douhaodang0403
2016-03-29 12:04
浏览 87
已采纳

前往:time.sleep和内存使用情况

When running the code below, the program starts at around 1.5M and then gradually grows until 6.4M. I'm wondering why. Removing time.sleep fixes the issue.

Is there a way to use the for-select pattern with a default and sleep some time in the default without any mem change?

Calling runtime.GC() after the sleep does fix the issue. Can we achieve the same thing without having to call the GC ?

package main

import (
    "time"
)

func main() {
    c := make(chan struct{})
    for {
        select {
        case <-c:
            //some work
        default:
            //some work
            time.Sleep(time.Millisecond * 1)
        }
    }
}

Same with :

package main

import (
    "time"
)

func main() {
    c := make(chan struct{})
    for {
        select {
        case <-c:
        case <-time.After(time.Millisecond * 10):
        }
    }
}

After some time researching, I achieved it with the following code. Still wonder why time.sleep increases mem usage?

package main

import (
    "time"
)

func main() {
    c := make(chan bool)
    timer := time.NewTimer(0)
    for {
        select {
        case <-c:
        default:
            timer.Reset(time.Millisecond * 1)
            <-timer.C
        }
    }
}
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2条回答 默认 最新

  • dongyi1524 2016-03-29 15:51
    已采纳

    After some time researching, I achieved it with the following code.

    package main
    
    import (
        "time"
    )
    
    func main() {
        c := make(chan bool)
        timer := time.NewTimer(0)
        for {
            select {
            case <-c:
            default:
                timer.Reset(time.Millisecond * 1)
                <-timer.C
            }
        }
    }
    
    已采纳该答案
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  • downloadbooks_2014 2016-03-29 12:17

    You can implement a timeout using a select and receive from <-time.After():

    select {
      case res := <-c:
        fmt.Println("do some work")
      case <-time.After(time.Second * 1):
        fmt.Println("timeout")
    }
    

    In case you want to understand how your program is utilizing memory you can do profiling. Here is a nice article about this topic.

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