这章理一下channel,先分享一句学习时候看到的话:Do not communicate by sharing memory; instead, share memory by communicating.。本来好像是用在go上的，但也有着异曲同工之妙啊
channel顾名思义是管道,有入口与出口。因此最底层有sendChannel&receiveChannel
produce
Produce = Coroutine + Channel
example:
val channel: ReceiveChannel<Int> = produce<Int>(CommonPool) {
for (i in 0 .. 100) {
delay(1000)
channel.send(i)
}
}
launch(UI) {
for (number in channel) {
textView.text = "Latest number is $number"
}
}
produce也是产生协程,跟普通的launch不同他会返回一个receiveChannel,后面会看到receiveChannel是一个迭代器,同时会suspend在hasNext和next()上,因此另一个协程就可以使用for...in...等待接受。
@ExperimentalCoroutinesApi
public fun <E> CoroutineScope.produce(
context: CoroutineContext = EmptyCoroutineContext,
capacity: Int = 0,
@BuilderInference block: suspend ProducerScope<E>.() -> Unit
): ReceiveChannel<E> {
val channel = Channel<E>(capacity)
val newContext = newCoroutineContext(context)
val coroutine = ProducerCoroutine(newContext, channel)
coroutine.start(CoroutineStart.DEFAULT, coroutine, block)
return coroutine
}
同时,produce发射完成后是会自己关闭的,省的我们自己关闭信道:
override fun onCompletionInternal(state: Any?, mode: Int, suppressed: Boolean) {
val cause = (state as? CompletedExceptionally)?.cause
val processed = _channel.close(cause)
if (cause != null && !processed && suppressed) handleExceptionViaHandler(context, cause)
}
通过job的invokeOnCompletion实现。
actor
example
val channel: SendChannel<View> = actor(UI) {
for (number in channel) {
textView.text = "A new click happend!"
}
}
button.setOnClickListener {
launch(CommonPool) {
channel.send(it)
}
}
与produce相反返回sendChannel
高级用法
fun Node.onClick(action: suspend (MouseEvent) -> Unit) {
// launch one actor to handle all events on this node
val eventActor = GlobalScope.actor<MouseEvent>(Dispatchers.Main) {
for (event in channel) action(event) // pass event to action
}
// install a listener to offer events to this actor
onMouseClicked = EventHandler { event ->
eventActor.offer(event)
}
}
我们看这里用了offer而不是send,我们可以把for..in..先简单的写成以下形式:
while(iterator.hasNext()){ //suspend fuction
val event = iterator.next() //suspend function
action(event)
}
private suspend fun hasNextSuspend(): Boolean = suspendAtomicCancellableCoroutine sc@ { cont ->
val receive = ReceiveHasNext(this, cont)
while (true) {
if (channel.enqueueReceive(receive)) {
channel.removeReceiveOnCancel(cont, receive)
return@sc
}
// hm... something is not right. try to poll
val result = channel.pollInternal()
this.result = result
if (result is Closed<*>) {
if (result.closeCause == null)
cont.resume(false)
else
cont.resumeWithException(result.receiveException)
return@sc
}
if (result !== POLL_FAILED) {
cont.resume(true)
return@sc
}
}
}
假设队列里没有东西时,enqueue一个receiveHasNext进行等待。过会解释一下channel的原理。现在只要知道,当有sender.send时,与receive关联的cont就会被调用resume,那么显而易见,当action正在处理时队列中没有receiver,而offer是不会suspend的,因此事件就被抛弃。
conflation事件合并
fun Node.onClick(action: suspend (MouseEvent) -> Unit) {
// launch one actor to handle all events on this node
val eventActor = GlobalScope.actor<MouseEvent>(Dispatchers.Main, capacity = Channel.CONFLATED) { // <--- Changed here
for (event in channel) action(event) // pass event to action
}
// install a listener to offer events to this actor
onMouseClicked = EventHandler { event ->
eventActor.offer(event)
}
}
这里我们使用CONFALTED,即合并所有事件,因此接受者永远处理最近一个。原理如下:
result === OFFER_FAILED -> { // try to buffer
val sendResult = sendConflated(element)
when (sendResult) {
null -> return OFFER_SUCCESS
is Closed<*> -> {
conflatePreviousSendBuffered(sendResult)
return sendResult
}
}
// otherwise there was receiver in queue, retry super.offerInternal
}
当offer失败时需要suspend等待,（说明还没有接受者或者人家正忙着），插入sendBuffered，同时移除前面已有的sendBuffered
var prev = node.prevNode
while (prev is SendBuffered<*>) {
if (!prev.remove()) {
prev.helpRemove()
}
prev = prev.prevNode
}
这样永远是最近一个生效。
大概channel原理
其实看abstractChannel会先看到一个queue,这时候显而易见会把它当做是像linkedlist那种塞数据的地方。但其实queue是用来放receive/send node。当队列为空时,send时会先从队列取第一个receiveNode,取不到就suspend，把自己当成sendNode放入;不然就把数据直接交给receiveNode。
具体channel实现时，例如ArrayChannel(buffer),会多加一个buffer队列，当队列为空时,send时会先从队列取第一个receiveNode,取不到就放入buffer队列，如果buffer队列满了，把自己当成sendNode放入就suspend;同时把不然就把数据直接交给receiveNode。
select
suspend fun selectInsult(john: ReceiveChannel<String>, mike: ReceiveChannel<String>) {
select<Unit> { // <Unit> means that this select expression does not produce any result
john.onReceive { value -> // this is the first select clause
println("John says '$value'")
}
mike.onReceive { value -> // this is the second select clause
println("Mike says '$value'")
}
}
}
select可以等任何一个回来,也可以等await:
fun adult(): Deferred<String> = async(CommonPool) {
// the adult stops the exchange after a while
delay(Random().nextInt(2000).toLong())
"Stop it!"
