使用 F# 代理 Map Reduce [英] Map Reduce with F# agents
本文介绍了使用 F# 代理 Map Reduce的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
在玩过 F# 代理后，我尝试使用它们进行地图缩减.
After playing with F# agents I tried to do a map reduce using them.
我使用的基本结构是:
- 地图主管将所有工作排入其状态并接收来自地图工作者的工作请求
- reduce supervisor 和 map supervisor 做同样的事情来做 reduce 工作
- 一组 map 和 reduce 工作人员进行 map 和 reduce，如果其中一个工作失败，它会将其发送回各自的主管进行重新处理.
我想知道的问题是:
- 与使用 PSeq 的更传统(但非常好)的 map reduce (http://tomasp.net/blog/fsharp-parallel-aggregate.aspx)相比，这是否有意义?
- 我实现 map 和 reduce workers 的方式看起来很丑，有没有更好的方法?
- 好像我可以创建一个 1000 000 个 map workers 和 1000 0000 个 reduce workers 哈哈，我应该如何选择这些数字，越多越好?
非常感谢，
type Agent<'T> = MailboxProcessor<'T>
//This is the response the supervisor
//gives to the worker request for work
type 'work SupervisorResponse =
| Work of 'work //a piece of work
| NoWork//no work left to do
//This is the message to the supervisor
type 'work WorkMsg =
| ToDo of 'work //piles up work in the Supervisor queue
| WorkReq of AsyncReplyChannel<SupervisorResponse<'work>> //'
//The supervisor agent can be interacted with
type AgentOperation =
| Stop //stop the agent
| Status //yield the current status of supervisor
type 'work SupervisorMsg =
| WorkRel of 'work WorkMsg
| Operation of AgentOperation
//Supervises Map and Reduce workers
module AgentSupervisor=
let getNew (name:string) =
new Agent<SupervisorMsg<'work>>(fun inbox -> //'
let rec loop state = async {
let! msg = inbox.Receive()
match msg with
| WorkRel(m) ->
match m with
| ToDo(work) ->
let newState = work:state
return! loop newState
| WorkReq(replyChannel) ->
match state with
| [] ->
replyChannel.Reply(NoWork)
return! loop []
| [item] ->
replyChannel.Reply(Work(item))
return! loop []
| (item::remaining) ->
replyChannel.Reply(Work(item))
return! loop remaining
| Operation(op) ->
match op with
| Status ->
Console.WriteLine(name+" current Work Queue "+
string (state.Length))
return! loop state
| Stop ->
Console.WriteLine("Stoppped SuperVisor Agent "+name)
return()
}
loop [] )
let stop (agent:Agent<SupervisorMsg<'work>>) = agent.Post(Operation(Stop))
let status (agent:Agent<SupervisorMsg<'work>>) =agent.Post(Operation(Status))
//Code for the workers
type 'success WorkOutcome =
| Success of 'success
| Fail
type WorkerMsg =
| Start
| Stop
| Continue
module AgentWorker =
type WorkerSupervisors<'reduce,'work> =
{ Map:Agent<SupervisorMsg<'work>> ; Reduce:Agent<SupervisorMsg<'reduce>> }
let stop (agent:Agent<WorkerMsg>) = agent.Post(Stop)
let start (agent:Agent<WorkerMsg>) = agent.Start()
agent.Post(Start)
let getNewMapWorker( map, supervisors:WorkerSupervisors<'reduce,'work> ) =
new Agent<WorkerMsg>(fun inbox ->
let rec loop () = async {
let! msg = inbox.Receive()
match msg with
| Start -> inbox.Post(Continue)
return! loop ()
| Continue ->
let! supervisorOrder =
supervisors.Map.PostAndAsyncReply(
fun replyChannel ->
WorkRel(WorkReq(replyChannel)))
match supervisorOrder with
| Work(work) ->
let! res = map work
match res with
| Success(toReduce) ->
supervisors.Reduce
.Post(WorkRel(ToDo(toReduce)))
| Fail ->
Console.WriteLine("Map Fail")
supervisors.Map
.Post(WorkRel(ToDo(work)))
inbox.Post(Continue)
| NoWork ->
inbox.Post(Continue)
return! loop ()
| Stop ->
Console.WriteLine("Map worker stopped")
return ()
}
loop () )
let getNewReduceWorker(reduce,reduceSupervisor:Agent<SupervisorMsg<'work>>)=//'
new Agent<WorkerMsg>(fun inbox ->
let rec loop () = async {
let! msg = inbox.Receive()
match msg with
| Start -> inbox.Post(Continue)
return! loop()
| Continue ->
let! supervisorOrder =
reduceSupervisor.PostAndAsyncReply(fun replyChannel ->
WorkRel(WorkReq(replyChannel)))
match supervisorOrder with
