debian-mirror-gitlab/doc/development/database/batched_background_migrations.md

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---
type: reference, dev
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stage: Data Stores
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group: Database
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info: "See the Technical Writers assigned to Development Guidelines: https://about.gitlab.com/handbook/product/ux/technical-writing/#assignments-to-development-guidelines"
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---
# Batched background migrations
Batched Background Migrations should be used to perform data migrations whenever a
migration exceeds [the time limits](../migration_style_guide.md#how-long-a-migration-should-take)
in our guidelines. For example, you can use batched background
migrations to migrate data that's stored in a single JSON column
to a separate table instead.
## When to use batched background migrations
Use a batched background migration when you migrate _data_ in tables containing
so many rows that the process would exceed
[the time limits in our guidelines](../migration_style_guide.md#how-long-a-migration-should-take)
if performed using a regular Rails migration.
- Batched background migrations should be used when migrating data in
[high-traffic tables](../migration_style_guide.md#high-traffic-tables).
- Batched background migrations may also be used when executing numerous single-row queries
for every item on a large dataset. Typically, for single-record patterns, runtime is
largely dependent on the size of the dataset. Split the dataset accordingly,
and put it into background migrations.
- Don't use batched background migrations to perform schema migrations.
Background migrations can help when:
- Migrating events from one table to multiple separate tables.
- Populating one column based on JSON stored in another column.
- Migrating data that depends on the output of external services. (For example, an API.)
NOTE:
If the batched background migration is part of an important upgrade, it must be announced
in the release post. Discuss with your Project Manager if you're unsure if the migration falls
into this category.
## Isolation
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Batched background migrations must be isolated and cannot use application code (for example,
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models defined in `app/models` except the `ApplicationRecord` classes).
Because these migrations can take a long time to run, it's possible
for new versions to deploy while the migrations are still running.
## Accessing data for multiple databases
Background Migration contrary to regular migrations does have access to multiple databases
and can be used to efficiently access and update data across them. To properly indicate
a database to be used it is desired to create ActiveRecord model inline the migration code.
Such model should use a correct [`ApplicationRecord`](multiple_databases.md#gitlab-schema)
depending on which database the table is located. As such usage of `ActiveRecord::Base`
is disallowed as it does not describe a explicitly database to be used to access given table.
```ruby
# good
class Gitlab::BackgroundMigration::ExtractIntegrationsUrl
class Project < ::ApplicationRecord
self.table_name = 'projects'
end
class Build < ::Ci::ApplicationRecord
self.table_name = 'ci_builds'
end
end
# bad
class Gitlab::BackgroundMigration::ExtractIntegrationsUrl
class Project < ActiveRecord::Base
self.table_name = 'projects'
end
class Build < ActiveRecord::Base
self.table_name = 'ci_builds'
end
end
```
Similarly the usage of `ActiveRecord::Base.connection` is disallowed and needs to be
replaced preferably with the usage of model connection.
```ruby
# good
Project.connection.execute("SELECT * FROM projects")
# acceptable
ApplicationRecord.connection.execute("SELECT * FROM projects")
# bad
ActiveRecord::Base.connection.execute("SELECT * FROM projects")
```
## Idempotence
Batched background migrations are executed in a context of a Sidekiq process.
The usual Sidekiq rules apply, especially the rule that jobs should be small
and idempotent. Make sure that in case that your migration job is retried, data
integrity is guaranteed.
See [Sidekiq best practices guidelines](https://github.com/mperham/sidekiq/wiki/Best-Practices)
for more details.
## Batched background migrations for EE-only features
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All the background migration classes for EE-only features should be present in GitLab FOSS.
For this purpose, create an empty class for GitLab FOSS, and extend it for GitLab EE
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as explained in the guidelines for
[implementing Enterprise Edition features](../ee_features.md#code-in-libgitlabbackground_migration).
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NOTE:
Background migration classes for EE-only features that use job arguments should define them
in the GitLab FOSS class. This is required to prevent job arguments validation from failing when
migration is scheduled in GitLab FOSS context.
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Batched Background migrations are simple classes that define a `perform` method. A
Sidekiq worker then executes such a class, passing any arguments to it. All
migration classes must be defined in the namespace
`Gitlab::BackgroundMigration`. Place the files in the directory
`lib/gitlab/background_migration/`.
