I need some advice on how propagating server-side changes of entities to the client is best handled with GWT's RequestFactory.
Let us assume we have two EntityProxies, a PersonProxy and a PersonListProxy (which has a getter for a List). Assume that the client has fetched a PersonList and a Person from the server.
In case the client is editing one of these proxies and firing a request, the machinery of RequestFactory (if I have understood the principles correctly) will fire an EntityProxyChange event if it detects changes done by server code (so that the client can update its display of the entities, for example).
Now assume that the server is changing its entities outside of a request by this client (e.g. due to another client calling the server) so that this client would see another version if it fetched the Person or the PersonList again.
My question is what is the best way inside the RequestFactory framework to tell the client of the changes (and to reuse as much of the machinery as possible)? We can assume that I have a way to send simple messages from the server to the client (e.g. Google App Engine's channel API or server-sent events).
One idea could be that the server sends over this channel a message telling that a Person or a PersonList with a specific id has changed. The client code handling the receipt of these messages could then use RequestFactory to re-fetch (e.g. find) the entity. This change should then be propagated to other parts of the client by an EntityProxyChange event.
Is this the way to go? (And in case that the client already has the current version of the entity, e.g. because the server was dumb and notified the client of changes the client itself made, would the triggered re-fetch just transport a few bits of metadata and not the whole entity again?)
ADDED:
Thinking a bit more about it, I wonder how EntityProxyId's can be generated for the server-sent event channel. When an entity on the server changes, the server only has the server id. It can then send it to the client, of course, but the client only knows of EntityProxyId's. Of course, I could add a getId() (in addition to getStableId()) to each EntityProxy, but it looks as if this would add redundant data to every server response.
Well, I realize that my post isn't precise answer to your question, but it's just my experience.
In fact, there is just a question how to deliver data from server to client.
I faced with some task couple years ago, and found for yourself an approach that make my life easier. To explain it, I want to specify my reasons:
You have to have full data delivery by requesting it from client - it's straight, natural way to requesting data;
You don't want to create and support 2 different models of full data delivery: one by requesting from client and second by pushing from server;
But you need to inform client about some changes on server side;
So, now I'm building my architecture using following approach:
Build full classical client-server API for data delivery - so you can load and refresh your application in natural way even if your pushing functionality is blocked or broken.
Define key information that may be changed on server side and should be delivered to client via push mechanism.
Create small push message construct(s) that will deliver to client just a notification about changes - no any valuable data should be delivered this way - just keys which data was changed.
All that is needed to do on client when it receives such notification is just to get/refresh data from server in natural client-server way that is already supported.
Server logic shouldn't bother client side by huge amount of notifications - sometimes is more effective do not deliver changes, but just refresh everything.
Hope this helps.
Related
Creating a user, adding some record to collection in the DB, updating some stuff, etc..
All of these we regularly do with HTTP requests against REST api.
Think about making Event bus as server instead of REST api.
In that method, create user will be an event name: "CreateUser" instead of REST api endpoint: POST /users.
In reflect to any action done in the event bus, it will re-emit a following event telling to any body needed to know about, that the event was done.
If for example someone viewing the vehicles collection and another user just edit one of the columns or add a new vehicle instance, it will be reflected immediately to who views it online.
My question is if there attitudes like I mentioned above, if there some formally names for it, if it a good practice, if you know someone who regularly uses it, a framework or something etc. Does the socket.io server can handle and behave like http server in high workloads?
You can use websockets for this; they provide a bidirectional channel between client and server to send messages across. You will have to catch and parse the messages on each end yourself, as there is no additional protocol on top of them.
They don't hold state, so there is no knowledge of who is looking at what, or who got what. You could send the same update message to all connected clients and leave it to the client to use it or not.
You would have to reprogram your client code and the API endpoints, because it's a different way of doing things, and it can also do server push.
I have no idea about frameworks though, as I always use them without one. Websockets are fast, but server behaviour at high workloads depends on implementation, and I only have experience with the websocket server I wrote myself. I suppose the performance of the socket.io can easily be googled.
