feat(vortex-geo): native Point extension type and GeoDistance scalar function

[HarukiMoriarty]

Summary

This PR adds a native point type to vortex-geo. Points are by far the most common geometry in analytical datasets, and a columnar representation makes their coordinates directly accessible without parsing WKB.

It also adds the scalar function: point-to-point distance with PostGIS ST_Distance semantics (planar/Euclidean, results in CRS units).

API Changes

Adds to vortex-geo, all registered through vortex_geo::initialize:

• Extension type Point (vortex.geo.point): a location stored as Struct<x, y, z?, m?> of non-nullable f64, where z? is an optional elevation and m? an optional measure.
• Coordinate: the internal value a point scalar unpacks to.
• Scalar function GeoDistance (vortex.geo.distance): per-row distance between two equal-length point columns; either or both operands may be constant, in which case the query point is decoded once and broadcast.

Testing

Unit tests cover dtype validation for every GeoArrow dimension (and rejection of invalid storage), round-tripping a point column through scalar execution back to the original coordinates, WKT display for all four dimensions, and distance over all operand shapes: column-to-constant (either side), column-to-column, and constant-to-constant.

[codspeed-hq]

Merging this PR will not alter performance

⚠️ Unknown Walltime execution environment detected

Using the Walltime instrument on standard Hosted Runners will lead to inconsistent data.

For the most accurate results, we recommend using CodSpeed Macro Runners: bare-metal machines fine-tuned for performance measurement consistency.

⚡ 6 improved benchmarks
❌ 5 regressed benchmarks
✅ 1521 untouched benchmarks

Warning

Please fix the performance issues or acknowledge them on CodSpeed.

Performance Changes

	Mode	Benchmark	BASE	HEAD	Efficiency
❌	Simulation	chunked_bool_canonical_into[(1000, 10)]	20.2 µs	35.2 µs	-42.51%
❌	Simulation	chunked_varbinview_into_canonical[(1000, 10)]	177.2 µs	213.3 µs	-16.93%
❌	Simulation	varbinview_large	113.1 µs	131.7 µs	-14.13%
❌	Simulation	decompress_rd[f64, (100000, 0.0)]	845.2 µs	980 µs	-13.76%
❌	Simulation	chunked_varbinview_canonical_into[(100, 100)]	274.4 µs	309.3 µs	-11.27%
⚡	Simulation	decompress_rd[f64, (10000, 0.0)]	138 µs	110.9 µs	+24.41%
⚡	Simulation	decompress_rd[f64, (10000, 0.1)]	137.8 µs	110.9 µs	+24.24%
⚡	Simulation	decompress_rd[f64, (10000, 0.01)]	137.4 µs	110.6 µs	+24.23%
⚡	Simulation	decompress_rd[f32, (10000, 0.1)]	89.3 µs	80.2 µs	+11.4%
⚡	Simulation	decompress_rd[f32, (10000, 0.0)]	89.6 µs	80.8 µs	+10.93%
⚡	Simulation	decompress_rd[f32, (10000, 0.01)]	89.3 µs	80.7 µs	+10.66%

Tip

Investigate this regression by commenting @codspeedbot fix this regression on this PR, or directly use the CodSpeed MCP with your agent.

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_{Comparing HarukiMoriarty:nemo/geo-point (ec95875) with develop (3d7bbfb)}