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Version: 5.2

Data Migrations

Data Migrations are available as of RedwoodJS v0.15

There are two kinds of changes you can make to your database:

  • Changes to structure
  • Changes to content

In Redwood, Prisma Migrate takes care of codifying changes to your database structure in code by creating a snapshot of changes to your database that can be reliably repeated to end up in some known state.

To track changes to your database content, Redwood includes a feature we call Data Migration. As your app evolves and you move data around, you need a way to consistently declare how that data should move.

Imagine a User model that contains several columns for user preferences. Over time, you may end up with more and more preferences to the point that you have more preference-related columns in the table than you do data unique to the user! This is a common occurrence as applications grow. You decide that the app should have a new model, Preference, to keep track of them all (and Preference will have a foreign key userId to reference it back to its User). You'll use Prisma Migrate to create the new Preference model, but how do you copy the preference data to the new table? Data migrations to the rescue!

Installing

Just like Prisma, we will store which data migrations have run in the database itself. We'll create a new database table DataMigration to keep track of which ones have run already.

Rather than create this model by hand, Redwood includes a CLI tool to add the model to schema.prisma and create the DB migration that adds the table to the database:

yarn rw data-migrate install

You'll see a new directory created at api/db/dataMigrations which will store our individual migration tasks.

Take a look at schema.prisma to see the new model definition:

api/db/schema.prisma
model RW_DataMigration {
version String @id
name String
startedAt DateTime
finishedAt DateTime
}

The install script also ran yarn rw prisma migrate dev --create-only automatically so you have a DB migration ready to go. You just need to run the prisma migrate dev command to apply it:

yarn rw prisma migrate dev

Creating a New Data Migration

Data migrations are just plain Typescript or Javascript files which export a single anonymous function that is given a single argument—an instance of PrismaClient called db that you can use to access your database. The files have a simple naming convention:

{version}-{name}.js

Where version is a timestamp, like 20200721123456 (an ISO8601 datetime without any special characters or zone identifier), and name is a param-case human readable name for the migration, like copy-preferences.

To create a data migration we have a generator:

yarn rw generate dataMigration copyPreferences

This will create api/db/dataMigrations/20200721123456-copy-preferences.js:

api/db/dataMigrations/20200721123456-copy-preferences.js
export default async ({ db }) => {
// Migration here...
}

Why such a long name?

So that if multiple developers are creating data migrations, the chances of them creating one with the exact same filename is essentially zero, and they will all run in a predictable order—oldest to newest.

Now it's up to you to define your data migration. In our user/preference example, it may look something like:

api/db/dataMigrations/20200721123456-copy-preferences.js
const asyncForEach = async (array, callback) => {
for (let index = 0; index < array.length; index++) {
await callback(array[index], index, array)
}
}

export default async ({ db }) => {
const users = await db.user.findMany()

asyncForEach(users, async (user) => {
await db.preference.create({
data: {
newsletter: user.newsletter,
frequency: user.frequency,
theme: user.theme,
user: { connect: { id: user.id } }
}
})
})
}

This loops through each existing User and creates a new Preference record containing each of the preference-related fields from User.

Note that in a case like this where you're copying data to a new table, you would probably delete the columns from User afterwards. This needs to be a two step process!

  1. Create the new table (db migration) and then move the data over (data migration)
  2. Remove the unneeded columns from User

When going to production, you would need to run this as two separate deploys to ensure no data is lost.

The reason is that all DB migrations are run and then all data migrations. So if you had two DB migrations (one to create Preference and one to drop the unneeded columns from User) they would both run before the Data Migration, so the columns containing the preferences are gone before the data migration gets a chance to copy them over!

Remember: Any destructive action on the database (removing a table or column especially) needs to be a two step process to avoid data loss.

Running a Data Migration

When you're ready, you can execute your data migration with data-migrate's up command:

yarn rw data-migrate up

This goes through each file in api/db/dataMigrations, compares it against the list of migrations that have already run according to the DataMigration table in the database, and executes any that aren't present in that table, sorted oldest to newest based on the timestamp in the filename.

Any logging statements (like console.info()) you include in your data migration script will be output to the console as the script is running.

If the script encounters an error, the process will abort, skipping any following data migrations.

The example data migration above didn't include this for brevity, but you should always run your data migration inside a transaction so that if any errors occur during execution the database will not be left in an inconsistent state where only some of your changes were performed.

Long-term Maintainability

Ideally you can run all database migrations and data migrations from scratch (like when a new developer joins the team) and have them execute correctly. Unfortunately you don't get that ideal scenario by default.

Take our example above—what happens when a new developer comes long and attempts to setup their database? All DB migrations will run first (including the one that drops the preference-related columns from User) before the data migrations run. They will get an error when they try to read something like user.newsletter and that column doesn't exist!

One technique to combat this is to check for the existence of these columns before the data migration does anything. If user.newsletter doesn't exist, then don't bother running the data migration at all and assume that your seed data is already in the correct format:

export default async ({ db }) => {
const users = await db.user.findMany()

if (typeof user.newsletter !== undefined) {
asyncForEach(users, async (user) => {
await db.preference.create({
data: {
newsletter: user.newsletter,
frequency: user.frequency,
theme: user.theme,
user: { connect: { id: user.id } }
}
})
})
}
}

Lifecycle Summary

Run once:

yarn rw data-migrate install
yarn rw prisma migrate dev

Run every time you need a new data migration:

yarn rw generate dataMigration migrationName
yarn rw data-migrate up