sql-patterns

majiayu000's avatarfrom majiayu000

SQL query patterns, optimization, and database best practices. Use when writing SQL queries, discussing database design, query optimization, or working with PostgreSQL, MySQL, SQLite. Triggers on mentions of SQL, SELECT, JOIN, INDEX, query optimization, database schema, PostgreSQL, MySQL.

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[SQL and Databases]

When & Why to Use This Skill

This Claude skill serves as a comprehensive reference for SQL query patterns, database design, and performance optimization. It provides ready-to-use templates for Common Table Expressions (CTEs), window functions, and advanced indexing strategies, helping developers and data analysts write efficient, scalable, and maintainable queries for PostgreSQL, MySQL, and SQLite.

Use Cases

  • Optimizing slow-running database queries by applying indexing best practices and avoiding common anti-patterns like 'SELECT *' or inefficient 'NOT IN' clauses.
  • Performing complex data analysis using window functions for tasks such as calculating running totals, row rankings, and time-series comparisons (LAG/LEAD).
  • Refactoring deeply nested queries into readable, modular, and maintainable code structures using chained Common Table Expressions (CTEs).
  • Implementing high-performance pagination for large datasets using keyset-based navigation to avoid the performance pitfalls of large OFFSET values.
  • Selecting the most appropriate index types (B-tree, Hash, GIN) for specific data structures like JSONB or arrays to significantly improve search performance.
namesql-patterns
description"Quick reference for common SQL patterns, CTEs, window functions, and indexing strategies. Triggers on: sql patterns, cte example, window functions, sql join, index strategy, pagination sql."
allowed-tools"Read Write"

SQL Patterns

Quick reference for common SQL patterns.

CTE (Common Table Expressions)

WITH active_users AS (
    SELECT id, name, email
    FROM users
    WHERE status = 'active'
)
SELECT * FROM active_users WHERE created_at > '2024-01-01';

Chained CTEs

WITH
    active_users AS (
        SELECT id, name FROM users WHERE status = 'active'
    ),
    user_orders AS (
        SELECT user_id, COUNT(*) as order_count
        FROM orders GROUP BY user_id
    )
SELECT u.name, COALESCE(o.order_count, 0) as orders
FROM active_users u
LEFT JOIN user_orders o ON u.id = o.user_id;

Window Functions (Quick Reference)

Function Use
ROW_NUMBER() Unique sequential numbering
RANK() Rank with gaps (1, 2, 2, 4)
DENSE_RANK() Rank without gaps (1, 2, 2, 3)
LAG(col, n) Previous row value
LEAD(col, n) Next row value
SUM() OVER Running total
AVG() OVER Moving average 
SELECT
    date,
    revenue,
    LAG(revenue, 1) OVER (ORDER BY date) as prev_day,
    SUM(revenue) OVER (ORDER BY date) as running_total
FROM daily_sales;

JOIN Reference

Type Returns
INNER JOIN Only matching rows
LEFT JOIN All left + matching right
RIGHT JOIN All right + matching left
FULL JOIN All rows, NULL where no match

Pagination

-- OFFSET/LIMIT (simple, slow for large offsets)
SELECT * FROM products ORDER BY id LIMIT 20 OFFSET 40;

-- Keyset (fast, scalable)
SELECT * FROM products WHERE id > 42 ORDER BY id LIMIT 20;

Index Quick Reference

Index Type Best For
B-tree Range queries, ORDER BY
Hash Exact equality only
GIN Arrays, JSONB, full-text
Covering Avoid table lookup

Anti-Patterns

Mistake Fix
SELECT * List columns explicitly
WHERE YEAR(date) = 2024 WHERE date >= '2024-01-01'
NOT IN with NULLs Use NOT EXISTS
N+1 queries Use JOIN or batch

Additional Resources

For detailed patterns, load:

  • ./references/window-functions.md - Complete window function patterns
  • ./references/indexing-strategies.md - Index types, covering indexes, optimization