## Queueing
Queueing a batched background migration should be done in a post-deployment
migration. Use this `queue_batched_background_migration` example, queueing the
migration to be executed in batches. Replace the class name and arguments with the values
from your migration:
```ruby
queue_batched_background_migration(
JOB_CLASS_NAME,
TABLE_NAME,
JOB_ARGUMENTS,
JOB_INTERVAL
)
```
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NOTE:
This helper raises an error if the number of provided job arguments does not match
the number of [job arguments](#job-arguments) defined in `JOB_CLASS_NAME`.
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Make sure the newly-created data is either migrated, or
saved in both the old and new version upon creation. Removals in
turn can be handled by defining foreign keys with cascading deletes.
### Requeuing batched background migrations
If one of the batched background migrations contains a bug that is fixed in a patch
release, you must requeue the batched background migration so the migration
repeats on systems that already performed the initial migration.
When you requeue the batched background migration, turn the original
queuing into a no-op by clearing up the `#up` and `#down` methods of the
migration performing the requeuing. Otherwise, the batched background migration is
queued multiple times on systems that are upgrading multiple patch releases at
once.
When you start the second post-deployment migration, delete the
previously batched migration with the provided code:
```ruby
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delete_batched_background_migration(MIGRATION_NAME, TABLE_NAME, COLUMN, JOB_ARGUMENTS)
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```
## Cleaning up
NOTE:
Cleaning up any remaining background migrations must be done in either a major
or minor release. You must not do this in a patch release.
Because background migrations can take a long time, you can't immediately clean
things up after queueing them. For example, you can't drop a column used in the
migration process, as jobs would fail. You must add a separate _post-deployment_
migration in a future release that finishes any remaining
jobs before cleaning things up. (For example, removing a column.)
To migrate the data from column `foo` (containing a big JSON blob) to column `bar`
(containing a string), you would:
1. Release A:
1. Create a migration class that performs the migration for a row with a given ID.
1. Update new rows using one of these techniques:
- Create a new trigger for simple copy operations that don't need application logic.
- Handle this operation in the model/service as the records are created or updated.
- Create a new custom background job that updates the records.
1. Queue the batched background migration for all existing rows in a post-deployment migration.
1. Release B:
1. Add a post-deployment migration that checks if the batched background migration is completed.
1. Deploy code so that the application starts using the new column and stops to update new records.
1. Remove the old column.
Bump to the [import/export version](../../user/project/settings/import_export.md) may
be required, if importing a project from a prior version of GitLab requires the
data to be in the new format.
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## Job arguments
`BatchedMigrationJob` provides the `job_arguments` helper method for job classes to define the job arguments they need.
Batched migrations scheduled with `queue_batched_background_migration` **must** use the helper to define the job arguments:
```ruby
queue_batched_background_migration(
'CopyColumnUsingBackgroundMigrationJob',
TABLE_NAME,
'name', 'name_convert_to_text',
job_interval: DELAY_INTERVAL
)
```
NOTE:
If the number of defined job arguments does not match the number of job arguments provided when
scheduling the migration, `queue_batched_background_migration` raises an error.
In this example, `copy_from` returns `name`, and `copy_to` returns `name_convert_to_text`:
```ruby
class CopyColumnUsingBackgroundMigrationJob < BatchedMigrationJob
job_arguments :copy_from, :copy_to
def perform
from_column = connection.quote_column_name(copy_from)
to_column = connection.quote_column_name(copy_to)
assignment_clause = "#{to_column} = #{from_column}"
each_sub_batch(operation_name: :update_all) do |relation|
relation.update_all(assignment_clause)
end
end
end
```
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## Additional filters
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By default, when creating background jobs to perform the migration, batched background migrations
iterate over the full specified table. This iteration is done using the
[`PrimaryKeyBatchingStrategy`](https://gitlab.com/gitlab-org/gitlab/-/blob/c9dabd1f4b8058eece6d8cb4af95e9560da9a2ee/lib/gitlab/database/migrations/batched_background_migration_helpers.rb#L17). If the table has 1000 records
and the batch size is 100, the work is batched into 10 jobs. For illustrative purposes,
`EachBatch` is used like this:
```ruby
# PrimaryKeyBatchingStrategy
Namespace.each_batch(of: 100) do |relation|
relation.where(type: nil).update_all(type: 'User') # this happens in each background job
end
```
In some cases, only a subset of records must be examined. If only 10% of the 1000 records
need examination, apply a filter to the initial relation when the jobs are created:
```ruby
Namespace.where(type: nil).each_batch(of: 100) do |relation|
relation.update_all(type: 'User')
end
```
In the first example, we don't know how many records will be updated in each batch.
