SQL Guide

Applies to: PostgreSQL 15+, MySQL 8+, Database Migrations, Query Optimization

Core Principles

1. Parameterized Queries Always: Never concatenate user input into SQL strings -- use bind parameters ($1, ?, :name) without exception
2. Explicit Over Implicit: Name all constraints, specify column lists in INSERT, avoid SELECT * in production code
3. Migrations Are Immutable: Once applied to a shared environment, never modify a migration -- create a new one
4. Indexes Are Not Free: Every index speeds reads but slows writes; justify each index with a query plan
5. Transactions Are Boundaries: Keep transactions short, choose the correct isolation level, and always handle rollback

Guardrails

Naming Conventions

• Tables: snake_case, plural (users, order_items, audit_logs)
• Columns: snake_case, singular (email, created_at, is_active)
• Primary keys: id (integer or UUID depending on project convention)
• Foreign keys: <singular_table>_id (user_id, order_id)
• Indexes: idx_<table>_<columns> (idx_users_email, idx_orders_user_id_created_at)
• Unique constraints: uq_<table>_<columns> (uq_users_email)
• Check constraints: ck_<table>_<description> (ck_orders_positive_total)
• Boolean columns: is_ or has_ prefix (is_active, has_verified_email)
• Timestamps: created_at, updated_at, deleted_at (always TIMESTAMPTZ)

Query Safety

• ALWAYS use parameterized queries -- no string interpolation of user input
• ALWAYS specify column lists in INSERT statements
• NEVER use SELECT * in application code (acceptable in ad-hoc queries only)
• ALWAYS add LIMIT to queries that return lists (prevent unbounded result sets)
• NEVER use TRUNCATE or DROP in application code without explicit safeguards
• ALWAYS use EXISTS instead of COUNT(*) > 0 for existence checks
• ALWAYS qualify column names with table aliases in JOINs

-- GOOD: parameterized, explicit columns, bounded
SELECT u.id, u.email, u.created_at
FROM users u
WHERE u.email = $1
  AND u.is_active = true
LIMIT 1;

-- BAD: string concatenation, SELECT *, no LIMIT
SELECT * FROM users WHERE email = '" + userInput + "';

Indexing

• Create indexes to support WHERE, JOIN, and ORDER BY clauses
• Composite index column order: equality columns first, then range, then sort
• Use UNIQUE indexes to enforce business rules at the database level
• Prefer partial indexes when filtering on a known subset (WHERE is_active = true)
• Use CONCURRENTLY for index creation on live tables (PostgreSQL)
• Review index usage periodically -- drop unused indexes

-- Composite index: equality (status) first, then range (created_at)
CREATE INDEX CONCURRENTLY idx_orders_status_created
ON orders (status, created_at DESC);

-- Partial index: only index active users
CREATE INDEX idx_users_email_active
ON users (email) WHERE is_active = true;

Transactions

• Keep transactions as short as possible (no I/O or external calls inside)
• Use READ COMMITTED for most operations (PostgreSQL default)
• Use REPEATABLE READ when a transaction reads the same data multiple times
• Use SERIALIZABLE for financial or inventory operations requiring strict consistency
• Always explicitly COMMIT or ROLLBACK -- never leave transactions hanging
• Use SAVEPOINT for partial rollback within complex transactions

BEGIN;
  SAVEPOINT before_update;

  UPDATE accounts SET balance = balance - 100.00 WHERE id = $1;
  UPDATE accounts SET balance = balance + 100.00 WHERE id = $2;

  -- If second update fails, roll back to savepoint
  -- ROLLBACK TO SAVEPOINT before_update;
COMMIT;

Migrations

• Every migration MUST have both up and down functions
• Migrations MUST be idempotent (IF NOT EXISTS, IF EXISTS guards)
• Never rename or drop columns in a single step -- use a multi-step process
• Add columns as NULL first, backfill, then add NOT NULL constraint
• Never modify a migration that has been applied to a shared environment
• Migration filenames: YYYYMMDDHHMMSS_description.sql or sequential numbering
• Test both up and down in development before committing

-- UP: 20250115120000_add_users_phone.sql
ALTER TABLE users ADD COLUMN IF NOT EXISTS phone VARCHAR(20);
CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_users_phone
ON users (phone) WHERE phone IS NOT NULL;

-- DOWN: 20250115120000_add_users_phone.sql
DROP INDEX CONCURRENTLY IF EXISTS idx_users_phone;
ALTER TABLE users DROP COLUMN IF EXISTS phone;

