[MIT6.5840]MapReduce

MapReduce

Lab 地址

https://pdos.csail.mit.edu/6.824/labs/lab-mr.html

论文地址

https://static.googleusercontent.com/media/research.google.com/zh-CN//archive/mapreduce-osdi04.pdf

工作原理

简单来讲，MapReduce是一种分布式框架，可以用来处理大规模数据。该框架抽象了两个接口，分别是Map和Reduce函数：

凡是符合这个模式的算法都可以使用该框架来实现并行化，执行流程如下图所示。

整个框架分为Master和Worker，Master负责分配map和reduce任务，Worker负责向Master申请任务并执行。执行流程如下：

Map阶段：

• 输入是大文件分割后的一组小文件，通常大小为16~64MB。
• Worker向Master申请任务，假设得到map任务in0。
• Worker开始执行map任务，将文件名和文件内容作为参数传入map函数中，得到kv list.
• 最后Worker将kv list分割成reduceNum份（超参数），要求使得具有相同key的kv对在一份中。可以通过hash值%reduceNum实现分割，然后输出到文件中，下图的0-*

Reduce阶段：

• 输入当前reduce的序号id，从map阶段的输出中选出*-id的文件，也就是将hash值%reduceNum值相同的kv对取出，这样可以保证具有相同key的kv对只用一次处理。
• 将所有的kv对根据键值排序，使得相同key的kv对能够连续排列，方便合并。
• 之后合并相同key的kv对，然后将每个key和其对应的value list输入reduce函数，得到合并的结果，再将其输出到文件中。

本文介绍了大致思想，详细内容请参考原论文。

代码详解

rpc.go

package mr//
// RPC definitions.
//
// remember to capitalize all names.
//import ("fmt""os""strconv"
)const (MAP    = "MAP"REDUCE = "REDUCE"DONE   = "DONE"
)//
// example to show how to declare the arguments
// and reply for an RPC.
//type ApplyArgs struct {WorkerID     intLastTaskType stringLastTaskID   int
}type ReplyArgs struct {TaskId    intTaskType  stringInputFile stringMapNum    intReduceNum int
}// Add your RPC definitions here.// Cook up a unique-ish UNIX-domain socket name
// in /var/tmp, for the coordinator.
// Can't use the current directory since
// Athena AFS doesn't support UNIX-domain sockets.
func coordinatorSock() string {s := "/var/tmp/5840-mr-"s += strconv.Itoa(os.Getuid())return s
}
// 构造文件名
func tmpMapResult(workerID int, taskID int, reduceId int) string {return fmt.Sprintf("tmp-worker-%d-%d-%d", workerID, taskID, reduceId)
}func finalMapResult(taskID int, reduceID int) string {return fmt.Sprintf("mr-%d-%d", taskID, reduceID)
}func tmpReduceResult(workerID int, reduceId int) string {return fmt.Sprintf("tmp-worker-%d-out-%d", workerID, reduceId)
}func finalReduceResult(reduceID int) string {return fmt.Sprintf("mr-out-%d", reduceID)
}