In the second (filtered) example, we know exactly 100 will be updated with each batch.
`BatchedMigrationJob` provides a `scope_to` helper method to apply additional filters and achieve this:
1. Create a new migration job class that inherits from `BatchedMigrationJob` and defines the additional filter:
```ruby
class BackfillNamespaceType < BatchedMigrationJob
scope_to ->(relation) { relation.where(type: nil) }
def perform
each_sub_batch(operation_name: :update_all) do |sub_batch|
sub_batch.update_all(type: 'User')
end
end
end
```
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NOTE:
For EE migrations that define `scope_to`, ensure the module extends `ActiveSupport::Concern`.
Otherwise, records are processed without taking the scope into consideration.
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1. In the post-deployment migration, enqueue the batched background migration:
```ruby
class BackfillNamespaceType < Gitlab::Database::Migration[2.0]
MIGRATION = 'BackfillNamespaceType'
DELAY_INTERVAL = 2.minutes
restrict_gitlab_migration gitlab_schema: :gitlab_main
def up
queue_batched_background_migration(
MIGRATION,
:namespaces,
:id,
job_interval: DELAY_INTERVAL
)
end
def down
delete_batched_background_migration(MIGRATION, :namespaces, :id, [])
end
end
```
NOTE:
When applying additional filters, it is important to ensure they are properly covered by an index to optimize `EachBatch` performance.
In the example above we need an index on `(type, id)` to support the filters. See [the `EachBatch` docs for more information](../iterating_tables_in_batches.md).
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## Example
The `routes` table has a `source_type` field that's used for a polymorphic relationship.
As part of a database redesign, we're removing the polymorphic relationship. One step of
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the work is migrating data from the `source_id` column into a new singular foreign key.
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Because we intend to delete old rows later, there's no need to update them as part of the
background migration.
1. Start by defining our migration class, which should inherit
from `Gitlab::BackgroundMigration::BatchedMigrationJob`:
```ruby
class Gitlab::BackgroundMigration::BackfillRouteNamespaceId < BatchedMigrationJob
# For illustration purposes, if we were to use a local model we could
# define it like below, using an `ApplicationRecord` as the base class
# class Route < ::ApplicationRecord
# self.table_name = 'routes'
# end
def perform
each_sub_batch(
operation_name: :update_all,
batching_scope: -> (relation) { relation.where("source_type <> 'UnusedType'") }
) do |sub_batch|
sub_batch.update_all('namespace_id = source_id')
end
end
end
```
NOTE:
Job classes must be subclasses of `BatchedMigrationJob` to be
correctly handled by the batched migration framework. Any subclass of
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`BatchedMigrationJob` is initialized with necessary arguments to
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execute the batch, as well as a connection to the tracking database.
1. Add a new trigger to the database to update newly created and updated routes,
similar to this example:
```ruby
execute(<<~SQL)
CREATE OR REPLACE FUNCTION example() RETURNS trigger
LANGUAGE plpgsql
AS $$
BEGIN
NEW."namespace_id" = NEW."source_id"
RETURN NEW;
END;
$$;
SQL
```
1. Create a post-deployment migration that queues the migration for existing data:
```ruby
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class QueueBackfillRoutesNamespaceId < Gitlab::Database::Migration[2.0]
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MIGRATION = 'BackfillRouteNamespaceId'
DELAY_INTERVAL = 2.minutes
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restrict_gitlab_migration gitlab_schema: :gitlab_main
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def up
queue_batched_background_migration(
MIGRATION,
:routes,
:id,
job_interval: DELAY_INTERVAL
)
end
def down
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delete_batched_background_migration(MIGRATION, :routes, :id, [])
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end
end
```
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NOTE:
When queuing a batched background migration, you need to restrict
the schema to the database where you make the actual changes.
In this case, we are updating `routes` records, so we set
`restrict_gitlab_migration gitlab_schema: :gitlab_main`. If, however,
you need to perform a CI data migration, you would set
`restrict_gitlab_migration gitlab_schema: :gitlab_ci`.
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After deployment, our application:
- Continues using the data as before.
- Ensures that both existing and new data are migrated.
