Merge commit 'd803bfe2b1fe7f5e219e50ac20d6801a0a58ac75' as 'vendor/ruvector'

vendor/ruvector/crates/ruvector-graph/benches/cypher_parser.rs

@@ -0,0 +1,58 @@
+use criterion::{black_box, criterion_group, criterion_main, Criterion};
+use ruvector_graph::cypher::parser::parse_cypher;
+
+fn bench_simple_match(c: &mut Criterion) {
+    c.bench_function("parse simple MATCH", |b| {
+        b.iter(|| parse_cypher(black_box("MATCH (n:Person) RETURN n")))
+    });
+}
+
+fn bench_complex_match(c: &mut Criterion) {
+    c.bench_function("parse complex MATCH with WHERE", |b| {
+        b.iter(|| {
+            parse_cypher(black_box(
+                "MATCH (a:Person)-[r:KNOWS]->(b:Person) WHERE a.age > 30 AND b.name = 'Alice' RETURN a.name, b.name, r.since ORDER BY r.since DESC LIMIT 10"
+            ))
+        })
+    });
+}
+
+fn bench_create_query(c: &mut Criterion) {
+    c.bench_function("parse CREATE query", |b| {
+        b.iter(|| {
+            parse_cypher(black_box(
+                "CREATE (n:Person {name: 'Bob', age: 30, email: 'bob@example.com'})",
+            ))
+        })
+    });
+}
+
+fn bench_hyperedge_query(c: &mut Criterion) {
+    c.bench_function("parse hyperedge query", |b| {
+        b.iter(|| {
+            parse_cypher(black_box(
+                "MATCH (person)-[r:TRANSACTION]->(acc1:Account, acc2:Account, merchant:Merchant) WHERE r.amount > 1000 RETURN person, r, acc1, acc2, merchant"
+            ))
+        })
+    });
+}
+
+fn bench_aggregation_query(c: &mut Criterion) {
+    c.bench_function("parse aggregation query", |b| {
+        b.iter(|| {
+            parse_cypher(black_box(
+                "MATCH (n:Person) RETURN COUNT(n), AVG(n.age), MAX(n.salary), COLLECT(n.name)",
+            ))
+        })
+    });
+}
+
+criterion_group!(
+    benches,
+    bench_simple_match,
+    bench_complex_match,
+    bench_create_query,
+    bench_hyperedge_query,
+    bench_aggregation_query
+);
+criterion_main!(benches);

vendor/ruvector/crates/ruvector-graph/benches/distributed_query.rs

@@ -0,0 +1,11 @@
+// Placeholder benchmark for distributed query
+// TODO: Implement comprehensive benchmarks
+
+use criterion::{black_box, criterion_group, criterion_main, Criterion};
+
+fn distributed_query_benchmark(c: &mut Criterion) {
+    c.bench_function("placeholder", |b| b.iter(|| black_box(42)));
+}
+
+criterion_group!(benches, distributed_query_benchmark);
+criterion_main!(benches);

