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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)
}