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/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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 kafka.utils.timer
import kafka.utils.nonthreadsafe
import java.util.concurrent.DelayQueue
import java.util.concurrent.atomic.AtomicInteger
/*
* Hierarchical Timing Wheels
*
* A simple timing wheel is a circular list of buckets of timer tasks. Let u be the time unit.
* A timing wheel with size n has n buckets and can hold timer tasks in n * u time interval.
* Each bucket holds timer tasks that fall into the corresponding time range. At the beginning,
* the first bucket holds tasks for [0, u), the second bucket holds tasks for [u, 2u), …,
* the n-th bucket for [u * (n -1), u * n). Every interval of time unit u, the timer ticks and
* moved to the next bucket then expire all timer tasks in it. So, the timer never insert a task
* into the bucket for the current time since it is already expired. The timer immediately runs
* the expired task. The emptied bucket is then available for the next round, so if the current
* bucket is for the time t, it becomes the bucket for [t + u * n, t + (n + 1) * u) after a tick.
* A timing wheel has O(1) cost for insert/delete (start-timer/stop-timer) whereas priority queue
* based timers, such as java.util.concurrent.DelayQueue and java.util.Timer, have O(log n)
* insert/delete cost.
*
* A major drawback of a simple timing wheel is that it assumes that a timer request is within
* the time interval of n * u from the current time. If a timer request is out of this interval,
* it is an overflow. A hierarchical timing wheel deals with such overflows. It is a hierarchically
* organized timing wheels. The lowest level has the finest time resolution. As moving up the
* hierarchy, time resolutions become coarser. If the resolution of a wheel at one level is u and
* the size is n, the resolution of the next level should be n * u. At each level overflows are
* delegated to the wheel in one level higher. When the wheel in the higher level ticks, it reinsert
* timer tasks to the lower level. An overflow wheel can be created on-demand. When a bucket in an
* overflow bucket expires, all tasks in it are reinserted into the timer recursively. The tasks
* are then moved to the finer grain wheels or be executed. The insert (start-timer) cost is O(m)
* where m is the number of wheels, which is usually very small compared to the number of requests
* in the system, and the delete (stop-timer) cost is still O(1).
*
* Example
* Let's say that u is 1 and n is 3. If the start time is c,
* then the buckets at different levels are:
*
* level buckets
* 1 [c,c] [c+1,c+1] [c+2,c+2]
* 2 [c,c+2] [c+3,c+5] [c+6,c+8]
* 3 [c,c+8] [c+9,c+17] [c+18,c+26]
*
* The bucket expiration is at the time of bucket beginning.
* So at time = c+1, buckets [c,c], [c,c+2] and [c,c+8] are expired.
* Level 1's clock moves to c+1, and [c+3,c+3] is created.
* Level 2 and level3's clock stay at c since their clocks move in unit of 3 and 9, respectively.
* So, no new buckets are created in level 2 and 3.
*
* Note that bucket [c,c+2] in level 2 won't receive any task since that range is already covered in level 1.
* The same is true for the bucket [c,c+8] in level 3 since its range is covered in level 2.
* This is a bit wasteful, but simplifies the implementation.
*
* 1 [c+1,c+1] [c+2,c+2] [c+3,c+3]
* 2 [c,c+2] [c+3,c+5] [c+6,c+8]
* 3 [c,c+8] [c+9,c+17] [c+18,c+26]
*
* At time = c+2, [c+1,c+1] is newly expired.
* Level 1 moves to c+2, and [c+4,c+4] is created,
*
* 1 [c+2,c+2] [c+3,c+3] [c+4,c+4]
* 2 [c,c+2] [c+3,c+5] [c+6,c+8]
* 3 [c,c+8] [c+9,c+17] [c+18,c+18]
*
* At time = c+3, [c+2,c+2] is newly expired.
* Level 2 moves to c+3, and [c+5,c+5] and [c+9,c+11] are created.
* Level 3 stay at c.
*
* 1 [c+3,c+3] [c+4,c+4] [c+5,c+5]
* 2 [c+3,c+5] [c+6,c+8] [c+9,c+11]
* 3 [c,c+8] [c+9,c+17] [c+8,c+11]
*
* The hierarchical timing wheels works especially well when operations are completed before they time out.
* Even when everything times out, it still has advantageous when there are many items in the timer.
* Its insert cost (including reinsert) and delete cost are O(m) and O(1), respectively while priority
* queue based timers takes O(log N) for both insert and delete where N is the number of items in the queue.
*
* This class is not thread-safe. There should not be any add calls while advanceClock is executing.
* It is caller's responsibility to enforce it. Simultaneous add calls are thread-safe.
*/
@nonthreadsafe
private[timer] class TimingWheel(tickMs: Long, wheelSize: Int, startMs: Long, taskCounter: AtomicInteger, queue: DelayQueue[TimerTaskList]) {
private[this] val interval = tickMs * wheelSize
private[this] val buckets = Array.tabulate[TimerTaskList](wheelSize) { _ => new TimerTaskList(taskCounter) }
private[this] var currentTime = startMs - (startMs % tickMs) // rounding down to multiple of tickMs
// overflowWheel can potentially be updated and read by two concurrent threads through add().
// Therefore, it needs to be volatile due to the issue of Double-Checked Locking pattern with JVM
@volatile private[this] var overflowWheel: TimingWheel = null
private[this] def addOverflowWheel(): Unit = {
synchronized {
if (overflowWheel == null) {
overflowWheel = new TimingWheel(
tickMs = interval,
wheelSize = wheelSize,
startMs = currentTime,
taskCounter = taskCounter,
queue
)
}
}
}
def add(timerTaskEntry: TimerTaskEntry): Boolean = {
val expiration = timerTaskEntry.expirationMs
if (timerTaskEntry.cancelled) {
// Cancelled
false
} else if (expiration < currentTime + tickMs) {
// Already expired
false
} else if (expiration < currentTime + interval) {
// Put in its own bucket
val virtualId = expiration / tickMs
val bucket = buckets((virtualId % wheelSize.toLong).toInt)
bucket.add(timerTaskEntry)
// Set the bucket expiration time
if (bucket.setExpiration(virtualId * tickMs)) {
// The bucket needs to be enqueued because it was an expired bucket
// We only need to enqueue the bucket when its expiration time has changed, i.e. the wheel has advanced
// and the previous buckets gets reused; further calls to set the expiration within the same wheel cycle
// will pass in the same value and hence return false, thus the bucket with the same expiration will not
// be enqueued multiple times.
queue.offer(bucket)
}
true
} else {
// Out of the interval. Put it into the parent timer
if (overflowWheel == null) addOverflowWheel()
overflowWheel.add(timerTaskEntry)
}
}
// Try to advance the clock
def advanceClock(timeMs: Long): Unit = {
if (timeMs >= currentTime + tickMs) {
currentTime = timeMs - (timeMs % tickMs)
// Try to advance the clock of the overflow wheel if present
if (overflowWheel != null) overflowWheel.advanceClock(currentTime)
}
}
}