Background
We are writing a Messenger-like app. We have setup Websockets to Inbox and Chat.
Question
My question is simple. What are the advantages and disadvantages when sending data from Client to Server using REST instead of Websockets? (I am not interested in updates now.)
We know that REST has higher overhead in terms of message sizes and that WS is duplex (thus open all time). What about the other things we didn't keep in mind?
Here's a summary of the tradeoffs I'm aware of.
Reasons to use webSocket:
You need/want server-push of data.
You are sending lots of small pieces of data from client to server and doing it very regularly. Using webSocket has significantly less overhead per transmission.
Reasons to use REST:
You want to use server-side frameworks or modules that are built for REST, not for webSocket (such as auth, rate limiting, security, streaming, etc...).
You aren't sending data very often from client to server and thus the server-side burden of keeping a webSocket connection open all the time may lessen your server scalability.
You want your client to run in places where a long-connected webSocket during inactive periods of time may not be practical (perhaps mobile).
You want your client to run in old browsers that don't support webSocket.
You want the browser to enforce same-origin restrictions (those are enforced for REST Ajax calls, but not for webSocket connections).
You don't want to have to write code that detects when the webSocket connection has died and then auto-reconnects and handles back-offs and handles mobile issues with battery usage issues, etc...
You need to run in situations where there are proxies or other network infrastructure that may not support long running webSocket connections.
If you want request/response built in. REST is request/response. WebSocket is not - it's message based. Responses from a webSocket are done by sending a messge back. That message back is not, by itself, a response to any specific request, it's just data being sent back. If you want request/response with webSocket, then you have to build some infrastructure yourself where you tag an id into a request and the response for that particular request contains that specific id. Otherwise, if there are every multiple requests in flight at the same time, then you don't know which response belongs with which request because all the data is being sent over the same connection and you would have no way of matching response with request.
If you want other clients to be able to carry out this operation via an Ajax call.
So, if you already have a webSocket implementation, don't have any problem with it that are lessened with REST and aren't interested in any of the reasons that REST might be better, then stick with your webSocket implementation.
Related references:
websocket vs rest API for real time data?
Ajax vs Socket.io
Adding comments per your request:
It sounds like you're expecting someone to tell you the "right" way to do it. There are reasons to pick one way over the other. If none of those reason compel you one way vs. the other, then it's just an architectural choice and you must take in the whole context of what you are doing and decide which architectural choice makes more sense to you. If you already have the reliably established webSocket connection and none of the advantages of REST apply to your situation then you can optimize for "efficiency" and send your data to the server over the webSocket connection.
On the other hand, if you wanted there to be a simple API on your server that could be reached with an Ajax call from other clients, then you'd want your server to support this operation via REST so it would simplest for these other clients to carry out this one operation. So, it all depends upon which direction your requirements drive you and, if there is no particular driving reason to go one way or the other, you just make an architectural choice yourself.
I understand the main principles behind both. I have however a thought which I can't answer.
Benchmarks show that WebSockets can serve more messages as this website shows: http://blog.arungupta.me/rest-vs-websocket-comparison-benchmarks/
This makes sense as it states the connections do not have to be closed and reopened, also the http headers etc.
My question is, what if the connections are always from different clients all the time (and perhaps maybe some from the same client). The benchmark suggests it's the same clients connecting from what I understand, which would make sense keeping a constant connection.
If a user only does a request every minute or so, would it not be beneficial for the communication to run over REST instead of WebSockets as the server frees up sockets and can handle a larger crowd as to speak?
To fix the issue of REST you would go by vertical scaling, and WebSockets would be horizontal?
Doe this make sense or am I out of it?
This is my experience so far, I am happy to discuss my conclusions about using WebSockets in big applications approached with CQRS:
Real Time Apps
Are you creating a financial application, game, chat or whatever kind of application that needs low latency, frequent, bidirectional communication? Go with WebSockets:
Well supported.
