Apache Iceberg Training in Astana, Kazakhstan

This course introduces Apache Iceberg, an open table format for managing large analytic datasets on data lakes. Participants will learn Iceberg concepts, architecture, features, and hands-on techniques for building scalable, reliable, and high-performance data pipelines.

Fundamentals & Core Features

Session 1: Introduction to Apache Iceberg 

• What is Apache Iceberg and why it matters
• Iceberg vs. traditional Hive tables and Delta Lake/Hudi
• Key features: ACID transactions, schema evolution, hidden partitioning

Session 2: Iceberg Architecture

• Table format design and metadata files
• Snapshots, manifests, and partitioning
• How Iceberg enables time travel and rollback

Session 3: Getting Started with Iceberg

• Setting up Iceberg with Spark/Trino
• Creating Iceberg tables (DDL/DML examples)

Session 4: Core Table Operations

• Inserts, updates, deletes, and merges
• Schema evolution (add, drop, rename columns)

Advanced Features & Integrations

Session 1: Partitioning & Performance Optimization

• Hidden partitioning explained
• Compaction, clustering, and file optimization

Session 2: Snapshots & Time Travel

• Snapshot lifecycle management
• Rollback to previous states

Session 3: Multi-Engine Integration

• Using Iceberg with Spark, Flink, Trino, Presto
• Query interoperability and governance

Session 4: Production Best Practices

• Security and access control considerations
• Monitoring and maintenance of Iceberg tables
• Governance, compliance, and data versioning
• Case studies: Real-world Iceberg deployments
• Hands-on Exercises
• Wrap-up & Q&A