vendor/ruvector/crates/ruvector-graph/benches/graph_bench.rs

@@ -0,0 +1,324 @@
+use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
+use ruvector_graph::types::{EdgeId, NodeId, Properties, PropertyValue};
+use ruvector_graph::{Edge, GraphDB, Node};
+use std::collections::HashMap;
+use std::sync::Arc;
+use std::time::Duration;
+
+/// Helper to create test graph
+fn create_test_graph() -> GraphDB {
+    GraphDB::new()
+}
+
+/// Benchmark: Single node insertion
+fn bench_node_insertion_single(c: &mut Criterion) {
+    let mut group = c.benchmark_group("node_insertion_single");
+
+    for size in [1, 10, 100, 1000].iter() {
+        group.throughput(Throughput::Elements(*size as u64));
+        group.bench_with_input(BenchmarkId::from_parameter(size), size, |b, &size| {
+            b.iter(|| {
+                let graph = create_test_graph();
+                for i in 0..size {
+                    let mut props = Properties::new();
+                    props.insert(
+                        "name".to_string(),
+                        PropertyValue::String(format!("node_{}", i)),
+                    );
+                    props.insert("value".to_string(), PropertyValue::Integer(i as i64));
+
+                    let node_id = NodeId(format!("node_{}", i));
+                    let node = Node::new(node_id, vec!["Person".to_string()], props);
+                    black_box(graph.create_node(node).unwrap());
+                }
+            });
+        });
+    }
+
+    group.finish();
+}
+
+/// Benchmark: Batch node insertion
+fn bench_node_insertion_batch(c: &mut Criterion) {
+    let mut group = c.benchmark_group("node_insertion_batch");
+
+    for batch_size in [100, 1000, 10000].iter() {
+        group.throughput(Throughput::Elements(*batch_size as u64));
+        group.bench_with_input(
+            BenchmarkId::from_parameter(batch_size),
+            batch_size,
+            |b, &batch_size| {
+                b.iter(|| {
+                    let graph = create_test_graph();
+                    for i in 0..batch_size {
+                        let mut props = Properties::new();
+                        props.insert(
+                            "name".to_string(),
+                            PropertyValue::String(format!("node_{}", i)),
+                        );
+                        props.insert("value".to_string(), PropertyValue::Integer(i as i64));
+
+                        let node_id = NodeId(format!("batch_node_{}", i));
+                        let node = Node::new(node_id, vec!["Person".to_string()], props);
+                        black_box(graph.create_node(node).unwrap());
+                    }
+                });
+            },
+        );
+    }
+
+    group.finish();
+}
+
+/// Benchmark: Bulk node insertion (optimized path)
+fn bench_node_insertion_bulk(c: &mut Criterion) {
+    let mut group = c.benchmark_group("node_insertion_bulk");
+    group.sample_size(10); // Reduce samples for large operations
+
+    for bulk_size in [10000, 100000].iter() {
+        group.throughput(Throughput::Elements(*bulk_size as u64));
+        group.bench_with_input(
+            BenchmarkId::from_parameter(bulk_size),
+            bulk_size,
+            |b, &bulk_size| {
+                b.iter(|| {
+                    let graph = create_test_graph();
+                    for i in 0..bulk_size {
+                        let mut props = Properties::new();
+                        props.insert("id".to_string(), PropertyValue::Integer(i as i64));
+                        props.insert(
+                            "name".to_string(),
+                            PropertyValue::String(format!("user_{}", i)),
+                        );
+
+                        let node_id = NodeId(format!("bulk_user_{}", i));
+                        let node = Node::new(node_id, vec!["User".to_string()], props);
+                        black_box(graph.create_node(node).unwrap());
+                    }
+                });
+            },
+        );
+    }
+
+    group.finish();
+}
+
+/// Benchmark: Edge creation
+fn bench_edge_creation(c: &mut Criterion) {
+    let mut group = c.benchmark_group("edge_creation");
+
+    // Setup: Create nodes once
+    let graph = Arc::new(create_test_graph());
+    let mut node_ids = Vec::new();
+    for i in 0..1000 {
+        let mut props = Properties::new();
+        props.insert("id".to_string(), PropertyValue::Integer(i as i64));
+        let node_id = NodeId(format!("edge_test_node_{}", i));
+        let node = Node::new(node_id.clone(), vec!["Person".to_string()], props);
+        graph.create_node(node).unwrap();
+        node_ids.push(node_id);
+    }
+
+    for num_edges in [100, 1000].iter() {
+        group.throughput(Throughput::Elements(*num_edges as u64));
+        group.bench_with_input(
+            BenchmarkId::from_parameter(num_edges),
+            num_edges,
+            |b, &num_edges| {
+                let graph = graph.clone();
+                let node_ids = node_ids.clone();
+                b.iter(|| {
+                    for i in 0..num_edges {
+                        let from = &node_ids[i % node_ids.len()];
+                        let to = &node_ids[(i + 1) % node_ids.len()];
+
+                        let mut props = Properties::new();
+                        props.insert("weight".to_string(), PropertyValue::Float(i as f64));
+
+                        let edge_id = EdgeId(format!("edge_{}", i));
+                        let edge = Edge::new(
+                            edge_id,
+                            from.clone(),
+                            to.clone(),
+                            "KNOWS".to_string(),
+                            props,
+                        );
