Our company has a web service which I want to send XML files (stored on my drive) via my own HTTPWebRequest client in C#. This already works. The web service supports 5 synchronuous requests at the same time (I get a response from the web service once the processing on the server is completed). Processing takes about 5 minutes for each request.
Throwing too many requests (> 5) results in timeouts for my client. Also, this can lead to errors on the server side and incoherent data. Making changes on the server side is not an option (from different vendor).
Right now, my Webrequest client will send the XML and wait for the response using result.AsyncWaitHandle.WaitOne();
However, this way, only one request can be processed at a time although the web service supports 5. I tried using a Backgroundworker and Threadpool but they create too many requests at same, which make them useless to me. Any suggestion, how one could solve this problem? Create my own Threadpool with exactly 5 threads? Any suggestions, how to implement this?
The easy way is to create 5 threads ( aside: that's an odd number! ) that consume the xml files from a BlockingCollection.
Something like:
var bc = new BlockingCollection<string>();
for ( int i = 0 ; i < 5 ; i++ )
{
new Thread( () =>
{
foreach ( var xml in bc.GetConsumingEnumerable() )
{
// do work
}
}
).Start();
}
bc.Add( xml_1 );
bc.Add( xml_2 );
...
bc.CompleteAdding(); // threads will end when queue is exhausted
If you're on .Net 4, this looks like a perfect fit for Parallel.ForEach(). You can set its MaxDegreeOfParallelism, which means you are guaranteed that no more items are processed at one time.
Parallel.ForEach(items,
new ParallelOptions { MaxDegreeOfParallelism = 5 },
ProcessItem);
Here, ProcessItem is a method that processes one item by accessing your server and blocking until the processing is done. You could use a lambda instead, if you wanted.
Creating your own threadpool of five threads isn't tricky - Just create a concurrent queue of objects describing the request to make, and have five threads that loop through performing the task as needed. Add in an AutoResetEvent and you can make sure they don't spin furiously while there are no requests that need handling.
It can though be tricky to return the response to the correct calling thread. If this is the case for how the rest of your code works, I'd take a different approach and create a limiter that acts a bit like a monitor but allowing 5 simultaneous threads rather than only one:
private static class RequestLimiter
{
private static AutoResetEvent _are = new AutoResetEvent(false);
private static int _reqCnt = 0;
public ResponseObject DoRequest(RequestObject req)
{
for(;;)
{
if(Interlocked.Increment(ref _reqCnt) <= 5)
{
//code to create response object "resp".
Interlocked.Decrement(ref _reqCnt);
_are.Set();
return resp;
}
else
{
if(Interlocked.Decrement(ref _reqCnt) >= 5)//test so we don't end up waiting due to race on decrementing from finished thread.
_are.WaitOne();
}
}
}
}
You could write a little helper method, that would block the current thread until all the threads have finished executing the given action delegate.
static void SpawnThreads(int count, Action action)
{
var countdown = new CountdownEvent(count);
for (int i = 0; i < count; i++)
{
new Thread(() =>
{
action();
countdown.Signal();
}).Start();
}
countdown.Wait();
}
And then use a BlockingCollection<string> (thread-safe collection), to keep track of your xml files. By using the helper method above, you could write something like:
static void Main(string[] args)
{
var xmlFiles = new BlockingCollection<string>();
// Add some xml files....
SpawnThreads(5, () =>
{
using (var web = new WebClient())
{
web.UploadFile(xmlFiles.Take());
}
});
Console.WriteLine("Done");
Console.ReadKey();
}
Update
An even better approach would be to upload the files async, so that you don't waste resources on using threads for an IO task.
Again you could write a helper method:
static void SpawnAsyncs(int count, Action<CountdownEvent> action)
{
var countdown = new CountdownEvent(count);
for (int i = 0; i < count; i++)
{
action(countdown);
}
countdown.Wait();
}
And use it like:
static void Main(string[] args)
{
var urlXML = new BlockingCollection<Tuple<string, string>>();
urlXML.Add(Tuple.Create("http://someurl.com", "filename"));
// Add some more to collection...
