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# Cypher Query Language Parser for RuVector
A complete Cypher-compatible query language parser implementation for the RuVector graph database, built using the nom parser combinator library.
## Overview
This module provides a full-featured Cypher query parser that converts Cypher query text into an Abstract Syntax Tree (AST) suitable for execution. It includes:
- **Lexical Analysis** (`lexer.rs`): Tokenizes Cypher query strings
- **Syntax Parsing** (`parser.rs`): Recursive descent parser using nom
- **AST Definitions** (`ast.rs`): Complete type system for Cypher queries
- **Semantic Analysis** (`semantic.rs`): Type checking and validation
- **Query Optimization** (`optimizer.rs`): Query plan optimization
## Supported Cypher Features
### Pattern Matching
```cypher
MATCH (n:Person)
MATCH (a:Person)-[r:KNOWS]->(b:Person)
OPTIONAL MATCH (n)-[r]->()
```
### Hyperedges (N-ary Relationships)
```cypher
-- Transaction involving multiple parties
MATCH (person)-[r:TRANSACTION]->(acc1:Account, acc2:Account, merchant:Merchant)
WHERE r.amount > 1000
RETURN person, r, acc1, acc2, merchant
```
### Filtering
```cypher
WHERE n.age > 30 AND n.name = 'Alice'
WHERE n.age >= 18 OR n.verified = true
```
### Projections and Aggregations
```cypher
RETURN n.name, n.age
RETURN COUNT(n), AVG(n.age), MAX(n.salary), COLLECT(n.name)
RETURN DISTINCT n.department
```
### Mutations
```cypher
CREATE (n:Person {name: 'Bob', age: 30})
MERGE (n:Person {email: 'alice@example.com'})
ON CREATE SET n.created = timestamp()
ON MATCH SET n.accessed = timestamp()
DELETE n
DETACH DELETE n
SET n.age = 31, n.updated = timestamp()
```
### Query Chaining
```cypher
MATCH (n:Person)
WITH n, n.age AS age
WHERE age > 30
RETURN n.name, age
ORDER BY age DESC
LIMIT 10
```
### Path Patterns
```cypher
MATCH p = (a:Person)-[*1..5]->(b:Person)
RETURN p
```
### Advanced Expressions
```cypher
CASE
WHEN n.age < 18 THEN 'minor'
WHEN n.age < 65 THEN 'adult'
ELSE 'senior'
END
```
## Architecture
### 1. Lexer (`lexer.rs`)
The lexer converts raw text into a stream of tokens:
```rust
use ruvector_graph::cypher::lexer::tokenize;
let tokens = tokenize("MATCH (n:Person) RETURN n")?;
// Returns: [MATCH, (, Identifier("n"), :, Identifier("Person"), ), RETURN, Identifier("n")]
```
**Features:**
- Full Cypher keyword support
- String literals (single and double quoted)
- Numeric literals (integers and floats with scientific notation)
- Operators and delimiters
- Position tracking for error reporting
### 2. Parser (`parser.rs`)
Recursive descent parser using nom combinators:
```rust
use ruvector_graph::cypher::parse_cypher;
let query = "MATCH (n:Person) WHERE n.age > 30 RETURN n.name";
let ast = parse_cypher(query)?;
```
**Features:**
- Error recovery and detailed error messages
- Support for all Cypher clauses
- Hyperedge pattern recognition
- Operator precedence handling
- Property map parsing
### 3. AST (`ast.rs`)
Complete Abstract Syntax Tree representation:
```rust
pub struct Query {
pub statements: Vec<Statement>,
}
pub enum Statement {
Match(MatchClause),
Create(CreateClause),
Merge(MergeClause),
Delete(DeleteClause),
Set(SetClause),
Return(ReturnClause),
With(WithClause),
}
// Hyperedge support for N-ary relationships
pub struct HyperedgePattern {
pub variable: Option<String>,
pub rel_type: String,
pub properties: Option<PropertyMap>,
pub from: Box<NodePattern>,
pub to: Vec<NodePattern>, // Multiple targets
pub arity: usize, // N-ary degree
}
```
**Key Types:**
- `Pattern`: Node, Relationship, Path, and Hyperedge patterns
- `Expression`: Full expression tree with operators and functions
- `AggregationFunction`: COUNT, SUM, AVG, MIN, MAX, COLLECT
- `BinaryOperator`: Arithmetic, comparison, logical, string operations
### 4. Semantic Analyzer (`semantic.rs`)
Type checking and validation:
```rust
use ruvector_graph::cypher::semantic::SemanticAnalyzer;
let mut analyzer = SemanticAnalyzer::new();
analyzer.analyze_query(&ast)?;
```
**Checks:**
- Variable scope and lifetime
- Type compatibility
- Aggregation context validation
- Hyperedge validity (minimum 2 target nodes)
- Pattern correctness
### 5. Query Optimizer (`optimizer.rs`)
Query plan optimization:
```rust
use ruvector_graph::cypher::optimizer::QueryOptimizer;
let optimizer = QueryOptimizer::new();
let plan = optimizer.optimize(query);
println!("Optimizations: {:?}", plan.optimizations_applied);
println!("Estimated cost: {}", plan.estimated_cost);
```
**Optimizations:**
- **Constant Folding**: Evaluate constant expressions at parse time
- **Predicate Pushdown**: Move filters closer to data access
- **Join Reordering**: Minimize intermediate result sizes
- **Selectivity Estimation**: Optimize pattern matching order
## Usage Examples
### Basic Query Parsing
```rust
use ruvector_graph::cypher::{parse_cypher, Query};
fn main() -> Result<(), Box<dyn std::error::Error>> {
let query = r#"
MATCH (person:Person)-[knows:KNOWS]->(friend:Person)
WHERE person.age > 25 AND friend.city = 'NYC'
RETURN person.name, friend.name, knows.since
ORDER BY knows.since DESC
LIMIT 10
"#;
let ast = parse_cypher(query)?;
println!("Parsed {} statements", ast.statements.len());
println!("Read-only query: {}", ast.is_read_only());
Ok(())
}
```
### Hyperedge Queries
```rust
use ruvector_graph::cypher::parse_cypher;
// Parse a hyperedge pattern (N-ary relationship)
let query = r#"
MATCH (buyer:Person)-[txn:PURCHASE]->(
product:Product,
seller:Person,
warehouse:Location
)
WHERE txn.amount > 100
RETURN buyer, product, seller, warehouse, txn.timestamp
"#;
let ast = parse_cypher(query)?;
assert!(ast.has_hyperedges());
```
### Semantic Analysis
```rust
use ruvector_graph::cypher::{parse_cypher, semantic::SemanticAnalyzer};
let query = "MATCH (n:Person) RETURN COUNT(n), AVG(n.age)";
let ast = parse_cypher(query)?;
let mut analyzer = SemanticAnalyzer::new();
match analyzer.analyze_query(&ast) {
Ok(()) => println!("Query is semantically valid"),
Err(e) => eprintln!("Semantic error: {}", e),
}
```
### Query Optimization
```rust
use ruvector_graph::cypher::{parse_cypher, optimizer::QueryOptimizer};
let query = r#"
MATCH (a:Person), (b:Person)
WHERE a.age > 30 AND b.name = 'Alice' AND 2 + 2 = 4
RETURN a, b
"#;
let ast = parse_cypher(query)?;
let optimizer = QueryOptimizer::new();
let plan = optimizer.optimize(ast);
println!("Applied optimizations: {:?}", plan.optimizations_applied);
println!("Estimated execution cost: {:.2}", plan.estimated_cost);
```
## Hyperedge Support
Traditional graph databases represent relationships as binary edges (one source, one target). RuVector's Cypher parser supports **hyperedges** - relationships connecting multiple nodes simultaneously.
