We are using the Azure SignalR service from functions to send messages back to our UI and all is working without issue. But I can't find a definitive answer on how long lived the ServiceManager or HubContext should be.
At the moment each time we want to send a message to the UI we call a class we have written which does the following:
using var serviceManager = return new ServiceManagerBuilder().WithOptions(option =>
{
option.ConnectionString = _connectionString;
option.ServiceTransportType = ServiceTransportType.Persistent;
})
.WithNewtonsoftJson()
.BuildServiceManager();
await using var hubContext = await serviceManager .CreateHubContextAsync(hubName, System.Threading.CancellationToken.None);
await hubContext.Clients.Group(group).SendAsync(method, message);
This all works fine, but we are creating a new ServiceManager and ServiceHubContext every time we send a message.
The samples I have looked at do not include running in functions where we inject a service which handles publishing. Should either of these be Singleton? The functions we have are processing data and sending updates in a loop so we may send 100s of messages in a single function.
Related
I am new in flutter. I need to call 5 API network calls in a single screen. It is taking very long time while i am using Async/await. How can we execute it on separate threads parallelly using isolate or anything else like it?
You may use isolate for this purpose isolate is a sort of multi threading in dart. Isolate creates a new thread and execute operation on the new thread so that the load will be distributed. You cannot send variables as a data back and forth but use port to send messages.
Here is a simple example of isolate with an API call and sending data back to the main thread using port.
First lets create a function which will be the entrypoint of isolate:
static entryPoint(SendPort sendPort)async{
var response = await http.get('https://www.thecocktaildb.com/api/json/v1/1/search.php?s=margarita');
sendPort.send(response.body); //sending data back to main thread's function
}
Now lets create isolate:
static void callApi()async{
var recievePort = new ReceivePort(); //creating new port to listen data
await Isolate.spawn(entryPoint, recievePort.sendPort);//spawing/creating new thread as isolates.
recievePort.listen((message) { //listening data from isolate
print(message);
});
}
You can use dio package and call multiple concurrent API requests, do check the documentation:
Package: https://pub.dev/packages/dio
You can use Future.wait()
Here is the answer with an example
I'm using .NET Core app with a PostgreSQL database (with Npgsql) combined with SignalR to receive real-time data and latest data entries. However, I am not receiving the latest entry, and sometimes the Clients.All.SendAsync method sends more than one entry to the client. Here is my code:
Hub method that sends new data to client:
public async Task SendForexAsync(string name)
{
var product = GetForex(name);
await Clients.All.SendAsync("CurrentData", product);
using (var conn = new NpgsqlConnection(ApplicationDbContext.GetConnectionString()))
{
conn.Open();
var cmd = new NpgsqlCommand("LISTEN new_forex", conn).ExecuteNonQuery();
conn.Notification += async (o, e) =>
{
var newProduct = GetForex(name);
await Clients.All.SendAsync("NewData", newProduct);
};
while (true)
{
await conn.WaitAsync();
}
}
}
Console app that periodically polls for new data from an API:
var addedStocksDJI = FetchNewStocks("DJI");
if (addedStocksAAPL > 0 || addedStocksDJI > 0)
{
using (var conn = new NpgsqlConnection(ApplicationDbContext.GetConnectionString()))
{
conn.Open();
var cmd = new NpgsqlCommand("NOTIFY new_stocks", conn).ExecuteNonQuery();
}
}
The other code of the app is most definitely correct because I was receiving new and correct data before I tried implementing the LISTEN/NOTIFY feature. But now, I get one (or more) of entries of newProduct on my client, but it is the "old" product, that is, the database does not query and send the latest entries, but only the old ones via SignalR. When I refresh the page manually, the new data is correctly displayed, though.
I believe it has something to do with a single connection being open so I constantly receive only the "old" set of data, but even if that is the case, I am unable to figure out why I sometimes get more than one packet of data, even though I am only trying to send one, and I am calling NOTIFY only once.
I figured it out. Hopefully this will help someone else who gets stuck with this in the future!
The issue was that I was declaring my dbContext via .NET Core's dependency injection in my Hub class, which created the context only once per that class, and also because of that per page or WebSocket transaction. Which is why I was unable to get the latest data, I assume, since the dbContext was "old" and unaware of changes.
