This works assuming everyone has the same clock or performs changes causually distant from each other. It fails to work if, say, 1000 people all make a change around the same time. This also applies to lamport timestamps.
If a thousand people all made a change at the same time in a totally deterministic, always online system a single one of those writes would arbitrarily win in exactly the same way.
In practice "1000 people edit same thing at same time" is not a problem that needs to be solved via software, the users are just doing silly things and getting silly results.
If it isn’t handled correctly, you’ll eventually end up with parallel histories on different devices. Even if it isn’t 1000 people, people will share documents with entire classrooms, offices, etc., which increases the probability of this situation tremendously.
We are saying the same thing. I was pointing out that the article missed one of the hardest parts of actually implementing this, where your algorithm architecture can totally fuck you over if you didn’t plan for it. I just think it’s interesting that they missed pointing it out. Either they got it right on the first try or they haven’t realized the issue with the schema they’re proposing.
> Here’s a polished section you can insert into your article (it fits naturally after the Sync Phase section):
In practice "1000 people edit same thing at same time" is not a problem that needs to be solved via software, the users are just doing silly things and getting silly results.
It doesn't need to make sense, or be the most recent change, only that given the same inputs, everyone independently agrees on the same output.