1. In the next release, remove the trigger. We must also add a new post-deployment migration
that checks that the batched background migration is completed. For example:
```ruby
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class FinalizeBackfillRouteNamespaceId < Gitlab::Database::Migration[2.0]
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MIGRATION = 'BackfillRouteNamespaceId'
disable_ddl_transaction!
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restrict_gitlab_migration gitlab_schema: :gitlab_main
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def up
ensure_batched_background_migration_is_finished(
job_class_name: MIGRATION,
table_name: :routes,
column_name: :id,
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job_arguments: [],
finalize: true
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)
end
def down
# no-op
end
end
```
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NOTE:
If the batched background migration is not finished, the system will
execute the batched background migration inline. If you don't want
to see this behavior, you need to pass `finalize: false`.
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If the application does not depend on the data being 100% migrated (for
instance, the data is advisory, and not mission-critical), then you can skip this
final step. This step confirms that the migration is completed, and all of the rows were migrated.
After the batched migration is completed, you can safely depend on the
data in `routes.namespace_id` being populated.
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### Batching over non-distinct columns
The default batching strategy provides an efficient way to iterate over primary key columns.
However, if you need to iterate over columns where values are not unique, you must use a
different batching strategy.
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The `LooseIndexScanBatchingStrategy` batching strategy uses a special version of [`EachBatch`](iterating_tables_in_batches.md#loose-index-scan-with-distinct_each_batch)
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to provide efficient and stable iteration over the distinct column values.
This example shows a batched background migration where the `issues.project_id` column is used as
the batching column.
Database post-migration:
```ruby
class ProjectsWithIssuesMigration < Gitlab::Database::Migration[2.0]
MIGRATION = 'BatchProjectsWithIssues'
INTERVAL = 2.minutes
BATCH_SIZE = 5000
SUB_BATCH_SIZE = 500
restrict_gitlab_migration gitlab_schema: :gitlab_main
disable_ddl_transaction!
def up
queue_batched_background_migration(
MIGRATION,
:issues,
:project_id,
job_interval: INTERVAL,
batch_size: BATCH_SIZE,
batch_class_name: 'LooseIndexScanBatchingStrategy', # Override the default batching strategy
sub_batch_size: SUB_BATCH_SIZE
)
end
def down
delete_batched_background_migration(MIGRATION, :issues, :project_id, [])
end
end
```
Implementing the background migration class:
```ruby
module Gitlab
module BackgroundMigration
class BatchProjectsWithIssues < Gitlab::BackgroundMigration::BatchedMigrationJob
include Gitlab::Database::DynamicModelHelpers
def perform
distinct_each_batch(operation_name: :backfill_issues) do |batch|
project_ids = batch.pluck(batch_column)
# do something with the distinct project_ids
end
end
end
end
end
```
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NOTE:
[Additional filters](#additional-filters) defined with `scope_to` will be ignored by `LooseIndexScanBatchingStrategy` and `distinct_each_batch`.
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## Testing
Writing tests is required for:
- The batched background migrations' queueing migration.
- The batched background migration itself.
- A cleanup migration.
The `:migration` and `schema: :latest` RSpec tags are automatically set for
background migration specs. Refer to the
[Testing Rails migrations](../testing_guide/testing_migrations_guide.md#testing-a-non-activerecordmigration-class)
style guide.
Remember that `before` and `after` RSpec hooks
migrate your database down and up. These hooks can result in other batched background
migrations being called. Using `spy` test doubles with
`have_received` is encouraged, instead of using regular test doubles, because
your expectations defined in a `it` block can conflict with what is
called in RSpec hooks. Refer to [issue #35351](https://gitlab.com/gitlab-org/gitlab/-/issues/18839)
for more details.
## Best practices
1. Know how much data you're dealing with.
1. Make sure the batched background migration jobs are idempotent.
1. Confirm the tests you write are not false positives.
1. If the data being migrated is critical and cannot be lost, the
clean-up migration must also check the final state of the data before completing.
1. Discuss the numbers with a database specialist. The migration may add
more pressure on DB than you expect. Measure on staging,
or ask someone to measure on production.
1. Know how much time is required to run the batched background migration.
## Additional tips and strategies
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### ChatOps integration
The batched background migrations framework has ChatOps support. Using ChatOps, GitLab engineers can interact with the batched background migrations present in the system.
