Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
1. Introduction to Distributed PostgreSQL
- Challenges associated with scaling single-node PostgreSQL
- Overview of the Citus extension: purpose, architecture, and components
- Core concepts: coordinator nodes, worker nodes, metadata, and distribution keys
2. Cluster Architecture and Setup
- Node types: coordinating versus worker nodes
- Table types: distributed, replicated, and local tables
- Installing and configuring Citus within existing PostgreSQL environments
- Cluster discovery and node management
3. Data Distribution and Sharding Strategies
- Sharding methods: hash-based versus append-based approaches
- Choosing a distribution column for optimal performance
- Managing distributed and replicated tables
- Re-balancing shards and scaling out the cluster
4. Distributed Query Execution and Optimisation
- Mechanisms for how Citus routes and parallelises queries
- Understanding distributed query execution plans
- Query pushdown techniques and execution optimisation
5. Consistency, Transactions and Fault Tolerance
- Two-Phase Commit (2PC) and atomic operations
- Strategies for handling failures in distributed transactions
6. Operational Management and Use Cases
- Monitoring tools and views specific to Citus
- Maintenance procedures and upgrades in distributed environments
Requirements
- Completion of Advanced Administration (High Availability & Replication) or equivalent experience
- Strong understanding of PostgreSQL configuration and performance tuning
- Familiarity with Linux operating systems and fundamental network concepts
Audience
Experienced Database Administrators, DevOps Engineers, and System Architects who currently manage production PostgreSQL environments and require methods to scale them horizontally.
7 Hours
Testimonials (1)
Logging behaviour when the instance is under stress, and the hierarchy/nomenclature of instances, databases, files, etc.