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Database Migrations

Django migrations are how we handle changes to the database in Sentry.

Django migration official docs: https://docs.djangoproject.com/en/2.2/topics/migrations/ . These will cover most things you need to understand what a migration is doing.

Commands

Note that for all of these commands you can substitute getsentry for sentry if in the getsentry repo.

Upgrade your database to latest

sentry upgrade will automatically bring your migrations up to date. You can also run sentry django migrate to access the migration command directly.

Move your database to a specific migration

This can be helpful for when you want to test a migration.

sentry django migrate <app_name> <migration_name> - Note that migration_name can be a partial match, often the number is all you need.

eg: sentry django migrate sentry 0005

This can be used to roll a migration back as well. Useful in dev if you make a mistake.

Produce SQL for a migration

This is helpful for people reviewing your code, since it's not always clear exactly what a Django migration is actually going to do.

sentry django sqlmigrate <app_name> <migration_name>

eg sentry django sqlmigrate sentry 0003

Generate Migrations

This generates migrations for you automatically based on changes you've made to models.

sentry django makemigrations

or

sentry django makemigrations <app_name> for a specific app.

eg sentry django makemigrations sentry

When you include a migration in a pr, also generate the sql for the migration and include it as a comment so that your reviewers can more easily understand what Django is doing.

You can also generate an empty migration with sentry django makemigrations <app_name> --empty. This is useful for data migrations and other custom work.

Merging migrations to master

When merging to master you might notice a conflict with migrations_lockfile.txt. This file is in place to help us avoid merging two migrations with the same migration number to master, and if you're conflicting with it then it's likely someone has committed a migration ahead of you.

To resolve this, rebase against latest master, delete your current migration and then regenerate it. If your migration was custom, just save the operations in a text file somewhere so that you can reapply them on the regenerated migration.

Always commit the changes to migrations_lockfile.txt with your migration.

Guidelines

There are some things we need to be careful about when running migrations.

Filters

If a (data) migration involves large tables, or columns that aren't indexed it is better to iterate over the entire table instead of using a filter. For example:

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EnvironmentProject.objects.filter(environment__name="none")

Because there are too many EnvironmentProject rows, this will bring too many rows into memory at once. Instead we should iterate over all the EnvironmentProject rows using RangeQuerySetWrapperWithProgressBar since it will do it in chunks. For example:

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for env in RangeQuerySetWrapperWithProgressBar(EnvironmentProject.objects.all()):
	if env.name == 'none':
		# Do what you need

We generally prefer to avoid using .filter with RangeQuerySetWrapperWithProgressBar. Since it already orders by the id to iterate through the table, we can't take advantage of any indexes on the fields, and could potentially scan a large number of rows for each chunk. This will run slower, but we generally prefer that, since it averages the load out over a longer period of time, and makes each query to fetch each chunk fairly cheap.

Indexes

We prefer to create indexes on large existing tables with CREATE INDEX CONCURRENTLY. Our migration framework will do this automatically when creating a new index. Note that when CONCURRENTLY is used we can't run the migration in a transaction, so it's important to use atomic = False to run these.

Deleting columns/tables

This is complicated due to our deploy process. When we deploy, we run migrations, and then push out the application code, which takes a while. This means that if we just delete a column or model, then code in sentry will be looking for those columns/tables and erroring until the deploy completes. In some cases, this can mean Sentry is hard down until the deploy is finished.

To avoid this, follow these steps:

Columns

  • Mark the column as nullable if it isn't, and create a migration.
  • Deploy.
  • Remove the column from the model, but in the migration make sure we only mark the state as removed.
  • Deploy.
  • Finally, create a migration that deletes the column.

Here's an example of removing columns that were already nullable. First we remove the columns from the model, and then modify the migration to only update the state and make no database operations.

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operations = [
        migrations.SeparateDatabaseAndState(
            database_operations=[],
            state_operations=[
                migrations.RemoveField(model_name="alertrule", name="alert_threshold"),
                migrations.RemoveField(model_name="alertrule", name="resolve_threshold"),
                migrations.RemoveField(model_name="alertrule", name="threshold_type"),
            ],
        )
    ]

Once this is deployed, we can then deploy the actual column deletion. This pr will have only a migration, since Django no longer knows about these fields. Note that the reverse SQL is only for dev, so it's fine to not assign a default or do any sort of backfill:

