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Duration 14 hours
Course Outline
1. Understanding PostgreSQL Query Planner
- Query execution plans and Query Planner algorithms (classic, genetic)
- Interpreting query execution plans (data access methods, join strategies)
- Influencing plan selection (configuration parameters, pg_hint_plan)
2. Query Planner Statistics
- Estimating execution plan costs
- The default statistics model
- ANALYZE operations and extended statistics
3. Using Indexes
- B-tree indexes (single column, composite, function-based, partial)
- Hash indexes
- BRIN indexes
- GiST and 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 overview
- Relevant configuration parameters
- Analyzing parallel query execution plans
7. Workload and Performance Monitoring
- Logging slow-running queries
- Leveraging the auto_explain extension
- Utilizing the pg_stat_statements extension
- Cumulative Statistics
8. Benchmarking with PgBench
Requirements
- Completion of PostgreSQL Server Administration or possessing comparable expertise
- Practical experience with SQL and PostgreSQL operations
Audience
Database Administrators, DevOps Engineers, and Developers who are tasked with optimizing and maintaining PostgreSQL instances 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.
