19862 Token bucket reimplemented

akka-actor-tests/src/test/scala/akka/util/TokenBucketSpec.scala

@@ -0,0 +1,253 @@
+/**
+ * Copyright (C) 2015-2016 Lightbend Inc. <http://www.lightbend.com>
+ */
+package akka.util
+
+import akka.testkit.AkkaSpec
+
+import scala.util.Random
+
+class TokenBucketSpec extends AkkaSpec {
+
+  class TestBucket(_cap: Long, _period: Long) extends TokenBucket(_cap, _period) {
+    var currentTime: Long = 0L
+  }
+
+  "A Token Bucket" must {
+
+    "start full" in {
+      val bucket = new TestBucket(10, 1)
+      bucket.init()
+
+      bucket.offer(1) should ===(0)
+      bucket.offer(1) should ===(0)
+      bucket.offer(1) should ===(0)
+      bucket.offer(7) should ===(0)
+
+      bucket.offer(3) should ===(3)
+    }
+
+    "calculate correctly with different rates and capacities" in {
+      val bucketRate2 = new TestBucket(10, 2)
+      bucketRate2.init()
+
+      bucketRate2.offer(5) should ===(0)
+      bucketRate2.offer(5) should ===(0)
+      bucketRate2.offer(5) should ===(10)
+
+      val bucketRate3 = new TestBucket(8, 3)
+      bucketRate3.init()
+      bucketRate3.offer(5) should ===(0)
+      bucketRate3.offer(5) should ===(6)
+
+      bucketRate3.currentTime = 6
+      bucketRate3.offer(3) should ===(9)
+    }
+
+    "allow sending elements larger than capacity" in {
+      val bucket = new TestBucket(10, 2)
+      bucket.init()
+
+      bucket.offer(5) should ===(0)
+      bucket.offer(20) should ===(30)
+
+      bucket.currentTime = 30
+      bucket.offer(1) should ===(2)
+
+      bucket.currentTime = 34
+      bucket.offer(1) should ===(0)
+      bucket.offer(1) should ===(2)
+    }
+
+    "work with zero capacity" in {
+      val bucket = new TestBucket(0, 2)
+      bucket.init()
+
+      bucket.offer(10) should ===(20)
+
+      bucket.currentTime = 40
+      bucket.offer(10) should ===(20)
+    }
+
+    "not delay if rate is higher than production" in {
+      val bucket = new TestBucket(1, 10)
+      bucket.init()
+
+      for (time ← 0 to 100 by 10) {
+        bucket.currentTime = time
+        bucket.offer(1) should ===(0)
+      }
+
+    }
+
+    "maintain maximum capacity" in {
+      val bucket = new TestBucket(10, 1)
+      bucket.init()
+      bucket.offer(10) should ===(0)
+
+      bucket.currentTime = 100000
+      bucket.offer(20) should ===(10)
+    }
+
+    "work if currentTime is negative" in {
+      val bucket = new TestBucket(10, 1)
+      bucket.currentTime = -100 // Must be set before init()!
+      bucket.init()
+
+      bucket.offer(5) should ===(0)
+      bucket.offer(10) should ===(5)
+
+      bucket.currentTime += 10
+
+      bucket.offer(5) should ===(0)
+    }
+
+    "work if currentTime wraps over" in {
+      val bucket = new TestBucket(10, 1)
+      bucket.currentTime = Long.MaxValue - 5 // Must be set before init()!
+      bucket.init()
+
+      bucket.offer(5) should ===(0)
+      bucket.offer(10) should ===(5)
+
+      bucket.currentTime += 10
+
+      bucket.offer(5) should ===(0)
+    }
+
+    "(attempt to) maintain equal time between token renewal intervals" in {
+      val bucket = new TestBucket(5, 3)
+      bucket.init()
+
+      bucket.offer(10) should ===(15)
+
+      bucket.currentTime = 16
+      // At this point there is no token in the bucket (we consumed it at T15) but the next token will arrive at T18!
+      // A naive calculation would consider that there is 1 token needed hence we need to wait 3 units, but in fact
+      // we only need to wait 2 units, otherwise we shift the whole token arrival sequence resulting in lower rates.
+      //
+      // 0   3   9  12  15  18  21  24  27
+      // +---+---+---+---+---+---+---+---+