+                        black_box(graph.create_edge(edge).unwrap());
+                    }
+                });
+            },
+        );
+    }
+
+    group.finish();
+}
+
+/// Benchmark: Simple node lookup by ID
+fn bench_query_node_lookup(c: &mut Criterion) {
+    let mut group = c.benchmark_group("query_node_lookup");
+
+    // Setup: Create 10k nodes (reduced for faster benchmark)
+    let graph = Arc::new(create_test_graph());
+    let mut node_ids = Vec::new();
+    for i in 0..10000 {
+        let mut props = Properties::new();
+        props.insert("id".to_string(), PropertyValue::Integer(i as i64));
+        let node_id = NodeId(format!("lookup_node_{}", i));
+        let node = Node::new(node_id.clone(), vec!["Person".to_string()], props);
+        graph.create_node(node).unwrap();
+        node_ids.push(node_id);
+    }
+
+    group.bench_function("lookup_by_id", |b| {
+        let graph = graph.clone();
+        let node_ids = node_ids.clone();
+        b.iter(|| {
+            let id = &node_ids[black_box(1234 % node_ids.len())];
+            black_box(graph.get_node(id).unwrap());
+        });
+    });
+
+    group.finish();
+}
+
+/// Benchmark: Edge lookup
+fn bench_query_edge_lookup(c: &mut Criterion) {
+    let mut group = c.benchmark_group("query_edge_lookup");
+
+    // Setup: Create nodes and edges
+    let graph = Arc::new(create_test_graph());
+    let mut node_ids = Vec::new();
+    let mut edge_ids = Vec::new();
+
+    // Create 100 nodes
+    for i in 0..100 {
+        let mut props = Properties::new();
+        props.insert("id".to_string(), PropertyValue::Integer(i as i64));
+        let node_id = NodeId(format!("trav_node_{}", i));
+        let node = Node::new(node_id.clone(), vec!["Person".to_string()], props);
+        graph.create_node(node).unwrap();
+        node_ids.push(node_id);
+    }
+
+    // Create edges (each node has ~5 outgoing edges)
+    for i in 0..node_ids.len() {
+        for j in 0..5 {
+            let to_idx = (i + j + 1) % node_ids.len();
+            let edge_id = EdgeId(format!("trav_edge_{}_{}", i, j));
+            let edge = Edge::new(
+                edge_id.clone(),
+                node_ids[i].clone(),
+                node_ids[to_idx].clone(),
+                "KNOWS".to_string(),
+                Properties::new(),
+            );
+            graph.create_edge(edge).unwrap();
+            edge_ids.push(edge_id);
+        }
+    }
+
+    group.bench_function("edge_by_id", |b| {
+        let graph = graph.clone();
+        let edge_ids = edge_ids.clone();
+        b.iter(|| {
+            let id = &edge_ids[black_box(10 % edge_ids.len())];
+            black_box(graph.get_edge(id).unwrap());
+        });
+    });
+
+    group.finish();
+}
+
+/// Benchmark: Get nodes by label
+fn bench_query_get_by_label(c: &mut Criterion) {
+    let mut group = c.benchmark_group("query_get_by_label");
+
+    let graph = Arc::new(create_test_graph());
+
+    // Create diverse nodes with different labels
+    for i in 0..1000 {
+        let mut props = Properties::new();
+        props.insert("id".to_string(), PropertyValue::Integer(i as i64));
+        let node_id = NodeId(format!("label_node_{}", i));
+
+        let label = if i % 3 == 0 {
+            "Person"
+        } else if i % 3 == 1 {
+            "Organization"
+        } else {
+            "Location"
+        };
+
+        let node = Node::new(node_id, vec![label.to_string()], props);
+        graph.create_node(node).unwrap();
+    }
+
+    group.bench_function("get_persons", |b| {
+        let graph = graph.clone();
+        b.iter(|| {
+            let nodes = graph.get_nodes_by_label("Person");
+            black_box(nodes.len());
+        });
+    });
+
+    group.finish();
+}
+
+/// Benchmark: Memory usage tracking
+fn bench_memory_usage(c: &mut Criterion) {
+    let mut group = c.benchmark_group("memory_usage");
+    group.sample_size(10);
+
+    for num_nodes in [1000, 10000].iter() {
+        group.throughput(Throughput::Elements(*num_nodes as u64));
+        group.bench_with_input(
+            BenchmarkId::from_parameter(num_nodes),
+            num_nodes,
+            |b, &num_nodes| {
+                b.iter_custom(|iters| {
+                    let mut total_duration = Duration::ZERO;
+
+                    for _ in 0..iters {
+                        let graph = create_test_graph();
+
+                        let start = std::time::Instant::now();
+                        for i in 0..*num_nodes {
+                            let mut props = Properties::new();
+                            props.insert("id".to_string(), PropertyValue::Integer(i as i64));
+                            props.insert(
+                                "name".to_string(),
+                                PropertyValue::String(format!("node_{}", i)),
+                            );
+
+                            let node_id = NodeId(format!("mem_node_{}", i));
+                            let node = Node::new(node_id, vec!["TestNode".to_string()], props);
+                            graph.create_node(node).unwrap();
+                        }
+                        total_duration += start.elapsed();
+
+                        // Force drop to measure cleanup
+                        drop(graph);
+                    }
+
+                    total_duration
+                });
+            },
+        );
+    }
+
+    group.finish();
+}
+
+criterion_group!(
+    benches,
+    bench_node_insertion_single,
+    bench_node_insertion_batch,
+    bench_node_insertion_bulk,
+    bench_edge_creation,
+    bench_query_node_lookup,
+    bench_query_edge_lookup,
+    bench_query_get_by_label,
+    bench_memory_usage
+);
+
+criterion_main!(benches);