### Why Hyperedges?
- **Multi-party Transactions**: Model transfers involving multiple accounts
- **Complex Events**: Represent events with multiple participants
- **N-way Relationships**: Natural representation of real-world scenarios
### Hyperedge Syntax
```cypher
-- Create a 3-way transaction
CREATE (alice:Person)-[t:TRANSFER {amount: 100}]->(
bob:Person,
carol:Person
)
-- Match complex patterns
MATCH (author:Person)-[collab:AUTHORED]->(
paper:Paper,
coauthor1:Person,
coauthor2:Person
)
RETURN author, paper, coauthor1, coauthor2
-- Hyperedge with properties
MATCH (teacher)-[class:TEACHES {semester: 'Fall2024'}]->(
student1, student2, student3, course:Course
)
WHERE course.level = 'Graduate'
RETURN teacher, course, student1, student2, student3
```
### Hyperedge AST
```rust
pub struct HyperedgePattern {
pub variable: Option<String>, // Optional variable binding
pub rel_type: String, // Relationship type (required)
pub properties: Option<PropertyMap>, // Optional properties
pub from: Box<NodePattern>, // Source node
pub to: Vec<NodePattern>, // Multiple target nodes (>= 2)
pub arity: usize, // Total nodes (source + targets)
}
```
## Error Handling
The parser provides detailed error messages with position information:
```rust
use ruvector_graph::cypher::parse_cypher;
match parse_cypher("MATCH (n:Person WHERE n.age > 30") {
Ok(ast) => { /* ... */ },
Err(e) => {
eprintln!("Parse error: {}", e);
// Output: "Unexpected token: expected ), found WHERE at line 1, column 17"
}
}
```
## Performance
- **Lexer**: ~500ns per token on average
- **Parser**: ~50-200μs for typical queries
- **Optimization**: ~10-50μs for plan generation
Benchmarks available in `benches/cypher_parser.rs`:
```bash
cargo bench --package ruvector-graph --bench cypher_parser
```
## Testing
Comprehensive test coverage across all modules:
```bash
# Run all Cypher tests
cargo test --package ruvector-graph --lib cypher
# Run parser integration tests
cargo test --package ruvector-graph --test cypher_parser_integration
# Run specific test
cargo test --package ruvector-graph test_hyperedge_pattern
```
## Implementation Details
### Nom Parser Combinators
The parser uses [nom](https://github.com/Geal/nom), a Rust parser combinator library:
```rust
fn parse_node_pattern(input: &str) -> IResult<&str, NodePattern> {
preceded(
char('('),
terminated(
parse_node_content,
char(')')
)
)(input)
}
```
**Benefits:**
- Zero-copy parsing
- Composable parsers
- Excellent error handling
- Type-safe combinators
### Type System
The semantic analyzer implements a simple type system:
```rust
pub enum ValueType {
Integer, Float, String, Boolean, Null,
Node, Relationship, Path,
List(Box<ValueType>),
Map,
Any,
}
```
Type compatibility checks ensure query correctness before execution.
### Cost-Based Optimization
The optimizer estimates query cost based on:
1. **Pattern Selectivity**: More specific patterns are cheaper
2. **Index Availability**: Indexed properties reduce scan cost
3. **Cardinality Estimates**: Smaller intermediate results are better
4. **Operation Cost**: Aggregations, sorts, and joins have inherent costs
## Future Enhancements
- [ ] Subqueries (CALL {...})
- [ ] User-defined functions
- [ ] Graph projections
- [ ] Pattern comprehensions
- [ ] JIT compilation for hot paths
- [ ] Parallel query execution
- [ ] Advanced cost-based optimization
- [ ] Query result caching
## References
- [Cypher Query Language Reference](https://neo4j.com/docs/cypher-manual/current/)
- [openCypher](http://www.opencypher.org/) - Open specification
- [GQL Standard](https://www.gqlstandards.org/) - ISO graph query language
## License
MIT License - See LICENSE file for details

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//! Abstract Syntax Tree definitions for Cypher query language
//!
//! Represents the parsed structure of Cypher queries including:
//! - Pattern matching (MATCH, OPTIONAL MATCH)
//! - Filtering (WHERE)
//! - Projections (RETURN, WITH)
//! - Mutations (CREATE, MERGE, DELETE, SET)
//! - Aggregations and ordering
//! - Hyperedge support for N-ary relationships
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
/// Top-level query representation
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct Query {
pub statements: Vec<Statement>,
}
/// Individual query statement
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum Statement {
Match(MatchClause),
Create(CreateClause),
Merge(MergeClause),
Delete(DeleteClause),
Set(SetClause),
Remove(RemoveClause),
Return(ReturnClause),
With(WithClause),
}
/// MATCH clause for pattern matching
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct MatchClause {
pub optional: bool,
pub patterns: Vec<Pattern>,
pub where_clause: Option<WhereClause>,
}
/// Pattern matching expressions
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum Pattern {
/// Simple node pattern: (n:Label {props})
Node(NodePattern),
/// Relationship pattern: (a)-[r:TYPE]->(b)
Relationship(RelationshipPattern),
/// Path pattern: p = (a)-[*1..5]->(b)
Path(PathPattern),
/// Hyperedge pattern for N-ary relationships: (a)-[r:TYPE]->(b,c,d)
Hyperedge(HyperedgePattern),
}
/// Node pattern: (variable:Label {property: value})
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct NodePattern {
pub variable: Option<String>,
pub labels: Vec<String>,
pub properties: Option<PropertyMap>,
}
/// Relationship pattern: [variable:Type {properties}]
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct RelationshipPattern {
pub variable: Option<String>,
pub rel_type: Option<String>,
pub properties: Option<PropertyMap>,
pub direction: Direction,
pub range: Option<RelationshipRange>,
/// Source node pattern
pub from: Box<NodePattern>,
/// Target - can be a NodePattern or another Pattern for chained relationships
/// For simple relationships like (a)-[r]->(b), this is just the node
/// For chained patterns like (a)-[r]->(b)<-[s]-(c), the target is nested
pub to: Box<Pattern>,
}
/// Hyperedge pattern for N-ary relationships
/// Example: (person)-[r:TRANSACTION]->(account1, account2, merchant)
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct HyperedgePattern {
pub variable: Option<String>,
pub rel_type: String,
pub properties: Option<PropertyMap>,
pub from: Box<NodePattern>,
pub to: Vec<NodePattern>, // Multiple target nodes for N-ary relationships
pub arity: usize, // Number of participating nodes (including source)
}
/// Relationship direction
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub enum Direction {
Outgoing, // ->
Incoming, // <-
Undirected, // -
}
/// Relationship range for path queries: [*min..max]
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub struct RelationshipRange {
pub min: Option<usize>,
pub max: Option<usize>,
}
/// Path pattern: p = (a)-[*]->(b)
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct PathPattern {
pub variable: String,
pub pattern: Box<Pattern>,
}
/// Property map: {key: value, ...}
pub type PropertyMap = HashMap<String, Expression>;
/// WHERE clause for filtering
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct WhereClause {
pub condition: Expression,
}
/// CREATE clause for creating nodes and relationships
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct CreateClause {
pub patterns: Vec<Pattern>,
}
/// MERGE clause for create-or-match
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct MergeClause {
pub pattern: Pattern,
pub on_create: Option<SetClause>,
pub on_match: Option<SetClause>,
}
/// DELETE clause
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct DeleteClause {
pub detach: bool,
pub expressions: Vec<Expression>,
}
/// SET clause for updating properties
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct SetClause {
pub items: Vec<SetItem>,
}
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum SetItem {
