Desk joins in Fluent 4

Database fashions

Fluent is a Swift ORM framework written for Vapor. You need to use fashions to signify rows in a desk, migrations to create the construction for the tables and you may outline relations between the fashions utilizing Swift property wrappers. That is fairly a easy manner of representing mum or dad, youngster or sibling connections. You’ll be able to “keen load” fashions by means of these predefined relation properties, which is nice, however typically you do not wish 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? Effectively, I would like to have the ability to load modules at runtime, so if module A relies upon from module B by means of a relation property then I can not compile module A independently. That is why I dropped a lot of the cross-module relations, however I’ve to jot down 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. Think about the next:

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

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

last class OrderModel: Mannequin, Content material {
    static let schema = "orders"
    
    @ID(key: .id) var id: UUID?
    @Subject(key: "date") var date: Date
    @Subject(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 might benefit from the @Father or mother and @Little one 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 overseas key constraint on this relation to make sure that referenced objects are legitimate identifiers.

Product mannequin

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

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

last class OrderProductModel: Mannequin, Content material {
    static let schema = "order_products"
    
    @ID(key: .id) var id: UUID?
    @Subject(key: "order_id") var orderId: UUID
    @Subject(key: "product_id") var productId: UUID
    @Subject(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 may see we will retailer further 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 option 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, you must at all times use the overseas key and distinctive constraints. A overseas key can be utilized to test 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

Now we have to run the InitialMigration script earlier than we begin utilizing the database. This may be executed by passing a command argument to the backend software or we will obtain the identical factor by calling the autoMigrate() technique on the applying occasion.

For the sake of simplicity I’ll use the wait technique as an alternative of async Futures & Guarantees, that is wonderful for demo functions, however in a real-world server software you must by no means block the present occasion loop with the wait technique.

That is one doable setup of our dummy database utilizing an SQLite storage, however after all you should utilize PostgreSQL, MySQL and even MariaDB by means of the out there 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()
}

Now we have 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 part of utilizing one-to-many relations

Now the query is: how can we get the client knowledge primarily based on the order?

let orders = strive OrderModel
    .question(on: app.db)
    .be part of(CustomerModel.self, on: OrderModel.$customerId == CustomerModel.$id, technique: .interior)
    .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 interior be part of to fetch the client mannequin by means of the order.customerId and buyer.id relation. After we iterate by means of the fashions we will ask for the associated mannequin utilizing the joined technique.

Joins and lots 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 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 part of(ProductModel.self, on: OrderProductModel.$productId == ProductModel.$id, technique: .interior)
        .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 client. 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 may specify the kind of the be part of.

Inside be part of vs left be part of

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

There are lots of several types of SQL joins, however interior and left be part of are the most typical ones. If you wish to know extra in regards to the different varieties you must learn the linked article. 👍

Abstract

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

There is a matter on GitHub in regards to the Fluent 4 API, and one other one about querying particular fields utilizing the .area technique. Lengthy story brief, joins may be nice and we want higher docs. 🙉