vendor/ruvector/crates/ruvector-graph/benches/graph_traversal.rs

@@ -0,0 +1,11 @@
+// Placeholder benchmark for graph traversal
+// TODO: Implement comprehensive benchmarks
+
+use criterion::{black_box, criterion_group, criterion_main, Criterion};
+
+fn graph_traversal_benchmark(c: &mut Criterion) {
+    c.bench_function("placeholder", |b| b.iter(|| black_box(42)));
+}
+
+criterion_group!(benches, graph_traversal_benchmark);
+criterion_main!(benches);

vendor/ruvector/crates/ruvector-graph/benches/hybrid_vector_graph.rs

@@ -0,0 +1,11 @@
+// Placeholder benchmark for hybrid vector graph
+// TODO: Implement comprehensive benchmarks
+
+use criterion::{black_box, criterion_group, criterion_main, Criterion};
+
+fn hybrid_vector_graph_benchmark(c: &mut Criterion) {
+    c.bench_function("placeholder", |b| b.iter(|| black_box(42)));
+}
+
+criterion_group!(benches, hybrid_vector_graph_benchmark);
+criterion_main!(benches);

vendor/ruvector/crates/ruvector-graph/benches/new_capabilities_bench.rs

@@ -0,0 +1,251 @@
+//! Benchmarks for new capabilities
+//!
+//! Run with: cargo bench --package ruvector-graph --bench new_capabilities_bench
+
+use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
+use ruvector_graph::cypher::parser::parse_cypher;
+use ruvector_graph::hybrid::semantic_search::{SemanticSearch, SemanticSearchConfig};
+use ruvector_graph::hybrid::vector_index::{EmbeddingConfig, HybridIndex, VectorIndexType};
+
+// ============================================================================
+// Parser Benchmarks
+// ============================================================================
+
+fn bench_simple_match(c: &mut Criterion) {
+    let query = "MATCH (n:Person) RETURN n";
+
+    c.bench_function("parser/simple_match", |b| {
+        b.iter(|| parse_cypher(black_box(query)))
+    });
+}
+
+fn bench_relationship_match(c: &mut Criterion) {
+    let query = "MATCH (a:Person)-[r:KNOWS]->(b:Person) RETURN a, r, b";
+
+    c.bench_function("parser/relationship_match", |b| {
+        b.iter(|| parse_cypher(black_box(query)))
+    });
+}
+
+fn bench_chained_relationship(c: &mut Criterion) {
+    let mut group = c.benchmark_group("parser/chained_relationships");
+
+    // 2-hop chain
+    let query_2hop = "MATCH (a)-[r]->(b)-[s]->(c) RETURN a, c";
+    group.bench_function("2_hop", |b| b.iter(|| parse_cypher(black_box(query_2hop))));
+
+    // 3-hop chain
+    let query_3hop = "MATCH (a)-[r]->(b)-[s]->(c)-[t]->(d) RETURN a, d";
+    group.bench_function("3_hop", |b| b.iter(|| parse_cypher(black_box(query_3hop))));
+
+    // 4-hop chain
+    let query_4hop = "MATCH (a)-[r]->(b)-[s]->(c)-[t]->(d)-[u]->(e) RETURN a, e";
+    group.bench_function("4_hop", |b| b.iter(|| parse_cypher(black_box(query_4hop))));
+
+    group.finish();
+}
+
+fn bench_mixed_direction_chain(c: &mut Criterion) {
+    let query = "MATCH (a:Person)-[r:KNOWS]->(b:Person)<-[s:MANAGES]-(c:Manager) RETURN a, b, c";
+
+    c.bench_function("parser/mixed_direction_chain", |b| {
+        b.iter(|| parse_cypher(black_box(query)))
+    });
+}
+
+fn bench_map_literal(c: &mut Criterion) {
+    let mut group = c.benchmark_group("parser/map_literal");
+
+    // Empty map
+    let query_empty = "MATCH (n) RETURN {}";
+    group.bench_function("empty", |b| b.iter(|| parse_cypher(black_box(query_empty))));
+
+    // Small map (2 keys)
+    let query_small = "MATCH (n) RETURN {name: n.name, age: n.age}";
+    group.bench_function("2_keys", |b| {
