits = requiredPermits - storedPermitsToSpend;

    long waitMicros = storedPermitsToWaitTime(this.storedPermits, storedPermitsToSpend)
        + (long) (freshPermits * stableIntervalMicros);

    this.nextFreeTicketMicros = nextFreeTicketMicros + waitMicros;
    this.storedPermits -= storedPermitsToSpend;
    return returnValue;
  }

  /**
   * Translates a specified portion of our currently stored permits which we want to
   * spend/acquire, into a throttling time. Conceptually, this evaluates the integral
   * of the underlying function we use, for the range of
   * [(storedPermits - permitsToTake), storedPermits].
   *
   * <p>This always holds: {@code 0 <= permitsToTake <= storedPermits}
   */
  abstract long storedPermitsToWaitTime(double storedPermits, double permitsToTake);

  private void resync(long nowMicros) {
    // if nextFreeTicket is in the past, resync to now
    if (nowMicros > nextFreeTicketMicros) {
      storedPermits = min(maxPermits,
          storedPermits + (nowMicros - nextFreeTicketMicros) / stableIntervalMicros);
      nextFreeTicketMicros = nowMicros;
    }
  }
}