}
suspend fun selectInsult(john: ReceiveChannel<String>, mike: ReceiveChannel<String>,
adult: Deferred<String>) {
select {
// [..] the rest is like before
adult.onAwait { value ->
println("Exasperated adult says '$value'")
}
}
}
跟linux里的select其实类似,(能知道是哪个吗？):
final override val onReceive: SelectClause1<E>
get() = object : SelectClause1<E> {
override fun <R> registerSelectClause1(select: SelectInstance<R>, block: suspend (E) -> R) {
registerSelectReceive(select, block)
}
}
private fun <R> registerSelectReceive(select: SelectInstance<R>, block: suspend (E) -> R) {
while (true) {
if (select.isSelected) return
if (isEmpty) {
val enqueueOp = TryEnqueueReceiveDesc(select, block as (suspend (E?) -> R), nullOnClose = false)
val enqueueResult = select.performAtomicIfNotSelected(enqueueOp) ?: return
when {
enqueueResult === ALREADY_SELECTED -> return
enqueueResult === ENQUEUE_FAILED -> {} // retry
else -> error("performAtomicIfNotSelected(TryEnqueueReceiveDesc) returned $enqueueResult")
}
} else {
val pollResult = pollSelectInternal(select)
when {
pollResult === ALREADY_SELECTED -> return
pollResult === POLL_FAILED -> {} // retry
pollResult is Closed<*> -> throw recoverStackTrace(pollResult.receiveException)
else -> {
block.startCoroutineUnintercepted(pollResult as E, select.completion)
return
}
}
}
}
}
能看到onReceive是实现SelectCaluse1,同时在selectBuilderImpl环境下:
override fun <Q> SelectClause1<Q>.invoke(block: suspend (Q) -> R) {
registerSelectClause1(this@SelectBuilderImpl, block)
}
所以会往queue中enqueue两个receive节点。 以
同时能看到如果任何一次select节点获取数据以后:
when {
pollResult === ALREADY_SELECTED -> return
pollResult === POLL_FAILED -> {} // retry
pollResult is Closed<*> -> throw recoverStackTrace(pollResult.receiveException)
else -> {
block.startCoroutineUnintercepted(pollResult as E, select.completion)
return
}
}
会调用block.startCoroutineUnintercepted:
/**
* Use this function to restart coroutine directly from inside of [suspendCoroutine],
* when the code is already in the context of this coroutine.
* It does not use [ContinuationInterceptor] and does not update context of the current thread.
*/
internal fun <R, T> (suspend (R) -> T).startCoroutineUnintercepted(receiver: R, completion: Continuation<T>) {
startDirect(completion) { actualCompletion ->
startCoroutineUninterceptedOrReturn(receiver, actualCompletion)
}
}
之前讲过startCoroutineUnintercepted其实就是function.invoke(),所以就调用block.invoke(select的completion是自己)，获得值后通过uCont.resume即可。
onAwait
这个和defered即job(Support)搞在一起:
private class SelectAwaitOnCompletion<T, R>(
job: JobSupport,
private val select: SelectInstance<R>,
private val block: suspend (T) -> R
) : JobNode<JobSupport>(job) {
override fun invoke(cause: Throwable?) {
if (select.trySelect(null))
job.selectAwaitCompletion(select, block)
}
override fun toString(): String = "SelectAwaitOnCompletion[$select]"
}
可以看到当任务成功后，select会被继续进行
broadcast
首先解决一个问题,一个sender多个receiver是怎么处理的。
val channel = Channel<Int>()
launch {
val value1 = channel.receive()
}
launch {
val value2 = channel.receive()
}
launch {
channel.send(1)
}
因为是1vs1消费。只有第一个会收到，因为它插在等待队列的第一个。用broadcast可以保证大家都收到。它维护一个subscribe的user list,所有消费者都能收到channel.send的element
operation
map
public fun <E, R> ReceiveChannel<E>.map(context: CoroutineContext = Dispatchers.Unconfined, transform: suspend (E) -> R): ReceiveChannel<R> =
GlobalScope.produce(context, onCompletion = consumes()) {
consumeEach {
send(transform(it))
}
}
可以实现跟RX一样的操作符，接受者收到后经过转换再进行发送返回最终新的receiveChannel
hot or cold
channel是hot的。
When the data is produced by the Observable itself, we call it a cold Observable. When the data is produced outside the Observable, we call it a hot Observable.
Provide abstraction for cold streams
... 这个todo,后续再说。
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