+        b.iter(|| parse_cypher(black_box(query_small)))
+    });
+
+    // Medium map (5 keys)
+    let query_medium = "MATCH (n) RETURN {a: n.a, b: n.b, c: n.c, d: n.d, e: n.e}";
+    group.bench_function("5_keys", |b| {
+        b.iter(|| parse_cypher(black_box(query_medium)))
+    });
+
+    // Large map (10 keys)
+    let query_large = "MATCH (n) RETURN {a: n.a, b: n.b, c: n.c, d: n.d, e: n.e, f: n.f, g: n.g, h: n.h, i: n.i, j: n.j}";
+    group.bench_function("10_keys", |b| {
+        b.iter(|| parse_cypher(black_box(query_large)))
+    });
+
+    group.finish();
+}
+
+fn bench_remove_statement(c: &mut Criterion) {
+    let mut group = c.benchmark_group("parser/remove");
+
+    // Remove property
+    let query_prop = "MATCH (n:Person) REMOVE n.age RETURN n";
+    group.bench_function("property", |b| {
+        b.iter(|| parse_cypher(black_box(query_prop)))
+    });
+
+    // Remove single label
+    let query_label = "MATCH (n:Person:Employee) REMOVE n:Employee RETURN n";
+    group.bench_function("single_label", |b| {
+        b.iter(|| parse_cypher(black_box(query_label)))
+    });
+
+    // Remove multiple labels
+    let query_multi = "MATCH (n:A:B:C:D) REMOVE n:B:C:D RETURN n";
+    group.bench_function("multi_label", |b| {
+        b.iter(|| parse_cypher(black_box(query_multi)))
+    });
+
+    group.finish();
+}
+
+fn bench_complex_query(c: &mut Criterion) {
+    let query = r#"
+        MATCH (p:Person)-[r:WORKS_AT]->(c:Company)<-[h:HEADQUARTERED]-(l:Location)
+        WHERE p.age > 30 AND c.revenue > 1000000
+        RETURN {
+            person: p.name,
+            company: c.name,
+            location: l.city
+        }
+        ORDER BY p.age DESC
+        LIMIT 10
+    "#;
+
+    c.bench_function("parser/complex_query", |b| {
+        b.iter(|| parse_cypher(black_box(query)))
+    });
+}
+
+// ============================================================================
+// Semantic Search Benchmarks
+// ============================================================================
+
+fn setup_semantic_search(num_vectors: usize, dimensions: usize) -> SemanticSearch {
+    let config = EmbeddingConfig {
+        dimensions,
+        ..Default::default()
+    };
+    let index = HybridIndex::new(config).unwrap();
+    index.initialize_index(VectorIndexType::Node).unwrap();
+
+    // Add test embeddings
+    for i in 0..num_vectors {
+        let mut embedding = vec![0.0f32; dimensions];
+        // Create varied embeddings
+        embedding[i % dimensions] = 1.0;
+        embedding[(i + 1) % dimensions] = 0.5;
+
+        index
+            .add_node_embedding(format!("node_{}", i), embedding)
+            .unwrap();
+    }
+
+    SemanticSearch::new(index, SemanticSearchConfig::default())
+}
+
+fn bench_semantic_search_small(c: &mut Criterion) {
+    let search = setup_semantic_search(100, 128);
+    let query: Vec<f32> = (0..128).map(|i| if i == 0 { 1.0 } else { 0.0 }).collect();
+
+    c.bench_function("semantic_search/100_vectors_128d", |b| {
+        b.iter(|| search.find_similar_nodes(black_box(&query), 10))
+    });
+}
+
+fn bench_semantic_search_medium(c: &mut Criterion) {
+    let search = setup_semantic_search(1000, 128);
+    let query: Vec<f32> = (0..128).map(|i| if i == 0 { 1.0 } else { 0.0 }).collect();
+
+    c.bench_function("semantic_search/1000_vectors_128d", |b| {
+        b.iter(|| search.find_similar_nodes(black_box(&query), 10))
+    });
+}
+
+fn bench_semantic_search_dimensions(c: &mut Criterion) {