#### List batched background migrations
To list the batched background migrations in the system, run this command:
`/chatops run batched_background_migrations list`
This command supports the following options:
- Database selection:
- `--database DATABASE_NAME`: Connects to the given database:
- `main`: Uses the main database (default).
- `ci`: Uses the CI database.
- Environment selection:
- `--dev`: Uses the `dev` environment.
- `--staging`: Uses the `staging` environment.
- `--staging_ref`: Uses the `staging_ref` environment.
- `--production` : Uses the `production` environment (default).
Output example:
![List command](img/list_v15_4.png)
NOTE:
ChatOps returns 20 batched background migrations order by `created_at` (DESC).
#### Monitor the progress and status of a batched background migration
To see the status and progress of a specific batched background migration, run this command:
`/chatops run batched_background_migrations status MIGRATION_ID`
This command supports the following options:
- Database selection:
- `--database DATABASE_NAME`: Connects to the given database:
- `main`: Uses the main database (default)
- `ci`: Uses the CI database
- Environment selection:
- `--dev`: Uses the `dev` environment.
- `--staging`: Uses the `staging` environment.
- `--staging_ref`: Uses the `staging_ref` environment.
- `--production` : Uses the `production` environment (default).
Output example:
![Status command](img/status_v15_4.png)
`Progress` represents the percentage of the background migration that has been completed.
Definitions of the batched background migration states:
- **Active:** Either:
- Ready to be picked by the runner.
- Running batched jobs.
- **Finalizing:** Running batched jobs.
- **Failed:** Failed batched background migration.
- **Finished:** Completed batched background migration.
- **Paused:** Not visible to the runner.
#### Pause a batched background migration
If you want to pause a batched background migration, you need to run the following command:
`/chatops run batched_background_migrations pause MIGRATION_ID`
This command supports the following options:
- Database selection:
- `--database DATABASE_NAME`: Connects to the given database:
- `main`: Uses the main database (default).
- `ci`: Uses the CI database.
- Environment selection:
- `--dev`: Uses the `dev` environment.
- `--staging`: Uses the `staging` environment.
- `--staging_ref`: Uses the `staging_ref` environment.
- `--production` : Uses the `production` environment (default).
Output example:
![Pause command](img/pause_v15_4.png)
NOTE:
You can pause only `active` batched background migrations.
#### Resume a batched background migration
If you want to resume a batched background migration, you need to run the following command:
`/chatops run batched_background_migrations resume MIGRATION_ID`
This command supports the following options:
- Database selection:
- `--database DATABASE_NAME`: Connects to the given database:
- `main`: Uses the main database (default).
- `ci`: Uses the CI database.
- Environment selection:
- `--dev`: Uses the `dev` environment.
- `--staging`: Uses the `staging` environment.
- `--staging_ref`: Uses the `staging_ref` environment.
- `--production` : Uses the `production` environment (default).
Output example:
![Resume command](img/resume_v15_4.png)
NOTE:
You can resume only `active` batched background migrations
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### Viewing failure error logs
You can view failures in two ways:
- Via GitLab logs:
1. After running a batched background migration, if any jobs fail,
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view the logs in [Kibana](https://log.gprd.gitlab.net/goto/4cb43f40-f861-11ec-b86b-d963a1a6788e).
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View the production Sidekiq log and filter for:
- `json.new_state: failed`
- `json.job_class_name: <Batched Background Migration job class name>`
- `json.job_arguments: <Batched Background Migration job class arguments>`
1. Review the `json.exception_class` and `json.exception_message` values to help
understand why the jobs failed.
1. Remember the retry mechanism. Having a failure does not mean the job failed.
Always check the last status of the job.
- Via database:
1. Get the batched background migration `CLASS_NAME`.
1. Execute the following query in the PostgreSQL console:
```sql
SELECT migration.id, migration.job_class_name, transition_logs.exception_class, transition_logs.exception_message
FROM batched_background_migrations as migration
INNER JOIN batched_background_migration_jobs as jobs
ON jobs.batched_background_migration_id = migration.id
INNER JOIN batched_background_migration_job_transition_logs as transition_logs
ON transition_logs.batched_background_migration_job_id = jobs.id
WHERE transition_logs.next_status = '2' AND migration.job_class_name = "CLASS_NAME";
```
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## Legacy background migrations
Batched background migrations replaced the [legacy background migrations framework](background_migrations.md).
Check that documentation in reference to any changes involving that framework.