Squashed 'vendor/ruvector/' content from commit b64c2172

git-subtree-dir: vendor/ruvector
git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900

crates/ruvector-router-core/benches/vector_search.rs

@@ -0,0 +1,114 @@
+use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
+use router_core::{DistanceMetric, SearchQuery, VectorDB, VectorEntry};
+use std::collections::HashMap;
+use tempfile::tempdir;
+
+fn bench_insert(c: &mut Criterion) {
+    let dir = tempdir().unwrap();
+    let path = dir.path().join("bench.db");
+
+    let db = VectorDB::builder()
+        .dimensions(384)
+        .storage_path(&path)
+        .build()
+        .unwrap();
+
+    let mut group = c.benchmark_group("insert");
+
+    for size in [10, 100, 1000].iter() {
+        group.bench_with_input(BenchmarkId::from_parameter(size), size, |b, &size| {
+            let entries: Vec<VectorEntry> = (0..size)
+                .map(|i| VectorEntry {
+                    id: format!("vec_{}", i),
+                    vector: vec![0.1; 384],
+                    metadata: HashMap::new(),
+                    timestamp: 0,
+                })
+                .collect();
+
+            b.iter(|| {
+                for entry in &entries {
+                    db.insert(entry.clone()).unwrap();
+                }
+            });
+        });
+    }
+
+    group.finish();
+}
+
+fn bench_search(c: &mut Criterion) {
+    let dir = tempdir().unwrap();
+    let path = dir.path().join("bench.db");
+
+    let db = VectorDB::builder()
+        .dimensions(384)
+        .storage_path(&path)
+        .build()
+        .unwrap();
+
+    // Insert test vectors
+    let entries: Vec<VectorEntry> = (0..1000)
+        .map(|i| VectorEntry {
+            id: format!("vec_{}", i),
+            vector: vec![i as f32 * 0.001; 384],
+            metadata: HashMap::new(),
+            timestamp: 0,
+        })
+        .collect();
+
+    db.insert_batch(entries).unwrap();
+
+    let mut group = c.benchmark_group("search");
+
+    for k in [1, 10, 100].iter() {
+        group.bench_with_input(BenchmarkId::from_parameter(k), k, |b, &k| {
+            let query = SearchQuery {
+                vector: vec![0.5; 384],
+                k,
+                filters: None,
+                threshold: None,
+                ef_search: None,
+            };
+
+            b.iter(|| {
+                black_box(db.search(query.clone()).unwrap());
+            });
+        });
+    }
+
+    group.finish();
+}
+
+fn bench_distance_calculations(c: &mut Criterion) {
+    use router_core::distance::*;
+
+    let a = vec![0.5; 384];
+    let b = vec![0.6; 384];
+
+    c.bench_function("euclidean_distance", |bencher| {
+        bencher.iter(|| {
+            black_box(euclidean_distance(black_box(&a), black_box(&b)));
+        });
+    });
+
+    c.bench_function("cosine_similarity", |bencher| {
+        bencher.iter(|| {
+            black_box(cosine_similarity(black_box(&a), black_box(&b)));
+        });
+    });
+
+    c.bench_function("dot_product", |bencher| {
+        bencher.iter(|| {
+            black_box(dot_product(black_box(&a), black_box(&b)));
+        });
+    });
+}
+
+criterion_group!(
+    benches,
+    bench_insert,
+    bench_search,
+    bench_distance_calculations
+);
+criterion_main!(benches);