+    let mut group = c.benchmark_group("semantic_search/dimensions");
+
+    for dim in [64, 128, 256, 384, 512].iter() {
+        let search = setup_semantic_search(500, *dim);
+        let query: Vec<f32> = (0..*dim).map(|i| if i == 0 { 1.0 } else { 0.0 }).collect();
+
+        group.bench_with_input(BenchmarkId::from_parameter(dim), dim, |b, _| {
+            b.iter(|| search.find_similar_nodes(black_box(&query), 10))
+        });
+    }
+
+    group.finish();
+}
+
+fn bench_semantic_search_top_k(c: &mut Criterion) {
+    let search = setup_semantic_search(1000, 128);
+    let query: Vec<f32> = (0..128).map(|i| if i == 0 { 1.0 } else { 0.0 }).collect();
+
+    let mut group = c.benchmark_group("semantic_search/top_k");
+
+    for k in [1, 5, 10, 25, 50, 100].iter() {
+        group.bench_with_input(BenchmarkId::from_parameter(k), k, |b, &k| {
+            b.iter(|| search.find_similar_nodes(black_box(&query), k))
+        });
+    }
+
+    group.finish();
+}
+
+// ============================================================================
+// Distance Conversion Benchmark (the fix we made)
+// ============================================================================
+
+fn bench_distance_conversion(c: &mut Criterion) {
+    let distances: Vec<f32> = (0..10000).map(|i| (i as f32) / 10000.0).collect();
+
+    c.bench_function("semantic_search/distance_conversion_10k", |b| {
+        b.iter(|| {
+            let _: Vec<f32> = distances.iter().map(|d| 1.0 - d).collect();
+        })
+    });
+}
+
+fn bench_similarity_filtering(c: &mut Criterion) {
+    let distances: Vec<f32> = (0..10000).map(|i| (i as f32) / 10000.0).collect();
+    let min_similarity = 0.7f32;
+
+    c.bench_function("semantic_search/similarity_filter_10k", |b| {
+        b.iter(|| {
+            let _: Vec<f32> = distances
+                .iter()
+                .map(|d| 1.0 - d)
+                .filter(|s| *s >= min_similarity)
+                .collect();
+        })
+    });
+}
+
+criterion_group!(
+    parser_benches,
+    bench_simple_match,
+    bench_relationship_match,
+    bench_chained_relationship,
+    bench_mixed_direction_chain,
+    bench_map_literal,
+    bench_remove_statement,
+    bench_complex_query,
+);
+
+criterion_group!(
+    semantic_search_benches,
+    bench_semantic_search_small,
+    bench_semantic_search_medium,
+    bench_semantic_search_dimensions,
+    bench_semantic_search_top_k,
+    bench_distance_conversion,
+    bench_similarity_filtering,
+);
+
+criterion_main!(parser_benches, semantic_search_benches);

vendor/ruvector/crates/ruvector-graph/benches/query_execution.rs

@@ -0,0 +1,11 @@
+// Placeholder benchmark for query execution
+// TODO: Implement comprehensive benchmarks
+
+use criterion::{black_box, criterion_group, criterion_main, Criterion};
+
+fn query_execution_benchmark(c: &mut Criterion) {
+    c.bench_function("placeholder", |b| b.iter(|| black_box(42)));
+}
+
+criterion_group!(benches, query_execution_benchmark);
+criterion_main!(benches);

vendor/ruvector/crates/ruvector-graph/benches/simd_operations.rs

@@ -0,0 +1,11 @@
+// Placeholder benchmark for SIMD operations
+// TODO: Implement comprehensive benchmarks
+
+use criterion::{black_box, criterion_group, criterion_main, Criterion};
+
+fn simd_operations_benchmark(c: &mut Criterion) {
+    c.bench_function("placeholder", |b| b.iter(|| black_box(42)));
+}
+
+criterion_group!(benches, simd_operations_benchmark);
+criterion_main!(benches);