How does this skill help with slow database queries?

It provides systematic patterns for analyzing EXPLAIN plans to identify bottlenecks like sequence scans, then suggests specific indexing or query refactoring solutions to improve execution speed.

Does this skill work for databases other than PostgreSQL?

While many examples are PostgreSQL-centric, the core optimization principles—such as indexing strategies, join optimization, and avoiding SELECT *—apply to all major relational databases including MySQL and SQL Server.

Can it help me fix N+1 query issues in my application?

Yes, it includes specific architectural patterns for identifying N+1 anti-patterns and refactoring them into efficient batch queries or optimized JOIN operations.

Does this skill cover advanced database scaling features?

Yes, it includes guidance on advanced topics such as table partitioning, materialized views, and specialized index types like BRIN for extremely large datasets.

SQL Optimization Patterns

Name: SQL Optimization Patterns
Author: goodnight000

bygoodnight000

数据库管理

Optimizes database performance through advanced indexing strategies, query plan analysis, and systematic refactoring of slow SQL queries.

关于

The SQL Optimization Patterns skill transforms Claude into a specialized database performance engineer. It provides deep expertise in interpreting EXPLAIN plans, implementing sophisticated indexing strategies (including B-Tree, GIN, and BRIN), and resolving common performance bottlenecks like the N+1 query anti-pattern. This skill is essential for developers looking to reduce database latency, lower infrastructure costs, and design scalable schemas for high-traffic applications. It covers everything from basic query cleanup to advanced techniques like cursor-based pagination and materialized views.

主要功能

Optimization patterns for pagination, aggregations, and complex subqueries
Strategies to eliminate N+1 query problems using JOINs and batch loading
Implementation of advanced indexing techniques including partial, composite, and covering indexes
Advanced database management techniques like partitioning and materialized views
In-depth analysis and interpretation of EXPLAIN and EXPLAIN ANALYZE query plans
0 GitHub stars

使用场景

Identifying and fixing performance bottlenecks in slow-running production queries
Refactoring legacy database interactions to improve scalability and reduce server load
Designing high-performance database schemas during the initial application build

关于

主要功能

Optimization patterns for pagination, aggregations, and complex subqueries
Strategies to eliminate N+1 query problems using JOINs and batch loading
Implementation of advanced indexing techniques including partial, composite, and covering indexes
Advanced database management techniques like partitioning and materialized views
In-depth analysis and interpretation of EXPLAIN and EXPLAIN ANALYZE query plans
0 GitHub stars

使用场景

Identifying and fixing performance bottlenecks in slow-running production queries
Refactoring legacy database interactions to improve scalability and reduce server load
Designing high-performance database schemas during the initial application build