we are looking at socket io implementation for a chat application.
Finding acknowledgement support to handle missing messages while broadcast we are looking at acknowledgement support.
as per documentation socket io does not have support for callbacks in broadcast / rooms.
e.g. in "Room 1" we send broadcast message to all sockets within that room. how we check without call back that some users/sockets missed the message. and how we will handle that in system.
below code does not work.
io.sockets.in(data.room).emit('message', data, function(responseData){
console.log(responseData);
});
according to below issue
https://github.com/socketio/socket.io-redis/issues/30
Callbacks are not supported when broadcasting.
what are the other methods to handle this scenario.
In order to solve your problem, the messages for a room need to be persisted somewhere, and then re-sent to individual clients as needed.
The most obvious place to store messages is server-side, in a datastore (e.g. Redis). Store each conversation effectively as a list of events, appending new events as they happen.
A simple scheme works as follows:
Each broadcast message has a UUID attached to it. When the server handles a new message, it appends the message to the list for that 'room'.
When a client connects/re-connects, it sends a message (e.g. 'LAST_MESSAGE_RECEIVED') indicating the UUID of the last message it received.
When the server receives one of these 'LAST_MESSAGE_RECEIVED' messages, it checks if that is the latest message for the room, and if not, it emits a message just to that individual socket with an array of the missed messages. The client is now back up-to-date.
Alternative: if you don't need to keep a history after a conversation ends, you could be clever and use the fact that other clients are already storing the messages, and ask the clients to re-send messages in a peer-to-peer kind of way. This avoids you needing to have your own server-side datastore.
Related
Recently I am trying to use MassTransit in our microservice ecosystem.
According to MassTransit vocabulary and from documents my understanding is :
Publish: Sends a message to 1 or many subscribers (Pub/Sub Pattern) to propagate the message.
Send: Used to send messages in fire and forget fashion like publish, but instead It is just used for one receiver. The main difference with Publish is that in Send if your destination didn't receive a message, it would return an exception.
Requests: uses request/reply pattern to just send a message and get a response in a different channel to be able to get response value from the receiver.
Now, my question is according to the Microservice concept, to follow the event-driven design, we use Publish to propagate messages(Events) to the entire ecosystem. but what is exactly the usage (use case) of Send here? Just to get an exception if the receiver doesn't exist?
My next question is that is it a good approach to use Publish, Send and Requests in a Microservices ecosystem at the same time? like publish for propagation events, Send for command (fire and forget), and Requests for getting responses from the destination.
----- Update
I also found here which Chris Patterson clear lots of things. It also helps me a lot.
Your question is not related to MassTransit. MassTransit implements well-known messaging patterns thoughtfully described on popular resources such as Enterprise Integration Patterns
As Eben wrote in his answer, the decision of what pattern to use is driven by intent. There are also technical differences in the message delivery mechanics for each pattern.
Send is for commands, you tell some other service to do something. You do not wait for a reply (fire and forget), although you might get a confirmation of the action success or failure by other means (an event, for example).
It is an implementation of the point-to-point channel, where you also can implement competing consumers to scale the processing, but those will be instances of the same service.
With MassTransit using RabbitMQ it's done by publishing messages to the endpoint exchange rather than to the message type exchange, so no other endpoints will get the message even though they can consume it.
Publish is for events. It's a broadcast type of delivery or fan-out. You might be publishing events to which no one is listening, so you don't really know who will be consuming them. You also don't expect any response.
It is an implementation of the publish-subscribe channel.
MassTransit with RabbitMQ creates exchanges for each message type published and publishes messages to those exchanges. Consumers create bindings between their endpoint exchanges and message exchanges, so each consumer service (different apps) will get those in their independent queues.
Request-response can be used for both commands that need to be confirmed, or for queries.
It is an implementation of the request-reply message pattern.
MassTransit has nice diagrams in the docs explaining the mechanics for RabbitMQ.
Those messaging patterns are frequently used in a complex distributed system in different combinations and variations.
The difference between Send and Publish has to do with intent.
As you stated, Send is for commands and Publish is for events. I worked on a large enterprise system once running on webMethods as the integration engine/service bus and only events were used. I can tell you that it was less than ideal. If the distinction had been there between commands and events it would've made a lot more sense to more people. Anyway, technically one needs a message enqueued and on that level it doesn't matter, which is why a queueing mechanism typically would not care about such semantics.
