Repositories » Composing Relations

Composing relations means defining various subsets of data in ways that make them composable into complex structures. A good example of relation composition is loading aggregates where two or more subsets of data are being merged into a nested data structure using in-memory transformation. This is a simple, yet powerful technique, as it allows us to compose data however we want, and it works cross-database too.

In order to be able to compose relations, we need two things - a unique identifier and a list of attributes that a given relation tuples have. To accomplish that we use a special syntax that allows you to define composable relation views. You could think of these views just like actual SQL views in a database.

Here's a simple example:

class Posts < ROM::Relation[:sql]
  schema(infer: true)

  view(:listing, [:id, :user_id, :title, :published_at]) do
    select(:id, :title, :user_id, :published_at).order(:published_at)
  end
end

Let's define another view so that we will be able to compose users and posts:

class Users < ROM::Relation[:sql]
  schema(infer: true)

  view(:authors, [:id, :name]) do |posts|
    select(:id, :name).where(id: posts.pluck(:user_id)).order(:name)
  end
end

This way we defined two views:

  • Posts#listing which includes :user_id key
  • Users#authors which narrows down the relation based on posts' :user_id keys

Having that, we can compose posts with their authors using our custom views via post repository:

class PostRepo < ROM::Repository[:posts]
  relations :users

  def listing
    posts.listing.combine_parents(one: { author: users.authors })
  end
end

Check out API documentation for all types of compositions that are available in repositories.

When to use custom compositions?

In many common cases using canonical asociations will be sufficient, which means that you simply define associations in schemas and read aggregates; however, you will find situations where custom views, with smaller data sets and more optimizied queries are useful too. You will also find this to be useful when you'd like to compose data that are fetched from multiple data sources (ie an SQL database and an HTTP API).

Relation composition helps you shape your data structures in ways that match your application's domain. Rather than using canonical representation defined by the database schemas, you can create simpler and more optimized representation of the data, which simplifies your domain layer.