There are few things one is supposed to know about MySQL replication in production, as manual doesn’t always discuss things openly.
This is small set of rules and advices I compiled (some apply to statement based replication only, but row based replication may benefit from one or two too):
- Don’t use MyISAM. Or in fact, don’t use any non-transactional engine, if you care about your data. On either side, master or slave, or both – using non-transactional engines will cause data drift, as partially executed statements on master would be fully executed on slave, or simply stop replication. Of course, every crash has the capacity of getting your tables desynced from each other and there are absolutely no guarantees.
This “don’t” can be easily transformed into “do” – just use InnoDB. Bonus point – one doesn’t need to take down the server, to clone a slave from a master :)
- Don’t use temporary tables. MySQL manual is very funny about temporary tables in replication, it says “do not shut down the slave while it has temporary tables open.” That of course means that you’re not supposed to crash either – and more slaves there are, more of them will crash because of various reasons (e.g. solar flares).
The operational overhead temporary tables add is huge – even though it may not show up in the benchmark.
- Prefer simple, idempotent statements. If one can replay same statements multiple times without having database drift it doesn’t matter much if replication position is somewhat outdated. Updating rows by PK to fixed values, avoiding multiple table updates/deletes can allow to recover after crash much faster.
- Set sync_binlog=1. This will introduce biggest bottleneck for transactions, but losing 30s of data may be worse (as this will force to do full slave resync in most cases). On really busy servers one can go for higher values (e.g. sync every 20 transactions), but 0 is asking for disaster.
- Avoid long running updates. Though all long statement would cause on a master is slightly longer locking window and some performance pressure, once it gets replicated to the slave, all the updates will have to wait for the giant one to finish, in many cases rendering the slave useless.
If something big has to be replicated, either split it into smaller chunks or run it directly against slaves (with binary logging on the master disabled for it).
Splitting into smaller chunks can allow wait-for-slave logic to be implemented, thus not having any major impact on production environments.
- Don’t use replicate-do-db. Or replicate-ignore-db. They both rely on database context, and statements like ‘INSERT INTO database.table’ will fail.
If you need it, use replicate-wild-do-table=db.% – but even then, be careful with cross-database statements, that involve tables from multiple databases – as they may be filtered out…
- Note the multiversioning. Some statements may become replication performance hogs because of long-running transactions (backups? reporting? ETL?) running on slaves – it may not need to rescan all the row versions on master, but they’d be still there on a slave. Such statements may need to be rewritten to avoid scanning gaps with too many invisible rows, or long transactions have to be split.
Though probably the best advice I can give now is “call your mysql vendor and ask for transactional replication“. Server, rack, datacenter crashes will not cause excessive work on fixing replication – it will be always consistent. One can even disable log syncing to disk then \o/