SpawnAsyncs(5, c =>
{
using (var web = new WebClient())
{
var current = urlXML.Take();
web.UploadFileCompleted += (s, e) =>
{
// some code to mess with e.Result (response)
c.Signal();
};
web.UploadFileAsyncAsync(new Uri(current.Item1), current.Item2);
}
});
Console.WriteLine("Done");
Console.ReadKey();
}
Related
By using the below code firstly some of the calls are not getting made lets say out of 250 , 238 calls are made and rest doesn't.Secondly I am not sure if the calls are made at the rate of 20 calls per 10 seconds.
public List<ShowData> GetAllShowAndTheirCast()
{
ShowResponse allShows = GetAllShows();
ShowCasts showCast = new ShowCasts();
showCast.showCastList = new List<ShowData>();
using (Semaphore pool = new Semaphore(20, 20))
{
for (int i = 0; i < allShows.Shows.Length; i++)
{
pool.WaitOne();
Thread t = new Thread(new ParameterizedThreadStart((taskId) =>
{
showCast.showCastList.Add(MapResponse(allShows.Shows[i]));
}));
pool.Release();
t.Start(i);
}
}
//for (int i = 0; i < allShows.Shows.Length; i++)
//{
// showCast.showCastList.Add(MapResponse(allShows.Shows[i]));
//}
return showCast.showCastList;
}
public ShowData MapResponse(Show s)
{
CastResponse castres = new CastResponse();
castres.CastlistResponse = (GetShowCast(s.id)).CastlistResponse;
ShowData sd = new ShowData();
sd.id = s.id;
sd.name = s.name;
if (castres.CastlistResponse != null && castres.CastlistResponse.Any())
{
sd.cast = new List<CastData>();
foreach (var item in castres.CastlistResponse)
{
CastData cd = new CastData();
cd.birthday = item.person.birthday;
cd.id = item.person.id;
cd.name = item.person.name;
sd.cast.Add(cd);
}
}
return sd;
}
public ShowResponse GetAllShows()
{
ShowResponse response = new ShowResponse();
string showUrl = ClientAPIUtils.apiUrl + "shows";
response.Shows = JsonConvert.DeserializeObject<Show[]>(ClientAPIUtils.GetDataFromUrl(showUrl));
return response;
}
public CastResponse GetShowCast(int showid)
{
CastResponse res = new CastResponse();
string castUrl = ClientAPIUtils.apiUrl + "shows/" + showid + "/cast";
res.CastlistResponse = JsonConvert.DeserializeObject<List<Cast>>(ClientAPIUtils.GetDataFromUrl(castUrl));
return res;
}
All the Calls should be made , but I am not sure where they are getting aborted and even please let me know how to check the rate of calls being made.
I'm assuming that your goal is to process all data about shows but no more than 20 at once.
For that kind of task you should probably use ThreadPool and limit maximum number of concurrent threads using SetMaxThreads.
https://learn.microsoft.com/en-us/dotnet/api/system.threading.threadpool?view=netframework-4.7.2
You have to make sure that collection that you are using to store your results is thread-safe.
showCast.showCastList = new List<ShowData>();
I don't think that standard List is thread-safe. Thread-safe collection is ConcurrentBag (there are others as well). You can make standard list thread-safe but it requires more code. After you are done processing and need to have results in list or array you can convert collection to desired type.
https://learn.microsoft.com/en-us/dotnet/api/system.collections.concurrent.concurrentbag-1?view=netframework-4.7.2
Now to usage of semaphore. What your semaphore is doing is ensuring that maximum 20 threads can be created at once. Assuming that this loop runs in your app main thread your semaphore has no purpose. To make it work you need to release semaphore once thread is completed; but you are calling thread Start() after calling Release(). That results in thread being executed outside "critical area".
using (Semaphore pool = new Semaphore(20, 20)) {
for (int i = 0; i < allShows.Shows.Length; i++) {
pool.WaitOne();
Thread t = new Thread(new ParameterizedThreadStart((taskId) =>
{
showCast.showCastList.Add(MapResponse(allShows.Shows[i]));
pool.Release();
}));
t.Start(i);
}
}
I did not test this solution; additional problems might arise.