I fixed the problem by using a dbContext via the using scheme inside of my methods, twice in my SendForexAsync method (once per every call of the GetForex function), as well as in the GetForex function itself. That way, a dbContext is created and disposed of immediately, so the next time I poll the database for new data via the GetForex function (when I get a notification from the database due to the NOTIFY from the console app), a new instance of dbContext is created which can contain that new data.
I am building a bot for for Facebook Messenger using Microsoft Bot Framework. I am planning to use CosmosDB for State Management and also as my backend data store. (I am not stuck to CosmosBD and can use any other store if needed)
I need to send daily/weekly proactive messages(push notifications) to users based on their time preference. I will capturing their time preference when they first interact with the bot.
What is the best way to deliver these notifications?
As I will be storing these preferences in CosmosDB, I am thinking using ComosDB trigger of creating an Azure Function and schedule it based on the user time preference. This Azure function will make a call to my webhook which will deliver these messages. If requried, I will change Function schedule when a user changes his/her preference.
My questions are:
Is this a good approach?
Are there any other alternatives (Notifications Hub?)
I should be able to set specific times for notifications (like at the top of the hour or something like that), does it make sense to schedule an Azure Function to run at these hours rather than creating a function based on user preference (I can actually combine these two approaches too)
Thank you in advance.
First, I don't think there's any "right" answer to be given here; it's going to depend a lot on your domain's specific needs. Scale is going to play a major factor in the design of this. Will you have 100 users? 10000 users? 1mil users? I'm going to assume you want to design for maximum scale up front, but it could be overkill.
First, based on what you've described, I don't think a CosmosDB trigger is necessarily the solution to your problem because that's only going to fire when the preference data is created/updated. I assume that, from that point forward, your function needs to continuously fire at the time slot they've opted into, correct?
So let's pretend you let people choose from the 24hrs in the day. A naïve approach would be to simply use a scheduled trigger that fires up every hour, queries the CosmosDB for all the documents where the preference is set to that particular hour and then begins sending out notifications from there. The problem is how you scale from there and deal with issues of idempotency in the face of failures.
First off, a timer trigger only ever spins up one instance. If you were to just go query the CosmosDB documents and start processing them one by one in the scope of that single trigger, you'd hit a ceiling relatively quickly on how many notifications you can scale to. Instead what you'd want to do is use that timer trigger to fan out the notifications to as many "worker" function instances as possible. The timer trigger can act as the orchestrator in the sense that it can own the query against the CosmosDB and then turn each document result it finds for that particular notification time window into a message that it places on a queue to be processed by a separate function which will scale out on its own.
There are actually a couple ways you can accomplish this with Azure Functions, it really depends on how early an adopter of technology you are comfortable with being.
The first is what I would call the "manual" way which would be done by simply using the existing Azure Storage Queue extension by taking an IAsyncCollector<YourNotificationWorkerMessage> as a parameter to the timer function that's bound to the worker queue and then pumping out the messages through that. Then you write a second companion function which uses a QueueTrigger, bind it to that same queue, and it will take care of processing each message. This second function is where you get the scaling, enabling process all of the queued messages as quickly as possible based on whatever scaling parameters you choose to configure. This is the "simplest" approach
The second approach would be to adopt the newer Durable Functions extension. With that model, you don't have to directly think about creating a worker queue. You simply kick off a new instance of your orchestrator function from the timer function and the orchestrator fans out the work by invoking N "concurrent" calls to an action for each notification. Now, it happens to distribute those calls using queues under the covers, but that's an implementation detail that you need no longer maintain yourself. Additionally, if the work of delivering the notification requires more involved work and/or retry logic, you might actually consider using a sub-orchestration instead of a simple action. Finally, another added benefit of this approach, is that you can "fan back in" to your main orchestrator function once all the notifications are delivered to do some follow up work... even if that's simply some kind of event logging that the notification cycle has completed for this hour.