| Work(work) ->
let! res = reduce work
match res with
| Success(toReduce) -> inbox.Post(Continue)
| Fail ->
Console.WriteLine("ReduceFail")
reduceSupervisor.Post(WorkRel(ToDo(work)))
inbox.Post(Continue)
| NoWork -> inbox.Post(Continue)
return! loop()
|Stop ->Console.WriteLine("Reduce worker stopped"); return ()
}
loop() )
open AgentWorker
type MapReduce<'work,'reduce>( numberMap:int ,
numberReduce: int,
toProcess:'work list,
map:'work->Async<'reduce WorkOutcome>,
reduce:'reduce-> Async<unit WorkOutcome>) =
let mapSupervisor= AgentSupervisor.getNew("MapSupervisor")
let reduceSupervisor = AgentSupervisor.getNew("ReduceSupervisor")
let workerSupervisors = {Map = mapSupervisor ; Reduce = reduceSupervisor }
let mapWorkers =
[for i in 1..numberMap ->
AgentWorker.getNewMapWorker(map,workerSupervisors) ]
let reduceWorkers =
[for i in 1..numberReduce ->
AgentWorker.getNewReduceWorker(reduce,workerSupervisors.Reduce) ]
member this.Start() =
//Post work to do
toProcess
|>List.iter(fun elem -> mapSupervisor.Post( WorkRel(ToDo(elem))))
//Start supervisors
mapSupervisor.Start()
reduceSupervisor.Start()
//start workers
List.iter( fun mapper -> mapper |>start) mapWorkers
List.iter( fun reducer ->reducer|>start) reduceWorkers
member this.Status() = (mapSupervisor|>AgentSupervisor.status)
(reduceSupervisor|>AgentSupervisor.status)
member this.Stop() =
List.map2(fun mapper reducer ->
mapper |>stop; reducer|>stop) mapWorkers reduceWorkers
//Run some tests
let map = function (n:int64) -> async{ return Success(n) }
let reduce = function (toto: int64) -> async{ return Success() }
let mp = MapReduce<int64,int64>( 1,1,[for i in 1L..1000000L->i],map,reduce)
mp.Start()
mp.Status()
mp.Stop()
推荐答案
我喜欢使用 MailboxProcessor 作为算法的 reduce 部分，使用 Async.Parallel 调用的异步块作为 map 部分.它使事情变得更加明确，让您可以更好地控制异常处理、超时和取消.
I like to use MailboxProcessor for the reduce part of the algorithm, and async block that's invoked with Async.Parallel for the map part. It makes things more explicit, giving you finer control over exception handling, timeouts, and cancellation.
以下代码是在 Brian 的帮助下设计的，并借助他出色的 F# 块突出显示 VS2010 的F# Depth Colorizer"插件.
The following code was designed with Brian's help, and with the help of his excellent F# block highlighting "F# Depth Colorizer" plug-in for VS2010.
此代码旨在以 map-reduce 模式从 yahoo 天气服务器中提取 RSS 提要.它演示了我们如何从实际算法的外部控制执行流程.
This code is meant to pull RSS feeds from yahoo weather server in a map-reduce pattern. It demonstrates how we can control execution flow from the outside of actual algorithm.
fetchWeather是map部分，mailboxLoop是算法的reduce部分.
fetchWeather is the map part, and mailboxLoop is the reduce part of the algorithm.
#r "System.Xml.Linq.dll"
#r "FSharp.PowerPack.dll"
open System
open System.Diagnostics
open System.IO
open System.Linq
open System.Net
open System.Xml.Linq
open Microsoft.FSharp.Control.WebExtensions
type Weather (city, region, temperature) = class
member x.City = city
member x.Region = region
member x.Temperature : int = temperature
override this.ToString() =
sprintf "%s, %s: %d F" this.City this.Region this.Temperature
end
type MessageForActor =
| ProcessWeather of Weather
| ProcessError of int
| GetResults of (Weather * Weather * Weather list) AsyncReplyChannel
let parseRss woeid (rssStream : Stream) =
let xn str = XName.Get str
let yweather elementName = XName.Get(elementName, "http://xml.weather.yahoo.com/ns/rss/1.0")
let channel = (XDocument.Load rssStream).Descendants(xn "channel").First()
let location = channel.Element(yweather "location")
let condition = channel.Element(xn "item").Element(yweather "condition")
// If the RSS server returns error, condition XML element won't be available.
