SPATIAL LAB CERTIFICATION

E2: Apache Iceberg for Geospatial Data

This brick introduces Apache Iceberg—an open table format that brings versioning, schema evolution, and SQL access to large-scale spatial data.

 

You’ll get hands-on experience building and querying Iceberg tables with:

 

  • GeoParquet for scalable vector storage
  • Cloud object storage as the data lake foundation
  • PyIceberg and DuckDB for spatial SQL exploration
Register & Get Started for $49

Brick E2 – Core Competencies (High-Level)

  1. Open Table Formats & Metadata Layers
    Understand Iceberg’s architecture, including manifest files, metadata layers, and snapshot tracking.
  2. Spatial Data in Iceberg Tables
    Create GeoParquet-based Iceberg tables, register geometry columns, and manage spatial schemas.
  3. Versioning & Time Travel
    Query datasets at specific points in time using Iceberg snapshots; explore schema evolution over time.
  4. Cross-Engine Querying
    Use PyIceberg and DuckDB to read spatial Iceberg tables; understand how catalogs enable interoperability.

What you'll learn

✅ The core architecture of Apache Iceberg for spatial data.
✅ How to build, version, and query Iceberg tables with GeoParquet.
✅ Benefits of Iceberg over traditional spatial storage formats.
✅ Real-world workflows for time travel, schema evolution, and cross-engine querying.

Learn by doing

You’ll learn by doing: coding inside a live cloud-based environment and running real code with best practices embedded.

Format

💻 4–6 hours to complete
🧪 Interactive notebook environment in Gitpod
✅ Autograded tests for completion
📛 Earn a verifiable Open Badge upon passing
🔁 Self-paced – start anytime
Lesson Skills

E2 Certified Skills

Full list of skills and tools used during this certification track. Anyone who has the validated badge for this track has used these tools and skills.

– Understand Iceberg’s table structure (manifests, metadata, snapshots)
– Explore how Iceberg separates table metadata from physical file storage

– Write spatial data in GeoParquet format into Iceberg tables
– Register geometry columns and ensure spatial metadata is preserved

– Query specific table states using Iceberg snapshot IDs
– Understand how to track and roll back changes over time

– Add, remove, and rename columns while preserving table history
– Handle spatial schema updates (e.g., geometry type or CRS changes)

– Use DuckDB and PyIceberg to query Iceberg tables
– Understand how catalogs (REST, Glue) manage table discovery

– Store Iceberg tables in S3-style object storage
– Inspect how Iceberg metadata references files in the lake

– Read and interpret metadata.json, manifest.json, and snapshots
– Visualize partitioning, file layout, and table evolution over time

Affordable plans

Flexible pricing to suit every team size

Choose from scalable pricing options that grow with your team’s needs and budget.

🔥 START E1 BRICK 🔥

E2 Brick

Learn the complete track and how to interweave skills in a Capstone seminar

$ 49
  • Full E1 Brick content
  • Certification badge on completion
  • Cloud resources and code
Sign Up Now

Full Brick Track

Learn the complete track and how to interweave skills in a Capstone seminar

$ 149
  • Access to all 4 E-Track Bricks
  • Certifications for each Brick
  • Capstone seminar for the track
  • Capstone certifiation
Get the Full E Track
Modern GIS

Spatial Lab Membership

Get full access to additional tracks, community resources, and live cohort events.

$ 19 /month
  • Access to the E-Track and other upcoming tracks
  • Community supported learning with other learners
  • Access to live events for this track
  • Much more...
Join the Lab