1.關聯
func (UserRepository UserRepository) GetUser() []models.User {
// var articles ArticleRepository
users := []models.User{}
// DB.Model(&users).Related(&articles, "Article")
DB.Find(&users)
for i, _ := range users {
DB.Model(users[i]).Related(&users[i].Articles)
}
return users
}
2.
TownID must be specified as the foreign key. The Place struct gets like this:
type Place struct {
ID int
Name string
Description string
TownID int
Town Town
}Now there are different approach to handle this. For example:
places := []Place{}
db.Find(&places)
for i, _ := range places {
db.Model(places[i]).Related(&places[i].Town)
}This will certainly produce the expected result, but notice the log output and the queries triggered.
[4.76ms] SELECT * FROM "places"
[1.00ms] SELECT * FROM "towns" WHERE ("id" = '1')
[0.73ms] SELECT * FROM "towns" WHERE ("id" = '1')
[{1 Place1 {1 Town1} 1} {2 Place2 {1 Town1} 1}]The output is the expected but this approach has a fundamental flaw, notice that for every place there is the need to do another db query which produce a n + 1 problem issue. This could solve the problem but will quickly gets out of control as the amount of places grow.
It turns out that the good approach is fairly simple using preloads.
db.Preload("Town").Find(&places)That's it, the query log produced is:
[22.24ms] SELECT * FROM "places"
[0.92ms] SELECT * FROM "towns" WHERE ("id" in ('1'))
[{1 Place1 {1 Town1} 1} {2 Place2 {1 Town1} 1}]This approach will only trigger two queries, one for all places, and one for all towns that has places. This approach scales well regarding of the amount of places and towns (only two queries in all cases).
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