+      //                 ^ ^
+      //  emitted here --+ +---- currently here (T16)
+      //
+
+      bucket.offer(1) should ===(2)
+
+      bucket.currentTime = 19
+      // At 18 bucket is empty, and so is at 19. For a cost of 2 we need to wait until T24 which is 5 units.
+      //
+      // 0   3   9  12  15  18  21  24  27
+      // +---+---+---+---+---+---+---+---+
+      //                     ^ ^
+      //      emptied here --+ +---- currently here (T19)
+      //
+      bucket.offer(2) should ===(5)
+
+      // Another case
+      val bucket2 = new TestBucket(10, 3)
+      bucket2.init()
+
+      bucket2.currentTime = 4
+      bucket2.offer(6) should ===(0)
+
+      // 4 tokens remain and new tokens arrive at T6 and T9 so here we have 6 tokens remaining.
+      // We need 1 more, which will arrive at T12
+      bucket2.currentTime = 10
+      bucket2.offer(7) should ===(2)
+    }
+
+    "work with cost of zero" in {
+      val bucket = new TestBucket(10, 1)
+      bucket.init()
+
+      // Can be called any number of times
+      bucket.offer(0)
+      bucket.offer(0)
+      bucket.offer(0)
+
+      bucket.offer(10) should ===(0)
+
+      // Bucket is empty now
+      // Still can be called any number of times
+      bucket.offer(0)
+      bucket.offer(0)
+      bucket.offer(0)
+    }
+
+    "work with very slow rates" in {
+      val T = Long.MaxValue >> 10
+      val bucket = new TestBucket(10, T)
+      bucket.init()
+
+      bucket.offer(20) should ===(10 * T)
+      bucket.currentTime += 10 * T
+
+      // Collect 5 tokens
+      bucket.currentTime += 5 * T
+
+      bucket.offer(4) should ===(0)
+      bucket.offer(2) should ===(T)
+    }
+
+    "behave exactly as the ideal (naive) token bucket if offer is called with perfect timing" in {
+      val Debug = false
+
+      for {
+        capacity ← List(0, 1, 5, 10)
+        period ← List(1, 3, 5)
+        arrivalPeriod ← List(1, 3, 5)
+        startTime ← List(Long.MinValue, -1L, 0L, Long.MaxValue)
+        maxCost ← List(1, 5, 10)
+      } {
+
+        val bucket = new TestBucket(capacity, period)
+        bucket.currentTime = startTime
+        bucket.init()
+
+        var idealBucket = capacity
+        var untilNextTick = period
+        var untilNextElement = Random.nextInt(arrivalPeriod) + 1
+        var nextEmit = 0L
+        var delaying = false
+
+        for (time ← 0 to 1000) {
+          if (untilNextTick == 0) {
+            untilNextTick = period
+            idealBucket = math.min(idealBucket + 1, capacity)
+          }
+
+          if (Debug) println(s"T:$time  bucket:$idealBucket")
+
+          if (delaying && idealBucket == 0) {
+            // Actual emit time should equal to what the optimized token bucket calculates
+            time should ===(nextEmit)
+            untilNextElement = time + Random.nextInt(arrivalPeriod)
+            if (Debug) println(s"  EMITTING")
+            delaying = false
+          }
+
+          if (untilNextElement == 0) {
+            // Allow cost of zer
+            val cost = Random.nextInt(maxCost + 1)
+            idealBucket -= cost // This can go negative
+            bucket.currentTime = startTime + time
+            val delay = bucket.offer(cost)
+            nextEmit = time + delay
+            if (Debug) println(s"  ARRIVAL cost: $cost at: $nextEmit")
+            if (delay == 0) {
+              (idealBucket >= 0) should be(true)
+              untilNextElement = time + Random.nextInt(arrivalPeriod)
+            } else delaying = true
+          }
+
+          untilNextTick -= 1
+          untilNextElement -= 1
+        }
+      }
+
+    }
+
+  }
+
+}

