Query Optimization Basics — Complete Guide
Query Optimization Basics — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of PostgreSQL Tutorial on Toolliyo Academy.
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PostgreSQL Tutorial · Lesson 20 of 100
Query Optimization Basics
SQL → Advanced
SQL · 1 — Queries · ~6 min · PostgreSQL — SQL & Queries
What is this?
Optimization means getting correct results with less I/O and CPU — better indexes, accurate statistics, simpler SQL, and appropriate limits. Start by measuring, then change one thing at a time.
Why should you care?
A PostgresVerse checkout query scanning 10M orders every click would melt CPU during Big Billion Days.
See it live — copy this example
Run in pgAdmin or psql.
EXPLAIN (ANALYZE, BUFFERS)
SELECT order_id, total_amount
FROM orders
WHERE customer_id = 1042
ORDER BY created_at DESC
LIMIT 10;What happened?
- EXPLAIN ANALYZE runs the query and shows actual timings.
- BUFFERS reveals cache hits vs disk reads.
- You look for Seq Scan on huge tables when Index Scan was expected.
Practice next
- Create index on orders(customer_id, created_at DESC) if missing.
- Run EXPLAIN ANALYZE before and after index.
- Compare execution time and scan type.
- Rewrite OR on two columns to UNION ALL and compare plans.
- Set enable_seqscan=off session-only to test index path (dev only).
Remember
Measure with EXPLAIN ANALYZE first. Index columns in WHERE and ORDER BY together when possible. Keep statistics fresh with ANALYZE.
PostgresVerse checkout fix
P95 latency drops from 800ms to 12ms after composite index on customer order history.
Outcome: Mobile checkout survives sale traffic without extra replicas.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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