We are exposing our current logic/business layer using WebAPI. As per my understanding, if we want to keep our self safe from thread starvation for the requests, we should make Async WebAPI controller, so a large number of concurrent request can make up.
I do understand that as the underlying service/business layer is synchronous, so there will be no performance gain. We are just aiming for a large number of concurrent requests to pass through.
Below is the code that i am using:
public async Task<IHttpActionResult> Get()
{
var result = await Task.Run(() => Service.GetAllCompanies()); //existing business layer
return Ok(result);
}
Wrapping underlying layer in a Task, is this good to proceed with and achieve the goal.
My understanding is that if your await-ed methods' implementations aren't async, then you are not really accomplishing what you think you are. If you have CPU-bound service methods, you're just releasing a thread from the request-handling pool and then spinning up a new one (from the same pool, mind you) when you Task.Run(); So you incur some overhead from that switch, but the ASP.NET thread pool is still doing the work, so you haven't achieved what you want.
If you service methods can be converted to be pure (or mostly pure) async code, then you would stand to benefit from working bottom up.
Reference: https://msdn.microsoft.com/en-us/magazine/dn802603.aspx
Related
I know that you utilize a port to address a process and that you have to use sockets for handling multiple requests on web server, but how does it work? Is the process creating multiple socket threads for each connection? Is threading the answer?
Overview
This is a great question, and one that will take a bit to explain fully. I will step through different parts of this topic below. I personally learned multi-threading in Java, which has quite an extensive concurrency library. Although my examples will be in Java, the concepts will stand between languages.
Is threading valid?
In short, yes this is a perfect use case for multi-threading, although single-threaded is fine for simple scenarios as well. However, there does exist better designs that may yield better performance and safer code. The great thing is there are loads of examples on how to do this on the internet!
Multi-Threading
Lets investigate sample code from this article, seen below.
public class Server
{
public static void main(String[] args) throws IOException
{
// server is listening on port 5056
ServerSocket ss = new ServerSocket(5056);
// running infinite loop for getting
// client request
while (true)
{
Socket s = null;
try
{
// socket object to receive incoming client requests
s = ss.accept();
System.out.println("A new client is connected : " + s);
// obtaining input and out streams
DataInputStream dis = new DataInputStream(s.getInputStream());
DataOutputStream dos = new DataOutputStream(s.getOutputStream());
System.out.println("Assigning new thread for this client");
// create a new thread object
Thread t = new ClientHandler(s, dis, dos);
// Invoking the start() method
t.start();
}
catch (Exception e){
s.close();
e.printStackTrace();
}
}
}
}
The Server code is actually quite basic but still does the job well. Lets step through all the logic seen here:
The Server sets up on Socket 5056
The Server begins its infinite loop
The client blocks on ss.accept() until a client request is received on part 5056
The Server does relatively minimal operations (i.e. System.out logging, set up IO streams)
A Thread is created and assigned to this request
The Thread is started
The loop repeats
The mentality here is that the server acts as a dispatcher. Requests enter the server, and the server allocates workers (Threads) to complete the operations in parallel so that the server can wait for and assist the next, incoming request.
Pros
Simple, readable code
Operations in parallel allows for increased performance with proper synchronization
Cons
The dangers of multi-threading
The creation of threads is quite cumbersome and resource intensive, thus should not be a frequent operation
No re-use of threads
Must manually limit threads
Thread Pool
Lets investigate sample code from this article, seen below.
while(! isStopped()){
Socket clientSocket = null;
try {
clientSocket = this.serverSocket.accept();
} catch (IOException e) {
if(isStopped()) {
System.out.println("Server Stopped.") ;
break;
}
throw new RuntimeException("Error accepting client connection", e);
}
this.threadPool.execute(new WorkerRunnable(clientSocket,"Thread Pooled Server"));
}
Note, I excluded the setup because it is rather similar to the Multi-Threaded example. Lets step through the logic in this example.
