前言
MapReduce作为hadoop的编程框架,是工程师最常接触的部分,也是除去了网络环境和集群配 置之外对整个Job执行效率影响很大的部分,所以很有必要深入了解整个过程。元旦放假的第一天,在家没事干,用golang实现了一下mapreduce的单进程版本,github地址。处理对大文件统计最高频的10个单词,因为功能比较简单,所以设计没有解耦合。
本文先对mapreduce大体概念进行介绍,然后结合代码介绍一下,如果接下来几天有空,我会实现一下分布式高可用的mapreduce版本。下面话不多说了,来一起看看详细的介绍吧。
1. Mapreduce大体架构
上图是论文中mapreduce的大体架构。总的来说Mapreduce的思想就是分治思想:对数据进行分片,然后用mapper进行处理,以key-value形式输出中间文件;然后用reducer进行对mapper输出的中间文件进行合并:将key一致的合到一块,并输出结果文件;如果有需要,采用Combiner进行最后的合并。
归纳来说主要分为5部分:用户程序、Master、Mapper、Reducer、Combiner(上图未给出)。
总的来说,架构不复杂。组件间通信用啥都可以,比如RPC、HTTP或者私有协议等。
2. 实现代码介绍
该版本代码实现了单机单进程版本,Mapper、Reducer和Combiner的实现用协程goroutine实现,通信采用channel。代码写的比较随意,没有解耦合。
为了方便起见,Combiner对最高频的10个单词进行堆排序处理,按规范来说应该放在用户程序处理。
文件目录如下,其中bin文件夹下的big_input_file.txt为输入文件,可以调用generate下的main文件生成,caller文件为入口的用户程序,master目录下分别存放master、mapper、reducer、combiner代码:
. ├── README.md ├── bin │ └── file-store │ └── big_input_file.txt └── src ├── caller │ └── main.go ├── generate │ └── main.go └── master ├── combiner.go ├── mapper.go ├── master.go └── reducer.go 6 directories, 8 files
2.1 caller
用户程序,读入文件并按固定行数进行划分;然后调用master.Handle进行处理。
package main import ( "os" "path" "path/filepath" "bufio" "strconv" "master" "github.com/vinllen/go-logger/logger" ) const ( LIMIT int = 10000 // the limit line of every file ) func main() { curDir, err := filepath.Abs(filepath.Dir(os.Args[0])) if err != nil { logger.Error("Read path error: ", err.Error()) return } fileDir := path.Join(curDir, "file-store") _ = os.Mkdir(fileDir, os.ModePerm) // 1. read file filename := "big_input_file.txt" inputFile, err := os.Open(path.Join(fileDir, filename)) if err != nil { logger.Error("Read inputFile error: ", err.Error()) return } defer inputFile.Close() // 2. split inputFile into several pieces that every piece hold 100,000 lines filePieceArr := []string{} scanner := bufio.NewScanner(inputFile) piece := 1 Outter: for { outputFilename := "input_piece_" + strconv.Itoa(piece) outputFilePos := path.Join(fileDir, outputFilename) filePieceArr = append(filePieceArr, outputFilePos) outputFile, err := os.Create(outputFilePos) if err != nil { logger.Error("Split inputFile error: ", err.Error()) continue } defer outputFile.Close() for cnt := 0; cnt < LIMIT; cnt++ { if !scanner.Scan() { break Outter } _, err := outputFile.WriteString(scanner.Text() + "\n") if err != nil { logger.Error("Split inputFile writting error: ", err.Error()) return } } piece++ } // 3. pass to master res := master.Handle(filePieceArr, fileDir) logger.Warn(res) }
2.2 master
Master程序,依次生成Combiner、Reducer、Mapper,处理消息中转,输出最后结果。
package master import ( "github.com/vinllen/go-logger/logger" ) var ( MapChanIn chan MapInput // channel produced by master while consumed by mapper MapChanOut chan string // channel produced by mapper while consumed by master ReduceChanIn chan string // channel produced by master while consumed by reducer ReduceChanOut chan string // channel produced by reducer while consumed by master CombineChanIn chan string // channel produced by master while consumed by combiner CombineChanOut chan []Item // channel produced by combiner while consumed by master ) func Handle(inputArr []string, fileDir string) []Item { logger.Info("handle called") const( mapperNumber int = 5 reducerNumber int = 2 ) MapChanIn = make(chan MapInput) MapChanOut = make(chan string) ReduceChanIn = make(chan string) ReduceChanOut = make(chan string) CombineChanIn = make(chan string) CombineChanOut = make(chan []Item) reduceJobNum := len(inputArr) combineJobNum := reducerNumber // start combiner go combiner() // start reducer for i := 1; i <= reducerNumber; i++ { go reducer(i, fileDir) } // start mapper for i := 1; i <= mapperNumber; i++ { go mapper(i, fileDir) } go func() { for i, v := range(inputArr) { MapChanIn <- MapInput{ Filename: v, Nr: i + 1, } // pass job to mapper } close(MapChanIn) // close map input channel when no more job }() var res []Item outter: for { select { case v := <- MapChanOut: go func() { ReduceChanIn <- v reduceJobNum-- if reduceJobNum <= 0 { close(ReduceChanIn) } }() case v := <- ReduceChanOut: go func() { CombineChanIn <- v combineJobNum-- if combineJobNum <= 0 { close(CombineChanIn) } }() case v := <- CombineChanOut: res = v break outter } } close(MapChanOut) close(ReduceChanOut) close(CombineChanOut) return res }
2.3 mapper
Mapper程序,读入并按key-value格式生成中间文件,告知Master。
