You mean, in that case tolerance to partition and availability should be perfect.
> Perhaps someday we may be able to say that the odds of enough partitions or machine failures to make the system unavailable are lower than the odds of you getting struck by lightning, at which point you will have for practical purposes defeated the constraints of the CAP theorem.
So this is the really interesting question. All the CAP theorem says is that (C,A,P) != (1.0,1.0,1.0). How close to (1.0,1.0,1.0) could we make (C,A,P)? If infinitely close, then we have achieved perfection by the limit, and the CAP theorem is rather pointless. If not, then what is the numeric limit?
As you speculate, maybe the numeric limit on C x A x P is so close to 1.0 that the odds of seeing a consistency, availability, or partitioning problem are much smaller than getting hit by lightning.
Then again, maybe not. Who knows? ;)
To avoid sounding like a total crackpot, here is an interesting paper that explores the physical limits of computation:
No. If a network is never partitioned, you don't need to write algorithms that can tolerate partitions. Therefore consistency and availability are possible.
> So this is the really interesting question. All the CAP theorem says is that (C,A,P) != (1.0,1.0,1.0). How close to (1.0,1.0,1.0) could we make (C,A,P)? If infinitely close, then we have achieved perfection by the limit, and the CAP theorem is rather pointless. If not, then what is the numeric limit?
I think you have misunderstood the theorem (at least, if my bachelor-degree-level understanding is correct). C, A, and P are not variables you can multiply together or perform mathematical operations on. They are more like booleans. "Is the web service consistent (are requests made against it atomically successful or unsuccessful)?" "Is the web service available (will all requests to it terminate)?" "Is the web service partition-tolerant (will the other properties still hold if some nodes in the system cannot communicate with others)?" These questions cannot be "0.5 yes". They are either all-the-way-yes or all-the-way-no.
> . . . and the CAP theorem is rather pointless
Not really. It is pointful for networks that experience partitions. It just doesn't apply to reliable networks. It also sort-of doesn't apply when an unreliable network is acting reliably, with the caveat that since it is not possible to tell in advance when a network will stop behaving reliably, you still have to choose between these three properties when writing your algorithms for when the network behaves badly.
Right, but I wasn't restating CAP, just wondering about a follow on to CAP that considers the probability of remaining consistent, the probability of remaining available, and the probability of no failures due to network partitions in physical terms.
Is this not an interesting thing to consider? What if someone proves a hard limit on the product of these probabilities in some physical computation context? The CAP theorem is absolutely fascinating to me, especially if it has something real to say about the systems we can build in the future. The future looks even more distributed.
> It is pointful for networks that experience partitions. It just doesn't apply to reliable networks.
Is there such a thing as a "reliable" network when thousands or millions of computational nodes are involved? Are the routers and switches which connect such a network 100% available? If an amplification attack saturates some network segment with noise, what then?
As programmers, we desperately want things to work, and it's easy to greet something like CAP with flat out denial. I know I'm always fighting it. "It will never fail." No, it can and will fail.
