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Course Outline
1. Understanding PostgreSQL Query Planner
- Query execution plans and Query Planner algorithms (classic, genetic)
- Interpreting query execution plans (data access methods, join methods)
- Controlling plan selection (configuration parameters, pg_hint_plan)
2. Query Planner Statistics
- Estimating execution plan costs
- Default statistics model
- The ANALYZE operation and extended statistics
3. Using Indexes
- B-tree indexes (single column, composite, function-based, partial)
- Hash indexes
- BRIN indexes
- GiST, GIN indexes
4. Using Advanced Table Structures
- Partitioned tables
- Unlogged tables
- Temporary tables
- Materialised views
5. Using Cache Memory
- Buffer Cache
- Work Memory
- Maintenance Work Memory
6. Parallel Query
- Architecture
- Configuration parameters
- Analyzing parallelised query execution plans
7. Workload and Performance Monitoring
- Logging slow queries
- Utilizing the auto_explain extension
- Utilizing the 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.
14 Hours
Testimonials (1)
Logging behaviour when the instance is under stress, and the hierarchy/nomenclature of instances, databases, files, etc.