Standard.
You can use either publisher/subscriber model or request/response model (by creating a correlationId with each request and subscribing once to it).
Small size apps
Do you need push communication and/or pub/sub in your client and your application is not too big? Go with WebSockets. Probably there is no point in complicating things further.
Regular Apps with some degree of high load expected
If you do not need to send commands very fast, and you expect to do far more reads than writes, you should expose a REST API to perform CRUD (create, read, update, delete), specially C_UD.
Not all devices prefer WebSockets. For example, mobile devices may prefer to use REST, since maintaining a WebSocket connection may prevent the device from saving battery.
You expect an outcome, even if it is a time out. Even when you can do request/response in WebSockets using a correlationId, still the response is not guaranteed. When you send a command to the system, you need to know if the system has accepted it. Yes you can implement your own logic and achieve the same effect, but what I mean, is that an HTTP request has the semantics you need to send a command.
Does your application send commands very often? You should strive for chunky communication rather than chatty, so you should probably batch those change request.
You should then expose a WebSocket endpoint to subscribe to specific topics, and to perform low latency query-response, like filling autocomplete boxes, checking for unique items (eg: usernames) or any kind of search in your read model. Also to get notification on when a change request (write) was actually processed and completed.
What I am doing in a pet project, is to place the WebSocket endpoint in the read model, then on connection the server gives a connectionID to the client via WebSocket. When the client performs an operation via REST, includes an optional parameter that indicates "when done, notify me through this connectionID". The REST server returns saying if the command was sent correctly to a service bus. A queue consumer processes the command, and when done (well or wrong), if the command had notification request, another message is placed in a "web notification queue" indicating the outcome of the command and the connectionID to be notified. The read model is subscribed to this queue, gets messessages and forward them to the appropriate WebSocket connection.
However, if your REST API is going to be consumed by non-browser clients, you may want to offer a way to check of the completion of a command using the async REST approach: https://www.adayinthelifeof.nl/2011/06/02/asynchronous-operations-in-rest/
I know, that is quite appealing to have an low latency UP channel available to send commands, but if you do, your overall architecture gets messed up. For example, if you are using a CQRS architecture, where is your WebSocket endpoint? in the read model or in the write model?
If you place it on the read model, then you can easy access to your read DB to answer fast search queries, but then you have to couple somehow the logic to process commands, being the read model the responsible of send the commands to the write model and notify if it is unable to do so.
If you place it on the write model, then you have it easy to place commands, but then you need access to your read model and read DB if you want to answer search queries through the WebSocket.
By considering WebSockets part of your read model and leaving command processing to the REST interface, you keep your loose coupling between your read model and your write model.
Assume the following scenario A web application serves up resources through a RESTful API. A number of clients consume this API. The goal is to keep the data on the clients synchronized with the web application (in both directions).
The easiest way to do this is to ask the API if any of the resources have changed since the client last synchronized with the API. This means that the client needs to ask the API for the appropriate resources accompanied by timestamp (to see if the data needs to be updated). This seems to me like the approach with the least overhead in terms of needless consumption of bandwidth.
However, I have the feeling that this approach has a few downsides in terms of design and responsibilities. For example, the API shouldn't have to deal with checking whether the resources are out of date. It seems that the only responsibility of the API should be to serve up the resources when asked without having to deal with the updating aspect. By following this second approach, the client would ask for a lot of data every time it wants to update its data to keep it synchronized with the web application. In other words, the client would check whether the data it got back is newer than the locally stored data. If this process takes place every few minutes, this might become a significant burden for the system.
Am I seeing this correctly or is there a middle road that I am overlooking?
This is a pretty common problem, and a RESTful approach can help you solve it. HTTP (the application protocol typically used to build RESTful services) supports a variety of techniques that can be used to keep API clients in sync with the data on the server side.