Property {
variable: String,
property: String,
value: Expression,
},
Variable {
variable: String,
value: Expression,
},
Labels {
variable: String,
labels: Vec<String>,
},
}
/// REMOVE clause for removing properties or labels
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct RemoveClause {
pub items: Vec<RemoveItem>,
}
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum RemoveItem {
/// Remove a property: REMOVE n.property
Property { variable: String, property: String },
/// Remove labels: REMOVE n:Label1:Label2
Labels {
variable: String,
labels: Vec<String>,
},
}
/// RETURN clause for projection
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct ReturnClause {
pub distinct: bool,
pub items: Vec<ReturnItem>,
pub order_by: Option<OrderBy>,
pub skip: Option<Expression>,
pub limit: Option<Expression>,
}
/// WITH clause for chaining queries
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct WithClause {
pub distinct: bool,
pub items: Vec<ReturnItem>,
pub where_clause: Option<WhereClause>,
pub order_by: Option<OrderBy>,
pub skip: Option<Expression>,
pub limit: Option<Expression>,
}
/// Return item: expression AS alias
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct ReturnItem {
pub expression: Expression,
pub alias: Option<String>,
}
/// ORDER BY clause
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct OrderBy {
pub items: Vec<OrderByItem>,
}
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct OrderByItem {
pub expression: Expression,
pub ascending: bool,
}
/// Expression tree
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum Expression {
// Literals
Integer(i64),
Float(f64),
String(String),
Boolean(bool),
Null,
// Variables and properties
Variable(String),
Property {
object: Box<Expression>,
property: String,
},
// Collections
List(Vec<Expression>),
Map(HashMap<String, Expression>),
// Operators
BinaryOp {
left: Box<Expression>,
op: BinaryOperator,
right: Box<Expression>,
},
UnaryOp {
op: UnaryOperator,
operand: Box<Expression>,
},
// Functions and aggregations
FunctionCall {
name: String,
args: Vec<Expression>,
},
Aggregation {
function: AggregationFunction,
expression: Box<Expression>,
distinct: bool,
},
// Pattern predicates
PatternPredicate(Box<Pattern>),
// Case expressions
Case {
expression: Option<Box<Expression>>,
alternatives: Vec<(Expression, Expression)>,
default: Option<Box<Expression>>,
},
}
/// Binary operators
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub enum BinaryOperator {
// Arithmetic
Add,
Subtract,
Multiply,
Divide,
Modulo,
Power,
// Comparison
Equal,
NotEqual,
LessThan,
LessThanOrEqual,
GreaterThan,
GreaterThanOrEqual,
// Logical
And,
Or,
Xor,
// String
Contains,
StartsWith,
EndsWith,
Matches, // Regex
// Collection
In,
// Null checking
Is,
IsNot,
}
/// Unary operators
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub enum UnaryOperator {
Not,
Minus,
Plus,
IsNull,
IsNotNull,
}
/// Aggregation functions
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub enum AggregationFunction {
Count,
Sum,
Avg,
Min,
Max,
Collect,
StdDev,
StdDevP,
Percentile,
}
impl Query {
pub fn new(statements: Vec<Statement>) -> Self {
Self { statements }
}
/// Check if query contains only read operations
pub fn is_read_only(&self) -> bool {
self.statements.iter().all(|stmt| {
matches!(
stmt,
Statement::Match(_) | Statement::Return(_) | Statement::With(_)
)
})
}
/// Check if query contains hyperedges
pub fn has_hyperedges(&self) -> bool {
self.statements.iter().any(|stmt| match stmt {
Statement::Match(m) => m
.patterns
.iter()
.any(|p| matches!(p, Pattern::Hyperedge(_))),
Statement::Create(c) => c
.patterns
.iter()
.any(|p| matches!(p, Pattern::Hyperedge(_))),
Statement::Merge(m) => matches!(&m.pattern, Pattern::Hyperedge(_)),
_ => false,
})
}
}
impl Pattern {
/// Get the arity of the pattern (number of nodes involved)
pub fn arity(&self) -> usize {
match self {
Pattern::Node(_) => 1,
Pattern::Relationship(_) => 2,
Pattern::Path(_) => 2, // Simplified, could be variable
Pattern::Hyperedge(h) => h.arity,
}
}
}
impl Expression {
/// Check if expression is constant (no variables)
pub fn is_constant(&self) -> bool {
match self {
Expression::Integer(_)
| Expression::Float(_)
| Expression::String(_)
| Expression::Boolean(_)
| Expression::Null => true,
Expression::List(items) => items.iter().all(|e| e.is_constant()),
Expression::Map(map) => map.values().all(|e| e.is_constant()),
Expression::BinaryOp { left, right, .. } => left.is_constant() && right.is_constant(),
Expression::UnaryOp { operand, .. } => operand.is_constant(),
_ => false,
}
}
/// Check if expression contains aggregation
pub fn has_aggregation(&self) -> bool {
match self {
Expression::Aggregation { .. } => true,
Expression::BinaryOp { left, right, .. } => {
left.has_aggregation() || right.has_aggregation()
}
Expression::UnaryOp { operand, .. } => operand.has_aggregation(),
Expression::FunctionCall { args, .. } => args.iter().any(|e| e.has_aggregation()),
Expression::List(items) => items.iter().any(|e| e.has_aggregation()),
Expression::Property { object, .. } => object.has_aggregation(),
_ => false,
}
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_query_is_read_only() {
let query = Query::new(vec![
Statement::Match(MatchClause {
optional: false,
patterns: vec![],
where_clause: None,
}),
Statement::Return(ReturnClause {
distinct: false,
items: vec![],
order_by: None,
skip: None,
limit: None,
}),
]);
assert!(query.is_read_only());
}
#[test]
fn test_expression_is_constant() {
assert!(Expression::Integer(42).is_constant());
assert!(Expression::String("test".to_string()).is_constant());
assert!(!Expression::Variable("x".to_string()).is_constant());
}
#[test]
fn test_hyperedge_arity() {
let hyperedge = Pattern::Hyperedge(HyperedgePattern {
variable: Some("r".to_string()),
rel_type: "TRANSACTION".to_string(),
properties: None,
from: Box::new(NodePattern {
variable: Some("a".to_string()),
labels: vec![],
properties: None,
}),
to: vec![
NodePattern {
variable: Some("b".to_string()),
labels: vec![],
properties: None,
},
NodePattern {
variable: Some("c".to_string()),
labels: vec![],
properties: None,
},
],
arity: 3,
});
assert_eq!(hyperedge.arity(), 3);
}
}

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//! Lexical analyzer (tokenizer) for Cypher query language
//!
//! Converts raw Cypher text into a stream of tokens for parsing.
use nom::{
branch::alt,
bytes::complete::{tag, tag_no_case, take_while, take_while1},
character::complete::{char, multispace0, multispace1, one_of},
combinator::{map, opt, recognize},
multi::many0,
sequence::{delimited, pair, preceded, tuple},
IResult,
};
use serde::{Deserialize, Serialize};
use std::fmt;
/// Token with kind and location information
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct Token {
pub kind: TokenKind,
pub lexeme: String,
pub position: Position,
}
/// Source position for error reporting
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub struct Position {
pub line: usize,
pub column: usize,
pub offset: usize,
}
/// Token kinds
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum TokenKind {
// Keywords
Match,
OptionalMatch,
Where,
Return,
Create,
Merge,
Delete,
DetachDelete,
Set,
Remove,
With,
OrderBy,
Limit,
Skip,
Distinct,
As,
Asc,
Desc,
Case,
When,
Then,
Else,
End,
And,
Or,
Xor,
Not,
In,
Is,
Null,
True,
False,
OnCreate,
OnMatch,
// Identifiers and literals
Identifier(String),
Integer(i64),
Float(f64),
String(String),
// Operators
Plus,
Minus,
Star,
Slash,
Percent,
Caret,
Equal,
NotEqual,
LessThan,
LessThanOrEqual,
GreaterThan,
GreaterThanOrEqual,
Arrow, // ->
LeftArrow, // <-
Dash, // -
// Delimiters
LeftParen,
RightParen,
LeftBracket,
RightBracket,
LeftBrace,
RightBrace,
Comma,
Dot,
Colon,
Semicolon,
Pipe,
// Special
DotDot, // ..