Another issue with this program is that it does not wait for all threads to complete. Once all threads are started; program will end. It is possible (and in your case I'm sure) that not all threads completed its operation; this is why ~240 data packets are done when program finishes.
thread.Join();
But if called right after Start() it will stop main thread until it is completed so to keep program concurrent you need to create a list of threads and Join() them at the end of program. It is not the best solution. How to wait on all threads that program can add to ThreadPool
Wait until all threads finished their work in ThreadPool
As final note you cannot access loop counter like that. Final value of loop counter is evaluated later and with test I ran; code has tendency to process odd records twice and skip even. This is happening because loop increases counter before previous thread is executed and causes to access elements outside bounds of array.
Possible solution to that is to create method that will create thread. Having it in separate method will evaluate allShows.Shows[i] to show before next loop pass.
public void CreateAndStartThread(Show show, Semaphore pool, ShowCasts showCast)
{
pool.WaitOne();
Thread t = new Thread(new ParameterizedThreadStart((s) => {
showCast.showCastList.Add(MapResponse((Show)s));
pool.Release();
}));
t.Start(show);
}
Concurrent programming is tricky and I would highly recommend to do some exercises with examples on common pitfalls. Books on C# programming are sure to have a chapter or two on the topic. There are plenty of online courses and tutorials on this topic to learn from.
Edit:
Working solution. Still might have some issues.
public ShowCasts GetAllShowAndTheirCast()
{
ShowResponse allShows = GetAllShows();
ConcurrentBag<ShowData> result = new ConcurrentBag<ShowData>();
using (var countdownEvent = new CountdownEvent(allShows.Shows.Length))
{
using (Semaphore pool = new Semaphore(20, 20))
{
for (int i = 0; i < allShows.Shows.Length; i++)
{
CreateAndStartThread(allShows.Shows[i], pool, result, countdownEvent);
}
countdownEvent.Wait();
}
}
return new ShowCasts() { showCastList = result.ToList() };
}
public void CreateAndStartThread(Show show, Semaphore pool, ConcurrentBag<ShowData> result, CountdownEvent countdownEvent)
{
pool.WaitOne();
Thread t = new Thread(new ParameterizedThreadStart((s) =>
{
result.Add(MapResponse((Show)s));
pool.Release();
countdownEvent.Signal();
}));
t.Start(show);
}
I have an application where i have 1000+ small parts of 1 large file.
I have to upload maximum of 16 parts at a time.
I used Thread parallel library of .Net.
I used Parallel.For to divide in multiple parts and assigned 1 method which should be executed for each part and set DegreeOfParallelism to 16.
I need to execute 1 method with checksum values which are generated by different part uploads, so i have to set certain mechanism where i have to wait for all parts upload say 1000 to complete.
In TPL library i am facing 1 issue is it is randomly executing any of the 16 threads from 1000.
I want some mechanism using which i can run first 16 threads initially, if the 1st or 2nd or any of the 16 thread completes its task next 17th part should be started.
How can i achieve this ?
One possible candidate for this can be TPL Dataflow. This is a demonstration which takes in a stream of integers and prints them out to the console. You set the MaxDegreeOfParallelism to whichever many threads you wish to spin in parallel:
void Main()
{
var actionBlock = new ActionBlock<int>(
i => Console.WriteLine(i),
new ExecutionDataflowBlockOptions {MaxDegreeOfParallelism = 16});
foreach (var i in Enumerable.Range(0, 200))
{
actionBlock.Post(i);
}
}
This can also scale well if you want to have multiple producer/consumers.
Here is the manual way of doing this.
You need a queue. The queue is sequence of pending tasks. You have to dequeue and put them inside list of working task. When ever the task is done remove it from list of working task and take another from queue. Main thread controls this process. Here is the sample of how to do this.
