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Duration 14 hours
Course Outline
1. Exploring the PostgreSQL Query Planner
- Understanding query execution plans and Planner algorithms (classic, genetic)
- Analyzing execution plans (data access methods, join methods)
- Influencing plan selection (configuration parameters, pg_hint_plan)
2. Query Planner Statistics
- Cost estimation for execution plans
- The default statistics model
- The ANALYZE operation and extended statistics
3. Leveraging Indexes
- B-tree indexes (single column, composite, function-based, partial)
- Hash indexes
- BRIN indexes
- GiST and GIN indexes
4. 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
- Underlying architecture
- Relevant configuration parameters
- Analysis of parallelised query execution plans
7. Workload and Performance Monitoring
- Logging slow queries
- Utilizing the auto_explain extension
- Leveraging the pg_stat_statements extension
- Cumulative Statistics
8. Benchmarking with PgBench
Requirements
- Completion of PostgreSQL Server Administration or equivalent foundational knowledge
- Hands-on experience with SQL and PostgreSQL operations
Target Audience
Database Administrators, DevOps Engineers, and Developers who are responsible for optimizing 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.
