Desk joins in Fluent 4

Database fashions

Fluent is a Swift ORM framework written for Vapor. You should use fashions to symbolize rows in a desk, migrations to create the construction for the tables and you’ll outline relations between the fashions utilizing Swift property wrappers. That is fairly a easy manner of representing mother or father, baby or sibling connections. You’ll be able to “keen load” fashions by these predefined relation properties, which is nice, however typically you do not need to have static varieties for the relationships.

I am engaged on a modular CMS and I can not have hardcoded relationship properties contained in the fashions. Why? Properly, I need to have the ability to load modules at runtime, so if module A relies upon from module B by a relation property then I can not compile module A independently. That is why I dropped a lot of the cross-module relations, nonetheless I’ve to put in writing joined queries. 😅

Buyer mannequin

On this instance we’re going to mannequin a easy Buyer-Order-Product relation. Our buyer mannequin could have a primary identifier and a reputation. Contemplate the next:

closing class CustomerModel: Mannequin, Content material {
    static let schema = "prospects"
    
    @ID(key: .id) var id: UUID?
    @Discipline(key: "identify") var identify: String

    init() { }

    init(id: UUID? = nil, identify: String) {
        self.id = id
        self.identify = identify
    }
}

Nothing particular, only a primary Fluent mannequin.

Order mannequin

Prospects could have a one-to-many relationship to the orders. Which means a buyer can have a number of orders, however an order will at all times have precisely one related buyer.

closing class OrderModel: Mannequin, Content material {
    static let schema = "orders"
    
    @ID(key: .id) var id: UUID?
    @Discipline(key: "date") var date: Date
    @Discipline(key: "customer_id") var customerId: UUID

    init() { }

    init(id: UUID? = nil, date: Date, customerId: UUID) {
        self.id = id
        self.date = date
        self.customerId = customerId
    }
}

We may make the most of the @Mother or father and @Youngster property wrappers, however this time we’re going to retailer a customerId reference as a UUID kind. In a while we’re going to put a international key constraint on this relation to make sure that referenced objects are legitimate identifiers.

Product mannequin

The product mannequin, identical to the shopper mannequin, is completely impartial from the rest. 📦

closing class ProductModel: Mannequin, Content material {
    static let schema = "merchandise"
    
    @ID(key: .id) var id: UUID?
    @Discipline(key: "identify") var identify: String

    init() { }

    init(id: UUID? = nil, identify: String) {
        self.id = id
        self.identify = identify
    }
}

We are able to create a property with a @Sibling wrapper to precise the connection between the orders and the merchandise, or use joins to question the required knowledge. It actually would not matter which manner we go, we nonetheless want a cross desk to retailer the associated product and order identifiers.

OrderProductModel

We are able to describe a many-to-many relation between two tables utilizing a 3rd desk.

closing class OrderProductModel: Mannequin, Content material {
    static let schema = "order_products"
    
    @ID(key: .id) var id: UUID?
    @Discipline(key: "order_id") var orderId: UUID
    @Discipline(key: "product_id") var productId: UUID
    @Discipline(key: "amount") var amount: Int

    init() { }

    init(id: UUID? = nil, orderId: UUID, productId: UUID, amount: Int) {
        self.id = id
        self.orderId = orderId
        self.productId = productId
        self.amount = amount
    }
}

As you’ll be able to see we will retailer additional information on the cross desk, in our case we’re going to affiliate portions to the merchandise on this relation proper subsequent to the product identifier.

Migrations

Luckily, Fluent provides us a easy strategy to create the schema for the database tables.

struct InitialMigration: Migration {

    func put together(on db: Database) -> EventLoopFuture<Void> {
        db.eventLoop.flatten([
            db.schema(CustomerModel.schema)
                .id()
                .field("name", .string, .required)
                .create(),
            db.schema(OrderModel.schema)
                .id()
                .field("date", .date, .required)
                .field("customer_id", .uuid, .required)
                .foreignKey("customer_id", references: CustomerModel.schema, .id, onDelete: .cascade)
                .create(),
            db.schema(ProductModel.schema)
                .id()
                .field("name", .string, .required)
                .create(),
            db.schema(OrderProductModel.schema)
                .id()
                .field("order_id", .uuid, .required)
                .foreignKey("order_id", references: OrderModel.schema, .id, onDelete: .cascade)
                .field("product_id", .uuid, .required)
                .foreignKey("product_id", references: ProductModel.schema, .id, onDelete: .cascade)
                .field("quantity", .int, .required)
                .unique(on: "order_id", "product_id")
                .create(),
        ])
    }

    func revert(on db: Database) -> EventLoopFuture<Void> {
        db.eventLoop.flatten([
            db.schema(OrderProductModel.schema).delete(),
            db.schema(CustomerModel.schema).delete(),
            db.schema(OrderModel.schema).delete(),
            db.schema(ProductModel.schema).delete(),
        ])
    }
}

If you wish to keep away from invalid knowledge within the tables, it is best to at all times use the international key and distinctive constraints. A international key can be utilized to examine if the referenced identifier exists within the associated desk and the distinctive constraint will ensure that just one row can exists from a given area.

