HAVING | PostgreSQL Tutorial

HAVING in Group Data helps you write SQL that is easier to test, review, and operate at scale.

Introduction to HAVING

Use HAVING to aggregate data into metrics for dashboards and analytics.

Commonly paired with: SELECT, FROM, WHERE, ORDER BY.

Practical examples with HAVING in PostgreSQL

Reference pattern: start from canonical syntax and keep it explicit.

SELECT customer_id, COUNT(*) AS order_count
FROM orders
GROUP BY customer_id
HAVING COUNT(*) >= 5;

Production-style scenario: apply the same concept to realistic application data.

SELECT
  o.order_id,
  o.total_amount,
  o.placed_at
FROM orders o
WHERE o.placed_at >= now() - interval '30 days'
ORDER BY o.placed_at DESC
LIMIT 50;

Additional example: use a variation to validate behavior and edge cases.

SELECT date_trunc('month', placed_at) AS month,
       SUM(total_amount) AS revenue
FROM orders
GROUP BY 1
ORDER BY 1;

Production tips

Prefer explicit column lists and deterministic ordering when results feed APIs or batch jobs.
Validate plans with EXPLAIN before adding indexes, then re-check after schema changes.
Keep DDL, data backfills, and cleanups in transactions when possible to avoid partial state.
Use isolated environments for risky changes so query tuning and schema experiments stay safe.

Vela workflow tip

Test this pattern in an isolated branch database, share the result with your team, and promote only after query plans and row counts look correct.

Reference: PostgreSQL official documentation.