Kotlin select使用方法介绍

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2023-06-23
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标签   Kotlin
目录
  • 一、select是什么
  • 二、select和Channel

一、select是什么

select——>用于选择更快的结果。

基于场景理解

比如客户端要查询一个商品的详情。两个服务：缓存服务，速度快但信息可能是旧的；网络服务，速度慢但信息一定是最新的。

如何实现上述逻辑：

 runBlocking {
    suspend fun getCacheInfo(productId: String): Product {
        delay(100L)
        return Product(productId, 8.9)
    }
    suspend fun getNetworkInfo(productId: String): Product? {
        delay(200L)
        return Product(productId, 8.8)
    }
    fun updateUI(product: Product) {
        println("${product.productId} : ${product.price}")
    }
    val startTime = System.currentTimeMillis()
    val productId = "001"
    val cacheInfo = getCacheInfo(productId)
    if (cacheInfo != null) {
        updateUI(cacheInfo)
        println("Time cost: ${System.currentTimeMillis() - startTime}")
    }
    val latestInfo = getNetworkInfo(productId)
    if (latestInfo != null) {
        updateUI(latestInfo)
        println("Time cost: ${System.currentTimeMillis() - startTime}")
    }
}
001 : 8.9
Time cost: 113
001 : 8.8
Time cost: 324

上述程序分为四步：第一步：查询缓存信息；第二步：缓存服务返回信息，更新 UI；第三步：查询网络服务；第四步：网络服务返回信息，更新 UI。

用户可以第一时间看到商品的信息，虽然它暂时会展示旧的信息，但由于我们同时查询了网络服务，旧缓存信息也马上会被替代成新的信息。但是可能存在一些问题：如果程序卡在了缓存服务，获取网络服务就会无法执行。是因为 getCacheInfo() 它是一个挂起函数，只有这个程序执行成功以后，才可以继续执行后面的任务。能否做到：两个挂起函数同时执行，谁返回的速度更快，就选择哪个结果。答案是使用select。

runBlocking {
        suspend fun getCacheInfo(productId: String): Product {
            delay(100L)
            return Product(productId, 8.9)
        }
        suspend fun getNetworkInfo(productId: String): Product {
            delay(200L)
            return Product(productId, 8.8)
        }
        fun updateUI(product: Product) {
            println("${product.productId} : ${product.price}")
        }
        val startTime = System.currentTimeMillis()
        val productId = "001"
        val product = select<Product?> {
            async {
                getCacheInfo(productId)
            }.onAwait {
                it
            }
            async {
                getNetworkInfo(productId)
            }.onAwait {
                it
            }
        }
        if (product != null) {
            updateUI(product)
            println("Time cost: ${System.currentTimeMillis() - startTime}")
        }
    }
001 : 8.9
Time cost: 134
 
Process finished with exit code 0

由于缓存的服务更快，所以，select 确实帮我们选择了更快的那个结果。我们的 select 可以在缓存服务出现问题的时候，灵活选择网络服务的结果。从而避免用户等待太长的时间，得到糟糕的体验。

在上述代码中，用户大概率是会展示旧的缓存信息。但实际场景下，我们是需要进一步更新最新信息的。

runBlocking {
        suspend fun getCacheInfo(productId: String): Product {
            delay(100L)
            return Product(productId, 8.9)
        }
        suspend fun getNetworkInfo(productId: String): Product {
            delay(200L)
            return Product(productId, 8.8)
        }
        fun updateUI(product: Product) {
            println("${product.productId} : ${product.price}")
        }
        val startTime = System.currentTimeMillis()
        val productId = "001"
        val cacheDeferred = async {
            getCacheInfo(productId)
        }
        val latestDeferred = async {
            getNetworkInfo(productId)
        }
        val product = select<Product?> {
 
            cacheDeferred.onAwait {
                it.copy(isCache = true)
            }
            latestDeferred.onAwait {
                it.copy(isCache = false)
            }
        }
        if (product != null) {
            updateUI(product)
            println("Time cost: ${System.currentTimeMillis() - startTime}")
        }
        if (product != null && product.isCache) {
            val latest = latestDeferred.await() ?: return@runBlocking
            updateUI(latest)
            println("Time cost: ${System.currentTimeMillis() - startTime}")
        }
    }
001 : 8.9
Time cost: 124
001 : 8.8
Time cost: 228
 
