Golang编程并发工具库MapReduce使用实践

环境

go version go1.16.4 windows/amd64
Intel(R) Core(TM) i7-7820HK CPU @ 2.90GHz 4核心8线程

项目需求

处理数个约5MB的小文件

计算源文件MD5和目标文件MD5进行对比，如不相同则报错并终止程序执行

mapReduce使用说明

go get -u github.com/tal-tech/go-zero

需求实现

判断上下文是否中止 → 读取数据 → 写入数据 → 校验MD5

 func fnBuilder(name string) func() error {
   return func() error {
        // 判断上下文是否终止
        select {
        case <-ctx.Done():
          return ctx.Err()
        default:
        }
        // 读取源数据
        data, _err := os.ReadFile(filepath.Join(sourcePath, fileName))
        // 计算源数据MD5
        sourceMD5 := hash.Md5(data)
        // 获取名称
        fields := strings.Split(d.Name(), "-")
        // 目标文件路径
        distFilePath := filepath.Join(distPath, fileName)
        // 拷贝数据
        os.WriteFile(distFilePath, data, 0600)
        // 校验数据
        distData, _err := os.ReadFile(distFilePath)
        distMD5 := hash.Md5(distData)
        if !bytes.EqualFold(sourceMD5, distMD5) {
          return errors.New("md5校验失败")
        }
        return nil
      }
 }

业务逻辑

创建任务队列

type SourceMap = map[string]fs.DirEntry
func CopyFileToDist(ctx context.Context, source SourceMap) (err error) {
  // 创建工作队列
  work := make([]func() error, 0, len(source))
  for _name := range source {
    // 创建任务
    work = append(work, fnBuilder(_name))
  }
  switch concurrency {
  default:
    // mapReduce
  case 1:
    // sync.waitGroup
  case 2:
    // 串行
  }
}

执行方式1：MapReduce

 func() {
    if err = mr.Finish(work...); err != nil {
      return err
    }
 }

执行方式2：sync.WaitGroup

func() {
    var wg sync.WaitGroup
    wg.Add(len(work))
    for k := range work {
      go func(index int) {
        defer wg.Done()
        if err = work[index](); err != nil {
          log.Errorln(err)
          return
        }
      }(k)
    }
    wg.Wait()
}

执行方式3：串行

func() {
    for _, fn := range work {
      if err = fn(); err != nil {
        return err
      }
    }
}

运行结果

MapReduce

耗时 109220900 ns

{"file":"D:/go/src/filenamesSorter/main.go:44","func":"main.init.0","level":"info","msg":"并发处理（0-mapReduce 1-Sync.WaitGroup 2-不并发） 0","time":"2021-06-02T13:32:05+08:00"}
{"file":"D:/go/src/filenamesSorter/main.go:69","func":"main.main","level":"info","msg":"文件分类完毕","time":"2021-06-02T13:32:05+08:00","文件数":17,"耗时(ns)":109220900}

sync.WaitGroup

耗时 109798000 ns

{"file":"D:/go/src/filenamesSorter/main.go:44","func":"main.init.0","level":"info","msg":"并发处理（0-mapReduce 1-Sync.WaitGroup 2-不并发） 1","time":"2021-06-02T13:31:28+08:00"}
{"file":"D:/go/src/filenamesSorter/main.go:69","func":"main.main","level":"info","msg":"文件分类完毕","time":"2021-06-02T13:31:28+08:00","文件数":17,"耗时(ns)":109798000}

串行

耗时 359307700 ns

{"file":"D:/go/src/filenamesSorter/main.go:44","func":"main.init.0","level":"info","msg":"并发处理（0-mapReduce 1-Sync.WaitGroup 2-不并发） 2","time":"2021-06-02T13:33:02+08:00"}
{"file":"D:/go/src/filenamesSorter/main.go:69","func":"main.main","level":"info","msg":"文件分类完毕","time":"2021-06-02T13:33:02+08:00","文件数":17,"耗时(ns)":359307700}

结论

在不严格的情况下，执行效率方面可以认为 mapReduce ≈ sync.WaitGroup
易用性（包括并发和错误处理），mapReduce 完胜 sync.WaitGroup
mapReduce好用

引申阅读

通过MapReduce降低服务响应时间

Golang编程并发工具库MapReduce使用实践

目录

环境

项目需求

mapReduce使用说明

需求实现

业务逻辑

创建任务队列

运行结果

结论

引申阅读