This document contains information on what you need to know about Django Migrations in the Open edX platform.  If you are unfamiliar with database migrations, or, specifically, Django migrations, please read the reference documentation.  Django does a good job of abstracting away what's behind the scenes when you run "./manage.py makemigrations" and "./manage.py migrate"- understanding what happens during these operations is extremely useful.

Reference documentation

• Django documentation for table models

• Django Migrations

• Documentation for admin site
  
  

When in doubt

If you have non-trivial migrations to apply, or if two non-local environments (e.g. stage and production) have different migration states, describe your situation in the #django Slack channel and go talk to the SRE team before doing anything else.  Similarly, migrations can become complicated when two different people create two different migrations around the same time.  When in doubt, post in #django and talk to SRE.

It is often useful to review or provide the SQL generated by a migration. See sqlmigrate doc for details.

Don't revert code that includes migrations, don't change old migrations.

Django migrations should be considered "applied" as soon as they land on master of a repo. Missing ( ghost ) migrations cause problems for Django, and require manual intervention to fix.  Fix forward on migrations. Be sure to properly consider all the points below so that you're less likely to want to delete or change a migration.  If you do delete a migration, or revert a commit that contains a migration, follow this guide to communicating with the organization and the community: How to revert a migration from master.  Also, you should never roll back migrations (manually) without rolling back the code that relies on them.

If you still think you need to change old migrations, and you want to verify that there isn't an alternative, see the "When in doubt" section.

Also, if you absolutely must change old migrations (this includes things like squashing), after merging and verifying your migration changes, you should update the sql that is used to populate devstack during provisioning. This is to prevent conflicts during provisioning in the future. To update the sql, in the devstack repository, run .update-dbs-init-sql-scripts.sh . This should update edxapp.sql, edxapp_csmh.sql, and ecommerce.sql. Create a PR with the updated sql and merge to devstack as usual.

Don't change the parent of a migration

Along the same lines of a migration being considered "applied" once merged into master, you should never change the dependencies of a migration once it has landed on master.  It will cause real problems and probably downtime for which environment it is deployed to.  When you create new migrations in a feature branch, you want those to be the most recent migrations when you merge into master.  Using an analogy to git, you always want your new migrations to be at the "HEAD" of the migration history in your app.

Deployment and backward-compatible migrations

Here at edX, we use the blue-green deployment method. The important detail about this deployment method is that, for some period of time, traffic is going to both the old code and new code. That detail is especially important when deploying database migrations that alter database columns and tables in a manner that is not backward-compatible with the previous release.

Let's go through a couple examples with our user table, auth_user. It has a few different columns, but we'll use the full_name column for the examples.

Say we decide to change the column's name from full_name (with an underscore) to fullname (no underscore). Our code in production is using full_name. When it's time to deploy this new release, we simply generate a migration and deploy it. Since we are using blue-green deployments, our old code is still looking for the original column name, full_name. However, the new deployment changed the name to fullname, so the original code starts failing.

Instead of renaming the column, say we delete it completely. Again, the database is modified when we deploy, and the original code that is still running will fail.

Because we operate in an environment where new and old code are running simultaneously against the same database, new code must always be compatible with the older database schema. Newer deployments can add tables and columns, but neither can be deleted unless the old code is no longer referencing the deleted tables or columns.

Migration Unit Test

In the edx-platform codebase there is a unit test test_migrations_are_in_sync in test_db.py which ensures that django migrations and models are in sync. Migrations to drop columns or tables generally require at least two releases, one which removes references and one which has the drop migration. The first release will fail the unit test. For this reason you will need to skip that unit test during your release sequence and restore it when you are done. This also applies to libraries used by edx-platform, such as edx-proctoring, the test will fail when edx-platform receives the interim version.

The skip should include a ticket number and brief info on what it's for:

How to drop a column

Nullable/Non-Nullable Columns

For either a nullable or non-nullable column, first make sure there are no other models or code that actually use the column. If there are, make adjustments to those first before working through the deletion flow.

For NULLABLE columns, this involves TWO releases:

1. Remove all usages of the column, including updating the model to not refer to the field/column anymore (i.e. Model field must be removed in this step)

   1. If this change is in the edx-platform codebase, add a skip to the test_migrations_are_in_sync unit test.

2. Drop the column (with a migration).

   1. If this change is in the edx-platform codebase, remove the skip to the test_migrations_are_in_sync unit test.

For NOT-NULLABLE columns, this involves THREE releases:

1. Update the model and generate a migration making the column nullable (`null=True`)

2. Remove all usages of the column, including updating the model to not refer to the field/column anymore (i.e. Model field must be removed in this step)

   1. If this change is in the edx-platform codebase, add a skip to the test_migrations_are_in_sync unit test.

3. Drop the column (with a migration).

   1. If this change is in the edx-platform codebase, remove the skip to the test_migrations_are_in_sync unit test.

Returning to our example with the auth_user table. If we still want to drop the full_name column, we should do the following:

1. Remove every usage of the full_name column in our codebase. Skip the unit test. Release that change to production, and ensure older code is no longer running. (We once had a stale ASG in production a few hours after a release, and it caused a few issues when we dropped a column.)