To illustrate this with a silly example: Facebook places and Event on my timeline that one of my friends is having a birthday on a particular day. I can respond directly (send a message) or I could publish a message on my timeline and hope my friend sees it. Another silly example: You send an e-mail to PersonA and CC 4 others asking "Please produce report ABC". PersonA would be expected to produce the report or arrange for it to be done. If that same e-mail went to all five people as the recipient (no CC) then who gets to do it? I know, even for Publish one could have a 1-1 recipient/topic but what if another endpoint subscribed? What would that mean?
So the sender is responsible, still configurable as subscriptions are, to determine where to Send the message to. For my own service bus I use an implementation of an IMessageRouteProvider interface. A practical example in a system I once developed was where e-mails received had to have their body converted to an image for a content store (IBM FileNet P8 if memory serves). For reasons I will not go into the systems were stopped each night at 20h00 and restarted at 6h00 in the morning. This led to a backlog of usually around 8000 e-mails that had to be converted. The conversion endpoint would process a conversion in about 2 seconds but that still takes a while to work through. In the meantime the web front-end folks could request PDF files for conversion to paged TIFF files. Now, these ended up at the end of the queue and they would have to wait hours for that to come back. The solution was to implement another conversion endpoint, with its own queue, and have the web front-end configured to send the same message type, e.g. ConvertDocumentCommand to that "priority" queue for processing. Pretty easy to do. Now, if that had been a publish how would I do that split? The same event going to 2 different endpoints under different circumstances? Well, you could have another subscription store for your system but now you'd need to maintain both. There could be another answer such as coding this logic into the send bit but that is a design choice and would require coding changes.
In my own Shuttle.Esb service bus I only have Send and Publish. For request/response both the sender and receiver have an inbox and a request would be sent (Send) to the receiver and it in turn could reply (also a Send but uses the sender's URI).
From the docs it is clear that message delivery is not guaranteed by django-channels. I want to implement a way in my chat app so that there is a guarantee that messages are delivered to the client.
I am using redis, if that matter. When I say messages I don't mean chat text messages. I haven't implemented that part and don't need that for now. I just have video call feature. What gets lost sometimes is when users join the room the room members list doesn't reach them. So I want to do something like:
Client connects.
Servers creates a record of the event in step 3 below.
Server sends the list of room members event to the client.
Client process and acknowledges the list.
Server on receiving the acknowledgment from the client marks the list sent event as SUCCESS or something.
My questions are.
Is this approach good?
And should I use a new model to store the message events so that server can know which messages to sent and which have been already sent successfully or is there anyway to do it in redis db?
I am new to this so I maybe overlooking something that you as experienced guys know of. Please guide me with your precious inputs.
Thanks
I'm designing a quite complicated system and was wondering what the best way is to put a jms consumer (activemq, vm protocol, non persitent) inside a netty handler.
Let me explain, i have several clients connecting to my netty server using websockets. For every client connection i create a jms consumer that listens for interesting messages on one or more topics. If a interesting message arrives i need to do a extra step (additional filtering) before sending the message to the client using the websocket.
Is the following a good way to do this:
inside a SimpleChannelInboundHandler i declare a private non static consumer
the consumer is initialized in channelActive
the consumer is destroyed in channelInactive
when a message is received by consumer i do the extra filter a send it using ctx.channel().write()
In this setup i'm a bit worried that the consumer might turn into slow consumer and slow everything down, cause the websocket goes over the internet.
I came up with a more complex one to decouple the "receiving of message by consumer" and "sending of message through a websocket".
inside a SimpleChannelInboundHandler i declare a private non static consumer
the consumer is initialized in channelActive
the consumer is destroyed in channelInactive
when a message is received by consumer i put it in a blockedqueue
every minute i let a thread (created for every client) look in the queue and send the found messages to the client using ctx.channel().write().
At this point i'm a bit worried about the extra thread per client.
Or is there maybe a better way to accomplish this task?
This is a classic slow consumer problem and the first step to resolving it is to determine what the appropriate action is when a slow consumer is detected. If it is acceptable that the slow consumer misses messages then the solution is some variation on dropping messages or unsubscribing them from the feed. For example, if it's acceptable that the client misses messages then, when one is received from JMS, check if the channel is writable. If it isn't, drop the message. If you want to give yourself a bit more of a buffer (although OS buffers are quite large) you can track the number of write completion future's that haven't completed (ie the messages haven't been written to the OS send buffer) and drop messages if there are too many outstanding write requests.
If the client may not miss messages, and is consistently slow, then the problem is more difficult. One option might be to divert messages to a JMS queue with a specific header value, then open a new consumer that reads messages from that queue using a JMS selector. This will put more load on the JMS server but might be appropriate for temporary slowness and hopefully it won't interfere with you main topic feeds. Alternatively you might want to stash the messages in a different store, such as a database, so you can poll for messages when they can be sent. If you do this right a single polling thread can cope with many clients (query for clients which have outstanding messages, then for each client, load a bunch of messages). However this isn't as convenient as using JMS.
