我尝试用 Go 编写一个程序，以在非常大的 DNA 序列文件中查找一些基因。我已经编写了一个 Perl 程序来执行此操作，但我想利用 goroutines 并行执行此搜索；)

因为文件很大，我的想法是一次读取 100 个序列，然后将分析发送到 goroutine，然后再次读取 100 个序列等。

我要感谢本网站的成员，感谢他们对 slice 和 goroutines 的真正有用的解释。

我已经进行了建议的更改，以使用由 goroutines 处理的 slice 的副本。但是 -race 执行仍然在 copy() 函数级别检测到一个数据竞争:

非常感谢您的意见!

    ==================
WARNING: DATA RACE
Read by goroutine 6:
  runtime.slicecopy()
      /usr/lib/go-1.6/src/runtime/slice.go:113 +0x0
  main.main.func1()
      test_chan006.go:71 +0xd8

Previous write by main goroutine:
  main.main()
      test_chan006.go:63 +0x3b7

Goroutine 6 (running) created at:
  main.main()
      test_chan006.go:73 +0x4c9
==================
[>5HSAA098909 BA098909 ...]
Found 1 data race(s)
exit status 66

    line 71 is : copy(bufCopy, buf_Seq)
    line 63 is : buf_Seq = append(buf_Seq, line)
    line 73 is :}(genes, buf_Seq)




    package main

import (
    "bufio"
    "fmt"
    "os"
    "github.com/mathpl/golang-pkg-pcre/src/pkg/pcre"
    "sync"
)

// function read a list of genes and return a slice of gene names
func read_genes(filename string) []string {
    var genes []string // slice of genes names
    // Open the file.
    f, _ := os.Open(filename)
    // Create a new Scanner for the file.
    scanner := bufio.NewScanner(f)
    // Loop over all lines in the file and print them.
    for scanner.Scan() {
          line := scanner.Text()
        genes = append(genes, line)
    }
    return genes
}

// function find the sequences with a gene matching gene[] slice
func search_gene2( genes []string, seqs []string) ([]string) {
  var res []string

  for r := 0 ; r <= len(seqs) - 1; r++ {
    for i := 0 ; i <= len(genes) - 1; i++ {

      match := pcre.MustCompile(genes[i], 0).MatcherString(seqs[r], 0)

      if (match.Matches() == true) {
          res = append( res, seqs[r])           // is the gene matches the gene name is append to res
          break
      }
    }
  }

  return res
}
//###########################################

func main() {
    var slice []string
    var buf_Seq []string
    read_buff := 100    // the number of sequences analysed by one goroutine

    var wg sync.WaitGroup
    queue := make(chan []string, 100)

    filename := "fasta/sequences.tsv"
    f, _ := os.Open(filename)
    scanner := bufio.NewScanner(f)
    n := 0
    genes := read_genes("lists/genes.csv")

    for scanner.Scan() {
            line := scanner.Text()
            n += 1
            buf_Seq = append(buf_Seq, line) // store the sequences into buf_Seq
            if n == read_buff {   // when the read buffer contains 100 sequences one goroutine analyses them

          wg.Add(1)

          go func(genes, buf_Seq []string) {
            defer wg.Done()
                        bufCopy := make([]string, len(buf_Seq))
                        copy(bufCopy, buf_Seq)
            queue <- search_gene2( genes, bufCopy)
            }(genes, buf_Seq)
                        buf_Seq = buf_Seq[:0]   // reset buf_Seq
              n = 0 // reset the sequences counter

        }
    }
    go func() {
            wg.Wait()
            close(queue)
        }()

        for t := range queue {
            slice = append(slice, t...)
        }

        fmt.Println(slice)
}

最佳答案

goroutines 只在 slice headers 的副本上工作，底层数组是相同的。要制作 slice 的副本，您需要使用 copy(或 append 到不同的 slice )。

buf_Seq = append(buf_Seq, line)
bufCopy := make([]string, len(buf_Seq))
copy(bufCopy, buf_Seq)

然后您可以安全地将 bufCopy 传递给 goroutine，或者直接在闭包中使用它。

关于arrays - Goroutines 共享 slice : : trying to understand a data race，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/38923237/