GeoParquet

Purpose

Describe how GeoParquet supports scalable vector data storage, analytics, and interchange in modern geospatial data systems.

Outline

• Relationship between Parquet columnar storage and geospatial vector workloads
• Geometry encoding, coordinate reference systems, and metadata expectations
• Partitioning and indexing strategies for spatial and temporal queries
• Integration patterns with data lakes, query engines, and ML feature generation
• Tradeoffs compared with GeoJSON, Shapefiles, spatial databases, and tiled vector formats

Later Examples

• Designing a partitioned GeoParquet dataset for repeated analysis
• Reading only required columns and spatial subsets
• Preparing vector features for a geospatial ML pipeline