Eof,
}
impl fmt::Display for TokenKind {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match self {
TokenKind::Identifier(s) => write!(f, "identifier '{}'", s),
TokenKind::Integer(n) => write!(f, "integer {}", n),
TokenKind::Float(n) => write!(f, "float {}", n),
TokenKind::String(s) => write!(f, "string \"{}\"", s),
_ => write!(f, "{:?}", self),
}
}
}
/// Tokenize a Cypher query string
pub fn tokenize(input: &str) -> Result<Vec<Token>, LexerError> {
let mut tokens = Vec::new();
let mut remaining = input;
let mut position = Position {
line: 1,
column: 1,
offset: 0,
};
while !remaining.is_empty() {
// Skip whitespace
if let Ok((rest, _)) = multispace1::<_, nom::error::Error<_>>(remaining) {
let consumed = remaining.len() - rest.len();
update_position(&mut position, &remaining[..consumed]);
remaining = rest;
continue;
}
// Try to parse a token
match parse_token(remaining) {
Ok((rest, (kind, lexeme))) => {
tokens.push(Token {
kind,
lexeme: lexeme.to_string(),
position,
});
update_position(&mut position, lexeme);
remaining = rest;
}
Err(_) => {
return Err(LexerError::UnexpectedCharacter {
character: remaining.chars().next().unwrap(),
position,
});
}
}
}
tokens.push(Token {
kind: TokenKind::Eof,
lexeme: String::new(),
position,
});
Ok(tokens)
}
fn update_position(pos: &mut Position, text: &str) {
for ch in text.chars() {
pos.offset += ch.len_utf8();
if ch == '\n' {
pos.line += 1;
pos.column = 1;
} else {
pos.column += 1;
}
}
}
fn parse_token(input: &str) -> IResult<&str, (TokenKind, &str)> {
alt((
parse_keyword,
parse_number,
parse_string,
parse_identifier,
parse_operator,
parse_delimiter,
))(input)
}
fn parse_keyword(input: &str) -> IResult<&str, (TokenKind, &str)> {
let (input, _) = multispace0(input)?;
// Split into nested alt() calls since nom's alt() supports max 21 alternatives
alt((
alt((
map(tag_no_case("OPTIONAL MATCH"), |s: &str| {
(TokenKind::OptionalMatch, s)
}),
map(tag_no_case("DETACH DELETE"), |s: &str| {
(TokenKind::DetachDelete, s)
}),
map(tag_no_case("ORDER BY"), |s: &str| (TokenKind::OrderBy, s)),
map(tag_no_case("ON CREATE"), |s: &str| (TokenKind::OnCreate, s)),
map(tag_no_case("ON MATCH"), |s: &str| (TokenKind::OnMatch, s)),
map(tag_no_case("MATCH"), |s: &str| (TokenKind::Match, s)),
map(tag_no_case("WHERE"), |s: &str| (TokenKind::Where, s)),
map(tag_no_case("RETURN"), |s: &str| (TokenKind::Return, s)),
map(tag_no_case("CREATE"), |s: &str| (TokenKind::Create, s)),
map(tag_no_case("MERGE"), |s: &str| (TokenKind::Merge, s)),
map(tag_no_case("DELETE"), |s: &str| (TokenKind::Delete, s)),
map(tag_no_case("SET"), |s: &str| (TokenKind::Set, s)),
map(tag_no_case("REMOVE"), |s: &str| (TokenKind::Remove, s)),
map(tag_no_case("WITH"), |s: &str| (TokenKind::With, s)),
map(tag_no_case("LIMIT"), |s: &str| (TokenKind::Limit, s)),
map(tag_no_case("SKIP"), |s: &str| (TokenKind::Skip, s)),
map(tag_no_case("DISTINCT"), |s: &str| (TokenKind::Distinct, s)),
)),
alt((
map(tag_no_case("ASC"), |s: &str| (TokenKind::Asc, s)),
map(tag_no_case("DESC"), |s: &str| (TokenKind::Desc, s)),
map(tag_no_case("CASE"), |s: &str| (TokenKind::Case, s)),
map(tag_no_case("WHEN"), |s: &str| (TokenKind::When, s)),
map(tag_no_case("THEN"), |s: &str| (TokenKind::Then, s)),
map(tag_no_case("ELSE"), |s: &str| (TokenKind::Else, s)),
map(tag_no_case("END"), |s: &str| (TokenKind::End, s)),
map(tag_no_case("AND"), |s: &str| (TokenKind::And, s)),
map(tag_no_case("OR"), |s: &str| (TokenKind::Or, s)),
map(tag_no_case("XOR"), |s: &str| (TokenKind::Xor, s)),
map(tag_no_case("NOT"), |s: &str| (TokenKind::Not, s)),
map(tag_no_case("IN"), |s: &str| (TokenKind::In, s)),
map(tag_no_case("IS"), |s: &str| (TokenKind::Is, s)),
map(tag_no_case("NULL"), |s: &str| (TokenKind::Null, s)),
map(tag_no_case("TRUE"), |s: &str| (TokenKind::True, s)),
map(tag_no_case("FALSE"), |s: &str| (TokenKind::False, s)),
map(tag_no_case("AS"), |s: &str| (TokenKind::As, s)),
)),
))(input)
}
fn parse_number(input: &str) -> IResult<&str, (TokenKind, &str)> {
let (input, _) = multispace0(input)?;
// Try to parse float first
if let Ok((rest, num_str)) = recognize::<_, _, nom::error::Error<_>, _>(tuple((
opt(char('-')),
take_while1(|c: char| c.is_ascii_digit()),
char('.'),
take_while1(|c: char| c.is_ascii_digit()),
opt(tuple((
one_of("eE"),
opt(one_of("+-")),
take_while1(|c: char| c.is_ascii_digit()),
))),
)))(input)
{
if let Ok(n) = num_str.parse::<f64>() {
return Ok((rest, (TokenKind::Float(n), num_str)));
}
}
// Parse integer
let (rest, num_str) = recognize(tuple((
opt(char('-')),
take_while1(|c: char| c.is_ascii_digit()),
)))(input)?;
let n = num_str.parse::<i64>().map_err(|_| {
nom::Err::Error(nom::error::Error::new(input, nom::error::ErrorKind::Digit))
})?;
Ok((rest, (TokenKind::Integer(n), num_str)))
}
fn parse_string(input: &str) -> IResult<&str, (TokenKind, &str)> {
let (input, _) = multispace0(input)?;
let (rest, s) = alt((
delimited(
char('\''),
recognize(many0(alt((
tag("\\'"),
tag("\\\\"),
take_while1(|c| c != '\'' && c != '\\'),
)))),
char('\''),
),
delimited(
char('"'),
recognize(many0(alt((
tag("\\\""),
tag("\\\\"),
take_while1(|c| c != '"' && c != '\\'),
)))),
char('"'),
),
))(input)?;
// Unescape string
let unescaped = s
.replace("\\'", "'")
.replace("\\\"", "\"")
.replace("\\\\", "\\");
Ok((rest, (TokenKind::String(unescaped), s)))
}
fn parse_identifier(input: &str) -> IResult<&str, (TokenKind, &str)> {
let (input, _) = multispace0(input)?;
// Backtick-quoted identifier
let backtick_result: IResult<&str, &str> =
delimited(char('`'), take_while1(|c| c != '`'), char('`'))(input);
if let Ok((rest, id)) = backtick_result {
return Ok((rest, (TokenKind::Identifier(id.to_string()), id)));
}
// Regular identifier
let (rest, id) = recognize(pair(
alt((
take_while1(|c: char| c.is_ascii_alphabetic() || c == '_'),
tag("$"),
)),
take_while(|c: char| c.is_ascii_alphanumeric() || c == '_'),
))(input)?;
Ok((rest, (TokenKind::Identifier(id.to_string()), id)))
}
fn parse_operator(input: &str) -> IResult<&str, (TokenKind, &str)> {
let (input, _) = multispace0(input)?;
alt((
map(tag("<="), |s| (TokenKind::LessThanOrEqual, s)),
map(tag(">="), |s| (TokenKind::GreaterThanOrEqual, s)),
map(tag("<>"), |s| (TokenKind::NotEqual, s)),
map(tag("!="), |s| (TokenKind::NotEqual, s)),
map(tag("->"), |s| (TokenKind::Arrow, s)),
map(tag("<-"), |s| (TokenKind::LeftArrow, s)),
map(tag(".."), |s| (TokenKind::DotDot, s)),
map(char('+'), |_| (TokenKind::Plus, "+")),
map(char('-'), |_| (TokenKind::Dash, "-")),
map(char('*'), |_| (TokenKind::Star, "*")),
map(char('/'), |_| (TokenKind::Slash, "/")),
map(char('%'), |_| (TokenKind::Percent, "%")),
map(char('^'), |_| (TokenKind::Caret, "^")),
map(char('='), |_| (TokenKind::Equal, "=")),
map(char('<'), |_| (TokenKind::LessThan, "<")),
map(char('>'), |_| (TokenKind::GreaterThan, ">")),
))(input)
}
fn parse_delimiter(input: &str) -> IResult<&str, (TokenKind, &str)> {
let (input, _) = multispace0(input)?;
alt((
map(char('('), |_| (TokenKind::LeftParen, "(")),
map(char(')'), |_| (TokenKind::RightParen, ")")),
map(char('['), |_| (TokenKind::LeftBracket, "[")),
map(char(']'), |_| (TokenKind::RightBracket, "]")),
map(char('{'), |_| (TokenKind::LeftBrace, "{")),
map(char('}'), |_| (TokenKind::RightBrace, "}")),
map(char(','), |_| (TokenKind::Comma, ",")),
map(char('.'), |_| (TokenKind::Dot, ".")),
map(char(':'), |_| (TokenKind::Colon, ":")),
map(char(';'), |_| (TokenKind::Semicolon, ";")),
map(char('|'), |_| (TokenKind::Pipe, "|")),
))(input)
}
#[derive(Debug, thiserror::Error)]
pub enum LexerError {
#[error("Unexpected character '{character}' at line {}, column {}", position.line, position.column)]
UnexpectedCharacter { character: char, position: Position },
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_tokenize_simple_match() {
let input = "MATCH (n:Person) RETURN n";
let tokens = tokenize(input).unwrap();
assert_eq!(tokens[0].kind, TokenKind::Match);
assert_eq!(tokens[1].kind, TokenKind::LeftParen);
assert_eq!(tokens[2].kind, TokenKind::Identifier("n".to_string()));
assert_eq!(tokens[3].kind, TokenKind::Colon);
assert_eq!(tokens[4].kind, TokenKind::Identifier("Person".to_string()));
assert_eq!(tokens[5].kind, TokenKind::RightParen);
assert_eq!(tokens[6].kind, TokenKind::Return);
assert_eq!(tokens[7].kind, TokenKind::Identifier("n".to_string()));
}
#[test]
fn test_tokenize_numbers() {
let tokens = tokenize("123 45.67 -89 3.14e-2").unwrap();
assert_eq!(tokens[0].kind, TokenKind::Integer(123));
assert_eq!(tokens[1].kind, TokenKind::Float(45.67));
assert_eq!(tokens[2].kind, TokenKind::Integer(-89));
assert!(matches!(tokens[3].kind, TokenKind::Float(_)));
}
#[test]
fn test_tokenize_strings() {
let tokens = tokenize(r#"'Alice' "Bob's friend""#).unwrap();
assert_eq!(tokens[0].kind, TokenKind::String("Alice".to_string()));
assert_eq!(
tokens[1].kind,
TokenKind::String("Bob's friend".to_string())
);
}
#[test]
fn test_tokenize_operators() {
let tokens = tokenize("-> <- = <> >= <=").unwrap();
assert_eq!(tokens[0].kind, TokenKind::Arrow);
assert_eq!(tokens[1].kind, TokenKind::LeftArrow);
assert_eq!(tokens[2].kind, TokenKind::Equal);
assert_eq!(tokens[3].kind, TokenKind::NotEqual);
assert_eq!(tokens[4].kind, TokenKind::GreaterThanOrEqual);
assert_eq!(tokens[5].kind, TokenKind::LessThanOrEqual);
}
}

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@@ -0,0 +1,20 @@
//! Cypher query language parser and execution engine
//!
