Execute spatial distance with RowFn

[connortsui20]

Rationale for this change

Moves spatial distance to the shared row executor. Each geometry column decodes once per batch, and a constant operand remains one decoded geometry.

• Progress towards: Epic: Row-oriented scalar functions #9128

What changes are included in this PR?

Adds the crate-private GeometryRow input element and expresses distance as a two-row kernel. Tests cover both constant positions, nullable inputs, mixed geometry types, and exact distance behavior.

Rust 1.97.1 one-CGU fat-LTO measurements keep the ordinary distance cases within 2.7% of develop; the nullable column-by-constant case improves by 13.9%.

What APIs are changed? Are there any user-facing changes?

There are no public API or behavior changes. SpatialDistance implements RowFn and receives the standard scalar-function vtable automatically.

[codspeed-hq]

Merging this PR will improve performance by 17.87%

⚡ 3 improved benchmarks
✅ 2016 untouched benchmarks
⏩ 89 skipped benchmarks¹

Performance Changes

	Mode	Benchmark	BASE	HEAD	Efficiency
⚡	Simulation	cold_misaligned[(64, 256)]	5.4 ms	4.4 ms	+22.48%
⚡	Simulation	slice_dict_tight_loop[10000]	803.3 µs	683.9 µs	+17.45%
⚡	Simulation	nullable_point_column_x_constant_point	762.7 µs	670 µs	+13.84%

Tip

Curious why this is faster? Comment @codspeedbot explain why this is faster on this PR, or directly use the CodSpeed MCP with your agent.

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_{Comparing ct/row-fn-spatial-distance (bba41db) with ct/row-fn-tensor-products (cb67153)²}

Footnotes

1. 89 benchmarks were skipped, so the baseline results were used instead. If they were deleted from the codebase, click here and archive them to remove them from the performance reports. ↩

2. No successful run was found on ct/row-fn-tensor-products (32bd4da) during the generation of this report, so 3d6daed was used instead as the comparison base. There might be some changes unrelated to this pull request in this report. ↩

[connortsui20]

Here are the local spatial-distance benchmark results from the final Rust 1.97.1 run.

The comparison used a develop baseline with benchmark-only backfills (1edd0fca) and the full RowFn stack (8ca9fc73). Later stack layers do not change spatial distance source, but unrelated code-placement effects can still affect these binaries.

The machine was an AMD Ryzen 9 7950X running Linux. The build used rustc 1.97.1, LLVM 22.1.6, one CGU, fat LTO, and -C target-cpu=native. Each target used two warm runs and seven alternating measured pairs. Each process used 100 samples with a 0.25–0.5 second measurement window on CPU 4.

Negative changes are faster. The values are medians across the seven paired runs.

The three ordinary distance cases remain within 2.65%. The nullable column-by-constant case improves by 13.85%.

All spatial-distance results: 4 cases

Benchmark	Baseline	RowFn stack	Change
point_column_x_constant_point	13.670 µs	14.080 µs	+2.65%
polygon_column_x_constant_polygon	33.550 µs	34.180 µs	+1.70%
point_column_x_point_column	17.140 µs	17.060 µs	+0.47%
nullable_point_column_x_constant_point	18.190 µs	15.680 µs	-13.85%