The server waits for a request to arrive on its alloted port
The server sends the request to a handler that is given to the ThreadPool to run
The ThreadPool receives Runnable code, allocated a worker, and begin code execution in parallel
The loop repeats
The server again acts as a dispatcher; it listens for the request, receives one, and ships it to a ThreadPool. The ThreadPool abstracts the complex resource management from the developer and executes the code optimized fully. This is very similar to the multi-thread example, but all resource management is packaged into the ThreadPool. The code is reduced further from the above example, and it is much safer for non-multi-threading professionals. Note, the WorkerRunnable is only a Runnable, not a raw Thread, whilst the ClientHandler in the Multi-Thread example was a raw Thread.
Pros
Threads are managed and re-used by the pool
Further simplify code base
Inherits all benefits from the Multi-Threaded example
Cons
There is a learning curve to fully understanding pooling and different configurations of them
Notes
In Java, there exists another implementation called RMI, that attempts to abstract away the network, thus allowing the communication of Client-Server to happen as though it is on one JVM, even if it is on many. Although this as well can use multi-threading, it is another approach to the issue instead of sockets.
I'm using MVC4 ApiController to upload data to Azure Blob. Here is the sample code:
public Task PostAsync(int id)
{
return Task.Factory.StartNew(() =>
{
// CloudBlob.UploadFromStream(stream);
});
}
Does this code even make sense? I think ASP.NET is already processing the request in a worker thread, so running UploadFromStream in another thread doesn't seem to make sense since it now uses two threads to run this method (I assume the original worker thread is waiting for this UploadFromStream to finish?)
So my understanding is that async ApiController only makes sense if we are using some built-in async methods such as HttpClient.GetAsync or SqlCommand.ExecuteReaderAsync. Those methods probably use I/O Completion Ports internally so it can free up the thread while doing the actual work. So I should change the code to this?
public Task PostAsync(int id)
{
// only to show it's using the proper async version of the method.
return TaskFactory.FromAsync(BeginUploadFromStream, EndUploadFromStream...)
}
On the other hand, if all the work in the Post method is CPU/memory intensive, then the async version PostAsync will not help throughput of requests. It might be better to just use the regular "public void Post(int id)" method, right?
I know it's a lot questions. Hopefully it will clarify my understanding of async usage in the ASP.NET MVC. Thanks.
Yes, most of what you say is correct. Even down to the details with completion ports and such.
Here is a tiny error:
I assume the original worker thread is waiting for this UploadFromStream to finish?
Only your task thread is running. You're using the async pipeline after all. It does not wait for the task to finish, it just hooks up a continuation. (Just like with HttpClient.GetAsync).
I have a .NET 4.5 WCF client app that uses the async/await pattern to make volumes of calls. My development machine is dual-proc with 8gb RAM (production will be 5 CPU with 8gb RAM at Amazon AWS) . The remote WCF service called by my code uses out and ref parameters on a web method that I need. My code instances a proxy client each time, writes any results to a public ConcurrentDictionary, and then returns null.
I ran Perfmon, watching the thread count on the system, and it goes between 28-30. It takes hours for my client to complete the volumes of calls that are made. Yes, hours. The remote service is backed by a big company, they have many servers to receive my WCF calls, so the more calls I can throw at them, the better.
I think that things are actually still happening synchronously, even though the method that makes the WCF call is decorated with "async" because the proxy method cannot have "await". Is that true?
My code looks like this:
async private void CallMe()
{
Console.WriteLine( DateTime.Now );
var workTasks = this.AnotherConcurrentDict.Select( oneB => GetData( etcetcetc ).Cast<Task>().ToList();
await Task.WhenAll( workTasks );
}
private async Task<WorkingBits> GetData(etcetcetc)
{
var commClient = new RemoteClient();
var cpResponse = new GetPackage();
var responseInfo = commClient.GetData( name, password , ref (cpResponse.aproperty), filterid , out cpResponse.Identifiers);
foreach (var onething in cpResponse.Identifiers)
{
// add to the ConcurrentDictionary
}
return null; // I already wrote to the ConcurrentDictionary so no need to return anything
responseInfo is not awaitable beacuse the WCF call has ref and out parameters.
