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The EtherPad UI had a bunch of checkboxes and whatnot that were synchronized live, so I definitely acknowledge the problem. We're working on it at Meteor now t

The EtherPad UI had a bunch of checkboxes and whatnot that were synchronized live, so I definitely acknowledge the problem. We're working on it at Meteor now too. The way I look at it, as long as the server has the final say over the "official" value at any given time -- which seems to be the case here, and is true in all real apps I've seen up to the backend datastore's ability to provide it -- you don't really have a consistency or convergence problem. You just have a UI problem. It's easy for the client to track both the latest official value and what the user is doing, and tell the server about the latter. The only question is what to show the user while their action is still outstanding, and the answer may be different for different kinds of UI. You may want to "fake it till you make it" (Meteor's default, aka latency compensation) or show some kind of loading indicator. What about conflicts? Well, depending on your app, your options for how the server handles operations from the client include: they sometimes fail; they always succeed via "last writer wins" (good for a checkbox, say); they always succeed via operational transforms; or there is application-level conflict resolution that ropes in the user (implemented on top of the foregoing). There's a trend at the moment to view everything as a distributed system, but if you treat a client as a tool for viewing information and calling APIs, it seems a lot simpler.

josephg 12y ago
We already have this sort of eventual consistency in Derby, built on top of ShareJS. All documents (JSON objects) can be edited synchronously in the browser, and changes are automatically replicated to all other clients. If two people make a change to the same documents at the same time, the changes are merged in a way that will never conflict. For example if we both simultaneously insert into a list embedded in some part of the data model, derby sends a "list insert at position X" operation, which is seamlessly transformed & merged into the document at all sites. The insertion position is updated automatically before merging using the same logic that makes collaborative text editing in etherpad work. Except you can do it over the JSON structures that power your web app.
macspoofing 12y ago
>There's a trend at the moment to view everything as a distributed system, but if you treat a client as a tool for viewing information and calling APIs, it seems a lot simpler. Ok, I guess I must have misunderstood. If you're the guy whose building on-top some synchronization layer, then yeah, it's not really a problem. The sync layer is just another controller that manipulates your model or another consumer of your model changes. If you're the guy implementing the synchronization layer, then you are thinking of distributed systems.

josephg 12y ago

We already have this sort of eventual consistency in Derby, built on top of ShareJS. All documents (JSON objects) can be edited synchronously in the browser, and changes are automatically replicated to all other clients. If two people make a change to the same documents at the same time, the changes are merged in a way that will never conflict. For example if we both simultaneously insert into a list embedded in some part of the data model, derby sends a "list insert at position X" operation, which is seamlessly transformed & merged into the document at all sites. The insertion position is updated automatically before merging using the same logic that makes collaborative text editing in etherpad work. Except you can do it over the JSON structures that power your web app.

macspoofing 12y ago

>There's a trend at the moment to view everything as a distributed system, but if you treat a client as a tool for viewing information and calling APIs, it seems a lot simpler. Ok, I guess I must have misunderstood. If you're the guy whose building on-top some synchronization layer, then yeah, it's not really a problem. The sync layer is just another controller that manipulates your model or another consumer of your model changes. If you're the guy implementing the synchronization layer, then you are thinking of distributed systems.