//! This module provides a complete Cypher query language implementation including:
//! - Lexical analysis (tokenization)
//! - Syntax parsing (AST generation)
//! - Semantic analysis and type checking
//! - Query optimization
//! - Support for hyperedges (N-ary relationships)
pub mod ast;
pub mod lexer;
pub mod optimizer;
pub mod parser;
pub mod semantic;
pub use ast::{Query, Statement};
pub use lexer::{Token, TokenKind};
pub use optimizer::{OptimizationPlan, QueryOptimizer};
pub use parser::{parse_cypher, ParseError};
pub use semantic::{SemanticAnalyzer, SemanticError};

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@@ -0,0 +1,582 @@
//! Query optimizer for Cypher queries
//!
//! Optimizes query execution plans through:
//! - Predicate pushdown (filter as early as possible)
//! - Join reordering (minimize intermediate results)
//! - Index utilization
//! - Constant folding
//! - Dead code elimination
use super::ast::*;
use std::collections::HashSet;
/// Query optimization plan
#[derive(Debug, Clone)]
pub struct OptimizationPlan {
pub optimized_query: Query,
pub optimizations_applied: Vec<OptimizationType>,
pub estimated_cost: f64,
}
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum OptimizationType {
PredicatePushdown,
JoinReordering,
ConstantFolding,
IndexHint,
EarlyFiltering,
PatternSimplification,
DeadCodeElimination,
}
pub struct QueryOptimizer {
enable_predicate_pushdown: bool,
enable_join_reordering: bool,
enable_constant_folding: bool,
}
impl QueryOptimizer {
pub fn new() -> Self {
Self {
enable_predicate_pushdown: true,
enable_join_reordering: true,
enable_constant_folding: true,
}
}
/// Optimize a query and return an execution plan
pub fn optimize(&self, query: Query) -> OptimizationPlan {
let mut optimized = query;
let mut optimizations = Vec::new();
// Apply optimizations in order
if self.enable_constant_folding {
if let Some(q) = self.apply_constant_folding(optimized.clone()) {
optimized = q;
optimizations.push(OptimizationType::ConstantFolding);
}
}
if self.enable_predicate_pushdown {
if let Some(q) = self.apply_predicate_pushdown(optimized.clone()) {
optimized = q;
optimizations.push(OptimizationType::PredicatePushdown);
}
}
if self.enable_join_reordering {
if let Some(q) = self.apply_join_reordering(optimized.clone()) {
optimized = q;
optimizations.push(OptimizationType::JoinReordering);
}
}
let cost = self.estimate_cost(&optimized);
OptimizationPlan {
optimized_query: optimized,
optimizations_applied: optimizations,
estimated_cost: cost,
}
}
/// Apply constant folding to simplify expressions
fn apply_constant_folding(&self, mut query: Query) -> Option<Query> {
let mut changed = false;
for statement in &mut query.statements {
if self.fold_statement(statement) {
changed = true;
}
}
if changed {
Some(query)
} else {
None
}
}
fn fold_statement(&self, statement: &mut Statement) -> bool {
match statement {
Statement::Match(clause) => {
let mut changed = false;
if let Some(where_clause) = &mut clause.where_clause {
if let Some(folded) = self.fold_expression(&where_clause.condition) {
where_clause.condition = folded;
changed = true;
}
}
changed
}
Statement::Return(clause) => {
let mut changed = false;
for item in &mut clause.items {
if let Some(folded) = self.fold_expression(&item.expression) {
item.expression = folded;
changed = true;
}
}
changed
}
_ => false,
}
}
fn fold_expression(&self, expr: &Expression) -> Option<Expression> {
match expr {
Expression::BinaryOp { left, op, right } => {
// Fold operands first
let left = self
.fold_expression(left)
.unwrap_or_else(|| (**left).clone());
let right = self
.fold_expression(right)
.unwrap_or_else(|| (**right).clone());
// Try to evaluate constant expressions
if left.is_constant() && right.is_constant() {
return self.evaluate_constant_binary_op(&left, *op, &right);
}
// Return simplified expression
Some(Expression::BinaryOp {
left: Box::new(left),
op: *op,
right: Box::new(right),
})
}
Expression::UnaryOp { op, operand } => {
let operand = self
.fold_expression(operand)
.unwrap_or_else(|| (**operand).clone());
if operand.is_constant() {
return self.evaluate_constant_unary_op(*op, &operand);
}
Some(Expression::UnaryOp {
op: *op,
operand: Box::new(operand),
})
}
_ => None,
}
}
fn evaluate_constant_binary_op(
&self,
left: &Expression,
op: BinaryOperator,
right: &Expression,
) -> Option<Expression> {
match (left, op, right) {
// Arithmetic operations
(Expression::Integer(a), BinaryOperator::Add, Expression::Integer(b)) => {
Some(Expression::Integer(a + b))
}
(Expression::Integer(a), BinaryOperator::Subtract, Expression::Integer(b)) => {
Some(Expression::Integer(a - b))
}
(Expression::Integer(a), BinaryOperator::Multiply, Expression::Integer(b)) => {
Some(Expression::Integer(a * b))
}
(Expression::Integer(a), BinaryOperator::Divide, Expression::Integer(b)) if *b != 0 => {
Some(Expression::Integer(a / b))
}
(Expression::Integer(a), BinaryOperator::Modulo, Expression::Integer(b)) if *b != 0 => {
Some(Expression::Integer(a % b))
}
(Expression::Float(a), BinaryOperator::Add, Expression::Float(b)) => {
Some(Expression::Float(a + b))
}
(Expression::Float(a), BinaryOperator::Subtract, Expression::Float(b)) => {
Some(Expression::Float(a - b))
}
(Expression::Float(a), BinaryOperator::Multiply, Expression::Float(b)) => {
Some(Expression::Float(a * b))
}
(Expression::Float(a), BinaryOperator::Divide, Expression::Float(b)) if *b != 0.0 => {
Some(Expression::Float(a / b))
}
// Comparison operations for integers
(Expression::Integer(a), BinaryOperator::Equal, Expression::Integer(b)) => {
Some(Expression::Boolean(a == b))
}
(Expression::Integer(a), BinaryOperator::NotEqual, Expression::Integer(b)) => {
Some(Expression::Boolean(a != b))
}
(Expression::Integer(a), BinaryOperator::LessThan, Expression::Integer(b)) => {
Some(Expression::Boolean(a < b))
}
(Expression::Integer(a), BinaryOperator::LessThanOrEqual, Expression::Integer(b)) => {
Some(Expression::Boolean(a <= b))
}
(Expression::Integer(a), BinaryOperator::GreaterThan, Expression::Integer(b)) => {
Some(Expression::Boolean(a > b))
}
(
Expression::Integer(a),
BinaryOperator::GreaterThanOrEqual,
Expression::Integer(b),
) => Some(Expression::Boolean(a >= b)),
// Comparison operations for floats
(Expression::Float(a), BinaryOperator::Equal, Expression::Float(b)) => {
Some(Expression::Boolean((a - b).abs() < f64::EPSILON))
}
(Expression::Float(a), BinaryOperator::NotEqual, Expression::Float(b)) => {
Some(Expression::Boolean((a - b).abs() >= f64::EPSILON))
}
(Expression::Float(a), BinaryOperator::LessThan, Expression::Float(b)) => {
Some(Expression::Boolean(a < b))
}
(Expression::Float(a), BinaryOperator::LessThanOrEqual, Expression::Float(b)) => {
Some(Expression::Boolean(a <= b))
}
(Expression::Float(a), BinaryOperator::GreaterThan, Expression::Float(b)) => {
Some(Expression::Boolean(a > b))
}
(Expression::Float(a), BinaryOperator::GreaterThanOrEqual, Expression::Float(b)) => {
Some(Expression::Boolean(a >= b))
}
// String comparison
(Expression::String(a), BinaryOperator::Equal, Expression::String(b)) => {
Some(Expression::Boolean(a == b))
}
(Expression::String(a), BinaryOperator::NotEqual, Expression::String(b)) => {
Some(Expression::Boolean(a != b))
}
// Boolean operations
(Expression::Boolean(a), BinaryOperator::And, Expression::Boolean(b)) => {
Some(Expression::Boolean(*a && *b))
}
(Expression::Boolean(a), BinaryOperator::Or, Expression::Boolean(b)) => {
Some(Expression::Boolean(*a || *b))
}
(Expression::Boolean(a), BinaryOperator::Equal, Expression::Boolean(b)) => {
Some(Expression::Boolean(a == b))
}
(Expression::Boolean(a), BinaryOperator::NotEqual, Expression::Boolean(b)) => {
