What is the N+1 query problem and how do you solve it in Go?

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Accepted Answer

// N+1 PROBLEM: 1 query for orders + N queries for each user
orders, _ := db.QueryContext(ctx, "SELECT id, user_id, total FROM orders")
for orders.Next() {
    var o Order
    orders.Scan(&o.ID, &o.UserID, &o.Total)
    // N additional queries!
    db.QueryRowContext(ctx, "SELECT name FROM users WHERE id = $1", o.UserID).Scan(&o.UserName)
}

// SOLUTION 1: JOIN query
const q = `
    SELECT o.id, o.total, u.name
    FROM orders o
    JOIN users u ON u.id = o.user_id
    WHERE o.created_at > $1
`
rows, _ := db.QueryContext(ctx, q, since)

// SOLUTION 2: Batch load with IN clause
var userIDs []string
for _, o := range orders { userIDs = append(userIDs, o.UserID) }

// Build parameterized IN query
placeholders := make([]string, len(userIDs))
args := make([]interface{}, len(userIDs))
for i, id := range userIDs {
    placeholders[i] = fmt.Sprintf("$%d", i+1)
    args[i] = id
}
q2 := "SELECT id, name FROM users WHERE id IN (" + strings.Join(placeholders, ",") + ")"

// SOLUTION 3: sqlx.In helper
query, args, _ := sqlx.In("SELECT id, name FROM users WHERE id IN (?)", userIDs)
query = db.Rebind(query) Enable query logging in development: pgx log level debug or EXPLAIN ANALYZE suspicious queries Use sqlc or GORM with Preload to generate/use optimized batch queries DataLoader pattern for GraphQL: batch all IDs within a request cycle then fetch in one query Look for database query counts in your APM (Datadog, New Relic) — sudden spikes indicate N+1 Code review: any DB call inside a loop is a red flag — prefer batch operations

What is the N+1 query problem and how do you solve it in Go?

The N+1 problem occurs when fetching N parent records then issuing N individual queries for related data. Solve it with JOIN queries, batch loading with IN clauses, or ORM preloading.

What is the N+1 query problem and how do you solve it in Go?

The N+1 problem occurs when fetching N parent records then issuing N individual queries for related data. Solve it with JOIN queries, batch loading with IN clauses, or ORM preloading.

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