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SQL Query Optimization

SQL Query Optimization

SQL Query Optimization

SQL Query Optimization

SQL Query Optimization

SQL Query Optimization

SQL Query Optimization

SQL Query Optimization

Why Query Optimization Matters

A poorly written query can take seconds or minutes instead of milliseconds, consuming database resources and degrading the experience for all users. Optimizing queries is often the highest-ROI performance improvement you can make because it requires no infrastructure changes.

Understanding EXPLAIN

Every database has a query planner that decides how to execute your SQL. EXPLAIN shows you the plan.

EXPLAIN ANALYZE

SELECT u.name, COUNT(o.id) AS order_count

FROM users u

LEFT JOIN orders o ON u.id = o.user_id

WHERE u.created_at > '2026-01-01'

GROUP BY u.id, u.name

HAVING COUNT(o.id) > 5;

Output analysis:

Hash Join (cost=125.4..892.1 rows=342 width=72)

Hash Cond: (u.id = o.user_id)

-> Seq Scan on users u (cost=0.0..423.1 rows=1250 width=36)

Filter: (created_at > '2026-01-01')

-> Hash (cost=89.2..89.2 rows=2892 width=8)

-> Seq Scan on orders o (cost=0.0..89.2 rows=2892 width=8)

Key metrics to watch:

| Metric | What It Means | Good | Bad | |--------|---------------|------|-----| | cost | Estimated cost (arbitrary units) | Low | High | | rows | Estimated rows returned | Accurate | Off by 10x+ | | actual time | Actual execution time | ms | seconds | | Seq Scan | Full table scan | Small tables | Large tables | | Sort | Explicit sort operation | Sorted data | Large sorts to disk |

Indexing for Query Performance

Covering Indexes

An index that contains all columns needed by a query, enabling index-only scans:

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\-- Query needs: id, email, status, created_at

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\-- Instead of:

CREATE INDEX idx_users_status ON users(status);

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\-- Create a covering index:

CREATE INDEX idx_users_status_covering

ON users(status) INCLUDE (email, created_at);

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\-- Now this query uses an index-only scan:

SELECT email, created_at

FROM users

WHERE status = 'active'

ORDER BY created_at DESC;

JOIN Optimization

Nested Loop vs Hash Join vs Merge Join

| Join Type | When It Is Used | Best For | |-----------|-----------------|----------| | Nested Loop | One table is small, other is indexed | Small result sets | | Hash Join | No useful index, medium tables | Unindexed joins | | Merge Join | Both tables sorted on join key | Large sorted datasets |

Opt

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