I was thinking that way to speed this up is not to put async/await in this method, but instead create a wrapper method where I can make things await/async, but I am not that is the smartest/safest way to work it.
What is a smart way to get more outbound calls to the service (expand IO completion thread pool, trick calls into running in the background so Task.WhenAll can complete quicker)?
Thanks for all ideas/samples/pointers. I am hitting a bottleneck somewhere.
1) Make sure you're really calling it asynchronously, rather than just blocking on the calls. Code samples would help here.
2) You may need to do this:
ServicePointManager.DefaultConnectionLimit = 100;
By default it only allows 2 simultaneous connections to the same server.
3) Make sure you dispose the proxy object after the call is complete so you're not tying up resources.
If you're doing things asynchronously the threadpool size shouldn't be a bottleneck. To get a better idea of what kind of problem you're having, you can use Interlocked.Increment and Interlocked.Decrement to track the number of pending calls and see if it's being limited somewhere.
You could also substitute your real call with a call to a very simple method that you know will not have any bottlenecks, to see if the problem is in the client or server.
I am trying solve this problem. I have WCF service. Client can call web method from this service which only "fire" another method (this method only write data to database) in another thread.
Code is here:
//this method will write data to database
public void WriteToDb()
{
}
//this web method will call only mehod WriteToDb() in another thread
public void SomeWebMethod()
{
new Task(WriteToDb).Start();
}
Problem is that in same time can web method call 5 clients. This cause that method WriteToDb is called 5 times in 5 thread.
In all 5 cases method WriteToDb will use same data.
My aim is achieve this behavior. 5 clients called web method SomeWebMethod. Method WriteToDb will run in 5 thread.
But I would like execute first thread, then second thread ....etc and on the end 5th thread.
I don’t want run method WriteToDb in same time in 5 thread.
So maybe I can use lock.
{
private object locker = new object();
//this method will write data to database
public void WriteToDb()
{
lock(locker)
{
//write to DB
}
}
I am not sure because .net assembly is host on app domain a app domain is host on win process. I woud like to avoid deadlocks.
What happens if I have a machine with 6 CPU? Use mutex instead lock ?
Thank you for help...
I'm not particulary sure what you are writing to DB, but your question is loosely coupled with WCF to be frank, try to read CLR via C# on multithreading etc.
Also regarding WCF, you can setup how your service object is created upon requests, ie per call, per session or singleton, and for later use specify if it's methods will stuck in queue or will be called on object concurrently.
So depending on choosing architecture you can either relay on WCF ability to host single object which will have logic you described or you can go the way tried.
Links
http://msdn.microsoft.com/en-us/magazine/cc163590.aspx
http://msdn.microsoft.com/en-us/library/ms731193.aspx
A lock is fine here, but you should make your locker object static so the same object instance is used in the lock every time.
It does not matter how many cores you have - if you hold the lock on an object then any other threads that attempt to acquire the lock will wait until the lock is released.
A deadlock can only occur if you are acquiring multiple locks in different orders in different threads.
I suggest you read Joe Albahari's excellent free ebook
I am developing a Asp.Net Core component which has some interface for getting requests for some process execution.This request would be sync one where the request is accepted and submission token is returned to caller. The requests are added to a queue and processed asynchronously. Each request execution involves making some rest calls for fetching some data , executing process, etc.
How to process multiple requests from the queue in parallel whether to use Task or Parallel class
What you are describing is a series of I/O bound REST calls. What you should do is loop over those calls, awaiting each. Something like
public async Task X()
{
// add requests to queue
...
foreach (var request in queue)
{
await ExecuteRequest(request);
}
}
Parallelism in the classic sense is about threads and CPU bound work, and so isn't suitable for your scenario.