Go学习之Channel的一些模式

除了在goroutine之间安全的传递数据以外，在看了《Concurrency in Go》以后，感慨channel还有那么多模式可供使用，在我的的学习中总结了如下几种经常使用的模式

pipeline

概念

咱们以爬虫为例，通常爬虫分为以下步骤：

抓取页面 -> 解析页面 -> 整合数据分析 -> 分析结果入库

若是你把上面全部的步骤都放在一个函数里面处理，那会是多难看，多难以维护，从解耦角度考虑，咱们能够起四个进程，分别承担不一样的角色，例如，进程1负责抓取页面， 进程2负责解析页面，等等，各个进程拿到一个数据后，交给下一个进程来处理，这就是pipeline的基本思想，每一个角色只负责关心本身的东西

示例

给定一个数n，执行 (n2 + 1) 2的操做

func pipeline() {
    generator := func(done chan interface{}, intergers ...int) <-chan int {
        inStream := make(chan int)
        go func() {
            defer close(inStream)
            for _, i := range intergers {
                select {
                case <-done:
                    return
                case inStream <- i:
                }
            }
        }()
        return inStream
    }

    add := func(done <-chan interface{}, inStream <-chan int, increment int) <-chan int {
        addInStream := make(chan int)
        go func() {
            defer close(addInStream)
            for i := range inStream {
                select {
                case <-done:
                    return
                case addInStream <- i + increment:
                }
            }
        }()
        return addInStream
    }

    multiply := func(done <-chan interface{}, inStream <-chan int, increment int) <-chan int {
        multiplyInStream := make(chan int)
        go func() {
            defer close(multiplyInStream)
            for i := range inStream {
                select {
                case <-done:
                    return
                case multiplyInStream <- i * increment:
                }
            }
        }()
        return multiplyInStream
    }

    done := make(chan interface{})
    defer close(done)
    inStream := generator(done, []int{1, 2, 3, 4, 5, 6, 7}...)
    pipeline := multiply(done, add(done, multiply(done, inStream, 2), 1), 2)

    for v := range pipeline {
        fmt.Println(v)
    }
}

扇入扇出

在pipeline模型中，是一种高效的流式处理，可是假如pipeline中有a,b,c三个环节，b环节处理的特别慢，这时候就会影响到c环节的处理，若是增长b环节进程处理的数量，也就能够减弱b环节的慢处理对整个pipeline的影响，那么a->多个b的过程就是 扇入， 多个b环节输出数据到c环节，就是扇出

示例

func FanInFanOut() {
    producer := func(intergers ...int) <-chan interface{} {
        inStream := make(chan interface{})
        go func() {
            defer close(inStream)
            for _, v := range intergers {
                time.Sleep(5 * time.Second)
                inStream <- v
            }
        }()
        return inStream
    }

    fanIn := func(channels ...<-chan interface{},
    ) <-chan interface{} {
        var wg sync.WaitGroup
        multiplexStream := make(chan interface{})

        multiplex := func(c <-chan interface{}) {
            defer wg.Done()
            for i := range c {
                multiplexStream <- i
            }
        }

        wg.Add(len(channels))
        for _, c := range channels {
            go multiplex(c)
        }
        go func() {
            wg.Wait()
            close(multiplexStream)
        }()
        return multiplexStream
    }

    consumer := func(inStream <-chan interface{}) {
        for v := range inStream {
            fmt.Println(v)
        }
    }

    nums := runtime.NumCPU()
    producerStreams := make([]<-chan interface{}, nums)
    for i := 0; i < nums; i++ {
        producerStreams[i] = producer(i)
    }

    consumer(fanIn(producerStreams...))
}

tee- channel

概念

假如你从channel中拿到了一条sql语句，这时候，你想对这条sql记录，分析并执行，那你就须要将这条sql分别转发给这三个任务对应的channel，tee-channel 就是作这个事情的

示例

func teeChannel() {
    producer := func(intergers ...int) <-chan interface{} {
        inStream := make(chan interface{})
        go func() {
            defer close(inStream)
            for _, v := range intergers {
                inStream <- v
            }
        }()
        return inStream
    }
    tee := func(in <-chan interface{}) (_, _ <-chan interface{}) {
        out1 := make(chan interface{})
        out2 := make(chan interface{})
        go func() {
            defer close(out1)
            defer close(out2)

            for val := range in {
                out1, out2 := out1, out2
                for i := 0; i < 2; i++ {
                    select {
                    case out1 <- val:
                        out1 = nil
                    case out2 <- val:
                        out2 = nil
                    }
                }
            }
        }()
        return out1, out2
    }

    out1, out2 := tee(producer(1, 2, 3, 4, 5))
    for val1 := range out1 {
        fmt.Printf("out1: %v, out2: %v", val1, <-out2)
    }
}

桥接channel

概念

不管是前面提到的pipeline仍是扇入扇出，每一个goroutine都是对一个channel进行消费，可是实际场景中，可能会有多个channel来供给咱们消费，而做为消费者，咱们不关心这些值是来自于哪一个channel，这种状况下，处理一个充满channel的channel可能会不少。若是咱们定义一个功能，能够将充满channel的channel拆解为一个简单的channel，这将使消费者更专一于手头的工做，这就是桥接channel的思想

示例

func bridge() {
    gen := func() <-chan <-chan interface{} {
        in := make(chan (<-chan interface{}))
        go func() {
            defer close(in)
            for i := 0; i < 10; i++ {
                stream := make(chan interface{}, 1)
                stream <- i
                close(stream)
                in <- stream
            }
        }()
        return in
    }

    bridge := func(in <-chan (<-chan interface{})) <-chan interface{} {
        valStream := make(chan interface{})
        go func() {
            defer close(valStream)
            for {
                stream := make(<-chan interface{})
                select {
                case maybeStream, ok := <-in:
                    if ok == false {
                        return
                    }
                    stream = maybeStream
                }
                for val := range stream {
                    valStream <- val
                }
            }
        }()
        return valStream
    }

    for val := range bridge(gen()) {
        fmt.Println(val)
    }
}