A bit back, I was looking into database replication and specifically, two-way replication. Meaning that either server could be updated and it would replicate any changes to it’s nice neighbour. Microsoft SQL offer a solution – but it was way out of our price-range. So, we looked into the world of MySQL and at the time, the sparkly and new MySQL 5.0.
MySQL replication currently does not support any locking protocol between master and slave to guarantee the atomicity of a distributed (cross-server) update. In other words, it is possible for client A to make an update to co-master 1, and in the meantime, before it propagates to co-master 2, client B could make an update to co-master 2 that makes the update of client A work differently than it did on co-master 1. Thus, when the update of client A makes it to co-master 2, it produces tables that are different from what you have on co-master 1, even after all the updates from co-master 2 have also propagated. This means that you should not chain two servers together in a two-way replication relationship unless you are sure that your updates can safely happen in any order, or unless you take care of miss-ordered updates somehow in the client code.
You should also realize that two-way replication actually does not improve performance very much (if at all) as far as updates are concerned. Each server must do the same number of updates, just as you would have a single server do. The only difference is that there is a little less lock contention, because the updates originating on another server are serialized in one slave thread. Even this benefit might be offset by network delays.
This offers some good advice and you really do need to understand exactly what you are doing before you can continue down this path. But suppose that it doesn’t really matter what order things happen, as long as they happen consistently across all servers, what are we to do then to get it all working? Well, enhancing and copying from my response to a question on the awesome Stack Overflow, here is what I’d do.
The first major problem that you must overcome, is that when a new incremental seed is created, it’s normally created 1, 2, 3, 4, 5 (the glorious one times table). However, this will be no good if the theoretical two-inserts-at-once-on-different-boxes happens. It would great two number 4′s. A BIG data-integrity issue. This is solved simply however, by simply providing a seed which equals the total number of masters you would have. So, in my case (and maybe most), there would be two Masters, one would be counting evens, and the other ones odd. 2,4,6,8 and 1,3,5,7. Following this logic there can be no duplicates. It does create the OCD-Offensive side-effect that there are numbers that are never used – but that doesn’t really matter a great deal as far as things go. In addition, you should ensure both your server_id’s are different (two MySQL servers with the same name in replication has distinct disadvantage to the other setups (it doesn’t work) – but that’s standard replication setup anyway. ;0
Master MySQL 1:
auto_increment_increment = 2 auto_increment_offset = 1
Master MySQL 2:
auto_increment_increment = 2 auto_increment_offset = 2
Using all the functionality and commands of the standard MySQL replication, you should then be able to start both servers up as slaves of the other one. Then to check both are working OK, connect to both machines and perform the command
SHOW SLAVE STATUS and you should note that both
Slave_SQL_Running should both say “YES” on each box.
When creating your code to connect to the database servers, you want to send to both boxes equally? Or maybe favour one because it’s a bit beefier? You could add in death-checks to make sure a server is still serving queries and allowing connections – and if its not, use the other one.
All being told, I really like this solution for replication. For the fuller picture, you’d obviously add a slave somewhere that is remotely connected periodically (or all the time) and allowed to update. It acts as an off-site backup should your building be compromised (burns to the ground in a huge inferno-type-mess scenario. For example ).