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Uniqueness constraints require consensus

In Chapter 9 we saw that in a distributed setting, enforcing a uniqueness constraint requires consensus: if there are several concurrent requests with the same value, the system somehow needs to decide which one of the conflicting operations is accepted, and reject the others as violations of the constraint.

The most common way of achieving this consensus is to make a single node the leader, and put it in charge of making all the decisions. That works fine as long as you don’t mind funneling all requests through a single node (even if the client is on the other side of the world), and as long as that node doesn’t fail. If you need to tolerate the leader failing, you’re back at the consensus problem again (see “Single-leader replication and consensus” on page 367).

Uniqueness checking can be scaled out by partitioning based on the value that needs to be unique. For example, if you need to ensure uniqueness by request ID, as in Example 12-2, you can ensure all requests with the same request ID are routed to the same partition (see Chapter 6). If you need usernames to be unique, you can partition by hash of username.

However, asynchronous multi-master replication is ruled out, because it could happen that different masters concurrently accept conflicting writes, and thus the values are no longer unique (see “Implementing Linearizable Systems” on page 332). If you want to be able to immediately reject any writes that would violate the constraint, synchronous coordination is unavoidable [56].

 
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