I wouldn't go with option 2 because the blocking queue is only going to solve the problem temporarily, and you can achieve the same thing by tracking how many write operations are waiting to complete.
I'm just starting understanding and trying ZeroMQ.
It's not clear to me how could I have a two way communication between more than two actors (publisher and subscriber) so that each component is able both to read and write on the MQ.
This would allow to create event-driven architecture, because each component could be listening for an event and reply with another event.
Is there a way to do this with ZeroMQ directly or I should implement my own solution on top of that?
If you want simple two-way communication then you simply set up a publishing socket on each node, and let each connect to the other.
In an many to many setup this quickly becomes tricky to handle. Basically, it sounds like you want some kind of central node that all nodes can "connect" to, receive messages from and, if some conditions on the subscriber are met, send messages to.
Since ZeroMq is a simple "power-socket", and not a message queue (hence its name, ZeroMQ - Zero Message Queue) this is not feasible out-of-the-box.
A simple alternative could be to let each node set up an UDP broadcast socket (not using ZeroMq, just regular sockets). All nodes can listen in to whatever takes place and "publish" its own messages back on the socket, effectively sending it to any nodes listening. This setup works on a LAN and in a setting where it is ok for messages to get lost (like periodical state updates). If the messages needs to be reliable (and possibly durable) you need a more advanced full-blown message queue.
If you can do without durable message queues, you can create a solution based on a central node, a central message handler, to which all nodes can subscribe to and send data to. Basically, create a "server" with one REP (Response) socket (for incoming data) and one PUB (Publisher) socket (for outgoing data). Each client then publishes data to the servers REP socket over a REQ (Request) socket and sets up a SUB (Subscriber) socket to the servers PUB socket.
Check out the ZeroMq guide regarding the various message patterns available.
To spice it up a bit, you could add event "topics", including server side filtering, by splitting up the outgoing messages (on the servers PUB socket) into two message parts (see multi-part messages) where the first part specifies the "topic" and the second part contains the payload (e.g. temp|46.2, speed|134). This way, each client can register its interest in any topic (or all) and let the server filter out only matching messages. See this example for details.
Basically, ZeroMq is "just" an abstraction over regular sockets, providing a couple of messaging patterns to build your solution on top of. However, it relieves you of a lot of tedious work and provides scalability and performance out of the ordinary. It takes some getting used to though. Check out the ZeroMq Guide for more details.
I’m writing a server/client game, a typical scenario looks like this: one client (clientA) send a message to the server, there is a MessageDrivenBean in server to handle such messages. After the MDB finished its job, it sends the result message back to another client (clientB).
In my opinion I only need two queues for such communication, one for input the other for output. Creating new queue for each connection is not a good idea, right?
The Input queue is relative clear, if more clients are sending message at the same time, the messages are just waiting in the queue, while there are more MDB instances in server, that should not a big performance issue.
But on the other side I am not quite clear about the output queue, should I use a topic instead of a queue? Every client is listening the output queue, one of them gets the new message and checks the property to determine if the message is to it, if not, it rollback the transaction, the message goes back to queue and be ready for other client … It should work but must be very slow. If I use topic instead, every client gets a copy of the message, if it’s not to it, just ignores the message. It should be better, right?
I’m new about message system. Is there any suggestion about my implementation? Thanks!
To begin with, choosing JMS as a gaming platform is, well, unusual — businesses use JMS brokers for delivery reliability and transaction support. Do you really need this heavy lifiting in a game? Shouldn't you resort to your own HTTP-based protocol, for example?
That said, two queues are a standard pattern for point-to-point communication. Creating a queue for a new connection is definitely not OK — message-driven beans are attached to queues at deployment time, so you won't be able to respond to queue creation events. Besides, queues are not meant to be created and destroyed in short cycles, they're rather designed to be long-living entities. If you need to deliver a message to one precise client, have the client listen on the server response queue with a message selector set to filter only the messages intended for this client (see javax.jms.Message API).
With topics it's exactly as you noted — each connected client will get a copy of the message — so again, it's not a good pattern to send to n clients a message that has to be discarded by n-1 clients.
MaDa;
You could stick one output queue (or topic) and simply tag the message with a header that identifies the intended client. Then, clients can listen on the queue/topic using a selector. Hopefully your JMS implementation has efficient server-side listener evaluation.