How does this skill help with slow queries?

It provides systematic patterns for analyzing EXPLAIN plans and suggests specific indexing or refactoring techniques to dramatically reduce query execution time.

Is cursor-based pagination included?

Absolutely. The skill provides patterns to move away from slow OFFSET-based pagination toward high-performance cursor-based navigation for large tables.

Which databases are supported by these patterns?

While many examples focus on PostgreSQL and MySQL, the core optimization concepts like index selection and join optimization apply to most relational database systems.

Can it help solve the N+1 query problem?

Yes, it includes specific strategies for identifying N+1 anti-patterns and converting them into efficient JOINs or batch loading operations.

Does it cover advanced indexing beyond basic B-Trees?

Yes, it includes guidance on GIN, GiST, and BRIN indexes, as well as functional, partial, and covering indexes for specialized performance needs.

SQL Performance Optimization Patterns

Name: SQL Performance Optimization Patterns
Author: Activer007

byActiver007

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数据库管理

Optimizes database performance through advanced SQL query patterns, strategic indexing, and detailed execution plan analysis.

关于

This skill empowers developers to transform sluggish database operations into high-performance queries by applying systematic optimization techniques. It provides comprehensive guidance on interpreting EXPLAIN outputs, implementing advanced indexing strategies like GIN and BRIN, and refactoring common performance bottlenecks such as N+1 queries and inefficient pagination. Whether you are designing a new schema for scale or debugging production bottlenecks, these patterns help reduce database load and improve application responsiveness across PostgreSQL, MySQL, and other relational systems.

主要功能

Deep EXPLAIN and EXPLAIN ANALYZE plan interpretation
Refactoring patterns for N+1 queries and subquery optimization
Batch operation patterns for efficient bulk inserts and updates
Advanced indexing strategies including composite, partial, and covering indexes
High-performance pagination techniques using cursor-based logic
1 GitHub stars

使用场景

Reducing cloud infrastructure costs by minimizing database CPU and I/O usage
Debugging and fixing slow-running production database queries
Designing performant schemas for applications with large datasets

关于

主要功能

Deep EXPLAIN and EXPLAIN ANALYZE plan interpretation
Refactoring patterns for N+1 queries and subquery optimization
Batch operation patterns for efficient bulk inserts and updates
Advanced indexing strategies including composite, partial, and covering indexes
High-performance pagination techniques using cursor-based logic
1 GitHub stars

使用场景

Reducing cloud infrastructure costs by minimizing database CPU and I/O usage
Debugging and fixing slow-running production database queries
Designing performant schemas for applications with large datasets