Course Outline

1. Introduction to Distributed PostgreSQL

  • Addressing scaling challenges with single-node PostgreSQL
  • Overview of the Citus extension: its purpose, architecture, and components for government use
  • Key concepts: coordinator node, worker nodes, metadata, and distribution keys

2. Cluster Architecture and Setup

  • Node types: coordinator versus workers
  • Table types: distributed, replicated, and local tables
  • Installing and configuring Citus on existing PostgreSQL environments for government operations
  • Cluster discovery and node management processes

3. Data Distribution and Sharding Strategies

  • Sharding methods: hash versus append
  • Selecting a distribution column for optimal performance in government applications
  • Managing distributed and replicated tables effectively
  • Re-balancing shards and scaling out the cluster

4. Distributed Query Execution and Optimization

  • How Citus routes and parallelizes queries for government databases
  • Understanding distributed query plans in a public sector context
  • Query pushdown and execution optimization techniques

5. Consistency, Transactions, and Fault Tolerance

  • Two-Phase Commit (2PC) and atomic operations for government transactions
  • Handling failures in distributed transactions to ensure reliability

6. Operational Management and Use Cases

  • Monitoring tools and views for Citus in a government setting
  • Maintenance and upgrades in distributed environments for government operations

Requirements

  • Completion of Advanced Administration (High Availability & Replication) or equivalent experience for government.
  • Solid understanding of PostgreSQL configuration and performance optimization.
  • Proficiency with Linux and foundational network concepts.

Audience

This course is designed for experienced Database Administrators, DevOps Engineers, and System Architects who currently manage production PostgreSQL environments within the public sector and require strategies to scale these systems horizontally.

 7 Hours

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