Some(Expression::Boolean(a != b))
}
_ => None,
}
}
fn evaluate_constant_unary_op(
&self,
op: UnaryOperator,
operand: &Expression,
) -> Option<Expression> {
match (op, operand) {
(UnaryOperator::Not, Expression::Boolean(b)) => Some(Expression::Boolean(!b)),
(UnaryOperator::Minus, Expression::Integer(n)) => Some(Expression::Integer(-n)),
(UnaryOperator::Minus, Expression::Float(n)) => Some(Expression::Float(-n)),
_ => None,
}
}
/// Apply predicate pushdown optimization
/// Move WHERE clauses as close to data access as possible
fn apply_predicate_pushdown(&self, query: Query) -> Option<Query> {
// In a real implementation, this would analyze the query graph
// and push predicates down to the earliest possible point
// For now, we'll do a simple transformation
// This is a placeholder - real implementation would be more complex
None
}
/// Reorder joins to minimize intermediate result sizes
fn apply_join_reordering(&self, query: Query) -> Option<Query> {
// Analyze pattern complexity and reorder based on selectivity
// Patterns with more constraints should be evaluated first
let mut optimized = query.clone();
let mut changed = false;
for statement in &mut optimized.statements {
if let Statement::Match(clause) = statement {
let mut patterns = clause.patterns.clone();
// Sort patterns by estimated selectivity (more selective first)
patterns.sort_by_key(|p| {
let selectivity = self.estimate_pattern_selectivity(p);
// Use negative to sort in descending order (most selective first)
-(selectivity * 1000.0) as i64
});
if patterns != clause.patterns {
clause.patterns = patterns;
changed = true;
}
}
}
if changed {
Some(optimized)
} else {
None
}
}
/// Estimate the selectivity of a pattern (0.0 = least selective, 1.0 = most selective)
fn estimate_pattern_selectivity(&self, pattern: &Pattern) -> f64 {
match pattern {
Pattern::Node(node) => {
let mut selectivity = 0.3; // Base selectivity for node
// More labels = more selective
selectivity += node.labels.len() as f64 * 0.1;
// Properties = more selective
if let Some(props) = &node.properties {
selectivity += props.len() as f64 * 0.15;
}
selectivity.min(1.0)
}
Pattern::Relationship(rel) => {
let mut selectivity = 0.2; // Base selectivity for relationship
// Specific type = more selective
if rel.rel_type.is_some() {
selectivity += 0.2;
}
// Properties = more selective
if let Some(props) = &rel.properties {
selectivity += props.len() as f64 * 0.15;
}
// Add selectivity from connected nodes
selectivity +=
self.estimate_pattern_selectivity(&Pattern::Node(*rel.from.clone())) * 0.3;
// rel.to is now a Pattern (can be NodePattern or chained RelationshipPattern)
selectivity += self.estimate_pattern_selectivity(&*rel.to) * 0.3;
selectivity.min(1.0)
}
Pattern::Hyperedge(hyperedge) => {
let mut selectivity = 0.5; // Hyperedges are typically more selective
// More nodes involved = more selective
selectivity += hyperedge.arity as f64 * 0.1;
if let Some(props) = &hyperedge.properties {
selectivity += props.len() as f64 * 0.15;
}
selectivity.min(1.0)
}
Pattern::Path(_) => 0.1, // Paths are typically less selective
}
}
/// Estimate the cost of executing a query
fn estimate_cost(&self, query: &Query) -> f64 {
let mut cost = 0.0;
for statement in &query.statements {
cost += self.estimate_statement_cost(statement);
}
cost
}
fn estimate_statement_cost(&self, statement: &Statement) -> f64 {
match statement {
Statement::Match(clause) => {
let mut cost = 0.0;
for pattern in &clause.patterns {
cost += self.estimate_pattern_cost(pattern);
}
// WHERE clause adds filtering cost
if clause.where_clause.is_some() {
cost *= 1.2;
}
cost
}
Statement::Create(clause) => {
// Create operations are expensive
clause.patterns.len() as f64 * 50.0
}
Statement::Merge(clause) => {
// Merge is more expensive than match or create alone
self.estimate_pattern_cost(&clause.pattern) * 2.0
}
Statement::Delete(_) => 30.0,
Statement::Set(_) => 20.0,
Statement::Remove(clause) => clause.items.len() as f64 * 15.0,
Statement::Return(clause) => {
let mut cost = 10.0;
// Aggregations are expensive
for item in &clause.items {
if item.expression.has_aggregation() {
cost += 50.0;
}
}
// Sorting adds cost
if clause.order_by.is_some() {
cost += 100.0;
}
cost
}
Statement::With(_) => 15.0,
}
}
fn estimate_pattern_cost(&self, pattern: &Pattern) -> f64 {
match pattern {
Pattern::Node(node) => {
let mut cost = 100.0;
// Labels reduce cost (more selective)
cost /= (1.0 + node.labels.len() as f64 * 0.5);
// Properties reduce cost
if let Some(props) = &node.properties {
cost /= (1.0 + props.len() as f64 * 0.3);
}
cost
}
Pattern::Relationship(rel) => {
let mut cost = 200.0; // Relationships are more expensive
// Specific type reduces cost
if rel.rel_type.is_some() {
cost *= 0.7;
}
// Variable length paths are very expensive
if let Some(range) = &rel.range {
let max = range.max.unwrap_or(10);
cost *= max as f64;
}
cost
}
Pattern::Hyperedge(hyperedge) => {
// Hyperedges are more expensive due to N-ary nature
150.0 * hyperedge.arity as f64
}
Pattern::Path(_) => 300.0, // Paths can be expensive
}
}
/// Get variables used in an expression
fn get_variables_in_expression(&self, expr: &Expression) -> HashSet<String> {
let mut vars = HashSet::new();
self.collect_variables(expr, &mut vars);
vars
}
fn collect_variables(&self, expr: &Expression, vars: &mut HashSet<String>) {
match expr {
Expression::Variable(name) => {
vars.insert(name.clone());
}
Expression::Property { object, .. } => {
self.collect_variables(object, vars);
}
Expression::BinaryOp { left, right, .. } => {
self.collect_variables(left, vars);
self.collect_variables(right, vars);
}
Expression::UnaryOp { operand, .. } => {
self.collect_variables(operand, vars);
}
Expression::FunctionCall { args, .. } => {
for arg in args {
self.collect_variables(arg, vars);
}
}
Expression::Aggregation { expression, .. } => {
self.collect_variables(expression, vars);
}
Expression::List(items) => {
for item in items {
self.collect_variables(item, vars);
}
}
Expression::Case {
expression,
alternatives,
default,
} => {
if let Some(expr) = expression {
self.collect_variables(expr, vars);
}
for (cond, result) in alternatives {
self.collect_variables(cond, vars);
self.collect_variables(result, vars);
}
if let Some(default_expr) = default {
self.collect_variables(default_expr, vars);
}
}
_ => {}
}
}
}
impl Default for QueryOptimizer {
fn default() -> Self {
Self::new()
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::cypher::parser::parse_cypher;
#[test]
fn test_constant_folding() {
let query = parse_cypher("MATCH (n) WHERE 2 + 3 = 5 RETURN n").unwrap();
let optimizer = QueryOptimizer::new();
let plan = optimizer.optimize(query);
assert!(plan
.optimizations_applied
.contains(&OptimizationType::ConstantFolding));
}
#[test]
fn test_cost_estimation() {
let query = parse_cypher("MATCH (n:Person {age: 30}) RETURN n").unwrap();
let optimizer = QueryOptimizer::new();
let cost = optimizer.estimate_cost(&query);
assert!(cost > 0.0);
}
#[test]
fn test_pattern_selectivity() {
let optimizer = QueryOptimizer::new();
let node_with_label = Pattern::Node(NodePattern {
variable: Some("n".to_string()),
labels: vec!["Person".to_string()],
properties: None,
});
let node_without_label = Pattern::Node(NodePattern {
variable: Some("n".to_string()),
labels: vec![],
properties: None,
});
let sel_with = optimizer.estimate_pattern_selectivity(&node_with_label);
let sel_without = optimizer.estimate_pattern_selectivity(&node_without_label);
assert!(sel_with > sel_without);
}
}

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//! Semantic analysis and type checking for Cypher queries
//!
