I'm using socket.io and nodejs,
I have a server and I use it as my nodeJS server. What I'm trying to do is moving clients according to messages sent as client -> server -> clients
For example; client1 sending a message "MOVE-RIGHT" to server. Server redirecting this message to all clients LIKE "MOVE-RIGHT-CLIENT1" and according to this message, all clients starting to move client1 to the right direction.
The problem is, all clients may have different latency according to their network status. For example, if server->client1 communication happens in 50 ms, server->client2 communication may happen in 250 ms. Therefore, client1 does this job nearly 200 ms earlier. So we can say that these two movements are not synchronized because one of them happens earlier than other ones.
As you know latency between clients and server may be different for each clients, and also it can be different for each message for the same client.
My question is, Which method should I use to synchronize these clients, to do their jobs at the same time. Is there any feature of socket.io or nodejs about this? What would you recommend for me?
Related
I kinda understand that Websocket is the protocol that is used for real-time data flowing back & forth.
My question can be very pre-mature but couldn't find much help on the web.
Say 1000 clients are connected to a server which sends out real-time stock prices. When there is an update on the server front, how will server know all the 1000 clients to which it needs to send an update?
If this is some sort of looping that happens on the server side where all connected clients details are cached & then update will be sent out to all of them, isn't is an overhead ?
This SOF answer made some sense but didn't clear my doubt.
How does Server keep track of all Client(s) connected in Real time data pushing scenario?
It doesn't... it only keeps track of the clients it's serving specifically.
This answer is not node.js specific.
Say 1000 clients are connected to a server which sends out real-time stock prices. When there is an update on the server front, how will server know all the 1000 clients to which it needs to send an update?
To actually understand this a little better, we should consider larger numbers. i.e., let's assume 1 million clients connected to a service.
Obviously, a sane design will require redundancy, so no single service will hold all 1 million connections (and if a single server instance fails, clients can re-connect to a different server instance).
In this case, there's no single server that is aware of all clients.
It makes more sense for each server to manage it's own internal subscription / client list. Each server will also act as a pub/sub client for a centralized pub/sub service (such as a Redis cluster or whatever).
Assuming 1000 server instances, each serving 1000 clients, we would have find that the pub/sub service is aware only of 1,000 "clients" (server instances). Each server is unaware of the other clients, it's only aware of the 1,000 clients it's managing.
If this is some sort of looping that happens on the server side where all connected clients details are cached & then update will be sent out to all of them, isn't is an overhead?
The algorithm itself is implementation specific, but in general, each server will incur some overhead in order to manage the pub/sub layer.
However, since each server only manages a small subset of the total client count, the overhead is distributed across a number of systems.
Channel Oriented vs. Connection Oriented Design
I should probably note that the pub/sub design isn't connection oriented.
The server isn't (or shouldn't be) looping over all the connections asking "are you subscribed to this channel"?.
Rather, pub/sub design assumes a "channel" oriented design, where it locates the channel object(s) and loops over a client list.
On one hand, this approach might (or might not) consume more memory. Since each "channel" should contain a list of clients listening to that channel, a single client object might belong to more than a single list.
On the other hand, the loop has less code branches and experiences less overhead than a connection oriented design. Also, this approach allows for pub/sub clients that aren't connection bound (such as internal hooks / callbacks).
Say 1000 clients are connected to a server which sends out real-time stock prices. When there is an update on the server front, how will server know all the 1000 clients to which it needs to send an update?
Socket.io already keeps track by itself and its pretty easy to emit to all connected clients.
Socket.io - Emit Cheatsheet
If you are worried about what would happen when your user-base grows, you can scale your service to multiple nodes.
If you actually end up scaling and have more than one server node, then you can use
socketio-redis.
Adapter to enable broadcasting of events to multiple separate socket.io server nodes.
I have a node server accepting websocket connections from the clients. Each client can broadcast a message to all of the other clients.
UPDATE: I am using https://github.com/websockets/ws as my library of choice.
At the moment, the server has an array with all of the connections. Each connection has a tabId. When one of the client emits a message, I go through all of the connections and check: if the connection's tabId doesn't match, I send the message to the client.
For loading issues, I am facing the problem of having to have more than one server. So, there will be say two servers, each one with a number of clients.
How do I make sure that a message gets broadcast to all of the websocket clients, and not only the ones connected to the same server?
One possible solution I thought is to have the connections stored on a database, where each record has the tabId and the serverId. However, even a simple broadcast gets tricky as messages to "local" sockets are easy to broadcast (the socket is local and available) whereas messages to "remote" sockets are tricky, and would imply intra-server communication.
Is there a good pattern to solve this? Surely, this is something that people face every day.
You could use a messagequeue like RabbitMQ.
When a client logs in to your server, create a consumer which listens to a queue which will receive messages directed to that particular client. And when the clients are sending messages, just use a publisher to publish them to the recipients queue.
This way it doesn't matter and you don't need to know on which nodes the clients are on, or if they jump from a node to another.
On the Server side for websockets there is already an ping/pong implementation where the server sends a ping and client replies with a pong to let the server node whether a client is connected or not. But there isn't something implemented in reverse to let the client know if the server is still connected to them.
There are two ways to go about this I have read:
Every client sends a message to server every x seconds and whenever
an error is thrown when sending, that means the server is down, so
reconnect.
Server sends a message to every client every x seconds, the client receives this message and updates a variable on the client, and on the client side you have a thread that constantly checks every x seconds which checks if this variable has changed, if it hasn't in a while it means it hasn't received a message from the server and you can assume the server is down so reestablish a connection.