Now, the challenge with either of these approach is actually dealing with failure in initially fetching the candidates for notification from CosmosDB, paging through the results and making sure you actually fan all of them out in an idempotent manner. You need to deal with possible hiccups as you page and you need to deal with the fact that your whole function could be torn down and you might have to restart. Perhaps on the initial run of the 8AM notifications you got through page 273 out of 371 pages and then you got hit with a complete network connectivity fail or the VM your function was running on suffered a power failure. You could resume, but you'd need to know that you left off on page 273 and that you actually processed the 27th record out of that page and start from there. Otherwise, you risk sending double notifications to your users. Maybe that's something you can accept, maybe it's not. Maybe you're ok with the 27 notifications on that page being duplicated as long as the first 272 pages aren't. Again, this is something you need to decide for your domain, but if you want to avoid this issue your orchestrator function will need to track its progress to ensure that it doesn't send out dupes. Again I would say Durable Functions has a leg up here as it comes with the ability to configure retries. Maintaining the state of a particular run is left up to the author in either approach though.
I use pro-active dialog extensively with botframwork and messenger without any issue. During your facebook approval process you simply need to inform them you will be sending notifications trough messenger with your bot. Usually if you use it to inform your user and stay away from promotional content you should be fine.
I also use azure function to trigger the pro-active dialog from a custom controller endpoint.
Bellow sample code for azure function:
public static void Run(TimerInfo notificationTrigger, TraceWriter log)
{
try
{
//Serialize request object
string timerInfo = JsonConvert.SerializeObject(notificationTrigger);
//Create a request for bot service with security token
HttpRequestMessage hrm = new HttpRequestMessage()
{
Method = HttpMethod.Post,
RequestUri = new Uri(NotificationEndPointUrl),
Content = new StringContent(timerInfo, Encoding.UTF8, "application/json")
};
hrm.Headers.Add("Authorization", NotificationApiKey);
log.Info(JsonConvert.SerializeObject(hrm));
//Call service
using (var client = new HttpClient())
{
Task task = client.SendAsync(hrm).ContinueWith((taskResponse) =>
{
HttpResponseMessage result = taskResponse.Result;
var jsonString = result.Content.ReadAsStringAsync();
jsonString.Wait();
if (result.StatusCode != System.Net.HttpStatusCode.OK)
{
//Throw what ever problem as an exception with details
throw new Exception($"AzureFunction - ERRROR - HTTP {result.StatusCode}");
}
});
task.Wait();
}
}
catch (Exception ex)
{
//TODO log
}
}
Bellow sample code for starting the pro-active dialog:
public static async Task Resume<T, R>(string resumptionCookie) where T : IDialog<R>, new()
{
//Deserialize reference to conversation
ConversationReference conversationReference = JsonConvert.DeserializeObject<ConversationReference>(resumptionCookie);
//Generate message from bot to user
var message = conversationReference.GetPostToBotMessage();
var builder = new ContainerBuilder();
using (var scope = DialogModule.BeginLifetimeScope(Conversation.Container, message))
{
//From a cold start the service is not yet authenticated with dev bot azure services
//We thus must trust endpoint url.
if (!MicrosoftAppCredentials.IsTrustedServiceUrl(message.ServiceUrl))
{
MicrosoftAppCredentials.TrustServiceUrl(message.ServiceUrl, DateTime.MaxValue);
}
var botData = scope.Resolve<IBotData>();
await botData.LoadAsync(CancellationToken.None);
//This is our dialog stack
var task = scope.Resolve<IDialogTask>();
T dialog = scope.Resolve<T>(); //Resolve the dialog using autofac
try
{
task.Call(dialog.Void<R, IMessageActivity>(), null);
await task.PollAsync(CancellationToken.None);
}
catch (Exception ex)
{
//TODO log
}
finally
{
//flush dialog stack
await botData.FlushAsync(CancellationToken.None);
}
}
}
Your dialog needs to be registered in autofac.
Your resumptionCookie needs to be saved in your db.
You might want to check FB policy regarding proactive messages
There’s a 24h limit but it might not be totally screwed in your case
https://developers.facebook.com/docs/messenger-platform/policy/policy-overview#standard_messaging
I have a ServiceWorker registered on my page and want to pass some data to it so it can be stored in an IndexedDB and used later for network requests (it's an access token).
Is the correct thing just to use network requests and catch them on the SW side using fetch, or is there something more clever?
Note for future readers wondering similar things to me:
Setting properties on the SW registration object, e.g. setting self.registration.foo to a function within the service worker and doing the following in the page:
navigator.serviceWorker.getRegistration().then(function(reg) { reg.foo; })
Results in TypeError: reg.foo is not a function. I presume this is something to do with the lifecycle of a ServiceWorker meaning you can't modify it and expect those modification to be accessible in the future, so any interface with a SW likely has to be postMessage style, so perhaps just using fetch is the best way to go...?
