Aggregation

Group By#

Group by name and age fields of all users, and sum their total age.

package main

import (
    "context"
    
    "<project>/ent"
    "<project>/ent/user"
)

func Do(ctx context.Context, client *ent.Client) {
    var v []struct {
        Name  string `json:"name"`
        Age   int    `json:"age"`
        Sum   int    `json:"sum"`
        Count int    `json:"count"`
    }
    err := client.User.Query().
        GroupBy(user.FieldName, user.FieldAge).
        Aggregate(ent.Count(), ent.Sum(user.FieldAge)).
        Scan(ctx, &v)
}

Group by one field.

package main

import (
    "context"
    
    "<project>/ent"
    "<project>/ent/user"
)

func Do(ctx context.Context, client *ent.Client) {
    names, err := client.User.
        Query().
        GroupBy(user.FieldName).
        Strings(ctx)
}

Group By Edge#

Custom aggregation functions can be useful if you want to write your own storage-specific logic.

The following shows how to group by the id and the name of all users and calculate the average age of their pets.

package main

import (
    "context"
    "log"

    "<project>/ent"
    "<project>/ent/pet"
    "<project>/ent/user"
)

func Do(ctx context.Context, client *ent.Client) {
    var users []struct {
        ID      int
        Name    string
        Average float64
    }
    err := client.User.Query().
        GroupBy(user.FieldID, user.FieldName).
        Aggregate(func(s *sql.Selector) string {
            t := sql.Table(pet.Table)
            s.Join(t).On(s.C(user.FieldID), t.C(pet.OwnerColumn))
            return sql.As(sql.Avg(t.C(pet.FieldAge)), "average")
        }).
        Scan(ctx, &users)
}