Marketplace database-optimization
SQL query optimization and database performance specialist. Use when
install
source · Clone the upstream repo
git clone https://github.com/aiskillstore/marketplace
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/aiskillstore/marketplace "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/89jobrien/database-optimization" ~/.claude/skills/aiskillstore-marketplace-database-optimization && rm -rf "$T"
manifest:
skills/89jobrien/database-optimization/SKILL.mdsource content
Database Optimization
This skill optimizes database performance including query optimization, indexing strategies, N+1 problem resolution, and caching implementation.
When to Use This Skill
- When optimizing slow database queries
- When fixing N+1 query problems
- When designing indexes
- When implementing caching strategies
- When optimizing database migrations
- When improving database performance
What This Skill Does
- Query Optimization: Analyzes and optimizes SQL queries
- Index Design: Creates appropriate indexes
- N+1 Resolution: Fixes N+1 query problems
- Caching: Implements caching layers (Redis, Memcached)
- Migration Optimization: Optimizes database migrations
- Performance Monitoring: Sets up query performance monitoring
How to Use
Optimize Queries
Optimize this slow database query
Fix the N+1 query problem in this code
Specific Analysis
Analyze query performance and suggest indexes
Optimization Areas
Query Optimization
Techniques:
- Use EXPLAIN ANALYZE
- Optimize JOINs
- Reduce data scanned
- Use appropriate indexes
- Avoid SELECT *
Index Design
Strategies:
- Index frequently queried columns
- Composite indexes for multi-column queries
- Avoid over-indexing
- Monitor index usage
- Remove unused indexes
N+1 Problem
Pattern:
# Bad: N+1 queries users = User.all() for user in users: posts = Post.where(user_id=user.id) # N queries # Good: Single query with JOIN users = User.all().includes(:posts) # 1 query
Examples
Example 1: Query Optimization
Input: Optimize slow user query
Output:
## Database Optimization: User Query ### Current Query ```sql SELECT * FROM users WHERE email = 'user@example.com'; -- Execution time: 450ms
Analysis
- Full table scan (no index on email)
- Scanning 1M+ rows
Optimization
-- Add index CREATE INDEX idx_users_email ON users(email); -- Optimized query SELECT id, email, name FROM users WHERE email = 'user@example.com'; -- Execution time: 2ms
Impact
- Query time: 450ms → 2ms (99.5% improvement)
- Index size: ~50MB
## Best Practices ### Database Optimization 1. **Measure First**: Use EXPLAIN ANALYZE 2. **Index Strategically**: Not every column needs an index 3. **Monitor**: Track slow query logs 4. **Cache**: Cache expensive queries 5. **Denormalize**: When justified by read patterns ## Reference Files - **`references/query_patterns.md`** - Common query optimization patterns, anti-patterns, and caching strategies ## Related Use Cases - Query optimization - Index design - N+1 problem resolution - Caching implementation - Database performance improvement