package master import ( "fmt" "path" "os" "bufio" "strconv" "github.com/vinllen/go-logger/logger" ) type MapInput struct { Filename string Nr int } func mapper(nr int, fileDir string) { for { val, ok := <- MapChanIn // val: filename if !ok { // channel close break } inputFilename := val.Filename nr := val.Nr file, err := os.Open(inputFilename) if err != nil { errMsg := fmt.Sprintf("Read file(%s) error in mapper(%d)", inputFilename, nr) logger.Error(errMsg) MapChanOut <- "" continue } mp := make(map[string]int) scanner := bufio.NewScanner(file) scanner.Split(bufio.ScanWords) for scanner.Scan() { str := scanner.Text() //logger.Info(str) mp[str]++ } outputFilename := path.Join(fileDir, "mapper-output-" + strconv.Itoa(nr)) outputFileHandler, err := os.Create(outputFilename) if err != nil { errMsg := fmt.Sprintf("Write file(%s) error in mapper(%d)", outputFilename, nr) logger.Error(errMsg) } else { for k, v := range mp { str := fmt.Sprintf("%s %d\n", k, v) outputFileHandler.WriteString(str) } outputFileHandler.Close() } MapChanOut <- outputFilename } }
2.4 reducer
Reducer程序,读入Master传递过来的中间文件并归并。
package master import ( "fmt" "bufio" "os" "strconv" "path" "strings" "github.com/vinllen/go-logger/logger" ) func reducer(nr int, fileDir string) { mp := make(map[string]int) // store the frequence of words // read file and do reduce for { val, ok := <- ReduceChanIn if !ok { break } logger.Debug("reducer called: ", nr) file, err := os.Open(val) if err != nil { errMsg := fmt.Sprintf("Read file(%s) error in reducer", val) logger.Error(errMsg) continue } scanner := bufio.NewScanner(file) for scanner.Scan() { str := scanner.Text() arr := strings.Split(str, " ") if len(arr) != 2 { errMsg := fmt.Sprintf("Read file(%s) error that len of line(%s) != 2(%d) in reducer", val, str, len(arr)) logger.Warn(errMsg) continue } v, err := strconv.Atoi(arr[1]) if err != nil { errMsg := fmt.Sprintf("Read file(%s) error that line(%s) parse error in reduer", val, str) logger.Warn(errMsg) continue } mp[arr[0]] += v } if err := scanner.Err(); err != nil { logger.Error("reducer: reading standard input:", err) } file.Close() } outputFilename := path.Join(fileDir, "reduce-output-" + strconv.Itoa(nr)) outputFileHandler, err := os.Create(outputFilename) if err != nil { errMsg := fmt.Sprintf("Write file(%s) error in reducer(%d)", outputFilename, nr) logger.Error(errMsg) } else { for k, v := range mp { str := fmt.Sprintf("%s %d\n", k, v) outputFileHandler.WriteString(str) } outputFileHandler.Close() } ReduceChanOut <- outputFilename }
2.5 combiner
Combiner程序,读入Master传递过来的Reducer结果文件并归并成一个,然后堆排序输出最高频的10个词语。
package master import ( "fmt" "strings" "bufio" "os" "container/heap" "strconv" "github.com/vinllen/go-logger/logger" ) type Item struct { key string val int } type PriorityQueue []*Item func (pq PriorityQueue) Len() int { return len(pq) } func (pq PriorityQueue) Less(i, j int) bool { return pq[i].val > pq[j].val } func (pq PriorityQueue) Swap(i, j int) { pq[i], pq[j] = pq[j], pq[i] } func (pq *PriorityQueue) Push(x interface{}) { item := x.(*Item) *pq = append(*pq, item) } func (pq *PriorityQueue) Pop() interface{} { old := *pq n := len(old) item := old[n - 1] *pq = old[0 : n - 1] return item } func combiner() { mp := make(map[string]int) // store the frequence of words // read file and do combine for { val, ok := <- CombineChanIn if !ok { break } logger.Debug("combiner called") file, err := os.Open(val) if err != nil { errMsg := fmt.Sprintf("Read file(%s) error in combiner", val) logger.Error(errMsg) continue } scanner := bufio.NewScanner(file) for scanner.Scan() { str := scanner.Text() arr := strings.Split(str, " ") if len(arr) != 2 { errMsg := fmt.Sprintf("Read file(%s) error that len of line != 2(%s) in combiner", val, str) logger.Warn(errMsg) continue } v, err := strconv.Atoi(arr[1]) if err != nil { errMsg := fmt.Sprintf("Read file(%s) error that line(%s) parse error in combiner", val, str) logger.Warn(errMsg) continue } mp[arr[0]] += v } file.Close() } // heap sort // pq := make(PriorityQueue, len(mp)) pq := make(PriorityQueue, 0) heap.Init(&pq) for k, v := range mp { node := &Item { key: k, val: v, } // logger.Debug(k, v) heap.Push(&pq, node) } res := []Item{} for i := 0; i < 10 && pq.Len() > 0; i++ { node := heap.Pop(&pq).(*Item) res = append(res, *node) } CombineChanOut <- res }
3. 总结
不足以及未实现之处:
接下来要是有空,我会实现分布式高可用的代码,模块间采用RPC通讯。
好了,以上就是这篇文章的全部内容了,希望本文的内容对大家的学习或者工作具有一定的参考学习价值,如果有疑问大家可以留言交流,谢谢大家对呐喊教程的支持。
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