Sql optimization patterns

SQL Optimization Patterns

Diagnose slow SQL with query plans, preserve query results, and verify indexing or query changes against representative data.

Use this skill when

• Debugging slow-running queries
• Designing performant database schemas
• Optimizing application response times
• Reducing database load and costs
• Improving scalability for growing datasets
• Analyzing EXPLAIN query plans
• Implementing efficient indexes
• Resolving N+1 query problems

Do not use this skill when

• The task is unrelated to sql optimization patterns
• You need a different domain or tool outside this scope

Instructions

• Confirm database engine/version, query parameters, expected rows, data distribution and the permitted environment. Start read-only; obtain authorization before DDL, data changes, configuration changes or maintenance.
• Compare result sets before comparing performance. EXPLAIN ANALYZE executes the statement: use approved representative data, account for functions and triggers, and do not assume a transaction rollback undoes every side effect.
• Record the observed plan, timing conditions and correctness checks. Indexes and query rewrites are hypotheses, not universal speed improvements.
• If detailed examples are required, open resources/implementation-playbook.md.

Resources

• resources/implementation-playbook.md for detailed patterns and examples.

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Worked example

The playbook includes an executable SQLite batch-loading example with bound values and an empty-input case. The repository test exercises it alongside pagination ties and aggregation equivalence. SQLite correctness checks do not establish PostgreSQL performance or production safety.