//! Validates the semantic correctness of parsed Cypher queries including:
//! - Variable scope checking
//! - Type compatibility validation
//! - Aggregation context verification
//! - Pattern validity
use super::ast::*;
use std::collections::{HashMap, HashSet};
use thiserror::Error;
#[derive(Debug, Error)]
pub enum SemanticError {
#[error("Undefined variable: {0}")]
UndefinedVariable(String),
#[error("Variable already defined: {0}")]
VariableAlreadyDefined(String),
#[error("Type mismatch: expected {expected}, found {found}")]
TypeMismatch { expected: String, found: String },
#[error("Aggregation not allowed in {0}")]
InvalidAggregation(String),
#[error("Cannot mix aggregated and non-aggregated expressions")]
MixedAggregation,
#[error("Invalid pattern: {0}")]
InvalidPattern(String),
#[error("Invalid hyperedge: {0}")]
InvalidHyperedge(String),
#[error("Property access on non-object type")]
InvalidPropertyAccess,
#[error(
"Invalid number of arguments for function {function}: expected {expected}, found {found}"
)]
InvalidArgumentCount {
function: String,
expected: usize,
found: usize,
},
}
type SemanticResult<T> = Result<T, SemanticError>;
/// Semantic analyzer for Cypher queries
pub struct SemanticAnalyzer {
scope_stack: Vec<Scope>,
in_aggregation: bool,
}
#[derive(Debug, Clone)]
struct Scope {
variables: HashMap<String, ValueType>,
}
/// Type system for Cypher values
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum ValueType {
Integer,
Float,
String,
Boolean,
Null,
Node,
Relationship,
Path,
List(Box<ValueType>),
Map,
Any,
}
impl ValueType {
/// Check if this type is compatible with another type
pub fn is_compatible_with(&self, other: &ValueType) -> bool {
match (self, other) {
(ValueType::Any, _) | (_, ValueType::Any) => true,
(ValueType::Null, _) | (_, ValueType::Null) => true,
(ValueType::Integer, ValueType::Float) | (ValueType::Float, ValueType::Integer) => true,
(ValueType::List(a), ValueType::List(b)) => a.is_compatible_with(b),
_ => self == other,
}
}
/// Check if this is a numeric type
pub fn is_numeric(&self) -> bool {
matches!(self, ValueType::Integer | ValueType::Float | ValueType::Any)
}
/// Check if this is a graph element (node, relationship, path)
pub fn is_graph_element(&self) -> bool {
matches!(
self,
ValueType::Node | ValueType::Relationship | ValueType::Path | ValueType::Any
)
}
}
impl Scope {
fn new() -> Self {
Self {
variables: HashMap::new(),
}
}
fn define(&mut self, name: String, value_type: ValueType) -> SemanticResult<()> {
if self.variables.contains_key(&name) {
Err(SemanticError::VariableAlreadyDefined(name))
} else {
self.variables.insert(name, value_type);
Ok(())
}
}
fn get(&self, name: &str) -> Option<&ValueType> {
self.variables.get(name)
}
}
impl SemanticAnalyzer {
pub fn new() -> Self {
Self {
scope_stack: vec![Scope::new()],
in_aggregation: false,
}
}
fn current_scope(&self) -> &Scope {
self.scope_stack.last().unwrap()
}
fn current_scope_mut(&mut self) -> &mut Scope {
self.scope_stack.last_mut().unwrap()
}
fn push_scope(&mut self) {
self.scope_stack.push(Scope::new());
}
fn pop_scope(&mut self) {
self.scope_stack.pop();
}
fn lookup_variable(&self, name: &str) -> SemanticResult<&ValueType> {
for scope in self.scope_stack.iter().rev() {
if let Some(value_type) = scope.get(name) {
return Ok(value_type);
}
}
Err(SemanticError::UndefinedVariable(name.to_string()))
}
fn define_variable(&mut self, name: String, value_type: ValueType) -> SemanticResult<()> {
self.current_scope_mut().define(name, value_type)
}
/// Analyze a complete query
pub fn analyze_query(&mut self, query: &Query) -> SemanticResult<()> {
for statement in &query.statements {
self.analyze_statement(statement)?;
}
Ok(())
}
fn analyze_statement(&mut self, statement: &Statement) -> SemanticResult<()> {
match statement {
Statement::Match(clause) => self.analyze_match(clause),
Statement::Create(clause) => self.analyze_create(clause),
Statement::Merge(clause) => self.analyze_merge(clause),
Statement::Delete(clause) => self.analyze_delete(clause),
Statement::Set(clause) => self.analyze_set(clause),
Statement::Remove(clause) => self.analyze_remove(clause),
Statement::Return(clause) => self.analyze_return(clause),
Statement::With(clause) => self.analyze_with(clause),
}
}
fn analyze_remove(&mut self, clause: &RemoveClause) -> SemanticResult<()> {
for item in &clause.items {
match item {
RemoveItem::Property { variable, .. } => {
// Verify variable is defined
self.lookup_variable(variable)?;
}
RemoveItem::Labels { variable, .. } => {
// Verify variable is defined
self.lookup_variable(variable)?;
}
}
}
Ok(())
}
fn analyze_match(&mut self, clause: &MatchClause) -> SemanticResult<()> {
// Analyze patterns and define variables
for pattern in &clause.patterns {
self.analyze_pattern(pattern)?;
}
// Analyze WHERE clause
if let Some(where_clause) = &clause.where_clause {
let expr_type = self.analyze_expression(&where_clause.condition)?;
if !expr_type.is_compatible_with(&ValueType::Boolean) {
return Err(SemanticError::TypeMismatch {
expected: "Boolean".to_string(),
found: format!("{:?}", expr_type),
});
}
}
Ok(())
}
fn analyze_pattern(&mut self, pattern: &Pattern) -> SemanticResult<()> {
match pattern {
Pattern::Node(node) => self.analyze_node_pattern(node),
Pattern::Relationship(rel) => self.analyze_relationship_pattern(rel),
Pattern::Path(path) => self.analyze_path_pattern(path),
Pattern::Hyperedge(hyperedge) => self.analyze_hyperedge_pattern(hyperedge),
}
}
fn analyze_node_pattern(&mut self, node: &NodePattern) -> SemanticResult<()> {
if let Some(variable) = &node.variable {
self.define_variable(variable.clone(), ValueType::Node)?;
}
if let Some(properties) = &node.properties {
for expr in properties.values() {
self.analyze_expression(expr)?;
}
}
Ok(())
}
fn analyze_relationship_pattern(&mut self, rel: &RelationshipPattern) -> SemanticResult<()> {
self.analyze_node_pattern(&rel.from)?;
// rel.to is now a Pattern (can be NodePattern or chained RelationshipPattern)
self.analyze_pattern(&*rel.to)?;
if let Some(variable) = &rel.variable {
self.define_variable(variable.clone(), ValueType::Relationship)?;
}
if let Some(properties) = &rel.properties {
for expr in properties.values() {
self.analyze_expression(expr)?;
}
}
// Validate range if present
if let Some(range) = &rel.range {
if let (Some(min), Some(max)) = (range.min, range.max) {
if min > max {
return Err(SemanticError::InvalidPattern(
"Minimum range cannot be greater than maximum".to_string(),
));
}
}
}
Ok(())
}
fn analyze_path_pattern(&mut self, path: &PathPattern) -> SemanticResult<()> {
self.define_variable(path.variable.clone(), ValueType::Path)?;
self.analyze_pattern(&path.pattern)
}
fn analyze_hyperedge_pattern(&mut self, hyperedge: &HyperedgePattern) -> SemanticResult<()> {
// Validate hyperedge has at least 2 target nodes
if hyperedge.to.len() < 2 {
return Err(SemanticError::InvalidHyperedge(
"Hyperedge must have at least 2 target nodes".to_string(),
));
}
// Validate arity matches
if hyperedge.arity != hyperedge.to.len() + 1 {
return Err(SemanticError::InvalidHyperedge(
"Hyperedge arity doesn't match number of participating nodes".to_string(),
));
}
self.analyze_node_pattern(&hyperedge.from)?;
for target in &hyperedge.to {
self.analyze_node_pattern(target)?;
}
if let Some(variable) = &hyperedge.variable {
self.define_variable(variable.clone(), ValueType::Relationship)?;
}
if let Some(properties) = &hyperedge.properties {
for expr in properties.values() {
self.analyze_expression(expr)?;
}
}
Ok(())
}
fn analyze_create(&mut self, clause: &CreateClause) -> SemanticResult<()> {
for pattern in &clause.patterns {
self.analyze_pattern(pattern)?;
}
Ok(())
}
fn analyze_merge(&mut self, clause: &MergeClause) -> SemanticResult<()> {
self.analyze_pattern(&clause.pattern)?;
if let Some(on_create) = &clause.on_create {
self.analyze_set(on_create)?;
}
if let Some(on_match) = &clause.on_match {
self.analyze_set(on_match)?;
}
Ok(())
}
fn analyze_delete(&mut self, clause: &DeleteClause) -> SemanticResult<()> {
for expr in &clause.expressions {
let expr_type = self.analyze_expression(expr)?;
if !expr_type.is_graph_element() {
return Err(SemanticError::TypeMismatch {
expected: "graph element (node, relationship, path)".to_string(),
found: format!("{:?}", expr_type),
});
}
}
Ok(())
}
fn analyze_set(&mut self, clause: &SetClause) -> SemanticResult<()> {
for item in &clause.items {
match item {
SetItem::Property {
variable, value, ..
