ruvector/examples/graph/cypher_queries.rs
Claude f3f7a95752 feat: Add Neo4j-compatible hypergraph database package (ruvector-graph)
Major new package implementing a distributed hypergraph database with:

## Core Components (crates/ruvector-graph/)
- Cypher-compatible query parser with lexer, AST, optimizer
- Query execution engine with SIMD optimization and parallel execution
- ACID transaction support with MVCC isolation levels
- Distributed consensus and federation layer
- Vector-graph hybrid queries for AI/RAG workloads
- Performance optimizations (100x faster than Neo4j target)

## Bindings
- WASM bindings (crates/ruvector-graph-wasm/)
- NAPI-RS Node.js bindings (crates/ruvector-graph-node/)
- NPM packages for both targets

## CLI Integration
- 8 new graph commands: create, query, shell, import, export, info, benchmark, serve

## CI/CD
- Updated build-native.yml for graph packages
- New graph-ci.yml for testing and benchmarks
- New graph-release.yml for automated publishing

## Data Generation
- OpenRouter/Kimi K2 integration (packages/graph-data-generator/)
- Agentic-synth benchmark suite integration

## Tests & Benchmarks
- 11 test files covering all components
- Criterion benchmarks for performance validation
- Neo4j compatibility test suite

## Architecture Highlights
- CSR graph layout for cache-friendly access
- SIMD-vectorized query operators
- Roaring bitmaps for label indexes
- Bloom filters for fast negative lookups
- Adaptive radix tree for property indexes

Note: This is a comprehensive implementation created by 15 parallel agents.
Some integration fixes may be needed to resolve cross-module dependencies.

Co-authored-by: Claude AI Swarm <swarm@claude.ai>
2025-11-25 23:11:54 +00:00

122 lines
4.1 KiB
Rust

//! Cypher Query Examples
//!
//! This example demonstrates Neo4j-compatible Cypher queries:
//! - CREATE: Creating nodes and relationships
//! - MATCH: Pattern matching
//! - WHERE: Filtering results
//! - RETURN: Projecting results
//! - Aggregations and complex queries
fn main() {
println!("=== RuVector Graph - Cypher Queries ===\n");
// TODO: Once the graph API is exposed, implement:
println!("1. Simple CREATE Query");
// let query = "CREATE (n:Person {name: 'Charlie', age: 28}) RETURN n";
// let result = db.execute_cypher(query)?;
// println!(" Query: {}", query);
// println!(" Result: {:?}", result);
println!("\n2. Pattern Matching");
// let query = r#"
// MATCH (p:Person)
// WHERE p.age > 25
// RETURN p.name, p.age
// ORDER BY p.age DESC
// "#;
// let result = db.execute_cypher(query)?;
// println!(" Query: {}", query);
// println!(" Result: {:?}", result);
println!("\n3. Creating Relationships");
// let query = r#"
// MATCH (a:Person {name: 'Alice'})
// MATCH (b:Person {name: 'Charlie'})
// CREATE (a)-[r:KNOWS {since: 2023}]->(b)
// RETURN r
// "#;
// let result = db.execute_cypher(query)?;
// println!(" Query: {}", query);
// println!(" Result: {:?}", result);
println!("\n4. Traversal Queries");
// let query = r#"
// MATCH (start:Person {name: 'Alice'})-[:KNOWS*1..3]->(end:Person)
// RETURN end.name, length((start)-[:KNOWS*]->(end)) as distance
// ORDER BY distance
// "#;
// let result = db.execute_cypher(query)?;
// println!(" Query: {}", query);
// println!(" Result: {:?}", result);
println!("\n5. Aggregation Queries");
// let query = r#"
// MATCH (p:Person)
// RETURN
// count(p) as total_people,
// avg(p.age) as average_age,
// min(p.age) as youngest,
// max(p.age) as oldest
// "#;
// let result = db.execute_cypher(query)?;
// println!(" Query: {}", query);
// println!(" Result: {:?}", result);
println!("\n6. Shortest Path");
// let query = r#"
// MATCH path = shortestPath(
// (a:Person {name: 'Alice'})-[:KNOWS*]-(b:Person {name: 'Bob'})
// )
// RETURN path, length(path) as distance
// "#;
// let result = db.execute_cypher(query)?;
// println!(" Query: {}", query);
// println!(" Result: {:?}", result);
println!("\n7. Pattern Comprehension");
// let query = r#"
// MATCH (p:Person)
// RETURN p.name, [(p)-[:KNOWS]->(friend) | friend.name] as friends
// "#;
// let result = db.execute_cypher(query)?;
// println!(" Query: {}", query);
// println!(" Result: {:?}", result);
println!("\n8. Complex Multi-Pattern Query");
// let query = r#"
// MATCH (p:Person)-[:LIVES_IN]->(city:City)
// MATCH (p)-[:WORKS_AT]->(company:Company)
// WHERE city.name = 'San Francisco' AND company.industry = 'Tech'
// RETURN p.name, company.name, p.salary
// ORDER BY p.salary DESC
// LIMIT 10
// "#;
// let result = db.execute_cypher(query)?;
// println!(" Query: {}", query);
// println!(" Result: {:?}", result);
println!("\n9. Updating Properties with Cypher");
// let query = r#"
// MATCH (p:Person {name: 'Alice'})
// SET p.age = p.age + 1, p.updated_at = timestamp()
// RETURN p
// "#;
// let result = db.execute_cypher(query)?;
// println!(" Query: {}", query);
// println!(" Result: {:?}", result);
println!("\n10. Conditional Creation (MERGE)");
// let query = r#"
// MERGE (p:Person {email: 'alice@example.com'})
// ON CREATE SET p.name = 'Alice', p.created_at = timestamp()
// ON MATCH SET p.last_seen = timestamp()
// RETURN p
// "#;
// let result = db.execute_cypher(query)?;
// println!(" Query: {}", query);
// println!(" Result: {:?}", result);
println!("\n=== Example Complete ===");
println!("\nNote: This is a template. Actual implementation pending graph API exposure.");
}