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operations = [
        migrations.SeparateDatabaseAndState(
            database_operations=[
                migrations.RunSQL(
                    """
                    ALTER TABLE "sentry_alertrule" DROP COLUMN "alert_threshold";
                    ALTER TABLE "sentry_alertrule" DROP COLUMN "resolve_threshold";
                    ALTER TABLE "sentry_alertrule" DROP COLUMN "threshold_type";
                    """,
                    reverse_sql="""
                    ALTER TABLE "sentry_alertrule" ADD COLUMN "alert_threshold" smallint NULL;
                    ALTER TABLE "sentry_alertrule" ADD COLUMN "resolve_threshold" int NULL;
                    ALTER TABLE "sentry_alertrule" ADD COLUMN "threshold_type" int NULL;

                    """,
                )
            ],
            state_operations=[],
        )
    ]

Tables

Extra care is needed here if the table is referenced as a foreign key in other tables. In that case, first remove the foreign key columns in the other tables, then come back to this step.

  • Remove any database level foreign key constraints from this table to other tables by setting db_constraint=False on the columns.
  • Deploy
  • Remove the model and all references from the sentry codebase. Make sure that the migration only marks the state as removed.
  • Deploy.
  • Create a migrations that deletes the table.
  • Deploy

Here's an example of removing this model:

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class AlertRuleTriggerAction(Model):
    alert_rule_trigger = FlexibleForeignKey("sentry.AlertRuleTrigger")
    integration = FlexibleForeignKey("sentry.Integration", null=True)
    type = models.SmallIntegerField()
    target_type = models.SmallIntegerField()
    # Identifier used to perform the action on a given target
    target_identifier = models.TextField(null=True)
    # Human readable name to display in the UI
    target_display = models.TextField(null=True)
    date_added = models.DateTimeField(default=timezone.now)

    class Meta:
        app_label = "sentry"
        db_table = "sentry_alertruletriggeraction"

First we checked that it's not referenced by any other models, and it's not. Next we need to remove and db level foreign key constraints. To do this, we change these two columns and generate a migration:

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alert_rule_trigger = FlexibleForeignKey("sentry.AlertRuleTrigger", db_constraint=False)
integration = FlexibleForeignKey("sentry.Integration", null=True, db_constraint=False)

The operations in the migration look like

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    operations = [
        migrations.AlterField(
            model_name='alertruletriggeraction',
            name='alert_rule_trigger',
            field=sentry.db.models.fields.foreignkey.FlexibleForeignKey(db_constraint=False, on_delete=django.db.models.deletion.CASCADE, to='sentry.AlertRuleTrigger'),
        ),
        migrations.AlterField(
            model_name='alertruletriggeraction',
            name='integration',
            field=sentry.db.models.fields.foreignkey.FlexibleForeignKey(db_constraint=False, null=True, on_delete=django.db.models.deletion.CASCADE, to='sentry.Integration'),
        ),
    ]

And we can see the sql it generates just drops the FK constaints

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BEGIN;
SET CONSTRAINTS "a875987ae7debe6be88869cb2eebcdc5" IMMEDIATE; ALTER TABLE "sentry_alertruletriggeraction" DROP CONSTRAINT "a875987ae7debe6be88869cb2eebcdc5";
SET CONSTRAINTS "sentry_integration_id_14286d876e86361c_fk_sentry_integration_id" IMMEDIATE; ALTER TABLE "sentry_alertruletriggeraction" DROP CONSTRAINT "sentry_integration_id_14286d876e86361c_fk_sentry_integration_id";
COMMIT;

So now we deploy this and move onto the next stage.

The next stage involves removing all references to the model from the codebase. So we do that, and then we generate a migration that removes the model from the migration state, but not the database. The operations in this migration look like

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operations = [
        migrations.SeparateDatabaseAndState(
            state_operations=[migrations.DeleteModel(name="AlertRuleTriggerAction")],
            database_operations=[],
        )
    ]

and the generated SQL shows no database changes occurring. So now we deploy this and move into the final step.

In this last step, we just want to manually write DDL to remove the table. So we use sentry django makemigrations --empty to produce an empty migration, and then modify the operations to be like:

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operations = [
        migrations.RunSQL(
            """
            DROP TABLE "sentry_alertruletriggeraction";
            """,
            reverse_sql="CREATE TABLE sentry_alertruletriggeraction (fake_col int)", # We just create a fake table here so that the DROP will work if we roll back the migration.
        )
    ]

Then we deploy this and we're done.

Foreign Keys

Creating foreign keys is mostly fine, but for some large/busy tables like Project, Group it can cause problems due to difficulties in acquiring a lock. You can still create a Django level foreign key though, without creating a database constraint. To do so, set db_constraint=False when defining the key.

