Comparing MySQL and Postgres 9.0 Replication
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1] MySQL supports more replication options, whereas PostgreSQL focuses on the ones that 95% of users will care about and does not implement the rest.
2] MySQL's replication has several failure modes that can lead to data loss or non-synchronization. For example, it is statement based by default, so any statement which includes a call to NOW() will return different results on master and slave. PostgreSQL also has failure modes, but the defaults are designed to minimize them -- e.g. it always uses WAL and data file rewrites to ensure that data is properly synced and consistent.
3] Due to points 1 & 2, if you aren't an expert and don't need the extra features offered by MySQL, you are probably better off with PostgreSQL.
4] 3rd party tools exist for both servers which close many of the feature gaps between them.
Could someone who is more knowledgeable than me tell me if this is a fair reading?
Postgres was 'late' to the replication party, and only in this last release have they had hot slave machines. (with core functionality, 3rd party has a range of alternatives). Currently, it is single master, multi slave replication. Previously, it was been a warm spare arrangement, up to 1 WAL log behind, for durability, and not for load balancing. There were ways of making it less laggy, but it was not trivial to restore a log, bring the db up, and then be in a position to restore another log.
I wouldn't say it covers 95% of the use cases. In fact, I find it very limiting, but if all you need is to make sure your database is backed up it's a great step in the right direction.
That being said, the topology limitations suck. If you lose your master server, you are running in a degraded environment until you can rebuild ALL slaves from scratch. This really sucks if you have a very large database that takes a long time to rebuild.
Postgres 9.0 replication is a great first step, but it's only a step. There's still a lot of work to be done.
If you lose your master server, you are running in a
degraded environment until you can rebuild ALL slaves from
scratch. This really sucks if you have a very large
database that takes a long time to rebuild.
Assume you have 1 master, and 2 slaves(1=new master/2=additional slave) each replicating directly from the master. If they're in sync, then if you:
* shutdown the master
* shutdown slave1/new master
* remove slave1's recovery.conf file
* assign slave1 old master's ip address
* start slave1 as new master
I'd bet that there are some pretty basic failure modes in the timeline preserving case where the slaves could be out of sync when one was promoted, and then that out of syncness could be propagated. I suspect that a missing transaction on the new master would trigger some sort of duplicate transaction oid issue, but a missing transaction on the slave would be more likely to go unnoticed.
I've just tested a case where I killed the master when I was running transactions against it, and it seems to work as well as the shutdown case. Bringing up the slave is where the timeline gets incremented.
I suppose I could throw one of the replication connections through a ip delay and intentionally introduce replication lag..
edit: Looks like http://www.postgresql.org/docs/9.0/static/warm-standby.html#... , section on monitoring gives the pg_current_xlog_location on the primary and the pg_last_xlog_receive_location on the slaves, which would at least tell one if the slaves are in sync, and if not, which one is the farthest ahead.
So, the process could be:
* master dies. either gracefully or not.
* all slaves are queried
* most advanced one gets shutdown, promoted by ip and removing recovery.conf then started
* all the other slaves should track those changes and bring themselves up to date.
* Resync the old master as a new slave.That's great. That's the first time I've been able to get this to work smoothly. I'm sure there are still ways to break it but this gives me hope.
2. MySQL writes the timestamp for NOW() into the binlog so provided your master and slave are in the same timezone, it's replication safe. Functions like UUID() and RAND() will behave as you describe.
3. I disagree. MySQL's replication is more mature, widely understood, and has more documentation than PostgreSQL's.
1. Mature?
I have seen MySQL replication blow up in so many awful ways, it's not funny. And yes, I've seen it happen on 5.* deployments. The worst part is that MySQL hardly ever detects a problem, and you hardly ever know why it went wrong - it just silently corrupts. The only way to detect the corruption is through regular checksum runs which can be costly on large databases (there's a reason why the checksum-utility from maatkit has fairly sophisticated options for incremental checksumming).
