orf
5 hours ago
These kinds of rule-based migration safety checks are simple, but hardly complete.
The problem is that some migration safety depends on the state of the database, which isn’t represented in the DDL statement alone. For example, altering a column type is either a no-op or an exclusive locked table rewrite depending on the original type of the column.
There are other footguns that can happen if the column you’re altering is a foreign key, where multiple tables can be locked.
I went down a rabbit hole a few years ago and built a system[1] to introspect a given migration against a live schema, and actually let Postgres tell you what it’s doing[2].
It would be great to have better built-in support for this (EXPLAIN for DDL statements?), but this direction feels safer and more accurate than static rulesets.
Safety also depends on the size/activity of a table being altered (i.e rewriting an empty table is fine). Having an accurate representation of the locks and actions performed by the database lets you integrate with production metrics to actually determine real-world safety across a fleet of databases, rather than guessing.
1. https://github.com/orf/locksmith
2. https://github.com/orf/locksmith/blob/f8798c6ee92bfae10d416c...
grogers
3 hours ago
I would go further than this and argue that most bugs during database migrations happen because of mismatched application behavior with the action of the migration, not because the DDL was wrong. E.g. removing something that was still being relied on by the application, or starting to backfill data to a new column before the application is fully writing it. The most insidious version of this is where one application server doesn't have it's code updated (or comes back from the dead, etc) and causes the problem.
At a previous job what I did to prevent that was to have a special DB table that would signal what capabilities the database has, and the code would read that table and compare to its own requirements. If a capability required by the database was not present in the code (e.g. code not updated for a new feature) the code would refuse to make any writes to the DB and error all incoming requests. Likewise if a capability required by the code was missing from the database (e.g. code deployed too soon and database migration not run yet) it again would refuse requests. Before setting a feature to required in the DB and preforming the migration with feature flags, we could check all known application servers were reporting compatibility with the new feature (if any were down or not reporting at the time, they will be blocked in the next step - prioritizing safety over liveness)
catlifeonmars
14 minutes ago
I came here to say this too. Most bugs I run into are when databases schema versions interact with multiple software versions. If you are a low availability service, you can just take down the service and update the schema atomically, but 90% of the time you actually need to write backwards compatible migrations and forwards compatible code and coordinate the rollout accordingly.
My rule of thumb is no more than two distinct software versions can share a database at the same time. This effectively rules out database sharing between services. That way you push the problem to an API layer, which is better equipped to handle maintaining compatibility between many client versions.
weird-eye-issue
2 hours ago
Altering a column that already has data in production should be an absolute last resort, I don't think I've ever even done it, it's never 100% necessary
orf
2 hours ago
> that already has data in production
exactly: already has data. It’s not the statement that’s unsafe, it’s the size of the table. That’s what all pattern matching migration checkers get wrong.
You might be releasing a new feature gradually and you realised your schema is slightly wrong and want to alter a column type. You’ve got some tiny volume of data in one production cluster. Is it safe?
A pseudo rule determining the safety for any arbitrary migration that causes a rewrite could be:
smt.is_rewrite and tbl.size < 10MB
No: on your 10TB orders table
To accurately model migration safety you don’t really care about the statement: you care about the effects (locks, rewrites, additions, etc). That’s what is safe or unsafe.
weird-eye-issue
2 hours ago
Right I'm agreeing with you but if there even is a column that's already in production you should just assume it has data in it so I would favor just a blanket ban on altering columns at all
perrygeo
4 hours ago
Locksmith is awesome, how am I just now discovering this?
Your comments re: database state are spot on. DDL can fail in subtle ways. It's not even enough to take a snapshot of the current state and validate; things can change under your feet.
Take adding a unique index on a column: a simple CREATE UNIQUE INDEX statement, right? But you realize it will fail if the values aren't unique already, so you run a SELECT query to confirm. Yep, all unique. Deploy the app which runs the migration on startup - fail. A non-unique key arrived in the time between your queries.
Even more fun if you CREATE UNIQUE INDEX CONCURRENTLY and a non-unique key arrives in the middle of the DDL execution.
williamdclt
5 hours ago
The way I wished Postgres DDLs worked (at least optionally) is that you have to explicitly acquire the correct lock before a DDL statement, or it just immediately fails. Something like:
ACQUIRE ACCESS SHARE TABLE LOCK ON my_table ALTER TABLE my_table ALTER COLUMN my_column TYPE bigint
This way I _know_ that if the operation needs a stronger lock than I thought or than I'm willing to give it, it will just fail rather than locking up my database and causing unexpected downtime.
nijave
3 hours ago
I think you could automate this with 2 transactions
- connection A, lock timeout=0, acquire unwanted lock
- connection B, lock timeout=0, run migration
- collection A, rollback
Then connection B will fail if it tries to acquire an undesirable lock since it will conflict with A. You'd be adding a very small window when you're actually holding the undesirable lock, though
orf
3 hours ago
This is essentially how my tool discovers locks for a given arbitrary DDL statement.
mxey
4 hours ago
That’s an interesting idea but not all locks are held for the duration of the statement. A lot of them take a less intrusive lock for the whole statement and take an exclusive lock for a very short time when they finish up.
Edit: Looking this up, I’m not sure this is correct.
dathinab
3 hours ago
> whole statement
simplified you can think of a statement outside of a transaction as starting an implicit transaction just for itself
and (normal) locks are in general hold until the end of the transaction (while also allowing re-entrance from subsequent queries on the same transaction)
practically
- there are edge cases (e.g. Advisory Locks, but in general you don't want to use them)
- you normally(^1) would want to run your pg migration as a single transaction (but there are edge cases). And in turn the OPs idea of pre-acquiring locks would be for the whole transaction anyway. Plus it was just a general idea, so the end result could be more like an "expect lock" statement maybe with some scan ahead ability then an "acquire lock".
(^1): Exceptions include certain operations which need to be in different transactions, and some painful situations where too much data is touched/changed/computed and you need a lot of very careful handling you common small-ish PG DB use-case isn't exposed to (and in turn a lot of "naive but often good enough" migration setups can't handle either...)
samlinnfer
2 hours ago
What about the classic pg_dump running in the background?