I am creating a long-polling chat application on nodeJS without using Socket.io and scaling it using clusters.
I have to find a way to store all the long-polled HTTP requests and response objects in such a way that it is available across all node clusters(so that when a message is received for a long-polled request, I can get that request and respond to it)
I have tried using redis, however, when I stringify http request and response objects, I get "Cannot Stringify Cyclic Structure" Error.
Maybe I am approaching it in a wrong way. In that case, how do we generally implement lon-polling across different clusters?
What you're asking seems to be a bit confused.
In a long-polling situation, a client makes an http request that is routed to a specific HTTP server. If no data to satisfy that request is immediately available, the request is then kept alive for some extended period of time and either it will eventually timeout and the client will then issue another long polling request or some data will become available and a response will be returned to the request.
As such, you do not make this work in clusters by trying to centrally save request and response objects. Those belong to a specific TCP connection between a specific server and a specific client. You can't save them and use them elsewhere and it also isn't something that helps any of this work with clustering either.
What I would think the clustering problem you have here is that when some data does become available for a specific client, you need to know which server that client has a long polling request that is currently live so you can instruct that specific server to return the data from that request.
The usual way that you do this is you have some sort of userID that represents each client. When any client connects in with a long polling request, that connection is cluster distributed to one of your servers. That server that gets the request, then writes to a central database (often redis) that this userID userA is now connected to server12. Then, when some data becomes available for userA, any agent can lookup that user in the redis store and see that the user is currently connected to server12. So, they can instruct server12 to send the data to userA using the current long polling connection for userA.
This is just one strategy for dealing with clustering - there are many others such as sticky load balancing, algorithmic distribution, broadcast distribution, etc... You can see an answer that describes some of the various schemes here.