akka-actor/src/main/scala/akka/util/TokenBucket.scala

@@ -0,0 +1,88 @@
+/**
+ * Copyright (C) 2015-2016 Lightbend Inc. <http://www.lightbend.com>
+ */
+package akka.util
+
+/**
+ * INTERNAL API
+ */
+private[akka] abstract class TokenBucket(capacity: Long, nanosBetweenTokens: Long) {
+  require(capacity >= 0, "Capacity must be non-negative.")
+  require(nanosBetweenTokens > 0, "Time between tokens must be larger than zero nanoseconds.")
+
+  private[this] var availableTokens: Long = _
+  private[this] var lastUpdate: Long = _
+
+  /**
+   * This method must be called before the token bucket can be used.
+   */
+  def init(): Unit = {
+    availableTokens = capacity
+    lastUpdate = currentTime
+  }
+
+  /**
+   * The current time in nanos. The returned value is monotonic, might wrap over and has no relationship with wall-clock.
+   *
+   * @return return the current time in nanos as a Long.
+   */
+  def currentTime: Long
+
+  /**
+   * Call this (side-effecting) method whenever an element should be passed through the token-bucket. This method
+   * will return the number of nanoseconds the element needs to be delayed to conform with the token bucket parameters.
+   * Returns zero if the element can be emitted immediately. The method does not handle overflow, if an element is to
+   * be delayed longer in nanoseconds than what can be represented as a positive Long then an undefined value is returned.
+   *
+   * If a non-zero value is returned, it is the responsibility of the caller to not call this method before the
+   * returned delay has been elapsed (but can be called later). This class does not check or protect against early
+   * calls.
+   *
+   * @param cost How many tokens the element costs. Can be larger than the capacity of the bucket.
+   * @return
+   */
+  def offer(cost: Long): Long = {
+    if (cost < 0) throw new IllegalArgumentException("Cost must be non-negative")
+
+    val now = currentTime
+    val timeElapsed = now - lastUpdate
+
+    val tokensArrived =
+      // Was there even a tick since last time?
+      if (timeElapsed >= nanosBetweenTokens) {
+        // only one tick elapsed
+        if (timeElapsed < nanosBetweenTokens * 2) {
+          lastUpdate += nanosBetweenTokens
+          1
+        } else {
+          // Ok, no choice, do the slow integer division
+          val tokensArrived = timeElapsed / nanosBetweenTokens
+          lastUpdate += tokensArrived * nanosBetweenTokens
+          tokensArrived
+        }
+      } else 0
+
+    availableTokens = math.min(availableTokens + tokensArrived, capacity)
+
+    if (cost <= availableTokens) {
+      availableTokens -= cost
+      0
+    } else {
+      val remainingCost = cost - availableTokens
+      // Tokens always arrive at exact multiples of the token generation period, we must account for that
+      val timeSinceTokenArrival = now - lastUpdate
+      val delay = remainingCost * nanosBetweenTokens - timeSinceTokenArrival
+      availableTokens = 0
+      lastUpdate = now + delay
+      delay
+    }
+  }
+
+}
+
+/**
+ * Default implementation of [[TokenBucket]] that uses `System.nanoTime` as the time source.
+ */
+final class NanoTimeTokenBucket(_cap: Long, _period: Long) extends TokenBucket(_cap, _period) {
+  override def currentTime: Long = System.nanoTime()
+}

akka-stream-tests/src/test/scala/akka/stream/scaladsl/FlowThrottleSpec.scala

@@ -29,6 +29,23 @@ class FlowThrottleSpec extends AkkaSpec {
         .expectComplete()
     }
 
+    "accept very high rates" in Utils.assertAllStagesStopped {
+      Source(1 to 5).throttle(1, 1 nanos, 0, ThrottleMode.Shaping)
+        .runWith(TestSink.probe[Int])
+        .request(5)
+        .expectNext(1, 2, 3, 4, 5)
+        .expectComplete()
+    }
+
+    "accept very low rates" in Utils.assertAllStagesStopped {
+      Source(1 to 5).throttle(1, 100.days, 1, ThrottleMode.Shaping)
+        .runWith(TestSink.probe[Int])
+        .request(5)
+        .expectNext(1)
+        .expectNoMsg(100.millis)
+        .cancel() // We won't wait 100 days, sorry
+    }
+
     "emit single element per tick" in Utils.assertAllStagesStopped {
       val upstream = TestPublisher.probe[Int]()
       val downstream = TestSubscriber.probe[Int]()

akka-stream/src/main/scala/akka/stream/impl/Throttle.scala

@@ -7,36 +7,13 @@ import akka.stream.ThrottleMode.{ Enforcing, Shaping }
 import akka.stream.impl.fusing.GraphStages.SimpleLinearGraphStage
 import akka.stream.stage._
 import akka.stream._
+import akka.util.NanoTimeTokenBucket
 