worker.go

package mrimport ("fmt""hash/fnv""io""log""net/rpc""os""sort""strings"
)// Map functions return a slice of KeyValue.
type KeyValue struct {Key   stringValue string
}// for sorting by key.
type ByKey []KeyValue// for sorting by key.
func (a ByKey) Len() int           { return len(a) }
func (a ByKey) Swap(i, j int)      { a[i], a[j] = a[j], a[i] }
func (a ByKey) Less(i, j int) bool { return a[i].Key < a[j].Key }// use ihash(key) % NReduce to choose the reduce
// task number for each KeyValue emitted by Map.
func ihash(key string) int {h := fnv.New32a()h.Write([]byte(key))return int(h.Sum32() & 0x7fffffff)
}// main/mrworker.go calls this function.
func Worker(mapf func(string, string) []KeyValue,reducef func(string, []string) string) {// Your worker implementation here.id := os.Getegid()// log.Printf("worker %d start working", id)lastTaskId := -1lastTaskType := ""loop:for {args := ApplyArgs{WorkerID:     id,LastTaskType: lastTaskType,LastTaskID:   lastTaskId,}reply := ReplyArgs{}ok := call("Coordinator.ApplyForTask", &args, &reply)if !ok {fmt.Printf("call failed!\n")continue}// log.Printf("reply: %v", reply)lastTaskId = reply.TaskIdlastTaskType = reply.TaskTypeswitch reply.TaskType {case "":// log.Println("finished")break loopcase MAP:// log.Printf("worker %d get map task %d", id, reply.TaskId)doMapTask(id, reply.TaskId, reply.InputFile, reply.ReduceNum, mapf)case REDUCE:// log.Printf("worker %d get reduce task %d", id, reply.TaskId)doReduceTask(id, reply.TaskId, reply.MapNum, reducef)}}// uncomment to send the Example RPC to the coordinator.// CallExample()}// send an RPC request to the coordinator, wait for the response.
// usually returns true.
// returns false if something goes wrong.
func call(rpcname string, args interface{}, reply interface{}) bool {// c, err := rpc.DialHTTP("tcp", "127.0.0.1"+":1234")sockname := coordinatorSock()c, err := rpc.DialHTTP("unix", sockname)if err != nil {log.Fatal("dialing:", err)}defer c.Close()err = c.Call(rpcname, args, reply)if err == nil {return true}fmt.Println(err)return false
}func doMapTask(id int, taskId int, filename string, reduceNum int, mapf func(string, string) []KeyValue) {file, err := os.Open(filename)if err != nil {log.Fatalf("%s 文件打开失败! ", filename)return}content, err := io.ReadAll(file)if err != nil {log.Fatalf("%s 文件内容读取失败! ", filename)}file.Close()kvList := mapf(filename, string(content)) // kv listhashedKvList := make(map[int]ByKey)for _, kv := range kvList {hashedKey := ihash(kv.Key) % reduceNumhashedKvList[hashedKey] = append(hashedKvList[hashedKey], kv)}for i := 0; i < reduceNum; i++ {outFile, err := os.Create(tmpMapResult(id, taskId, i))if err != nil {log.Fatalf("can not create output file: %e", err)return}for _, kv := range hashedKvList[i] {fmt.Fprintf(outFile, "%v\t%v\n", kv.Key, kv.Value)}outFile.Close()}// log.Printf("worker %d finished map task\n", id)
}func doReduceTask(id int, taskId int, mapNum int, reducef func(string, []string) string) {var kvList ByKeyvar lines []stringfor i := 0; i < mapNum; i++ {mapOutFile := finalMapResult(i, taskId)file, err := os.Open(mapOutFile)if err != nil {log.Fatalf("can not open output file %s: %e", mapOutFile, err)return}content, err := io.ReadAll(file)if err != nil {log.Fatalf("file read failed %s: %e", mapOutFile, err)return}lines = append(lines, strings.Split(string(content), "\n")...)}for _, line := range lines {if strings.TrimSpace(line) == "" {continue}split := strings.Split(line, "\t")kvList = append(kvList, KeyValue{Key: split[0], Value: split[1]})}sort.Sort(kvList)outputFile := tmpReduceResult(id, taskId)file, err := os.Create(outputFile)if err != nil {log.Fatalf("can not create output file: %e", err)return}for i := 0; i < len(kvList); {j := i + 1key := kvList[i].Keyvar values []stringfor j < len(kvList) && kvList[j].Key == key {j++}for k := i; k < j; k++ {values = append(values, kvList[k].Value)}res := reducef(key, values)fmt.Fprintf(file, "%v %v\n", key, res)i = j}file.Close()// log.Printf("worker %d finished reduce task", id)
}