If the client receives a Last-Modified or E-Tag header in a HTTP response, it may use that information to make conditional GET calls in the future. This allows the server to quickly indicate with a 304 – Not Modified response that the client’s previously stored representation of the resource is still valid and accurate. This will allow the server (or even better, an intermediate proxy or cache server) to be as efficient as possible in how it responds to the client’s requests, potentially reducing costly round-trips to a back-end data store.
If a response contains a Last-Modified header and the client wishes to take advantage of the performance optimization available with it, they must include an If-Modified-Since directive in a subsequent GET call to the same URI, passing in the same timestamp value it received. This instructs the server to only GET the information from the authoritative back-end source if it knows it has changed since that time. Your server will have to be built to support this technique, of course.
A similar principle applies to E-Tag headers. An E-Tag is a simple hash code representing a specific state of the resource at a particular point in time. If the resource changes in any way, so does its E-Tag value. If the client sees an E-Tag in a response it should pass it in subsequent GET requests to the same URI, thereby allowing the server to quickly determine if the client has an up-to-date representation of the resource.
Finally, you should probably look at the long polling technique to reduce the number of repeated GET requests issued by your clients to the server. In essence, the trick is to issue very long GET requests to the server to watch for server data changes. The GET will not return a response until either the data has changed or the very long timeout fires. If the latter, the client just re-issues the same long-lived request to watch for changes again. See also topics like Comet and Web Sockets which are similar in approach.
We're using GWT Atmosphere to send strings from the server to the client and it works quite well.
However, we would like to send whole entities from the server to the client, serialized by the GWT RequestFactory. Without the need for a request by the client!
So I tried working with SimpleRequestProcessor#createOobMessage(domainObject) and sending that payload to the client. Computing the payload works.
I would then decode that message using AutoBeanCodex#decode and read the domainObject as the correct EntityProxy from the invocation list of the ResponseMessage - however when I do so, it requires some sort of serverId being set to proceed in AbstractRequestFactory#getId (around line 260: assert serverId != null : "serverId")
Any advice on how I can decode a Proxy payload without a request being sent by the client?
Update
The use case for this question is chat-like communication. The client doesn't request the messages from the server but instead will be notified of new messages. And we'd like to include the messages and info on who's sent the message in the notification payload. Since we're using RequestFactory in our project anyway, we want to take advantage of having set up all the Proxy wiring and now simply push the relevant object graph to the client.
Why are you trying to serialize RF messages and send them just as entities? RequestFactory is much more than justa way to send data over the wire - it has at least three different kinds of messages that can be sent from the client to the server: create instances, call setters, and invoke service methods. Based on what happens on the server, not only can data be returned to the client, but messages about what changes were made and if those setters made changes that are not valid under the JSR303 rules.
Are you trying for a simpler, interface way of describing, sending, and receiving entities? Or do you actually want the RF wiring on both client and server so you can batch requests, refer to EntityProxyId instances and have the client only send diffs?
If you just want simpler object declarations, try just using AutoBeans and the AutoBeadCodex you have already looked at - you'll be able to create and marshal instances on both client and server easily, and you can pass them as strings over atmosphere's transports.
If you actually want RequestFactory, but running over something other than AJAX, there are other options. Rather than sending/receiving strings through Atmosphere (which I believe is intended to provide push support for RPC calls), consider using that underlying push layer to implment a new request transport in RequestFactory.
com.google.web.bindery.requestfactory.shared.RequestTransport can be implemented (see com.google.web.bindery.requestfactory.gwt.client.DefaultRequestTransport for the default AJAX version) to use any communication mechanism you would like - and to build the server, take a look at com.google.web.bindery.requestfactory.server.RequestFactoryServlet for what actually must be done to push messages through the Locator, ServiceLocators, etc.
If you really want to use Atmosphere and RF, then consider building a RequestTransport that wraps a simple Atmosphere interface to call to the server with the string - the cometd/websocket calls will already be taken care of for you, and you'll just have to translate the string message into invocations (again, see how RequestFactoryServlet does it).