2. Create a database migration to drop the column. Restore the unit test. Release it.

3. (This step intentionally left bank...because nothing broke in production!)

ManyToManyField Columns

When dropping ManyToManyField columns, consider that the Django ORM uses a complicated automatic mapping to map the field to certain model names. So unlike other columns where it's easy to remove all usages of the column, unexpected column usages can still occur via the Django ORM manager (such as django.db.models.fields.related_descriptors.create_reverse_many_to_one_manager). So the field removal and the migration should be two separate steps.

So - for dropping ManyToManyField columns, use at least TWO releases:

1. Remove the ManyToManyField field from the model, while skipping the test_migrations_are_in_sync unit test. Deploy.

2. Add the migration which actually removes the ManyToManyField from the DB (which is actually implemented via a separate table) and unskip the test_migrations_are_in_sync unit test. Deploy.

Failing to separate the two steps may result in the field being used by the old code during the blue-green deployment after the migration has been performed, resulting in production errors.

How to rename a column

Renaming a column while keeping the business logic fully functional and without taking any down time is a very delicate and complex process.  Some things to keep in mind before you start:

1. Do not allow downtime or alter business logic between releases.

2. Do not allow downtime or alter business logic during a release, i.e. after migrations and before code deployment.

3. Do not allow any data to be permanently dropped, even if only a subset of the data.

4. Every release must have a functional rollback plan.

5. As best as possible, avoid releases that must be immediately followed up by another release.  It should be safe to walk away from the rollout halfway through (e.g. code freezes, vacations, etc. might stop work).

THREE releases:

1. Release:

   • Add the new field to the model.

     • If the old field has null=False, blank=False, and no default:

       • If the model is used in forms (django admin, or other forums):

         • Create the new field with null=True, editable=False.

         • disabling editable removes the field from

       • else:

         • Create the new field with null=True.

     • else if the old field is a BooleanField:

       • You might need to change the old field type to NullableBooleanField so that unit tests in release 2 will be happy when the old field is removed from code but not sqlite3.

       • Create the new field with BooleanField and the same signature, assuming there's a default set.

     • else if the old field has null=true:

       • Create the new field with the same field signature as the old.

   • Update any place where there are creates or updates on the field

     • Write the same value into both fields

     • If there is a Django admin page or other form and it is used regularly to create/update rows:

       • Register a signal handler to the model to update the new field whenever the old field changes or a new row is created.

2. Release:

   • Create a data migration to copy the values from the old field into the new field.

     • If the table is large, consider disabling atomicity and batching the copy.

   • Remove all references to the old field in the code.

     • Including removing the old field from the model in the code.

     • If this change is in the edx-platform codebase, add a skip to the test_migrations_are_in_sync unit test.

     • DO NOT include the migration for removing the old column (yet).

   • If you create the new field with a different field signature than the old, then update it now to be the same as the old.

     • e.g. change null back to False and editable back to True (the default).

       • CAUTION: Changing to null=False will cause a table rebuild during the ALTER. When performing this migration on a table with a large number of rows, degraded performance/downtime will likely result.

       • See Howtoaddanullablecolumntoanexistingtable(AWSAurora) below.

     • include the migration that goes with this, but NOT the migration to remove the old field.

3. Release:

   • Run makemigrations, this should pick up the field removal from the previous stage.

   • If this change is in the edx-platform codebase, remove the skip to the test_migrations_are_in_sync unit test.

How to drop a table

Pre-requirements:

• A 2U employee must create a Data Platform 1-off request to ensure that there will be no complications due to losing the table (e.g. financial data, or otherwise), and to determine the follow-up required.

  • This must happen before removing the actual tables in 2U Production.

TWO releases (after pre-requirements):

1. Remove all references to the table by removing references to the model and the model itself

   1. If this change is in the edx-platform codebase, add a skip to the test_migrations_are_in_sync unit test.

2. Remove the table with a migration

   1. Important: If 2U has determined that their data can't be lost during pre-requirements above, the merge should be timed with a pipeline pause so the delete migration can be faked.

