Goroutines 共享切片 :: 尝试理解数据竞争

Fre*_*red 3 arrays channel go goroutine

我尝试用 Go 编写一个程序,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 goroutine 并行执行此搜索;)

因为文件很大,所以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,依此类推。

我要感谢这个网站的成员对于切片和 goroutine 的非常有用的解释。

我已经进行了建议的更改,以使用 goroutine 处理的切片的副本。但 -race 执行仍然在函数级别检测到一个数据竞争copy()

非常感谢您的评论!

    ==================
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)
}
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Jim*_*imB 6

goroutine 仅处理切片头的副本,底层数组是相同的。要制作切片的副本,您需要使用copy(或append到不同的切片)。

buf_Seq = append(buf_Seq, line)
bufCopy := make([]string, len(buf_Seq))
copy(bufCopy, buf_Seq)
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然后,您可以安全地传递bufCopy给 goroutine,或者直接在闭包中使用它。