Golang技术在机器学习中的可扩展性设计

// 分发训练任务到工作节点的协调器
type Coordinator struct {
    tasks <-chan *Task
    done chan TaskResult
}

func (c *Coordinator) Run() {
    for {
        select {
        case task := <-c.tasks:
            go func(task *Task) {
                result := task.Run()
                c.done <- result
            }(task)
        case <-time.After(10 * time.Second):
            fmt.Println("No more tasks to coordinate")
            close(c.done)
            return
        }
    }
}

// 运行训练任务的工作节点
type Worker struct {
    tasks <-chan *Task
}

func (w *Worker) Run() {
    for task := range w.tasks {
        task.Run()
    }
}

// 用于在线学习和预测的服务器
type Server struct {
    model *Model
    port  string
}

func (s *Server) ServeForever() error {
    ln, err := net.Listen("tcp", s.port)
    if err != nil {
        return err
    }
    defer ln.Close()

    for {
        conn, err := ln.Accept()
        if err != nil {
            return err
        }
        go s.handleConnection(conn)
    }
}

func (s *Server) handleConnection(conn net.Conn) {
    defer conn.Close()

    data, err := ioutil.ReadAll(conn)
    if err != nil {
        fmt.Println(err)
        return
    }

    features := parseFeatures(data)
    prediction := s.model.Predict(features)

    fmt.Fprintf(conn, "%f", prediction)
}