Course Outline
1. Understanding the PostgreSQL Query Planner
- Query execution plans and Query Planner algorithms (classic, genetic)
- Analyzing query execution plans (data access methods, join methods)
- Controlling plan selection (configuration parameters, pg_hint_plan)
2. Query Planner Statistics
- Execution plan cost estimation
- Default statistics model
- ANALYZE operation, extended statistics
3. Leveraging Indexes
- B-tree indexes (single column, composite, function-based, partial)
- Hash indexes
- BRIN indexes
- GiST, GIN indexes
4. Utilizing Advanced Table Structures
- Partitioned tables
- Unlogged tables
- Temporary tables
- Materialised views
5. Managing Cache Memory
- Buffer Cache
- Work Memory
- Maintenance Work Memory
6. Parallel Query Execution
- Architecture
- Configuration parameters
- Analyzing parallelised query execution plans
7. Workload and Performance Monitoring
- Logging slow queries
- Using auto_explain extension
- Using pg_stat_statements extension
- Cumulative Statistics
8. Benchmarking with PgBench
Requirements
- Completion of PostgreSQL Server Administration or equivalent proficiency
- Practical experience with SQL and PostgreSQL operations
Audience
Database Administrators, DevOps Engineers, and Developers tasked with tuning and maintaining PostgreSQL in production environments.
Testimonials (2)
Tuning strategies.
Jeffrey Zieg - Matrix Consulting
Course - PostgreSQL Performance Tuning
Logging behaviour when the instance is under stress, and the hierarchy/nomenclature of instances, databases, files, etc.