Schema Design

Standard Table Template

CREATE TABLE IF NOT EXISTS orders (
    id            BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
    user_id       BIGINT NOT NULL REFERENCES users(id) ON DELETE CASCADE,
    status        VARCHAR(20) NOT NULL DEFAULT 'pending'
                    CONSTRAINT ck_orders_valid_status
                    CHECK (status IN ('pending', 'confirmed', 'shipped', 'delivered', 'cancelled')),
    total_cents   INTEGER NOT NULL
                    CONSTRAINT ck_orders_positive_total CHECK (total_cents >= 0),
    notes         TEXT,
    created_at    TIMESTAMPTZ NOT NULL DEFAULT now(),
    updated_at    TIMESTAMPTZ NOT NULL DEFAULT now()
);

-- Auto-update updated_at (PostgreSQL)
CREATE OR REPLACE FUNCTION update_updated_at()
RETURNS TRIGGER AS $$
BEGIN
    NEW.updated_at = now();
    RETURN NEW;
END;
$$ LANGUAGE plpgsql;

CREATE TRIGGER trg_orders_updated_at
    BEFORE UPDATE ON orders
    FOR EACH ROW EXECUTE FUNCTION update_updated_at();

Design Rules

• Use BIGINT GENERATED ALWAYS AS IDENTITY for auto-increment PKs (PostgreSQL 10+)
• Use UUID PKs when IDs are exposed externally or distributed systems require it
• Use TIMESTAMPTZ (not TIMESTAMP) for all time columns -- always store UTC
• Add NOT NULL constraints by default; allow NULL only when semantically meaningful
• Use CHECK constraints to enforce domain rules at the database level
• Use ENUM types sparingly -- prefer VARCHAR with CHECK for easier migration
• Add ON DELETE CASCADE or ON DELETE SET NULL explicitly to every foreign key
• Use soft deletes (deleted_at TIMESTAMPTZ) when audit trail is required

Key Patterns

Common Table Expressions (CTEs)

Prefer CTEs over subqueries for readability and maintainability.

-- Readable: each step has a name
WITH active_orders AS (
    SELECT user_id, COUNT(*) AS order_count, SUM(total_cents) AS total_spent
    FROM orders
    WHERE status != 'cancelled'
      AND created_at >= now() - INTERVAL '30 days'
    GROUP BY user_id
),
high_value_users AS (
    SELECT user_id
    FROM active_orders
    WHERE total_spent > 50000  -- over $500
)
SELECT u.id, u.email, ao.order_count, ao.total_spent
FROM users u
JOIN active_orders ao ON ao.user_id = u.id
WHERE u.id IN (SELECT user_id FROM high_value_users)
ORDER BY ao.total_spent DESC;

Window Functions

Use window functions for ranking, running totals, and row comparisons without self-joins.

-- Rank users by spending within each region
SELECT
    u.id,
    u.region,
    SUM(o.total_cents) AS total_spent,
    RANK() OVER (PARTITION BY u.region ORDER BY SUM(o.total_cents) DESC) AS rank
FROM users u
JOIN orders o ON o.user_id = u.id
GROUP BY u.id, u.region;

-- Running total of daily revenue
SELECT
    date_trunc('day', created_at) AS day,
    SUM(total_cents) AS daily_revenue,
    SUM(SUM(total_cents)) OVER (ORDER BY date_trunc('day', created_at)) AS running_total
FROM orders
WHERE status = 'delivered'
GROUP BY date_trunc('day', created_at)
ORDER BY day;

UPSERT (INSERT ... ON CONFLICT)

-- PostgreSQL: insert or update on conflict
INSERT INTO user_preferences (user_id, theme, language)
VALUES ($1, $2, $3)
ON CONFLICT (user_id)
DO UPDATE SET
    theme = EXCLUDED.theme,
    language = EXCLUDED.language,
    updated_at = now();

Batch Operations

-- Batch insert with unnest (PostgreSQL)
INSERT INTO tags (name, category)
SELECT unnest($1::text[]), unnest($2::text[])
ON CONFLICT (name) DO NOTHING;

-- Batch update with VALUES list
UPDATE products AS p
SET price_cents = v.new_price
FROM (VALUES
    (1, 2999),
    (2, 4999),
    (3, 1499)
) AS v(id, new_price)
WHERE p.id = v.id;

Parameterized Queries (Application Code)

# Python (psycopg2/asyncpg) -- ALWAYS use parameterized queries
cursor.execute(
    "SELECT id, email FROM users WHERE email = %s AND is_active = %s",
    (email, True),
)

# Node.js (pg)
const result = await pool.query(
    'SELECT id, email FROM users WHERE email = $1 AND is_active = $2',
    [email, true]
);

# Go (database/sql)
row := db.QueryRowContext(ctx,
    "SELECT id, email FROM users WHERE email = $1 AND is_active = $2",
    email, true,
)

Performance

EXPLAIN ANALYZE

Always use EXPLAIN ANALYZE to validate query plans before deploying.

