Send message to set of users within a group with SignalR - signalr

Is it possible to send a message to a selection of clients within a Group in SignalR?
...without having to maintain your own lists of subscribers and using context.Clients.Clients(includeConnectionIds[])

SignalR does not have state by default, or they actually do with groups... But it is not very dynamic. I had the same issue as you are having. I needed to send a message to a subset of a group.. Or actually I needed to send to clients where age was between x and y...
This is impossible with groups so you have to implement the functionality your self.
Bloated and ugly...
I actually ended up using Xsocket.net instead where I can target client with lambda expressions without messing around with custom static lists/groups etc.
Do not know your requirements but sending to any subset if clients is done by:
this.SendTo(p => p.Age > x && p.Age < y, new {Message="hello world"},"message");
//Signature of the extension method is...
//SendTo<T>(this IXSocketController socket, Func<T, bool> expression, object obj, string eventname)
//So you can actually send to clients on any controller is specifying T
Best of luck with whatever you choose.

In SignalR 2.0 you can send to a many groups or many connections in a single call via Clients.Groups or Clients.Clients.

Related

Streaming multiple events of different types using Axon

I am working on building streaming APIs for client/server communication using Axon and ServerSentEvents and not sure if it is possible to stream and identify multiple different events using Axon query update emitter and subscription query.
I am using Axon QueryUpdateEmitter.emit to emit the events from a projection based on different events. Emitter is emitting in projection whereas subscription query is taking place in the REST API that is supposed to stream the server sent events to client.
For example,
I want to emit 3 different events for a use case which creates, updates and deletes an entity.
I am wondering if we can emit different types of data from different events but still combine in one stream, i.e. send actual object upon entity create and update in the emitter but, since I don’t have any entity/data to emit in case of delete, I thinking whether to send a simple message for delete?
I also want a way to specify the type of event while emitting so when ServerSentEvent is build from subscription query, I can specify the type/action (for ex, differentiate between create or update event) along with data.
Main idea is to emit different events and add them in one stream despite knowing all events may not return exactly same data (create, update vs. delete) as part of one subscription query and to be able to accurately identify the event and specify in the stream of ServerSentEvents with appropriate event type.
Any ideas on how I can achieve this?
Here's how I am emitting an event upon creation using QueryUpdateEmitter:
#EventHandler
public void on(LibraryCreatedEvent event, #Timestamp Instant timestamp) {
final LibrarySummaryEntity librarySummary = mapper.createdEventToLibrarySummaryEntity(event, timestamp);
repository.save(librarySummary);
log.debug("On {}: Saved the first summary of the library named {}", event.getClass().getSimpleName(), event.getName());
queryUpdateEmitter.emit(
AllLibrarySummariesQuery.class,
query -> true,
librarySummary
);
log.debug("emitted library summary: {}", librarySummary.getId());
}
Since I need to distinguish between create and update so I tried using GenericSubscriptionQueryUpdateMessage.asUpdateMessage upon update event and added some metadata along with it but not sure if that is in the right direction as I am not sure how to retrieve that information during subscription query.
Map<String, String> map = new HashMap();
map.put(“Book Updated”, event.getLibraryId());
queryUpdateEmitter.emit(AllLibrarySummariesQuery.class,query → true,GenericSubscriptionQueryUpdateMessage.asUpdateMessage(librarySummary).withMetaData(map));
Here's how I am creating subscription query:
SubscriptionQueryResult<List<LibrarySummaryEntity>, LibrarySummaryEntity> result = queryGateway.subscriptionQuery(new AllLibrarySummariesQuery(),ResponseTypes.multipleInstancesOf(LibrarySummaryEntity.class),ResponseTypes.instanceOf(LibrarySummaryEntity.class));
And the part where I am building server sent event:
(.event is where I want to specify the type of event - create/update/delete and send the applicable data accordingly)
Flux<ServerSentEvent<LibrarySummaryResponseDto>> sseStream = result.initialResult()
.flatMapMany(Flux::fromIterable).map(value -> mapper.libraryEntityToResponseDto(value))
.concatWith((streamingTimeout == -1)? result.updates().map(value -> mapper.libraryEntityToResponseDto(value)): result.updates().take(Duration.ofMinutes(streamingTimeout)).map(value -> mapper.libraryEntityToResponseDto(value)))
.log()
.map(created -> ServerSentEvent.<LibrarySummaryResponseDto>builder()
.id(created.getId())
.event("library creation")
.data(created).build())
.doOnComplete(() -> {log.info("streaming completed");})
.doFinally(signal -> result.close());
As long as the object you return matches the expected type when making the subscription query, you should be good!
Note that this means you will have to make a response object that can fit your scenarios. Whether response is something you'd emit as the update (through the QueryUpdateEmitter) or a map operation from where you return the subscription query, is a different question, though.
Ideally, you'd decouple your internal messages from what you send outward, like with SSE. To move to a more specific solution, you could benefit from having a Flux response type. You can simply attach any mapping operations to adjust the responses emitted by the QueryUpdateEmitter to your desired SSE format.
Concluding, the short answer is "yes you can," as long as the emitted response object matches the expected update type when dispatching the subscription query on the QueryGateway.

