Relations and Foreign Keys

Hugr supports defining relationships between data objects using foreign key constraints. These relationships enable filtering by related data, subqueries, and cascading operations without requiring database-level foreign keys.

Field-Level Foreign Keys

Define a foreign key on a single field using @field_references:

type orders @table(name: "orders") {
  id: Int! @pk
  customer_id: Int! @field_references(
    name: "orders_customer_fk"
    references_name: "customers"
    field: "id"
    query: "customer"
    description: "Customer who placed the order"
    references_query: "orders"
    references_description: "Orders placed by this customer"
  )
  total: Float!
}

This generates:

• A customer field on orders to fetch the related customer
• An orders field on customers to fetch related orders
• Filter capabilities on both sides

Object-Level Foreign Keys

For multi-field relationships, use @references at the object level:

type order_details @table(name: "order_details")
  @references(
    name: "order_details_supplier_product_fk"
    references_name: "supplier_products"
    source_fields: ["supplier_id", "product_id"]
    references_fields: ["supplier_id", "product_id"]
    query: "supplier_product"
    references_query: "order_details"
  ) {
  id: Int! @pk
  order_id: Int!
  supplier_id: Int!
  product_id: Int!
  quantity: Int!
}

Many-to-Many Relationships

Define junction tables with is_m2m: true:

type product_categories @table(name: "product_categories", is_m2m: true) {
  product_id: Int! @pk @field_references(
    references_name: "products"
    field: "id"
    query: "product"
    references_query: "categories"
    references_description: "Categories for this product"
  )
  category_id: Int! @pk @field_references(
    references_name: "categories"
    field: "id"
    query: "category"
    references_query: "products"
    references_description: "Products in this category"
  )
}

This creates direct relationships between products and categories:

query {
  products {
    id
    name
    categories {  # Direct access to categories
      id
      name
    }
  }
  
  categories {
    id
    name
    products {  # Direct access to products
      id
      name
    }
  }
}

Using Relations in Queries

Subqueries

Fetch related data in a single query:

query {
  customers {
    id
    name
    orders(
      filter: { status: { eq: "pending" } }
      order_by: [{ field: "created_at", direction: DESC }]
      limit: 5
    ) {
      id
      total
      order_details {
        product {
          name
          price
        }
        quantity
      }
    }
  }
}

Filtering by Relations

Filter parent records based on related data:

query {
  # Customers with pending orders over $1000
  customers(filter: {
    orders: {
      any_of: {
        _and: [
          { status: { eq: "pending" } }
          { total: { gt: 1000 } }
        ]
      }
    }
  }) {
    id
    name
  }
}

Aggregating Relations

Aggregate related data:

query {
  customers {
    id
    name
    orders_aggregation {
      _rows_count
      total {
        sum
        avg
      }
    }
    # Filtered aggregation
    recent_orders: orders_aggregation(
      filter: { created_at: { gte: "2024-01-01" } }
    ) {
      _rows_count
      total {
        sum
      }
    }
  }
}

Relation Options

Inner Joins

Use inner: true to exclude records without relations:

query {
  customers {
    id
    name
    orders(inner: true) {  # Only customers with orders
      id
      total
    }
  }
}

Nested Pagination

Control pagination at relation level:

query {
  customers(limit: 10) {
    id
    name
    orders(
      nested_limit: 5
      nested_offset: 0
      nested_order_by: [{ field: "created_at", direction: DESC }]
    ) {
      id
      created_at
    }
  }
}

Cascading Operations

Insert with Relations

Create related records in a single mutation:

mutation {
  insert_customers(data: {
    name: "New Customer"
    email: "customer@example.com"
    orders: [
      {
        total: 150.00
        status: "pending"
        order_details: [
          {
            product_id: 1
            quantity: 2
            unit_price: 75.00
          }
        ]
      }
    ]
  }) {
    id
    orders {
      id
      order_details {
        id
      }
    }
  }
}

Many-to-Many Insert

For M2M relationships, link existing records:

mutation {
  insert_products(data: {
    name: "New Product"
    price: 99.99
    categories: [
      { id: 1 }  # Link to existing category
      { id: 2 }
    ]
  }) {
    id
    categories {
      id
      name
    }
  }
}

Self-Referential Relations

Define hierarchical relationships:

type employees @table(name: "employees") {
  id: Int! @pk
  name: String!
  manager_id: Int @field_references(
    references_name: "employees"
    field: "id"
    query: "manager"
    references_query: "subordinates"
    references_description: "Employees reporting to this manager"
  )
}

Query hierarchical data:

query {
  employees {
    id
    name
    manager {
      id
      name
    }
    subordinates {
      id
      name
    }
  }
}

Cross-Source Relations

Cross-source relations are not supported through @field_references or @references directives. To create relationships between different data sources, use the extension data source with @join or @function_call directives. See the Joins and Spatial Joins section for details.

Performance Considerations

N+1 Query Problem

Hugr optimizes relation queries to avoid N+1 problems by batching subqueries.

Limiting Subquery Results

Always limit subquery results for large datasets:

query {
  customers {
    id
    recent_orders: orders(
      filter: { created_at: { gte: "2024-01-01" } }
      limit: 10
    ) {
      id
    }
  }
}

Index Requirements

Ensure indexes exist on:

• Foreign key fields
• Fields used in relation filters
• Fields used in relation sorting