Process finished with exit code 0

如果是多个服务的缓存场景呢？

 runBlocking {
        val startTime = System.currentTimeMillis()
        val productId = "001"
        suspend fun getCacheInfo(productId: String): Product {
            delay(100L)
            return Product(productId, 8.9)
        }
        suspend fun getCacheInfo2(productId: String): Product {
            delay(50L)
            return Product(productId, 8.85)
        }
        suspend fun getNetworkInfo(productId: String): Product {
            delay(200L)
            return Product(productId, 8.8)
        }
        fun updateUI(product: Product) {
            println("${product.productId} : ${product.price}")
        }
        val cacheDeferred = async {
            getCacheInfo(productId)
        }
        val cacheDeferred2 = async {
            getCacheInfo2(productId)
        }
        val latestDeferred = async {
            getNetworkInfo(productId)
        }
        val product = select<Product?> {
            cacheDeferred.onAwait {
                it.copy(isCache = true)
            }
            cacheDeferred2.onAwait {
                it.copy(isCache = true)
            }
            latestDeferred.onAwait {
                it.copy(isCache = true)
            }
        }
        if (product != null) {
            updateUI(product)
            println("Time cost: ${System.currentTimeMillis() - startTime}")
        }
        if (product != null && product.isCache) {
            val latest = latestDeferred.await()
            updateUI(latest)
            println("Time cost: ${System.currentTimeMillis() - startTime}")
        }
    }
Log
 
001 : 8.85
Time cost: 79
001 : 8.8
Time cost: 229
 
Process finished with exit code 0

select 代码模式，可以提升程序的整体响应速度。

二、select和Channel

runBlocking {
        val startTime = System.currentTimeMillis()
        val channel1 = produce {
            send(1)
            delay(200L)
            send(2)
            delay(200L)
            send(3)
        }
        val channel2 = produce {
            delay(100L)
            send("a")
            delay(200L)
            send("b")
            delay(200L)
            send("c")
        }
        channel1.consumeEach {
            println(it)
        }
        channel2.consumeEach {
            println(it)
        }
        println("Time cost: ${System.currentTimeMillis() - startTime}")
    }
Log
 
1
2
3
a
b
c
Time cost: 853
 
Process finished with exit code 0

上述代码串行执行，可以使用select进行优化。

  runBlocking {
        val startTime = System.currentTimeMillis()
        val channel1 = produce {
            send(1)
            delay(200L)
            send(2)
            delay(200L)
            send(3)
        }
        val channel2 = produce {
            delay(100L)
            send("a")
            delay(200L)
            send("b")
            delay(200L)
            send("c")
        }
        suspend fun selectChannel(
            channel1: ReceiveChannel<Int>,
            channel2: ReceiveChannel<String>
        ): Any {
            return select<Any> {
                if (!channel1.isClosedForReceive) {
                    channel1.onReceive {
                        it.also {
                            println(it)
                        }
                    }
                }
                if (!channel2.isClosedForReceive) {
                    channel2.onReceive {
                        it.also {
                            println(it)
                        }
                    }
                }
            }
        }
        repeat(6) {
            selectChannel(channel1, channel2)
        }
        println("Time cost: ${System.currentTimeMillis() - startTime}")
    }
Log
1
a
2
b
3
c
Time cost: 574
 
Process finished with exit code 0

从代码执行结果可以发现程序的执行耗时有效减少。onReceive{} 是 Channel 在 select 当中的语法，当 Channel 当中有数据以后，它就会被回调，通过这个 Lambda，将结果传出去。执行了 6 次 select，目的是要把两个管道中的所有数据都消耗掉。

如果Channel1不生产数据了，程序会如何执行？

runBlocking {
        val startTime = System.currentTimeMillis()
        val channel1 = produce<String> {
            delay(5000L)
        }
        val channel2 = produce<String> {
            delay(100L)
            send("a")
            delay(200L)
            send("b")
            delay(200L)
            send("c")
        }
        suspend fun selectChannel(
            channel1: ReceiveChannel<String>,
            channel2: ReceiveChannel<String>
        ): String = select<String> {
            channel1.onReceive {
                it.also {
                    println(it)
                }
            }
            channel2.onReceive {
                it.also {
                    println(it)
                }
            }
        }
        repeat(3) {
            selectChannel(channel1, channel2)
        }
        println("Time cost: ${System.currentTimeMillis() - startTime}")
    }
Log
a
b
c
Time cost: 570
 
Process finished with exit code 0

如果不知道Channel的个数，如何避免ClosedReceiveChannelException?