if not(condition = null) then
let temperature = Int32.Parse(condition.Attribute(xn "temp").Value)
ProcessWeather(new Weather(
location.Attribute(xn "city").Value,
location.Attribute(xn "region").Value,
temperature))
else
ProcessError(woeid)
let fetchWeather (actor : MessageForActor MailboxProcessor) woeid =
async {
let rssAddress = sprintf "http://weather.yahooapis.com/forecastrss?w=%d&u=f" woeid
let webRequest = WebRequest.Create rssAddress
use! response = webRequest.AsyncGetResponse()
use responseStream = response.GetResponseStream()
let weather = parseRss woeid responseStream
//do! Async.Sleep 1000 // enable this line to see amplified timing that proves concurrent flow
actor.Post(weather)
}
let mailboxLoop initialCount =
let chooseCityByTemperature op (x : Weather) (y : Weather) =
if op x.Temperature y.Temperature then x else y
let sortWeatherByCityAndState (weatherList : Weather list) =
weatherList
|> List.sortWith (fun x y -> x.City.CompareTo(y.City))
|> List.sortWith (fun x y -> x.Region.CompareTo(y.Region))
MailboxProcessor.Start(fun inbox ->
let rec loop minAcc maxAcc weatherList remaining =
async {
let! message = inbox.Receive()
let remaining = remaining - 1
match message with
| ProcessWeather weather ->
let colderCity = chooseCityByTemperature (<) minAcc weather
let warmerCity = chooseCityByTemperature (>) maxAcc weather
return! loop colderCity warmerCity (weather :: weatherList) remaining
| ProcessError woeid ->
let errorWeather = new Weather(sprintf "Error with woeid=%d" woeid, "ZZ", 99999)
return! loop minAcc maxAcc (errorWeather :: weatherList) remaining
| GetResults replyChannel ->
replyChannel.Reply(minAcc, maxAcc, sortWeatherByCityAndState weatherList)
}
let minValueInitial = new Weather("", "", Int32.MaxValue)
let maxValueInitial = new Weather("", "", Int32.MinValue)
loop minValueInitial maxValueInitial [] initialCount
)
let RunSynchronouslyWithExceptionAndTimeoutHandlers computation =
let timeout = 30000
try
Async.RunSynchronously(Async.Catch(computation), timeout)
|> function Choice1Of2 answer -> answer |> ignore
| Choice2Of2 (except : Exception) -> printfn "%s" except.Message; printfn "%s" except.StackTrace; exit -4
with
| :? System.TimeoutException -> printfn "Timed out waiting for results for %d seconds!" <| timeout / 1000; exit -5
let main =
// Should have script name, sync/async select, and at least one woeid
if fsi.CommandLineArgs.Length < 3 then
printfn "Expecting at least two arguments!"
printfn "There were %d arguments" (fsi.CommandLineArgs.Length - 1)
exit -1
let woeids =
try
fsi.CommandLineArgs
|> Seq.skip 2 // skip the script name and sync/async select
|> Seq.map Int32.Parse
|> Seq.toList
with
| except -> printfn "One of supplied arguments was not an integer: %s" except.Message; exit -2
let actor = mailboxLoop woeids.Length
let processWeatherItemsConcurrently woeids =
woeids
|> Seq.map (fetchWeather actor)
|> Async.Parallel
|> RunSynchronouslyWithExceptionAndTimeoutHandlers
let processOneWeatherItem woeid =
woeid
|> fetchWeather actor
|> RunSynchronouslyWithExceptionAndTimeoutHandlers
let stopWatch = new Stopwatch()
stopWatch.Start()
match fsi.CommandLineArgs.[1].ToUpper() with
| "C" -> printfn "Concurrent execution: "; processWeatherItemsConcurrently woeids
| "S" -> printfn "Synchronous execution: "; woeids |> Seq.iter processOneWeatherItem
| _ -> printfn "Unexpected run options!"; exit -3
let (min, max, weatherList) = actor.PostAndReply GetResults
stopWatch.Stop()
assert (weatherList.Length = woeids.Length)
printfn "{"
weatherList |> List.iter (printfn " %O")
printfn "}"
printfn "Coldest place: %O" min
printfn "Hottest place: %O" max
printfn "Completed in %d millisec" stopWatch.ElapsedMilliseconds
main
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