Renaming Tables

Renaming tables is dangerous and will result in downtime. The reason this occurs is that during the deploy a mix of old/new code will be running. So once we rename the table in Postgres, the old code will immediately start erroring if it attempts to access it. There are two ways to handle renaming a table:

  • Don't rename the table in Postgres. Instead, just rename the model in Django, and make sure Meta.db_table is set to the current tablename so that nothing breaks. This is the preferred method.
  • If you absolutely want to rename the table, then the steps would be:
  • Create a table with the new name
  • Start dual-writing to both the old and new table, ideally in a transaction.
  • Backfill the old rows into the new table.
  • Change the model to start reading from the new table.
  • Stop writing to the old table and remove references from the code.
  • Drop the old table.
  • Generally, this is not worth doing and a lot of risk/effort compared to the reward.

Adding Columns

When creating new columns they should always be created as nullable. This is for two reasons:

  • If there are existing rows, adding a not null column requires a default to be set, and adding a default requires a full rewrite of the table. This is dangerous and will most likely result in downtime
  • During the deploy, a mix of old and new code is running. If old code attempts to insert a row to the table the insert will fail, since the old code doesn't know the new column exist, and so has no way to provide a value to the column.

Adding Not Null To Columns

It can be dangerous to add not null to columns, even if there is data in every row of the table for that column. This is because Postgres still needs to perform a not null check on all rows before it can add the constraint. On small tables this can be fine since the check will be quick, but on larger tables this can cause downtime. There are a few options here to make this safe:

  • ALTER TABLE tbl ADD CONSTRAINT cnstr CHECK (col IS NOT NULL) NOT VALID; ALTER TABLE tbl VALIDATE CONSTRAINT cnstr;. First we create the constraint as not valid. Then we validate it afterwards. We still need to scan the whole table to validate, but we only need to hold a SHARE UPDATE EXCLUSIVE lock, which only blocks other ALTER TABLE commands, but will allow reads/writes to continue. This works well, but has a slight performance penalty of 0.5-1%. After Postgres 12 we can extend this method to add a real NOT NULL constraint.
  • If the table is small enough and has low enough volume it should be safe to just create a normal NOT NULL constraint. Small being a few million rows or less.

Adding Columns With a Default

Adding columns with a default to an existing table is dangerous. This requires Postgres to lock the table and rewrite it. Instead, the better option is to:

  • Add the column without a default in Postgres, but with a default in Django. This allows us to be sure that all new rows have the default. This is done by modifying the migration file to include migrations.SeperateDatabaseAndState
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operations = [
    migrations.SeparateDatabaseAndState(
        database_operations=[
            migrations.AddField(
                model_name="mymodel",
                name="new_field",
                # Don't use a default in Postgres, a data migration can be used afterward to backfill
                field=models.PositiveSmallIntegerField(null=True),
            ),
        ],
        state_operations=[
            migrations.AddField(
                model_name="mymodel",
                name="new_field",
                # Use the default in Django, new rows will use the specified default
                field=models.PositiveSmallIntegerField(null=True, default=1),
            ),
        ],
    )
    ]
  • Backfill the pre-existing rows with the default via a data migration.

Altering Column Types

Altering the type of a column is usually dangerous, since it will require a whole table rewrite. There are some exceptions:

  • Altering a varchar(<size>) to a varchar with a larger size.
  • Altering any varchar to text
  • Altering a numeric to a numeric where the precision is higher but the scale is the same.

For any other types, the best path forward is usually:

  • Create a column with the new type
  • Start dual-writing to both the old and new column.
  • Backfill and convert the old column values into the new column.
  • Change the code to use the new field.
  • Stop writing to the old column and remove references from the code.
  • Drop the old column from the database.

Generally this can be worth a discussion in #discuss-backend.

Renaming Columns

Renaming columns is dangerous and will result in downtime. The reason this occurs is that during the deploy a mix of old/new code will be running. So once we rename the column in Postgres, the old code will immediately start erroring if it attempts to access it. There are two ways to handle renaming a column:

  • Don't rename the column in Postgres. Instead, just rename the field in Django, and use db_column in the definition to set it to the existing column name so that nothing breaks. This is the preferred method.
  • If you absolutely want to rename the column, then the steps would be:
    • Create a column with the new name
    • Start dual-writing to both the old and new column.
    • Backfill the old column values into the new column.
    • Change the field to start reading from the new column.
    • Stop writing to the old column and remove references from the code.
    • Drop the old column from the database.
    • Generally, this is not worth doing and a lot of risk/effort compared to the reward.
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