2. Widely understood?
I challenge you to prove your understanding and explain only a small subset of the functionality: Please enumerate all failure modes that can lead to corruption in statement based replication, and how to avoid them.
3. More documentation?
That has to be a joke. The MySQL documentation is a mess. It is poorly structured, poorly written and full of conflicting and misleading bits. Please show me the MySQL document about replication that comes remotely close to http://www.postgresql.org/docs/9.0/static/hot-standby.html in terms of clarity and exhaustiveness. Notice the long section about "query conflicts" - where is the MySQL equivalent?
2. No. It's widely understood because MySQL has a much larger mindshare than PostgreSQL. Statement based replication has its faults, but complexity isn't one of them.
3. It's not a joke. There is more documentation. There is the official documentation, but if you don't like that there are plenty of blog posts, books, and recorded talks on the subject.
That sounds nice in theory, but completely ignores the reality of the respective code-bases. Features in MySQL have a tendency to rot rather than mature. It could hardly become more obvious than in the comparison between this version 1 of postgres replication against the "evolved" MySQL equivalent.
Postgres may have the smaller feature set, it may be the first version, yet I'm still inclined to trust it a lot more than what MySQL has to offer. Simply because postgres has a track-record of being rock solid and MySQL, well, not so much.
Sure, in theory you can build fancy rings, cascades and even multi-master topologies in MySQL. But what is that worth when even the simplest master/slave mode still randomly and silently desyncs in various, undocumented situations?
Statement based replication has its faults, but complexity isn't one of them.
There's a nice quote from Alan Perlis:
Fools ignore complexity,
experts avoid it;
geniuses remove it.
It's not a joke. There is more documentation.
Sorry, measuring documentation in terms of quantity sounds like yet another joke to me. As you can tell by my snarky comments I'm responsible for babysitting the odd MySQL cluster in my day-job (and postgres, too, so I have a frame of reference). It is indeed true that for most common problems I'll find the solution not in the official docs but rather on some more or less obscure forum, in broken english, linked from page >3 of the google search results (after 2 pages of outdated and plain wrong information).
So, in all fairness, yes, most common problems can eventually be solved that way. But good luck debugging a not so common ring, multi-master or otherwise non-standard scenario that way. Or encoding issues. Or silent truncation. Or hotbackups that are strangely much smaller than they should be. Or the dreaded 'mysql'-database being screwed after restoring a backup to a newer minor-version...
Anyways, the way postgres handles this seems more sensible to me. In postgres the overwhelming majority of the "common" MySQL-issues simply doesn't exist.
Guess what, things have gotten incrementally better and continue to improve. Bugs get found and fixed. MySQL replication is mature enough to power huge sites like Twitter, Facebook, and countless others. There has been exactly one PostgreSQL release that supports replication suitable for read scaling.
But examples like this are so special case - it doesn't show the real danger. A DELETE with a LIMIT clause and no ORDER BY can semantically delete different rows on the slave than on the master.
You never, EVER want to use circular replication (A->B->C->A). Surrounding a crash it's such a pain to re-piece together the data.
Granted, multi-master setups aren't needed for most sites and PostgreSQL's new WAL replication and the fact that it makes sure that the WAL is written on the slave before the transaction is committed on the master means that data integrity should be top notch. It's exciting to see PostgreSQL's development progressing so well.
it makes sure that the WAL is written on the slave
before the transaction is committed on the master
means that data integrity should be top notch.
Basically, it means that there is the potential for replication lag and so you have to make sure you query from the master for just-updated data. However, it also means that if the master goes down, any data committed on the master is already on the slave in the WAL, just possibly not applied yet. So, it doesn't isolate you from replication lag, but it is a nice thing when it comes to making sure that the data remains intact even if a complete failure of the master occurs.
As the article points out, the data gets written to the WAL on
the slave before the transaction is committed on the master