For the test i used List of integer but it should work for other types because its using generics.
private static void Main()
{
Random r = new Random();
var items = Enumerable.Range(0, 100).Select(x => r.Next(100, 200)).ToList();
ParallelQueue(items, DoWork);
}
private static void ParallelQueue<T>(List<T> items, Action<T> action)
{
Queue pending = new Queue(items);
List<Task> working = new List<Task>();
while (pending.Count + working.Count != 0)
{
if (pending.Count != 0 && working.Count < 16) // Maximum tasks
{
var item = pending.Dequeue(); // get item from queue
working.Add(Task.Run(() => action((T)item))); // run task
}
else
{
Task.WaitAny(working.ToArray());
working.RemoveAll(x => x.IsCompleted); // remove finished tasks
}
}
}
private static void DoWork(int i) // do your work here.
{
// this is just an example
Task.Delay(i).Wait();
Console.WriteLine(i);
}
Please let me know if you encounter problem of how to implement DoWork for your self. because if you change method signature you may need to do some changes.
Update
You can also do this with async await without blocking the main thread.
private static void Main()
{
Random r = new Random();
var items = Enumerable.Range(0, 100).Select(x => r.Next(100, 200)).ToList();
Task t = ParallelQueue(items, DoWork);
// able to do other things.
t.Wait();
}
private static async Task ParallelQueue<T>(List<T> items, Func<T, Task> func)
{
Queue pending = new Queue(items);
List<Task> working = new List<Task>();
while (pending.Count + working.Count != 0)
{
if (working.Count < 16 && pending.Count != 0)
{
var item = pending.Dequeue();
working.Add(Task.Run(async () => await func((T)item)));
}
else
{
await Task.WhenAny(working);
working.RemoveAll(x => x.IsCompleted);
}
}
}
private static async Task DoWork(int i)
{
await Task.Delay(i);
}
var workitems = ... /*e.g. Enumerable.Range(0, 1000000)*/;
SingleItemPartitioner.Create(workitems)
.AsParallel()
.AsOrdered()
.WithDegreeOfParallelism(16)
.WithMergeOptions(ParallelMergeOptions.NotBuffered)
.ForAll(i => { Thread.Slee(1000); Console.WriteLine(i); });
This should be all you need. I forgot how the methods are named exactly... Look at the documentation.
Test this by printing to the console after sleeping for 1sec (which this sample code does).
Another option would be to use a BlockingCollection<T> as a queue between your file reader thread and your 16 uploader threads. Each uploader thread would just loop around consuming the blocking collection until it is complete.
And, if you want to limit memory consumption in the queue you can set an upper limit on the blocking collection such that the file-reader thread will pause when the buffer has reached capacity. This is particularly useful in a server environment where you may need to limit memory used per user/API call.
// Create a buffer of 4 chunks between the file reader and the senders
BlockingCollection<Chunk> queue = new BlockingCollection<Chunk>(4);
// Create a cancellation token source so you can stop this gracefully
CancellationTokenSource cts = ...
File reader thread
...
queue.Add(chunk, cts.Token);
...
queue.CompleteAdding();
Sending threads
for(int i = 0; i < 16; i++)
{
Task.Run(() => {
foreach (var chunk in queue.GetConsumingEnumerable(cts.Token))
{
.. do the upload
}
});
}
I have a program which loops through an apps list.
Apps
--------
App1
App2
App3
Now, for each of them, I do a http request to get a list of builds for each app as an Xml.
So a request like,
http://example.com/getapplist.do?appid=App1
gives me a response like,
<appid name="App1">
<buildid BldName="Bld3" Status="Not Ready"></buildid>
<buildid BldName="Bld2" Status="Ready"></buildid>
<buildid BldName="Bld1" Status="Ready"></buildid>
</appid>
Now I get the Highest build number with Status "Ready" and then do another web api call like,
http://example.com/getapplist.do?appid=App1&bldid=Bld2
This gives me a response like,
<buildinfo appid="App1" buildid="Bld2" value="someinfo"></build>
I feed these into internal data tables. But now, this program takes a painfully long time to complete (3 hours), since I have close to 2000 appids and there are 2 Web requests for each id. I tried sorting this issue using a BackgroundWorker as specified here. I thought of collating all info from http responses into a single XML and then using that XML for further processing. This throws the error,
file being used by another process
So my code looks like,
if (!backgroundWorker1.IsBusy)
{
for(int i = 0; i < appList.Count; i++)
{
BackgroundWorker bgw = new BackgroundWorker();
bgw.WorkerReportsProgress = true;
bgw.WorkerSupportsCancellation = true;
bgw.DoWork += new DoWorkEventHandler(bgw_DoWork);
bgw.ProgressChanged += new ProgressChangedEventHandler(bgw_ProgressChanged);
bgw.RunWorkerCompleted += new RunWorkerCompletedEventHandler(bgw_RunWorkerCompleted);
//Start The Worker
bgw.RunWorkerAsync();
}
}
And the DoWork function picks the tag values and puts it into an XML.