使用：onReceiveCatching{}

runBlocking {
        val startTime = System.currentTimeMillis()
        val channel1 = produce<String> {
            delay(5000L)
        }
        val channel2 = produce<String> {
            delay(100L)
            send("a")
            delay(200L)
            send("b")
            delay(200L)
            send("c")
        }
        suspend fun selectChannel(
            channel1: ReceiveChannel<String>,
            channel2: ReceiveChannel<String>
        ): String = select<String> {
            channel1.onReceiveCatching {
                it.getOrNull() ?: "channel1 is closed!"
            }
            channel2.onReceiveCatching {
                it.getOrNull() ?: "channel2 is closed!"
            }
        }
        repeat(6) {
            val result = selectChannel(channel1, channel2)
            println(result)
        }
        println("Time cost: ${System.currentTimeMillis() - startTime}")
    }
Log
a
b
c
channel2 is closed!
channel2 is closed!
channel2 is closed!
Time cost: 584
 
Process finished with exit code 0

得到所有结果以后，程序不会立即退出，因为 channel1 一直在 delay()。

所以我们需要在6次repeat之后将channel关闭。

runBlocking {
        val startTime = System.currentTimeMillis()
        val channel1 = produce<String> {
            delay(15000L)
        }
        val channel2 = produce<String> {
            delay(100L)
            send("a")
            delay(200L)
            send("b")
            delay(200L)
            send("c")
        }
        suspend fun selectChannel(
            channel1: ReceiveChannel<String>,
            channel2: ReceiveChannel<String>
        ): String = select<String> {
            channel1.onReceiveCatching {
                it.getOrNull() ?: "channel1 is closed!"
            }
            channel2.onReceiveCatching {
                it.getOrNull() ?: "channel2 is closed!"
            }
        }
        repeat(6) {
            val result = selectChannel(channel1, channel2)
            println(result)
        }
        channel1.cancel()
        channel2.cancel()
        println("Time cost: ${System.currentTimeMillis() - startTime}")
    }
Log
a
b
c
channel2 is closed!
channel2 is closed!
channel2 is closed!
Time cost: 612
 
Process finished with exit code 0

Deferred、Channel 的 API:

public interface Deferred : CoroutineContext.Element {
    public suspend fun join()
    public suspend fun await(): T
    public val onJoin: SelectClause0
    public val onAwait: SelectClause1<T>
}
public interface SendChannel<in E> 
    public suspend fun send(element: E)
    public val onSend: SelectClause2<E, SendChannel<E>>
}
public interface ReceiveChannel<out E> {
    public suspend fun receive(): E
    public suspend fun receiveCatching(): ChannelResult<E>
    public val onReceive: SelectClause1<E>
    public val onReceiveCatching: SelectClause1<ChannelResult<E>>
}

当 select 与 Deferred 结合使用的时候，当并行的 Deferred 比较多的时候，你往往需要在得到一个最快的结果以后，去取消其他的 Deferred。

通过 async 并发执行协程，也可以借助 select 得到最快的结果。

 runBlocking {
        suspend fun <T> fastest(vararg deferreds: Deferred<T>): T = select {
            fun cancelAll() = deferreds.forEach {
                it.cancel()
            }
            for (deferred in deferreds) {
                deferred.onAwait {
                    cancelAll()
                    it
                }
            }
        }
        val deferred1 = async {
            delay(100L)
            println("done1")
            "result1"
        }
        val deferred2 = async {
            delay(200L)
            println("done2")
            "result2"
        }
        val deferred3 = async {
            delay(300L)
            println("done3")
            "result3"
        }
        val deferred4 = async {
            delay(400L)
            println("done4")
            "result4"
        }
        val deferred5 = async {
            delay(5000L)
            println("done5")
            "result5"
        }
        val fastest = fastest(deferred1, deferred2, deferred3, deferred4, deferred5)
        println(fastest)
    }
Log
 
done1
result1
 
Process finished with exit code 0
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