Golang实现词频统计

本例使用golang实现词频统计。步骤：

（1）从文件中读取一篇文章。

（2）统计词频，按单词出现的频率从大到小进行排序。

（3）写入到文件中。

注：任何非英文字母的符号均认为是单词分隔符（即等同于空格）。

效率：使用本程序统计一篇150W单词的文章，大约需要70ms.

1.核心代码：

package wordtest

import (
	"bytes"
	"fmt"
	"io/ioutil"
	"os"
	"runtime"
	"sort"
	"strings"
	"time"
)

//简单的词频统计任务
func CountTestBase(inputFilePath string,outputFilePath string) {
	//时间开始点
	start := time.Now().UnixNano() / 1e6

	//读取文件
	fileData,err := ioutil.ReadFile(inputFilePath)
	CheckError(err,"read file")
	var fileText string = string(fileData)

	//根据CPU核数新开协程
	newRountineCount := runtime.NumCPU()*2 - 1
	runtime.GOMAXPROCS(newRountineCount + 1)
	//切分文件
	parts := splitFileText(fileText,newRountineCount)

	var ch chan map[string]int = make(chan map[string]int,newRountineCount)
	for i := 0; i < newRountineCount; i++ {
		go countTest(parts[i],ch)
	}

	//主线程接收数据
	var totalWordsMap map[string]int = make(map[string]int,0)
	completeCount := 0
	for {
		receiveData := <-ch
		for k,v := range receiveData {
			totalWordsMap[strings.ToLower(k)] += v
		}
		completeCount++

		if newRountineCount == completeCount {
			break
		}
	}

	//添加进slice，并排序
	list := make(WordCountBeanList,0)
	for k,v := range totalWordsMap {
		list = append(list,NewWordCountBean(k,v))
	}
	sort.Sort(list)
	//时间结束点
	end := time.Now().UnixNano() / 1e6
	fmt.Printf("time consume:%dmsn",end-start)

	//输出
	wordsCount := list.totalCount()
	var data bytes.Buffer
	data.WriteString(fmt.Sprintf("程序执行：%dmsn",end-start))
	data.WriteString(fmt.Sprintf("文章总单词数：%dnn",wordsCount))
	for _,v := range list {
		var percent float64 = 100.0 * float64(v.count) / float64(wordsCount)
		_,err := data.WriteString(fmt.Sprintf("%s: %d,%3.2f%%n",v.word,v.count,percent))
		CheckError(err,"bytes.Buffer,WriteString")
	}

	err = ioutil.WriteFile(outputFilePath,[]byte(data.String()),os.ModePerm)
	CheckError(err,"ioutil.WriteFile")
}

func countTest(text string,ch chan map[string]int) {
	var wordMap map[string]int = make(map[string]int,0)

	//按字母读取，除26个字母（大小写）之外的所有字符均认为是分隔符
	startIndex := 0
	letterStart := false
	for i,v := range text {
		if (v >= 65 && v <= 90) || (v >= 97 && v <= 122) {
			if !letterStart {
				letterStart = true
				startIndex = i
			}
		} else {
			if letterStart {
				wordMap[text[startIndex:i]]++
				letterStart = false
			}
		}
	}

	//最后一个单词
	if letterStart {
		wordMap[text[startIndex:]]++
	}
	ch <- wordMap
}

//将全文分成n段
func splitFileText(fileText string,n int) []string {
	length := len(fileText)
	parts := make([]string,n)

	lastPostion := 0
	for i := 0; i < n-1; i++ {
		position := length / n * (i + 1)
		for string(fileText[position]) != " " {
			position++
		}

		parts[i] = fileText[lastPostion:position]
		lastPostion = position
	}

	//最后一段
	parts[n-1] = fileText[lastPostion:]
	return parts
}

func CheckError(err error,msg string) {
	if err != nil {
		panic(msg + "," + err.Error())
	}
}

package wordtest

type WordCountBean struct {
	word  string
	count int
}

func NewWordCountBean(word string,count int) *WordCountBean {
	return &WordCountBean{word,count}
}

type WordCountBeanList []*WordCountBean

func (list WordCountBeanList) Len() int {
	return len(list)
}

func (list WordCountBeanList) Less(i,j int) bool {
	if list[i].count > list[j].count {
		return true
	} else if list[i].count < list[j].count {
		return false
	} else {
		return list[i].word < list[j].word
	}
}

func (list WordCountBeanList) Swap(i,j int) {
	var temp *WordCountBean = list[i]
	list[i] = list[j]
	list[j] = temp
}

func (list WordCountBeanList) totalCount() int {
	totalCount := 0
	for _,v := range list {
		totalCount += v.count
	}

	return totalCount
}

package main

import (
	"WordsTest/wordtest"
)

func main() {
	inputFilePath := "files/article.txt"
	outputFilePath := "files/result.txt"

	wordtest.CountTestBase(inputFilePath,outputFilePath)
}

（编辑：李大同）

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