What is the best way I can get the app- buildinfo details into a common file from all the http responses from all the background workers?
HTTP requests are IO bound and asynchronous by nature, there is no reason to use background workers to accomplish what you need.
You can take advantage of async-await which is compatible in .NET 4 via Microsoft.Bcl.Async and HttpClient:
private async Task ProcessAppsAsync(List<string> appList)
{
var httpClient = new HttpClient();
// This will execute your IO requests concurrently,
// no need for extra threads.
var appListTasks = appList.Select(app => httpClient.GetAsync(app.Url)).ToList();
// Wait asynchronously for all of them to finish
await Task.WhenAll(appListTasks);
// process each Task.Result and aggregate them to an xml
using (var streamWriter = new StreamWriter(#"PathToFile")
{
foreach (var appList in appListTasks)
{
await streamWriter.WriteAsync(appList.Result);
}
}
}
This way, you process all requests concurrently and handle results from all of them once they've completed.
This solution works for .Net 2.0 and up by using the async methods from the WebClient class and using a counter that is decremented with the Interlocked class and ordinary lock to serialize the writing of the results to the file.
var writer = XmlWriter.Create(
new FileStream("api.xml",
FileMode.Create));
writer.WriteStartElement("apps"); // root element in the xml
// lock for one write
object writeLock = new object();
// this many calls
int counter = appList.Count;
foreach (var app in appList)
{
var wc = new WebClient();
var url = String.Format(
"http://example.com/getapplist.do?appid={0}&bldid=Bld2",
app);
wc.DownloadDataCompleted += (o, args) =>
{
try
{
var xd = new XmlDocument();
xd.LoadXml(Encoding.UTF8.GetString(args.Result));
lock (writeLock)
{
xd.WriteContentTo(writer);
}
}
finally
{
// count down our counter in a thread safe manner
if (Interlocked.Decrement(ref counter) == 0)
{
// this was the last one, close nicely
writer.WriteEndElement();
writer.Close();
((IDisposable) writer).Dispose();
}
}
};
wc.DownloadDataAsync(
new Uri(url));
}
I'm using Asp .Net 4.5.1.
I have tasks to run, which call a web-service, and some might fail. I need to run N successful tasks which perform some light CPU work and mainly call a web service, then stop, and I want to throttle.
For example, let's assume we have 300 URLs in some collection. We need to run a function called Task<bool> CheckUrlAsync(url) on each of them, with throttling, meaning, for example, having only 5 run "at the same time" (in other words, have maximum 5 connections used at any given time). Also, we only want to perform N (assume 100) successful operations, and then stop.
I've read this and this and still I'm not sure what would be the correct way to do it.
How would you do it?
Assume ASP .Net
Assume IO call (http call to web serice), no heavy CPU operations.
Use Semaphore slim.
var semaphore = new SemaphoreSlim(5);
var tasks = urlCollection.Select(async url =>
{
await semaphore.WaitAsync();
try
{
return await CheckUrlAsync(url);
}
finally
{
semaphore.Release();
}
};
while(tasks.Where(t => t.Completed).Count() < 100)
{
await.Task.WhenAny(tasks);
}
Although I would prefer to use Rx.Net to produce some better code.
using(var semaphore = new SemaphoreSlim(5))
{
var results = urlCollection.ToObservable()
.Select(async url =>
{
await semaphore.WaitAsync();
try
{
return await CheckUrlAsync(url);
}
finally
{
semaphore.Release();
}
}).Take(100).ToList();
}
Okay...this is going to be fun.