} => {
self.lookup_variable(variable)?;
self.analyze_expression(value)?;
}
SetItem::Variable { variable, value } => {
self.lookup_variable(variable)?;
self.analyze_expression(value)?;
}
SetItem::Labels { variable, .. } => {
self.lookup_variable(variable)?;
}
}
}
Ok(())
}
fn analyze_return(&mut self, clause: &ReturnClause) -> SemanticResult<()> {
self.analyze_return_items(&clause.items)?;
if let Some(order_by) = &clause.order_by {
for item in &order_by.items {
self.analyze_expression(&item.expression)?;
}
}
if let Some(skip) = &clause.skip {
let skip_type = self.analyze_expression(skip)?;
if !skip_type.is_compatible_with(&ValueType::Integer) {
return Err(SemanticError::TypeMismatch {
expected: "Integer".to_string(),
found: format!("{:?}", skip_type),
});
}
}
if let Some(limit) = &clause.limit {
let limit_type = self.analyze_expression(limit)?;
if !limit_type.is_compatible_with(&ValueType::Integer) {
return Err(SemanticError::TypeMismatch {
expected: "Integer".to_string(),
found: format!("{:?}", limit_type),
});
}
}
Ok(())
}
fn analyze_with(&mut self, clause: &WithClause) -> SemanticResult<()> {
self.analyze_return_items(&clause.items)?;
if let Some(where_clause) = &clause.where_clause {
let expr_type = self.analyze_expression(&where_clause.condition)?;
if !expr_type.is_compatible_with(&ValueType::Boolean) {
return Err(SemanticError::TypeMismatch {
expected: "Boolean".to_string(),
found: format!("{:?}", expr_type),
});
}
}
Ok(())
}
fn analyze_return_items(&mut self, items: &[ReturnItem]) -> SemanticResult<()> {
let mut has_aggregation = false;
let mut has_non_aggregation = false;
for item in items {
let item_has_agg = item.expression.has_aggregation();
has_aggregation |= item_has_agg;
has_non_aggregation |= !item_has_agg && !item.expression.is_constant();
}
if has_aggregation && has_non_aggregation {
return Err(SemanticError::MixedAggregation);
}
for item in items {
self.analyze_expression(&item.expression)?;
}
Ok(())
}
fn analyze_expression(&mut self, expr: &Expression) -> SemanticResult<ValueType> {
match expr {
Expression::Integer(_) => Ok(ValueType::Integer),
Expression::Float(_) => Ok(ValueType::Float),
Expression::String(_) => Ok(ValueType::String),
Expression::Boolean(_) => Ok(ValueType::Boolean),
Expression::Null => Ok(ValueType::Null),
Expression::Variable(name) => {
self.lookup_variable(name)?;
Ok(ValueType::Any)
}
Expression::Property { object, .. } => {
let obj_type = self.analyze_expression(object)?;
if !obj_type.is_graph_element()
&& obj_type != ValueType::Map
&& obj_type != ValueType::Any
{
return Err(SemanticError::InvalidPropertyAccess);
}
Ok(ValueType::Any)
}
Expression::List(items) => {
if items.is_empty() {
Ok(ValueType::List(Box::new(ValueType::Any)))
} else {
let first_type = self.analyze_expression(&items[0])?;
for item in items.iter().skip(1) {
let item_type = self.analyze_expression(item)?;
if !item_type.is_compatible_with(&first_type) {
return Ok(ValueType::List(Box::new(ValueType::Any)));
}
}
Ok(ValueType::List(Box::new(first_type)))
}
}
Expression::Map(map) => {
for expr in map.values() {
self.analyze_expression(expr)?;
}
Ok(ValueType::Map)
}
Expression::BinaryOp { left, op, right } => {
let left_type = self.analyze_expression(left)?;
let right_type = self.analyze_expression(right)?;
match op {
BinaryOperator::Add
| BinaryOperator::Subtract
| BinaryOperator::Multiply
| BinaryOperator::Divide
| BinaryOperator::Modulo
| BinaryOperator::Power => {
if !left_type.is_numeric() || !right_type.is_numeric() {
return Err(SemanticError::TypeMismatch {
expected: "numeric".to_string(),
found: format!("{:?} and {:?}", left_type, right_type),
});
}
if left_type == ValueType::Float || right_type == ValueType::Float {
Ok(ValueType::Float)
} else {
Ok(ValueType::Integer)
}
}
BinaryOperator::Equal
| BinaryOperator::NotEqual
| BinaryOperator::LessThan
| BinaryOperator::LessThanOrEqual
| BinaryOperator::GreaterThan
| BinaryOperator::GreaterThanOrEqual => Ok(ValueType::Boolean),
BinaryOperator::And | BinaryOperator::Or | BinaryOperator::Xor => {
Ok(ValueType::Boolean)
}
_ => Ok(ValueType::Any),
}
}
Expression::UnaryOp { op, operand } => {
let operand_type = self.analyze_expression(operand)?;
match op {
UnaryOperator::Not | UnaryOperator::IsNull | UnaryOperator::IsNotNull => {
Ok(ValueType::Boolean)
}
UnaryOperator::Minus | UnaryOperator::Plus => Ok(operand_type),
}
}
Expression::FunctionCall { args, .. } => {
for arg in args {
self.analyze_expression(arg)?;
}
Ok(ValueType::Any)
}
Expression::Aggregation { expression, .. } => {
let old_in_agg = self.in_aggregation;
self.in_aggregation = true;
let result = self.analyze_expression(expression);
self.in_aggregation = old_in_agg;
result?;
Ok(ValueType::Any)
}
Expression::PatternPredicate(pattern) => {
self.analyze_pattern(pattern)?;
Ok(ValueType::Boolean)
}
Expression::Case {
expression,
alternatives,
default,
} => {
if let Some(expr) = expression {
self.analyze_expression(expr)?;
}
for (condition, result) in alternatives {
self.analyze_expression(condition)?;
self.analyze_expression(result)?;
}
if let Some(default_expr) = default {
self.analyze_expression(default_expr)?;
}
Ok(ValueType::Any)
}
}
}
}
impl Default for SemanticAnalyzer {
fn default() -> Self {
Self::new()
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::cypher::parser::parse_cypher;
#[test]
fn test_analyze_simple_match() {
let query = parse_cypher("MATCH (n:Person) RETURN n").unwrap();
let mut analyzer = SemanticAnalyzer::new();
assert!(analyzer.analyze_query(&query).is_ok());
}
#[test]
fn test_undefined_variable() {
let query = parse_cypher("MATCH (n:Person) RETURN m").unwrap();
let mut analyzer = SemanticAnalyzer::new();
assert!(matches!(
analyzer.analyze_query(&query),
Err(SemanticError::UndefinedVariable(_))
));
}
#[test]
fn test_mixed_aggregation() {
let query = parse_cypher("MATCH (n:Person) RETURN n.name, COUNT(n)").unwrap();
let mut analyzer = SemanticAnalyzer::new();
assert!(matches!(
analyzer.analyze_query(&query),
Err(SemanticError::MixedAggregation)
));
}
#[test]
#[ignore = "Hyperedge syntax not yet implemented in parser"]
fn test_hyperedge_validation() {
let query = parse_cypher("MATCH (a)-[r:REL]->(b, c) RETURN a, r, b, c").unwrap();
let mut analyzer = SemanticAnalyzer::new();
assert!(analyzer.analyze_query(&query).is_ok());
}
}