Support Geospatial Data Types (GEO)

[ddupg]

Description

The storage and analysis of geospatial data represent a significant demand, with a robust ecosystem already evolving around these needs. Projects like Iceberg and Parquet have introduced native support for geospatial types. Given this trend, should we consider adding native support for geospatial types in Lance as well?

I'm thinking there may be 4 main categories of implementation:

• Geospatial types: discovered repo geoarrow-rs, which is a Rust implementation of the GeoArrow specification. Perhaps we can draw inspiration from it to implement our own solution, or directly rely on it.
• Geospatial expressions: geoarrow-rs integrates with DataFusion , which aligns well with Lance’s selection and serves as a valuable reference.
• Geospatial index: Lance’s point lookup performance is a major strength. Perhaps we should also consider implementing geospatial type indexing to accelerate queries.
• Engine Integration: the integration of Spark, Daft engines may be necessary.

I created a simple demo based on geoarrow-rs to store geospatial data in LanceDB, then perform SQL queries and spatial computations on Lance Table.