coordinator.go

package mrimport ("fmt""log""math""net""net/http""net/rpc""os""sync""time"
)type Task struct {id        intinputFile stringworker    inttaskType  stringdeadLine  time.Time
}type Coordinator struct {// Your definitions here.mtx        sync.MutexinputFile  []stringreduceNum  intmapNum     inttaskStates map[string]TasktodoList   chan Taskstage      string
}// Your code here -- RPC handlers for the worker to call.// an example RPC handler.
//
// the RPC argument and reply types are defined in rpc.go.
func (c *Coordinator) ApplyForTask(args *ApplyArgs, reply *ReplyArgs) error {// process the last taskif args.LastTaskID != -1 {taskId := createTaskId(args.LastTaskID, args.LastTaskType)c.mtx.Lock()if task, ok := c.taskStates[taskId]; ok && task.worker != -1 { // 排除过期任务// log.Printf("worker %d finish task %d", args.WorkerID, task.id)if args.LastTaskType == MAP {for i := 0; i < c.reduceNum; i++ {err := os.Rename(tmpMapResult(task.worker, task.id, i), finalMapResult(task.id, i))if err != nil {log.Fatalf("can not rename %s: %e", tmpMapResult(task.worker, task.id, i), err)}}} else if args.LastTaskType == REDUCE {err := os.Rename(tmpReduceResult(task.worker, task.id), finalReduceResult(task.id))if err != nil {log.Fatalf("can not rename %s: %e", tmpReduceResult(task.worker, task.id), err)}}delete(c.taskStates, taskId)if len(c.taskStates) == 0 {c.shift()}}c.mtx.Unlock()}// assign the new tasktask, ok := <-c.todoListif !ok {return nil}reply.InputFile = task.inputFilereply.MapNum = c.mapNumreply.ReduceNum = c.reduceNumreply.TaskId = task.idreply.TaskType = task.taskTypetask.worker = args.WorkerIDtask.deadLine = time.Now().Add(10 * time.Second)// log.Printf("assign %s task %d to worker %d", task.taskType, task.id, args.WorkerID)c.mtx.Lock()c.taskStates[createTaskId(task.id, task.taskType)] = taskc.mtx.Unlock()return nil
}// start a thread that listens for RPCs from worker.go
func (c *Coordinator) server() {rpc.Register(c)rpc.HandleHTTP()//l, e := net.Listen("tcp", ":1234")sockname := coordinatorSock()os.Remove(sockname)l, e := net.Listen("unix", sockname)if e != nil {log.Fatal("listen error:", e)}go http.Serve(l, nil)
}
// 改变当前的状态
func (c *Coordinator) shift() {// 加锁状态if c.stage == MAP {// log.Printf("Map Task finished")c.stage = REDUCE// 分配reduce taskfor i := 0; i < c.reduceNum; i++ {task := Task{id:       i,worker:   -1,taskType: REDUCE,}c.todoList <- taskc.taskStates[createTaskId(i, REDUCE)] = task}} else if c.stage == REDUCE {close(c.todoList)c.stage = DONE}
}// main/mrcoordinator.go calls Done() periodically to find out
// if the entire job has finished.
func (c *Coordinator) Done() bool {// Your code here.c.mtx.Lock()defer c.mtx.Unlock()return c.stage == DONE
}// create a Coordinator.
// main/mrcoordinator.go calls this function.
// nReduce is the number of reduce tasks to use.
func MakeCoordinator(files []string, nReduce int) *Coordinator {c := Coordinator{mtx:        sync.Mutex{},inputFile:  files,reduceNum:  nReduce,mapNum:     len(files),taskStates: make(map[string]Task),todoList:   make(chan Task, int(math.Max(float64(nReduce), float64(len(files))))),stage:      MAP,}for i, file := range files {task := Task{id:        i,inputFile: file,worker:    -1,taskType:  MAP,}c.todoList <- taskc.taskStates[createTaskId(i, MAP)] = task}// 回收任务go c.collectTask()c.server()return &c
}func createTaskId(id int, taskType string) string {return fmt.Sprintf("%d-%s", id, taskType)
}
// worker执行过期后回收任务
func (c *Coordinator) collectTask() {for {time.Sleep(500 * time.Millisecond)c.mtx.Lock()if c.stage == DONE {c.mtx.Unlock()return}for _, task := range c.taskStates {if task.worker != -1 && time.Now().After(task.deadLine) {// task is expiredtask.worker = -1// log.Printf("task %d is expired", task.id)c.todoList <- task}}c.mtx.Unlock()}
}

运行说明

mrcoordinator

cd src/main/
go build -buildmode=plugin ../mrapps/wc.go
rm mr-out*
go run mrcoordinator.go pg-*.txt

mrworker

cd src/main/
go run mrworker.go wc.so

测试结果

bash test-mr.sh

MIT6.5840 课程Lab完整项目

https://github.com/Joker0x00/MIT-6.5840-Lab/