      1. This should be a rare occurrence, but it has happened.

   2. Remove the skip if you added one

Once a table is removed:

• A 2U employee should:

  • Follow up with the Data Platform ticket to clean up the table from downstream consumers of data. 

  • If there is an associated app-permissions group then a 2U employee must make an app-permissions PR to remove that group.

How to delete a Django app containing tables

See Removing a Djangoapp from an existing project.

Mathematical perspective: Database Expansion/Contraction

A good way to think of this is that migrations can "expand" and "contract" the database. Adding fields is an expansion, and removing them is a contraction. If you're feeling a bit more mathematical today, there's a partial ordering relation on (db, code) where your database and code are in the relation iff the set of fields in the DB is a (non-strict) superset of the fields in the code (... well, this isn't quite right, since changing fields is OK in circumstances like extending the length of a CharField. Defining the relation precisely is left as an exercise to the reader).  Under this model, changing a field (say, from a plain CharField to an EmailField) would consist of an expansion (adding the EmailField) followed later (potentially much later, but mainly not in the same release) by a contraction (deleting the CharField). Code can also expand and contract in similar ways, by changing which fields are declared in your Django models.

For a migration to be backwards compatible, the database must always be at least as "large" as the code. It can be larger (contain a field not referenced by the code), but not smaller.

Data migrations

If you're writing a data migration, don't import the model directly. Instead, allow Django to use the historical version of your model. This will allow your migration step to use the old (historical) version of your model, even if the model will later by changed by a subsequent database migration.

Sample code from the Django docs

Deployment and migrations for large or problematic tables

First read "Deployment and backward-compatible migrations" for general information about handling blue-green deployments. Then see this section for special consideration for large or problematic tables.

Modifying tables (MySQL 8, AWS Aurora version 3)

Operations in MySQL - and that includes AWS Aurora for MySQL - can have a significant performance impact on large tables, which causes downtime that needs to be avoided.
Generally there are two things that need to be avoided. 1. Rebuilding the table and 2. copying the table data.

For every operation performed by the migration, you want to ensure that it does not rebuild the table, and that it is performed in place or instant.
The documentation specifies which operations will rebuild tables, and which operations support ALGORITHM=INSTANT or ALGORITHM=INPLACE:

• https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/AuroraMySQL.Managing.FastDDL.html

• https://dev.mysql.com/doc/refman/8.0/en/innodb-online-ddl-operations.html

• https://dev.mysql.com/doc/refman/8.0/en/alter-table.html

Consider explicitly adding ALGORITHM=INSTANT / ALGORITHM=INPLACE and LOCK=NONE where you want it, even if they are sometimes already provided by default by Aurora. That way, if there's a problem, MySQL will generate an error instead of silently skipping them and running a slow migration.

How to add a nullable column to an existing table (AWS Aurora)

When using AWS Aurora, a nullable column can be added to existing large (100k rows+?) tables without causing downtime. However, the migration may still timeout in GoCD - so please coordinate the release with SRE.

1. Make a new field addition in model with null=True.

2. Generate the model-change migrations locally.

3. Create a pull request containing the model change and newly-generated migrations.

4. Merge the migration pull request.

5. The release process will run the migration and add the nullable column to table.

NOTES:

• The column must be nullable! (null=True)

  • When adding a column with null=False, these instructions do not apply and you'll need to plan for downtime.

• The Django ORM default for a column's null value is False.

  • So when adding new model columns which do not specify the null parameter, these instructions do not apply and you'll need to plan for downtime.

• If you first add a nullable column (null=True) and then change the constraint to non-nullable (null=False) in a later PR, the table will be re-built just as if you added a non-nullable column.

• If you change an existing nullable column (null=True) to become a non-nullable column (null=False), the table will be re-built just as if you added a non-nullable column.

AWS Aurora Docs: https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/AuroraMySQL.Managing.FastDDL.html

How to add index to existing table (AWS Aurora)

On AWS Aurora, indexes can be build on large tables without causing downtime, but this requires SRE coordination as the migration may timeout in GoCD.

1. Add the new index on model fields.

2. Generate the model-change migrations locally.

3. Make pull request containing the model change and newly-generated migrations.

4. Merge the migration pull request.

5. Release will run the migration and add the index to table.

Consider Making a New Model with a OneToOneField

Adding fields to large tables can cause operational issues. What is safe varies from database version (MySQL 5.7 vs. 5.8. vs. 8.0) and specialized backends (like Aurora). Also, even if the database supports adding things in a non-locking way, Django's migrations framework may not understand how to formulate the right SQL to do so.

A lower risk alternative is to create a new model and link it together with a OneToOneField. You can use the primary_key=True option in order to have the new table's primary key match the values of the parent table.