 import scala.concurrent.duration.{ FiniteDuration, _ }
 
 /**
  * INTERNAL API
  */
-private[stream] object Throttle {
-
-  val miniTokenBits = 30
-
-  private def tokenToMiniToken(e: Int): Long = e.toLong << Throttle.miniTokenBits
-}
-
-/**
- * INTERNAL API
- */
-/*
- * This class tracks a token bucket in an efficient way.
- *
- * For accuracy, instead of tracking integer tokens the implementation tracks "miniTokens" which are 1/2^30 fraction
- * of a token. This allows us to track token replenish rate as miniTokens/nanosecond which allows us to use simple
- * arithmetic without division and also less inaccuracy due to rounding on token count caculation.
- *
- * The replenish amount, and hence the current time is only queried if the bucket does not hold enough miniTokens, in
- * other words, replenishing the bucket is *on-need*. In addition, to compensate scheduler inaccuracy, the implementation
- * calculates the ideal "previous time" explicitly, not relying on the scheduler to tick at that time. This means that
- * when the scheduler actually ticks, some time has been elapsed since the calculated ideal tick time, and those tokens
- * are added to the bucket as any calculation is always relative to the ideal tick time.
- *
- */
 private[stream] class Throttle[T](cost: Int,
                                   per: FiniteDuration,
                                   maximumBurst: Int,
@@ -44,69 +21,64 @@ private[stream] class Throttle[T](cost: Int,
                                   mode: ThrottleMode)
   extends SimpleLinearGraphStage[T] {
   require(cost > 0, "cost must be > 0")
-  require(per.toMillis > 0, "per time must be > 0")
+  require(per.toNanos > 0, "per time must be > 0")
   require(!(mode == ThrottleMode.Enforcing && maximumBurst < 0), "maximumBurst must be > 0 in Enforcing mode")
+  require(per.toNanos >= cost, "Rates larger than 1 unit / nanosecond are not supported")
 
-  private val maximumBurstMiniTokens = Throttle.tokenToMiniToken(maximumBurst)
-  private val miniTokensPerNanos = (Throttle.tokenToMiniToken(cost).toDouble / per.toNanos).toLong
+  // There is some loss of precision here because of rounding, but this only happens if nanosBetweenTokens is very
+  // small which is usually at rates where that precision is highly unlikely anyway as the overhead of this stage
+  // is likely higher than the required accuracy interval.
+  private val nanosBetweenTokens = per.toNanos / cost
   private val timerName: String = "ThrottleTimer"
 
   override def createLogic(inheritedAttributes: Attributes): GraphStageLogic = new TimerGraphStageLogic(shape) {
+    private val tokenBucket = new NanoTimeTokenBucket(maximumBurst, nanosBetweenTokens)
+
     var willStop = false
-    var previousMiniTokens: Long = maximumBurstMiniTokens
-    var previousNanos: Long = System.nanoTime()
-
-    var currentElement: Option[T] = None
-
-    setHandler(in, new InHandler {
-
-      override def onUpstreamFinish(): Unit =
-        if (isAvailable(out) && isTimerActive(timerName)) willStop = true
-        else completeStage()
-
-      override def onPush(): Unit = {
-        val elem = grab(in)
-        val elementCostMiniTokens = Throttle.tokenToMiniToken(costCalculation(elem))
-
-        if (previousMiniTokens >= elementCostMiniTokens) {
-          previousMiniTokens -= elementCostMiniTokens
-          push(out, elem)
-        } else {
-          val currentNanos = System.nanoTime()
-          val currentMiniTokens = Math.min(
-            (currentNanos - previousNanos) * miniTokensPerNanos + previousMiniTokens,
-            maximumBurstMiniTokens)
-
-          if (currentMiniTokens < elementCostMiniTokens)
-            mode match {
-              case Shaping ⇒
-                currentElement = Some(elem)
-                val waitNanos = (elementCostMiniTokens - currentMiniTokens) / miniTokensPerNanos
-                previousNanos = currentNanos + waitNanos
-                scheduleOnce(timerName, waitNanos.nanos)
-              case Enforcing ⇒ failStage(new RateExceededException("Maximum throttle throughput exceeded"))
-            }
-          else {
-            previousMiniTokens = currentMiniTokens - elementCostMiniTokens
-            previousNanos = currentNanos
-            push(out, elem)
-          }
-        }
-      }
-    })
-
-    override protected def onTimer(key: Any): Unit = {
-      push(out, currentElement.get)
-      currentElement = None
-      previousMiniTokens = 0
-      if (willStop) completeStage()
+    var currentElement: T = _
+    val enforcing = mode match {
+      case Enforcing ⇒ true
+      case Shaping   ⇒ false
     }
 
-    setHandler(out, new OutHandler {
-      override def onPull(): Unit = pull(in)
-    })
+    override def preStart(): Unit = tokenBucket.init()
 
