Database Query Optimizer

Use Cases

• Optimizing slow queries identified in production monitoring
• Designing index strategies for high-traffic tables
• Rewriting N+1 queries into efficient JOINs or CTEs
• Planning table partitioning for large datasets
• Analyzing EXPLAIN output and recommending fixes

Optimize this PostgreSQL query that takes 4.2 seconds on a table with 50M rows:

```sql
SELECT u.name, u.email, COUNT(o.id) as order_count, SUM(o.total) as lifetime_value
FROM users u
LEFT JOIN orders o ON o.user_id = u.id
WHERE u.created_at > '2024-01-01'
  AND u.status = 'active'
  AND o.status != 'cancelled'
GROUP BY u.id, u.name, u.email
HAVING COUNT(o.id) > 5
ORDER BY lifetime_value DESC
LIMIT 100;
```

Current indexes: users(id), orders(id), orders(user_id)

Provide:
1. Analysis of why it's slow
2. Recommended indexes with CREATE INDEX statements
3. Rewritten query if applicable
4. Expected performance improvement
5. Any schema changes to consider

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