-- Check execution plan and actual timing
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT u.id, u.email, COUNT(o.id) AS order_count
FROM users u
LEFT JOIN orders o ON o.user_id = u.id
WHERE u.created_at >= '2025-01-01'
GROUP BY u.id, u.email
ORDER BY order_count DESC
LIMIT 20;

What to look for:

• Seq Scan on large tables -- usually needs an index
• Nested Loop with large outer sets -- consider Hash Join via index or rewrite
• Sort operations with high cost -- add index matching ORDER BY
• Rows Removed by Filter much larger than Actual Rows -- index the filter column
• Buffers: shared hit vs shared read -- high reads indicate cold cache

Index Strategy

Access Pattern	Index Type	Example
Equality lookup	B-tree (default)	WHERE email = $1
Range scan	B-tree	WHERE created_at > $1
Full-text search	GIN + tsvector	WHERE search_vector @@ to_tsquery($1)
JSONB field access	GIN	WHERE metadata @> '{"key": "val"}'
Array containment	GIN	WHERE tags @> ARRAY['sql']
Geometric/spatial	GiST	WHERE location <-> point($1,$2) < $3
Pattern matching (LIKE 'abc%')	B-tree with text_pattern_ops	WHERE name LIKE 'abc%'

N+1 Prevention

-- BAD: N+1 (one query per user to fetch orders)
-- Application loops: for each user, SELECT orders WHERE user_id = ?

-- GOOD: single query with JOIN
SELECT u.id, u.email, o.id AS order_id, o.total_cents
FROM users u
LEFT JOIN orders o ON o.user_id = u.id
WHERE u.is_active = true
ORDER BY u.id, o.created_at DESC;

-- GOOD: batch with ANY (when you have a list of IDs)
SELECT id, email, created_at
FROM users
WHERE id = ANY($1::bigint[]);

Pagination

-- Cursor-based pagination (preferred for large datasets)
SELECT id, email, created_at
FROM users
WHERE created_at < $1  -- cursor: last seen created_at
  AND is_active = true
ORDER BY created_at DESC
LIMIT 25;

-- Offset-based pagination (simpler but slower for deep pages)
SELECT id, email, created_at
FROM users
WHERE is_active = true
ORDER BY created_at DESC
LIMIT 25 OFFSET $1;

Tooling

Essential Commands

# PostgreSQL CLI
psql -h localhost -U myuser -d mydb       # Connect
psql -f migration.sql mydb                # Run migration file
pg_dump -Fc mydb > backup.dump            # Backup (custom format)
pg_restore -d mydb backup.dump            # Restore

# pgcli (enhanced CLI with autocomplete)
pgcli -h localhost -U myuser -d mydb

# Schema inspection
\dt                   # List tables
\d+ table_name        # Describe table with details
\di                   # List indexes
\df                   # List functions

Migration Tools

# golang-migrate
migrate create -ext sql -dir db/migrations -seq add_users_phone
migrate -path db/migrations -database "$DATABASE_URL" up
migrate -path db/migrations -database "$DATABASE_URL" down 1

# Alembic (Python/SQLAlchemy)
alembic revision -m "add users phone"
alembic upgrade head
alembic downgrade -1

# Prisma (Node.js)
npx prisma migrate dev --name add_users_phone
npx prisma migrate deploy

# dbmate
dbmate new add_users_phone
dbmate up
dbmate rollback

Useful Diagnostic Queries (PostgreSQL)

-- Find slow queries (requires pg_stat_statements extension)
SELECT query, calls, mean_exec_time, total_exec_time
FROM pg_stat_statements
ORDER BY mean_exec_time DESC
LIMIT 10;

-- Find unused indexes
SELECT schemaname, tablename, indexname, idx_scan
FROM pg_stat_user_indexes
WHERE idx_scan = 0
  AND indexname NOT LIKE '%pkey%'
ORDER BY pg_relation_size(indexrelid) DESC;

-- Table sizes
SELECT relname, pg_size_pretty(pg_total_relation_size(relid))
FROM pg_catalog.pg_statio_user_tables
ORDER BY pg_total_relation_size(relid) DESC;

-- Active connections and queries
SELECT pid, state, query, query_start, now() - query_start AS duration
FROM pg_stat_activity
WHERE state != 'idle'
ORDER BY duration DESC;

References

For detailed patterns and examples, see:

• references/patterns.md -- Window functions, CTE patterns, indexing strategies, advanced query techniques

External References

• PostgreSQL Documentation
• Use The Index, Luke -- SQL indexing and tuning
• Modern SQL -- Modern SQL features across databases
• pgMustard EXPLAIN Guide -- Reading query plans
• SQL Style Guide (Holywell) -- Formatting conventions
• Postgres Wiki: Don't Do This -- Common PostgreSQL anti-patterns