Returning multiple items in gRPC: repeated List or stream single objects?

gRPC newbie. I have a simple api:
Customer getCustomer(int id)
List<Customer> getCustomers()
So my proto looks like this:
message ListCustomersResponse {
repeated Customer customer = 1;
}
rpc ListCustomers (google.protobuf.Empty) returns (ListCustomersResponse);
rpc GetCustomer (GetCustomerRequest) returns (Customer);
I was trying to follow Googles lead on the style. Originally I had returns (stream Customer) for GetCustomers, but Google seems to favor the ListxxxResponse style. When I generate the code, it ends up being:
public void getCustomers(com.google.protobuf.Empty request,
StreamObserver<ListCustomersResponse> responseObserver) {
vs:
public void getCustomers(com.google.protobuf.Empty request,
StreamObserver<Customer> responseObserver) {
Am I missing something? Why would I want to go through the hassle of creating a ListCustomersResponse when I can just do stream Customer and get the streaming functionality?
The ListCustomersResponse is just streaming the whole list at once vs streaming each customer. Googles preference seems to be to return the ListCustomersResponse style all of the time.
When is it appropriate to use the ListxxxResponse vs the stream response?
This question is hard to answer without knowing what reference you're using. It's possible there's a miscommunication, or that the reference is simply wrong.
If you're looking at the gRPC Basics tutorial though, then I might have an inkling as to what caused a miscommunication. If that's indeed your reference, then it does not recommend returning repeated fields for streamed responses; your intuition is correct: you would just want to stream the singular Customer.
Here is what it says (screenshot intentional):
You might be reading rpc ListFeatures(Rectangle) as meaning an endpoint that returns a list [noun] of features. If so, that's a miscommunication. The guide actually means an endpoint to list [verb] features. It would have been less confusing if they just wrote rpc GetFeatures(Rectangle).
So, your proto should look more like this,
rpc GetCustomers (google.protobuf.Empty) returns (stream Customer);
rpc GetCustomer (GetCustomerRequest) returns (Customer);
generating exactly what you suspected made more sense.
Update
Ah I see, so you're looking at this example in googleapis:
// Lists shelves. The order is unspecified but deterministic. Newly created
// shelves will not necessarily be added to the end of this list.
rpc ListShelves(ListShelvesRequest) returns (ListShelvesResponse) {
option (google.api.http) = {
get: "/v1/shelves"
};
}
...
// Response message for LibraryService.ListShelves.
message ListShelvesResponse {
// The list of shelves.
repeated Shelf shelves = 1;
// A token to retrieve next page of results.
// Pass this value in the
// [ListShelvesRequest.page_token][google.example.library.v1.ListShelvesRequest.page_token]
// field in the subsequent call to `ListShelves` method to retrieve the next
// page of results.
string next_page_token = 2;
}
Yeah, I think you've probably figured the same by now, but here they have chosen to use a simple RPC, as opposed to a server-side streaming RPC (see here). I emphasize this because, I think the important choice is not the stylistic difference between repeated versus stream, but rather the difference between a simple request-response API versus a more complex and less-ubiquitous streaming API.
In the googleapis example above, they're defining an API that returns a fixed and static number of items per page, e.g. 10 or 50. It would simply be overcomplicated to use streaming for this, when pagination is already so well-understood and prevalent in software architecture and REST APIs. I think that is what they should have said, rather than "a small number." So the complexity of streaming (and learning cost to you and future maintainers) has to justified, that's all. Suppose you're actually fetching thousands of (x, y, z) items for a Point Cloud or you're creating a live-updating bid-ask visualizer for some cryptocurrency, e.g.
Then you'd start asking yourself, "Is a simple request-response API my best option here?" So it just tends to be that, the larger the number of items needing to be returned, the more streaming APIs start to make sense. And that can be for conceptual reasons, e.g. the items are a live-updating stream in time like the above crypto example, or architectural, e.g. it would be more efficient to start displaying results in the UI as partial data streams back. I think the "small number" thing you read was an oversimplification.