public static class SemaphoreHelper
{
public static Task<T> ContinueWith<T>(
this SemaphoreSlim semaphore,
Func<Task<T>> action)
var ret = semaphore.WaitAsync()
.ContinueWith(action);
ret.ContinueWith(_ => semaphore.Release(), TaskContinuationOptions.None);
return ret;
}
var semaphore = new SemaphoreSlim(5);
var results = urlCollection.Select(
url => semaphore.ContinueWith(() => CheckUrlAsync(url)).ToList();
I do need to add that the code as it stands will still run all 300 URLs, it just will return quicker...thats all. You would need to add the cancelation token to the semaphore.WaitAsync(token) to cancel the queued work. Again I suggest using Rx.Net for that. Its just easier to use Rx.Net to get the cancelation token to work with .Take(100).
Try something like this?
private const int u_limit = 100;
private const int c_limit = 5;
List<Task> tasks = new List<Task>();
int totalRun = 0;
while (totalRun < u_limit)
{
for (int i = 0; i < c_limit; i++)
{
tasks.Add(Task.Run (() => {
// Your code here.
}));
}
Task.WaitAll(tasks);
totalRun += c_limit;
}
I want to make 10 asynchronous http requests at once and only process the results when all have completed and in a single callback function. I also do not want to block any threads using WaitAll (it is my understanding that WaitAll blocks until all are complete). I think I want to make a custom IAsyncResult which will handle multiple calls. Am I on the right track? Are there any good resources or examples out there that describe handling this?
I like Darin's solution. But, if you want something more traditional, you can try this.
I would definitely use an array of wait handles and the WaitAll mechanism:
static void Main(string[] args)
{
WaitCallback del = state =>
{
ManualResetEvent[] resetEvents = new ManualResetEvent[10];
WebClient[] clients = new WebClient[10];
Console.WriteLine("Starting requests");
for (int index = 0; index < 10; index++)
{
resetEvents[index] = new ManualResetEvent(false);
clients[index] = new WebClient();
clients[index].OpenReadCompleted += new OpenReadCompletedEventHandler(client_OpenReadCompleted);
clients[index].OpenReadAsync(new Uri(#"http:\\www.google.com"), resetEvents[index]);
}
bool succeeded = ManualResetEvent.WaitAll(resetEvents, 10000);
Complete(succeeded);
for (int index = 0; index < 10; index++)
{
resetEvents[index].Dispose();
clients[index].Dispose();
}
};
ThreadPool.QueueUserWorkItem(del);
Console.WriteLine("Waiting...");
Console.ReadKey();
}
static void client_OpenReadCompleted(object sender, OpenReadCompletedEventArgs e)
{
// Do something with data...Then close the stream
e.Result.Close();
ManualResetEvent readCompletedEvent = (ManualResetEvent)e.UserState;
readCompletedEvent.Set();
Console.WriteLine("Received callback");
}
static void Complete(bool succeeded)
{
if (succeeded)
{
Console.WriteLine("Yeah!");
}
else
{
Console.WriteLine("Boohoo!");
}
}
In .NET 4.0 there's a nice parallel Task library that allows you to do things like:
using System;
using System.Linq;
using System.Net;
using System.Threading.Tasks;
class Program
{
public static void Main()
{
var urls = new[] { "http://www.google.com", "http://www.yahoo.com" };
Task.Factory.ContinueWhenAll(
urls.Select(url => Task.Factory.StartNew(u =>
{
using (var client = new WebClient())
{
return client.DownloadString((string)u);
}
}, url)).ToArray(),
tasks =>
{
var results = tasks.Select(t => t.Result);
foreach (var html in results)
{
Console.WriteLine(html);
}
});
Console.ReadLine();
}
}
As you can see for each url in the list a different task is started and once all tasks are completed the callback is invoked and passed the result of all tasks.
I think you are better off using the WaitAll approach. Otherwise you will be processing 10 IAsyncResult callbacks, and using a semaphore to determine that all 10 are finally complete.
Keep in mind that WaitAll is very efficient; it is not like the silliness of having a thread "sleep." When a thread sleeps, it continues to use processing time. When a thread is "de-scheduled" because it hit a WaitAll, then the thread no longer consumes any processor time. It is very efficient.