You can achieve trying to figure out on client side whether the server is still online using either methods. The first one you'll be sending traffic to the server whereas the second one you'll be sending traffic out of the server. Both seem easy enough to implement but I'm not so sure which is the better way in terms of being the more efficient/cost effective.
Server upload speeds are higher than client upload speeds, but server CPUs are an expensive resource while client CPUs are relatively cheap. Unloading logic onto the client is a more cost-effective approach...
Having said that, servers must implement this specific logic (actually, all ping/timeout logic), otherwise they might be left with "half-open" sockets that drain resources but aren't connected to any client.
Remember that sockets (file descriptors) are a limited resource. Not only do they use memory even when no traffic is present, but they prevent new clients from connecting when the resource is maxed out.
Hence, servers must clear out dead sockets, either using timeouts or by implementing ping.
P.S.
I'm not a node.js expert, but this type of logic should be implemented using the Websocket protocol ping rather than by your application. You should probably look into the node.js server / websocket framework and check how to enable ping-ing.
You should set pings to accommodate your specific environment. i.e., if you host on Heroku, than Heroku will implement a timeout of ~55 seconds and your pings should be sent before this timeout occurs.
So i currently have a chat system running NodeJS that passes messages via rabbit and each connected user has their own unique queue that subscribed and only listening to messages (for only them). The backend can also use this chat pipeline to communicate other system messages like notifications/friend requests and other user event driven information.
Currently the backend would have to loop and publish each message 1 by 1 per user even if the payload of the message is the same for let's say 1000 users. I would like to get away from that and be able to send the same message to multiple different users but not EVERY user who's connected.
(example : notifying certain users their friend has come online).
I considered implementing a rabbit queue system where all messages are pooled into the same queue and instead of rabbit sending all user queues node takes these messages and emit's the message to the appropriate user via socket connections (to whoever is online).
Proposed - infrastructure
This way the backend does not need to loop for 100s and 1000s of users and can send a single payload containing all users this message should go to. I do plan to cluster the nodejs servers together.
I was also wondering since ive never done this in a production environment, will i need to track each socketID.
Potential pitfalls i've identified so far:
slower since 1000s of messages can pile up in a single queue.
manually storing socket IDs to manually trasmit to users.
offloading routing to NodeJS instead of RabbitMQ
Has anyone done anything like this before? If so, what are your recommendations. Is it better to scale with user unique queues, or pool all grouped messages for all users into smaller (but larger pools) of queues.
as a general rule, queue-per-user is an anti-pattern. there are some valid uses of this, but i've never seen it be a good idea for a chat app (in spite of all the demos that use this example)
RabbitMQ can be a great tool for facilitating the delivery of messages between systems, but it shouldn't be used to push messages to users.
I considered implementing a rabbit queue system where all messages are pooled into the same queue and instead of rabbit sending all user queues node takes these messages and emit's the message to the appropriate user via socket connections (to whoever is online).
this is heading down the right direction, but you have to remember that RabbitMQ is not a database (see previous link, again).
you can't randomly seek specific messages that are sitting in the queue and then leave them there. they are first in, first out.
in a chat app, i would have rabbitmq handling the message delivery between your systems, but not involved in delivery to the user.
your thoughts on using web sockets are going to be the direction you want to head for this. either that, or Server Sent Events.
if you need persistence of messages (history, search, last-viewed location, etc) then use a database for that. keep a timestamp or other marker of where the user left off, and push messages to them starting at that spot.
you're concerns about tracking sockets for the users are definitely something to think about.
if you have multiple instances of your node server running sockets with different users connected, you'll need a way to know which users are connected to which node server.
this may be a good use case for rabbitmq - but not in a queue-per-user manner. rather, in a binding-per-user. you could have each node server create a queue to receive messages from the exchange where messages are published. the node server would then create a binding between the exchange and queue based on the user id that is logged in to that particular node server
this could lead to an overwhelming number of bindings in rmq, though.
you may need a more intelligent method of tracking which server has which users connected, or just ignore that entirely and broadcast every message to every node server. in that case, each server would publish an event through the websocket based on the who the message should be delivered to.
if you're using a smart enough websocket library, it will only send the message to the people that need it. socket.io did this, i know, and i'm sure other websocket libraries are smart like this, as well.
...
I probably haven't given you a concrete answer to your situation, and I'm sure you have a lot more context to consider. hopefully this will get you down the right path, though.
We are developing a Javascript control which should be constantly connected to a server for receiving animation updates.
We are planning to host this stuff on an Amazon cloud.
The scenario is like this: server connects to activemq queue waiting for updates, for each update it broadcasts it to all connected clients.
Is it even possible to handle such load with node.js + socket.io?
Will a single node.js server be able to handle such load?
How to organize fast transport between different nodes if we will have to use more than one node?
Will single node.js server be able to handle such load?.. How to organize fast transport between different nodes if we will have to use more than one node
You say that you are planning to host on Amazon. So first off, nothing should be scoped for a single server. Amazon machines will simply "disappear", you have to assume that you are going to use multiple computers.
...handling 50k simultaneous clients
So to start with, 50k connections for a single box is a very big number. Here's a very detailed blog post discussing "getting to 10k" with node.js+socket.io.
Here's a very telling quote:
it seemed as though 10,000 clients simply required more serialization
than my server was able to handle.
So a key component to "getting to 50k" is going to be the amount of work required just pushing data over the wire.
How to organize fast transport between different nodes if we will have to use more than one node.
That blog post is the first of 3. When you're done the first, read the other two. That should point you in the right direction.