Generically forwarding a GRPC call

I have a GRPC API where, following a refactor, a few packages were renamed. This includes the package declaration in one of our proto files that defines the API. Something like this:
package foo;
service BazApi {
rpc FooEventStream(stream Ack) returns (stream FooEvent);
}
which was changed to
package bar;
service BazApi {
rpc FooEventStream(stream Ack) returns (stream FooEvent);
}
The server side is implemented using grpc-java with scala and monix on top.
This all works fine for clients that use the new proto files, but for old clients that were built on top of the old proto files, this causes problems: UNIMPLEMENTED: Method not found: foo.BazApi/FooEventStream.
The actual data format of the messages passed over the GRPC API has not changed, only the package.
Since we need to keep backwards compatibility, I've been looking into a way to make the old clients work while keeping the name change.
I was hoping to make this work with a generic ServerInterceptor which would be able to inspect an incoming call, see that it's from an old client (we have the client version in the headers) and redirect/forward it to the renamed service. (Since it's just the package name that changed, this is easy to figure out e.g. foo.BazApi/FooEventStream -> bar.BazApi/FooEventStream)
However, there doesn't seem to be an elegant way to do this. I think it's possible by starting a new ClientCall to the correct endpoint, and then handling the ServerCall within the interceptor by delegating to the ClientCall, but that will require a bunch of plumbing code to properly handle unary/clientStreaming/serverStreaming/bidiStreaming calls.
Is there a better way to do this?
If you can easily change the server, you can have it support both names simultaneously. You can consider a solution where you register your service twice, with two different descriptors.
Every service has a bindService() method that returns a ServerServiceDefinition. You can pass the definition to the server via the normal serverBuilder.addService().
So you could get the normal ServerServiceDefinition and then rewrite it to the new name and then register the new name.
BazApiImpl service = new BazApiImpl();
serverBuilder.addService(service); // register "bar"
ServerServiceDefinition barDef = service.bindService();
ServerServiceDefinition fooDefBuilder = ServerServiceDefinition.builder("foo.BazApi");
for (ServerMethodDefinition<?,?> barMethodDef : barDef.getMethods()) {
MethodDescriptor desc = barMethodDef.getMethodDescriptor();
String newName = desc.getFullMethodName().replace("foo.BazApi/", "bar.BazApi/");
desc = desc.toBuilder().setFullMethodName(newName).build();
foDefBuilder.addMethod(desc, barMethodDef.getServerCallHandler());
}
serverBuilder.addService(fooDefBuilder.build()); // register "foo"
Using the lower-level "channel" API you can make a proxy without too much work. You mainly just proxy events from a ServerCall.Listener to a ClientCall and the ClientCall.Listener to a ServerCall. You get to learn about the lower-level MethodDescriptor and the rarely-used HandlerRegistry. There's also some complexity to handle flow control (isReady() and request()).
I made an example a while back, but never spent the time to merge it to grpc-java itself. It is currently available on my random branch. You should be able to get it working just by changing localhost:8980 and by re-writing the MethodDescriptor passed to channel.newCall(...). Something akin to:
MethodDescriptor desc = serverCall.getMethodDescriptor();
if (desc.getFullMethodName().startsWith("foo.BazApi/")) {
String newName = desc.getFullMethodName().replace("foo.BazApi/", "bar.BazApi/");
desc = desc.toBuilder().setFullMethodName(newName).build();
}
ClientCall<ReqT, RespT> clientCall
= channel.newCall(desc, CallOptions.DEFAULT);

Is there a tangible benefit to using wrapper requests over plain messages in grpc service calls?

Lets say we have a message containing ID of some record in the database
message Record {
uint64 id = 1;
}
We also have an rpc call that returns all of the rows from table DATA that said record is mentioned in.
rpc GetDataForRecord(Record) returns (Data) {}
If we, for example, wrap Record in
RqData{
Record id = 1;
}
then once we need to only return, for example, "active" data, we won't need to make
GetActiveDataForRecord
instead we could extend RqData as:
RqData{
Record id = 1;
bool use_active = 2;
}
and use
rpc GetDataForRecord(RqData) returns (Data) {}
and clients that know of this new functionality will be able to call it, while older clients will just use it as it was passing only Record part within the Rq wrapper, without specifying active or not.
Here's the question: is there really a reason to use this kind of wrapping of everything into a separate request, or am I overthinking things and just passing plain structures will do?
I am kinda trying to think about the future, but not sure if I am not overcomplicating things.
In general, making a method-specific request and response is a Good Thing™ and is encouraged. For a Foo method you'd have FooRequest and FooResponse. Having specialized messages for the method allows you to add new "arguments," as you mentioned.
But for some cases it turns out fine to break the pattern and avoid the wrapping; it's a judgement call. Although you're asking from a different perspective, you may be interested in this answer about related methods.

Client-Server how to identify two different methods

I am writing a code for Client-Server and there are two possibilities.
The user will request a specific information A to be transmitted.
The user will request a specific information B to be transmitted.
I would like to identify what the client want in my server side and how the client will do that.
Any other ideas?
I know is quite old question but I think what will be a good idea is to use the Chain of Responsibility Design Pattern!
The idea is that you can use a single port and send your request to Receiver 1, Receiver 1 will decide if can handle this request if not, will pass the request to the Receiver 2, Receiver 2 will have to do the same decision and if can handle the request, then will send the response back to the Sender.
So we have the following properties:
One port is required
The Sender(or the Client in other words) is only aware of the 1st Receiver.
The responsible receiver will return a response directly to the sender/client even if the sender/client is not aware of that specific receiver.
Reduced coupling
Dynamically manage the request handlers.
Furthermore, at the end of the chain, you can add behavior to indicate something like a final response, or a default response if the request send has no responsible class to handle it.
UML
Example
Depending on the size of the information, you can always transmit both information through one pipe and then decipher the needed one on the user side
string data = // .. data transmitted.
string[] dataSplit = data.Split(SEPARATOR);
// dataSplit[0] is type of information
switch(dataSplit[0]) {
case 'Name':
...
break;
case 'OS':
...
break;
}
Do you understand ?

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