Right, but the difference is that this is done on the backend with no app awareness. Doing it in the app ties the app logic to the database schema. Using pgroll would allow the database and app to get out of sync.
pgroll presents two versions of the database schema, to be used by the current and vNext versions of the app while syncing data between the two.
An old version of the app can continue to access the old version of the schema until such time as all instances of the application are gracefully shut down. At the same time the new versions of the app can be deployed and run against the new schema.
Seems like a dangerous way to introduce very hard to find data inconsistencies.
To do safe migrations it's a good idea to avoid rolling out versions that start making assumptions about the new schema until the migration is done and dusted.
This does of course start to create weird territory where migrations cease to become trivially "stackable" if you want to retain the whole zero-downtime thing, but this is true for a lot of "graceful update" patterns in computing (in fact I've not seen it solved properly before).
Or make the app do the migration as part of its normal operation, so you have total control over it. :)
I think we're saying the same thing, I'm just suggesting it's safer to do it in the app itself, because then app changes and database changes are tied together instead of divorced from each other.
If you only have one or two people working on the code that interacts with the table that is being changed, both methods are pretty much the same. But if you have a large team or want to be able to rollback better, then doing it all in the app code feels like the better way to go for me.
- For rows inserted/updated through the old version of the schema, the up function gets executed, copying the resulting value into the new column - For rows inserted/updated through the new version, the down function gets executed, copying the resulting value into the old column
For instance, you can test that up function works before releasing the new app relying on it, just by checking that the values present in the new schema are correct.
The good thing is that this will probably be detected during the start phase, as data would fail to be backfilled.
We are thinking of ideas to improve this in the longer term, for example: * Having a dry-run mode where you check that the data present in the DB will stay valid after applying the up function * Optionally allow for this to happen, but "quarantine" the affected rows so they are no longer available in the new schema.
This migration[0] adds a CHECK constraint to a column.
When the migration is started, a new column with the constraint is created and values from the old column are backfilled using the 'up' SQL from the migration. The 'up' SQL rewrites values that don't meet the constraint so that they do.
The same 'up' SQL is used 'on the fly' as data is written to the old schema by applications - the 'up' SQL is used (as part of a trigger) to copy data into the new column, rewriting as necessary to ensure the constraint on the new column is met.
As the sibling comment makes clear, it is currently the migration author's responsibility to ensure that the 'up' SQL really does rewrite values so that they meet the constraint.
[0] - https://github.com/xataio/pgroll/blob/main/examples/22_add_c...
May I suggest spelling this out more explicitly in the docs? As far as I can tell it’s only mentioned by example halfway down the tutorial. To me it seems like one of pgroll’s true killer features, worth more coverage :-)