Becoming a member of database tables utilizing Fluent 4

We’ve to run the InitialMigration script earlier than we begin utilizing the database. This may be executed by passing a command argument to the backend utility or we will obtain the identical factor by calling the autoMigrate() methodology on the applying occasion.

For the sake of simplicity I’ll use the wait methodology as a substitute of async Futures & Guarantees, that is tremendous for demo functions, however in a real-world server utility it is best to by no means block the present occasion loop with the wait methodology.

That is one attainable setup of our dummy database utilizing an SQLite storage, however in fact you should utilize PostgreSQL, MySQL and even MariaDB by the accessible Fluent SQL drivers. 🚙

public func configure(_ app: Utility) throws {

    app.databases.use(.sqlite(.file("db.sqlite")), as: .sqlite)

    app.migrations.add(InitialMigration())

    strive app.autoMigrate().wait()

    let prospects = [
        CustomerModel(name: "Bender"),
        CustomerModel(name: "Fry"),
        CustomerModel(name: "Leela"),
        CustomerModel(name: "Hermes"),
        CustomerModel(name: "Zoidberg"),
    ]
    strive prospects.create(on: app.db).wait()
    
    let merchandise = [
        ProductModel(name: "Hamburger"),
        ProductModel(name: "Fish"),
        ProductModel(name: "Pizza"),
        ProductModel(name: "Beer"),
    ]
    strive merchandise.create(on: app.db).wait()

    
    let order = OrderModel(date: Date(), customerId: prospects[0].id!)
    strive order.create(on: app.db).wait()

    let beerProduct = OrderProductModel(orderId: order.id!, productId: merchandise[3].id!, amount: 6)
    strive beerProduct.create(on: app.db).wait()
    let pizzaProduct = OrderProductModel(orderId: order.id!, productId: merchandise[2].id!, amount: 1)
    strive pizzaProduct.create(on: app.db).wait()
}

We’ve created 5 prospects (Bender, Fry, Leela, Hermes, Zoidberg), 4 merchandise (Hamburger, Fish, Pizza, Beer) and one new order for Bender containing 2 merchandise (6 beers and 1 pizza). 🤖

Inside be a part of utilizing one-to-many relations

Now the query is: how can we get the shopper knowledge based mostly on the order?

let orders = strive OrderModel
    .question(on: app.db)
    .be a part of(CustomerModel.self, on: OrderModel.$customerId == CustomerModel.$id, methodology: .internal)
    .all()
    .wait()

for order in orders {
    let buyer = strive order.joined(CustomerModel.self)
    print(buyer.identify)
    print(order.date)
}

The reply is fairly easy. We are able to use an internal be a part of to fetch the shopper mannequin by the order.customerId and buyer.id relation. Once we iterate by the fashions we will ask for the associated mannequin utilizing the joined methodology.

Joins and plenty of to many relations

Having a buyer is nice, however how can I fetch the related merchandise for the order? We are able to begin the question with the OrderProductModel and use a be a part of utilizing the ProductModel plus we will filter by the order id utilizing the present order.

for order in orders {
    

    let orderProducts = strive OrderProductModel
        .question(on: app.db)
        .be a part of(ProductModel.self, on: OrderProductModel.$productId == ProductModel.$id, methodology: .internal)
        .filter(.$orderId == order.id!)
        .all()
        .wait()

    for orderProduct in orderProducts {
        let product = strive orderProduct.joined(ProductModel.self)
        print(product.identify)
        print(orderProduct.amount)
    }
}

We are able to request the joined mannequin the identical manner as we did it for the shopper. Once more, the very first parameter is the mannequin illustration of the joined desk, subsequent you outline the relation between the tables utilizing the referenced identifiers. As a final parameter you’ll be able to specify the kind of the be a part of.

Inside be a part of vs left be a part of

There’s a nice SQL tutorial about joins on w3schools.com, I extremely suggest studying it. The primary distinction between an internal be a part of and a left be a part of is that an internal be a part of solely returns these data which have matching identifiers in each tables, however a left be a part of will return all of the data from the bottom (left) desk even when there aren’t any matches within the joined (proper) desk.

There are a lot of several types of SQL joins, however internal and left be a part of are the most typical ones. If you wish to know extra concerning the different varieties it is best to learn the linked article. 👍

Abstract

Desk joins are actually helpful, however it’s important to watch out with them. You must at all times use correct international key and distinctive constraints. Additionally think about using indexes on some rows while you work with joins, as a result of it could enhance the efficiency of your queries. Velocity might be an vital issue, so by no means load extra knowledge from the database than you really need.

There is a matter on GitHub concerning the Fluent 4 API, and one other one about querying particular fields utilizing the .area methodology. Lengthy story quick, joins might be nice and we’d like higher docs. 🙉