PS-11167: Add DISTANCE() for VECTOR data type

[catalinbp]

Implement SQL DISTANCE(vector, vector, metric) and the VECTOR_DISTANCE() synonym for vector similarity queries. Supported metrics: EUCLIDEAN (L2), MANHATTAN (L1), COSINE, and DOT.

Core library (vector-common/vector_distance.*):

• Runtime SIMD dispatch across Scalar, SSE4.2/NEON, AVX2, AVX-512F, and SVE2 tiers; per-kernel target attributes, no global -march=native
• Dim-aware wide/narrow dispatch (dims >= 16 use widest tier; smaller vectors use 128-bit tier to avoid AVX setup overhead)
• Unaligned load intrinsics throughout: VECTOR data may be misaligned (e.g. SUBSTR blobs); on modern CPUs unaligned and aligned loads have identical throughput when data is aligned; aligned loads would fault on misaligned inputs without a performance benefit. Loads that span a 64-byte cache-line boundary may still be slower (two line fetches); that depends on runtime address, not on loadu vs load, and is not avoided by switching to aligned intrinsics
• Float32 SIMD accumulation with double-precision horizontal sum and scalar tail: preserves correctness for large dimensions and extreme values (e.g. 2e38 Euclidean distance) without sacrificing SIMD width
• Manhattan (L1): sum of absolute differences;