This does complicate the code somewhat, and you should be careful about avoiding n+1 queries by calling select_related. The benefit is not having to hold your breath when the migration rolls out, for fear that you just froze a heavily used table and brought down the site.

Known large and/or problematic tables

Large tables

• Top ones (ordered by descending size):

  courseware_studentmodulehistory, courseware_studentmodule student_historicalcourseenrollment, student_courseenrollment student_anonymoususerid, user_api_userorgtag django_comment_client_role_users, certificates_generatedcertificate auth_userprofile, user_api_userpreference, auth_user, oauth2_accesstoken

• See this spreadsheet (edX only): https://docs.google.com/spreadsheets/d/1rrRGsjYYNV41rHYLmDluQw74a8HRegnbveXaMk95gBI/edit#gid=0

Contentious tables

• Top ones (ordered by descending calls-per-minute):

  user_api_userpreference auth_user student_understanding theming_sitetheme django_site course_modes_coursemode courseware_studentmodule course_overviews_courseoverview waffle_utils_waffleflagcourseoverridemodel edxval_videoimage edxval_profile completion_blockcompletion student_anonymoususerid

• See this list for highly contentious tables in edx-platform (LMS/Studio): https://rpm.newrelic.com/accounts/88178/applications/3343327/datastores#/overview/MySQL?value=calls_per_minute

Useful Checklists

Checklist for structural migrations

Existing Tables

New Tables

Checklist for data migrations

Checklist for adding indexes

Testing migrations

Unit testing

Migrations are currently not run in unit tests.

Acceptance tests

The paver commands that kick off the Lettuce and bokchoy tests run migrations. However, because this would take a long time if we started from scratch, we cache the latest state of the database after certain intervals (every couple months when someone checks in a new cache) so all the migrations are not run, but only the ones added since the last time the database state was cached.

• The caches are stored here in the repo: https://github.com/edx/edx-platform/tree/master/common/test/db_cache

• The script that operates on the db cache to prepare it for test execution is here in the repo: https://github.com/edx/edx-platform/blob/master/scripts/reset-test-db.sh

• To create an updated cache, follow the instructions on this page.

Common migration tasks

Making a migration to create a new table

1. Create a new directory under djangoapps and create a models.py file within it describing your model fields (example: common/djangoapps/track/models.py).

2. Add the name of your module to INSTALLED_APPS in the appropriate environment file. Do NOT run manage.py syncdb (recommended in the Django documentation).

Once you are happy with how your fields are defined in models.py, run the following command. The resulting file will be checked in with your PR.

Making a migration to modify an existing table 

When you make changes to your model, create migration file and check it in:

Make sure you are pointing to the correct environment file.

Checking SQL for a migration

After creating your migration file, if you are running Open edX via the DevStack configuration, it is sometimes useful to review the SQL for your new migration:

Performing a migration

After creating your migration file, if you are running Open edX via the DevStack configuration, you can perform the migration using the following command:

Rolling back a migration

where <number> is the prefix of the migration file that you want to roll back to.

Unapply all migrations

There's a special "zero" migration name to unapply all migrations, including the initial migration.

Rare migration tasks

Faking migrations

Example for CSM primary key to bigint migration.

Do the following before merging/deploying the code, otherwise the pipeline will try to run the migrations

Copy the migration file onto a machine, can be a worker if the app has worker machines

Run Migration Fake

Cleanup

Squashing Migrations

See Django's Documentation for Squashing Migrations. Some useful tips for squashing:

• The primary benefit of squashing migrations is the speed-up of running migrations from scratch.  If you are not running migrations from scratch, this may not help you.

• Managing you squash migrations PR:

  • Keep migration squashing to its own PR.  Introducing a migration in the same PR that you squash can cause issues.

  • Keep the auto-generated squash migration file as its own initial commit on PRs.  This will help your PR reviewers.

• You can sometimes get an improved squash by removing the data migrations or removing all old migrations to create fresh migrations.

  • Note: commit this separately from the initial auto-generated commit to help with review.

  • You may need to remove all migrations for apps that depend in your migrations as well, to get this to run.

  • If you use this method, ensure makemigrations shows that there is nothing missing from your squash.

• Testing your squashed migrations.

• Important: Squashing Migrations is a two part process, and each part needs to live in a separate Open edX Named Release in order for the community to get caught up before the second part is released.  From Django's docs:

This enables you to squash and not mess up systems currently in production that aren’t fully up-to-date yet. The recommended process is to squash, keeping the old files, commit and release, wait until all systems are upgraded with the new release (or if you’re a third-party project, ensure your users upgrade releases in order without skipping any), and then remove the old files, commit and do a second release.