-    override def preStart(): Unit = previousNanos = System.nanoTime()
+    // This scope is here just to not retain an extra reference to the handler below.
+    // We can't put this code into preRestart() because setHandler() must be called before that.
+    {
+      val handler = new InHandler with OutHandler {
+        override def onUpstreamFinish(): Unit =
+          if (isAvailable(out) && isTimerActive(timerName)) willStop = true
+          else completeStage()
+
+        override def onPush(): Unit = {
+          val elem = grab(in)
+          val cost = costCalculation(elem)
+          val delayNanos = tokenBucket.offer(cost)
+
+          if (delayNanos == 0L) push(out, elem)
+          else {
+            if (enforcing) failStage(new RateExceededException("Maximum throttle throughput exceeded."))
+            else {
+              currentElement = elem
+              scheduleOnce(timerName, delayNanos.nanos)
+            }
+          }
+        }
+
+        override def onPull(): Unit = pull(in)
+      }
+
+      setHandler(in, handler)
+      setHandler(out, handler)
+      // After this point, we no longer need the `handler` so it can just fall out of scope.
+    }
+
+    override protected def onTimer(key: Any): Unit = {
+      push(out, currentElement)
+      currentElement = null.asInstanceOf[T]
+      if (willStop) completeStage()
+    }
 
   }
 

akka-stream/src/main/scala/akka/stream/javadsl/Flow.scala

@@ -1614,6 +1614,13 @@ final class Flow[-In, +Out, +Mat](delegate: scaladsl.Flow[In, Out, Mat]) extends
    *  - [[akka.stream.ThrottleMode.Shaping]] makes pauses before emitting messages to meet throttle rate
    *  - [[akka.stream.ThrottleMode.Enforcing]] fails with exception when upstream is faster than throttle rate
    *
+   * It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing
+   * the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce
+   * most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).
+   *
+   * Throttler always enforces the rate limit, but in certain cases (mostly due to limited scheduler resolution) it
+   * enforces a tighter bound than what was prescribed. This can be also mitigated by increasing the burst size.
+   *
    * '''Emits when''' upstream emits an element and configured time per each element elapsed
    *
    * '''Backpressures when''' downstream backpressures

akka-stream/src/main/scala/akka/stream/javadsl/Source.scala

@@ -1742,6 +1742,13 @@ final class Source[+Out, +Mat](delegate: scaladsl.Source[Out, Mat]) extends Grap
    *  - [[akka.stream.ThrottleMode.Shaping]] makes pauses before emitting messages to meet throttle rate
    *  - [[akka.stream.ThrottleMode.Enforcing]] fails with exception when upstream is faster than throttle rate
    *
+   * It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing
+   * the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce
+   * most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).
+   *
+   * Throttler always enforces the rate limit, but in certain cases (mostly due to limited scheduler resolution) it
+   * enforces a tighter bound than what was prescribed. This can be also mitigated by increasing the burst size.
+   *
    * '''Emits when''' upstream emits an element and configured time per each element elapsed
    *
    * '''Backpressures when''' downstream backpressures

akka-stream/src/main/scala/akka/stream/javadsl/SubFlow.scala

@@ -1153,6 +1153,13 @@ class SubFlow[-In, +Out, +Mat](delegate: scaladsl.SubFlow[Out, Mat, scaladsl.Flo
    *  - [[akka.stream.ThrottleMode.Enforcing]] fails with exception when upstream is faster than throttle rate. Enforcing
    *  cannot emit elements that cost more than the maximumBurst
    *
+   * It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing
+   * the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce
+   * most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).
+   *
+   * Throttler always enforces the rate limit, but in certain cases (mostly due to limited scheduler resolution) it
+   * enforces a tighter bound than what was prescribed. This can be also mitigated by increasing the burst size.
+   *
    * '''Emits when''' upstream emits an element and configured time per each element elapsed
    *
    * '''Backpressures when''' downstream backpressures

akka-stream/src/main/scala/akka/stream/scaladsl/Flow.scala

@@ -1479,6 +1479,13 @@ trait FlowOps[+Out, +Mat] {
    * bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally
    * to their cost minus available tokens, meeting the target rate.
    *
+   * It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing
+   * the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce
+   * most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).
+   *
+   * Throttler always enforces the rate limit, but in certain cases (mostly due to limited scheduler resolution) it
+   * enforces a tighter bound than what was prescribed. This can be also mitigated by increasing the burst size.
+   *
    * Parameter `mode` manages behaviour when upstream is faster than throttle rate:
    *  - [[akka.stream.ThrottleMode.Shaping]] makes pauses before emitting messages to meet throttle rate
    *  - [[akka.stream.ThrottleMode.Enforcing]] fails with exception when upstream is faster than throttle rate. Enforcing