So it turns out that you can't actually call a method within a SW from your app (due to lifecycle issues), so you have to use a postMessage API to pass serialized JSON messages around (so no passing callbacks etc).
You can send a message to the controlling SW with the following app code:
navigator.serviceWorker.controller.postMessage({'hello': 'world'})
Combined with the following in the SW code:
self.addEventListener('message', function (evt) {
console.log('postMessage received', evt.data);
})
Which results in the following in my SW's console:
postMessage received Object {hello: "world"}
So by passing in a message (JS object) which indicates the function and arguments I want to call my event listener can receive it and call the right function in the SW. To return a result to the app code you will need to also pass a port of a MessageChannel in to the SW and then respond via postMessage, for example in the app you'd create and send over a MessageChannel with the data:
var messageChannel = new MessageChannel();
messageChannel.port1.onmessage = function(event) {
console.log(event.data);
};
// This sends the message data as well as transferring messageChannel.port2 to the service worker.
// The service worker can then use the transferred port to reply via postMessage(), which
// will in turn trigger the onmessage handler on messageChannel.port1.
// See https://html.spec.whatwg.org/multipage/workers.html#dom-worker-postmessage
navigator.serviceWorker.controller.postMessage(message, [messageChannel.port2]);
and then you can respond via it in your Service Worker within the message handler:
evt.ports[0].postMessage({'hello': 'world'});
To pass data to your service worker, the above mentioned is a good way. But in case, if someone is still having a hard time implementing that, there is an other hack around for that,
1 - append your data to get parameter while you load service-worker (for eg., from sw.js -> sw.js?a=x&b=y&c=z)
2- Now in service worker, fetch those data using self.self.location.search.
Note, this will be beneficial only if the data you pass do not change for a particular client very often, other wise it will keep changing the loading url of service worker for that particular client and every time the client reloads or revisits, new service worker is installed.
The preamble
We're implementing a MVC2 site that needs to consume an external API via https (We cannot use WCF or even old-style SOAP WebServices, I'm afraid). We're using AsyncController wherever we need to communicate with the API, and everything is running fine so far.
Some scenarios have come up where we need to make multiple API calls in series, using results from one step to perform the next.
The general pattern (simplified for demonstration purposes) so far is as follows:
public class WhateverController : AsyncController
{
public void DoStuffAsync(DoStuffModel data)
{
AsyncManager.OutstandingOperations.Increment();
var apiUri = API.getCorrectServiceUri();
var req = new WebClient();
req.DownloadStringCompleted += (sender, e) =>
{
AsyncManager.Parameters["result"] = e.Result;
AsyncManager.OutstandingOperations.Decrement();
};
req.DownloadStringAsync(apiUri);
}
public ActionResult DoStuffCompleted(string result)
{
return View(result);
}
}
We have several Actions that need to perform API calls in parallel working just fine already; we just perform multiple requests, and ensure that we increment AsyncManager.OutstandingOperations correctly.
The scenario
To perform multiple API service requests in series, we presently are calling the next step within the event handler for the first request's DownloadStringCompleted. eg,
req.DownloadStringCompleted += (sender, e) =>
{
AsyncManager.Parameters["step1"] = e.Result;
OtherActionAsync(e.Result);
AsyncManager.OutstandingOperations.Decrement();
}
where OtherActionAsync is another action defined in this same controller following the same pattern as defined above.
The question
Can calling other async actions from within the event handler cause a possible race when accessing values within AsyncManager?
I tried looking around MSDN but all of the commentary about AsyncManager.Sync() was regarding the BeginMethod/EndMethod pattern with IAsyncCallback. In that scenario, the documentation warns about potential race conditions.
We don't need to actually call another action within the controller, if that is off-putting to you. The code to build another WebClient and call .DownloadStringAsync() on that could just as easily be placed within the event handler of the first request. I have just shown it like that here to make it slightly easier to read.
Hopefully that makes sense! If not, please leave a comment and I'll attempt to clarify anything you like.
Thanks!
It turns out the answer is "No".
(for future reference incase anyone comes across this question via a search)