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Duration 14 hours
Course Outline
1. Exploring the PostgreSQL Query Planner
- Examining query execution plans and Planner algorithms (classic, genetic)
- Interpreting execution plans (data access methods, join strategies)
- Influencing plan selection via configuration parameters and pg_hint_plan
2. Query Planner Statistics
- Assessing execution plan cost estimates
- Reviewing the default statistical models
- Running ANALYZE operations and managing 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 Processing
- Understanding the architecture
- Configuring relevant parameters
- Analysing parallelised query execution plans
7. Monitoring Workload and Performance
- Capturing slow queries through logging
- Implementing the auto_explain extension
- Utilising the pg_stat_statements extension
- Tracking Cumulative Statistics
8. Benchmarking with PgBench
Requirements
- Completion of PostgreSQL Server Administration or equivalent foundational knowledge
- Practical experience with SQL and day-to-day PostgreSQL operations
Who Should Attend
This course is designed for Database Administrators, DevOps Engineers, and Developers who are responsible for optimising and maintaining PostgreSQL in production settings.
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.