《架构师训练营》第七周命题作业

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发布于: 2020 年 07 月 18 日
1、性能压测的时候，随着并发压力的增加，系统响应时间和吞吐量如何变化，为什么？压测初期，系统资源在可以接受的范围内，此时系统响应时间会相对比较稳定不会随并发压力的增加而增加，吞吐量会随并发数的增加而增加。
持续增加并发压力，到达系统资源使用的临界值，系统响应时间会逐渐变长，吞吐量逐渐边少，直至系统崩溃。
2、压测工具2.1 代码实现使用 go 语言开发，程序设计思路如下：
使用 goruntine 模拟并发请求，用一个 goruntine 等待其他并发的处理结果，通过 channel 将请求结果发送到负责处理结果的 goruntine 统计、处理。
request request 用来发送请求，只关心请求有没有成功。
func request(url string) error {
	response, err := http.Get(url)
	defer func() {
		if response != nil && response.Body != nil {
			_ = response.Body.Close()
		}
	}()
	if err != nil {
		return err
	}
	if response.StatusCode != http.StatusOK {
		return errors.New(fmt.Sprintf("Error response code: %d", response.StatusCode))
	}
	return nil
}
runner runner 用来顺序执行指定个数的请求，并将结果通过 channel 发送出去
type Response struct {
	label   string
	elapsed int64
	err     error
}
func runner(count int, url string, resChan chan Response, wg *sync.WaitGroup, label string) {
	for i := 0; i < count; i++ {
		start := time.Now()
		err := request(url)
		elapsed := time.Since(start)
		resChan <- Response{
			elapsed: elapsed.Milliseconds(),
			err:     err,
			label:   fmt.Sprintf("%s-%d", label, i),
		}
	}
	wg.Done()
}
receiver receiver 用来接收、统计请求结果
func receiver(recvChan chan Response) {
	var (
		resArr                                []Response
		totalCount, successCount, failedCount int
		totalTime, _95TotalTime               int64
	)
	for {
		totalCount++
		res, ok := <-recvChan
		if !ok {
			break
		}
		if res.err != nil {
			failedCount++
		} else {
			successCount++
		}
		totalTime += res.elapsed
		log.Printf("[%s\t%d\t]\tResponse takes %dms", res.label, totalCount, res.elapsed)
		resArr = append(resArr, res)
	}
	log.Printf("Toal success count: %d, failed count: %d", successCount, failedCount)
	log.Printf("Average time: %dms", totalTime/int64(totalCount))
	sort.Slice(resArr, func(i, j int) bool {
		return resArr[i].elapsed < resArr[j].elapsed
	})
	_95Count := totalCount * 95 / 100
	for i := 0; i < _95Count; i++ {
		_95TotalTime += resArr[i].elapsed
	}
	log.Printf("95%% average time: %dms", _95TotalTime/int64(_95Count))
}
LoadRunLoadRun 用来启动测试
func LoadRun(currency, count int, url string) {
	wg := sync.WaitGroup{}
	wg.Add(currency)
	resChan := make(chan Response, 10)
	for i := 0; i < currency; i++ {
		label := fmt.Sprintf("goroutine-%d", i)
		go runner(count, url, resChan, &wg, label)
	}
	go receiver(resChan)
	wg.Wait()
	close(resChan)
	time.Sleep(time.Second)
}
2.2 测试结果
// https://www.baidu.com
2020/07/18 14:30:34 Toal success count: 1000, failed count: 0
2020/07/18 14:30:34 Average time: 344ms
2020/07/18 14:30:34 95% average time: 333ms
// https://www.163.com
2020/07/18 14:45:34 Toal success count: 0, failed count: 1000
2020/07/18 14:45:34 Average time: 374ms
2020/07/18 14:45:34 95% average time: 361ms
// https://www.qq.com
2020/07/18 14:47:12 Toal success count: 1000, failed count: 0
2020/07/18 14:47:12 Average time: 375ms
2020/07/18 14:47:12 95% average time: 334ms
// https://www.taobao.com
2020/07/18 14:49:08 Toal success count: 1000, failed count: 0
2020/07/18 14:49:08 Average time: 838ms
2020/07/18 14:49:08 95% average time: 793ms
﻿
发布于: 2020 年 07 月 18 日阅读数: 29
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