What kind of indexing strategies are covered?

It covers a wide range of strategies including B-Tree, GIN, GiST, BRIN, composite, partial, and covering indexes to suit different data access patterns.

Does this skill support PostgreSQL and MySQL?

Yes, the skill includes patterns and syntax specific to PostgreSQL while maintaining general optimization principles applicable to MySQL and other SQL databases.

How does this skill help with database performance?

It provides systematic patterns for identifying bottlenecks using EXPLAIN plans and offers specific remedies like index optimization, query rewriting, and structural changes.

Can it help solve the N+1 query problem?

Absolutely. It contains specific strategies for identifying N+1 patterns and converting them into efficient JOINs or batch loading operations.

SQL Optimization Patterns

Name: SQL Optimization Patterns
Author: as4584

byas4584

数据库管理

Optimizes database performance through advanced indexing strategies, EXPLAIN plan analysis, and query restructuring patterns.

关于

This skill serves as a comprehensive guide for developers looking to eliminate slow-running queries and improve database scalability. It provides actionable patterns for interpreting execution plans, implementing specialized indexes (like GIN, BRIN, and covering indexes), and rewriting inefficient SQL. From resolving N+1 query issues to mastering cursor-based pagination and table partitioning, this skill enables Claude to provide expert-level database tuning and architectural advice for high-traffic applications.

主要功能

Advanced scaling techniques like materialized views and partitioning
Solutions for the N+1 query anti-pattern and inefficient joins
Deep EXPLAIN and EXPLAIN ANALYZE query plan interpretation
High-performance pagination and aggregation optimization
Sophisticated indexing strategies including composite and partial indexes
0 GitHub stars

使用场景

Debugging and accelerating slow-running production database queries
Designing performant schemas for applications with large datasets
Reducing database server load and infrastructure costs through optimization

关于

主要功能

Advanced scaling techniques like materialized views and partitioning
Solutions for the N+1 query anti-pattern and inefficient joins
Deep EXPLAIN and EXPLAIN ANALYZE query plan interpretation
High-performance pagination and aggregation optimization
Sophisticated indexing strategies including composite and partial indexes
0 GitHub stars

使用场景

Debugging and accelerating slow-running production database queries
Designing performant schemas for applications with large datasets
Reducing database server load and infrastructure costs through optimization