alopex_sql/planner/

type_checker.rs

//! Type checking module for the Alopex SQL dialect.
//!
//! This module provides type inference and validation for SQL expressions.
//! It checks that expressions are well-typed and that operations are valid
//! for the types involved.

use crate::ast::Span;
use crate::ast::Statement;
use crate::ast::ddl::VectorMetric;
use crate::ast::expr::{
    BinaryOp, Expr, ExprKind, Literal, PatternMatchKind, Quantifier as AstQuantifier, UnaryOp,
};
use crate::catalog::{Catalog, ColumnMetadata, TableMetadata};
use crate::planner::aggregate_expr::{AggregateExpr, AggregateFunction};
use crate::planner::error::PlannerError;
use crate::planner::logical_plan::LogicalPlan;
use crate::planner::typed_expr::{Quantifier, TypedExpr, TypedExprKind};
use crate::planner::types::ResolvedType;
use std::collections::{BTreeSet, HashMap, HashSet};
use std::sync::Arc;

/// A table visible to expression name resolution.
///
/// The metadata is shared rather than owned: every enclosing scope is copied
/// into each nested scope, and copying whole schemas there made resolution cost
/// grow with the square of the nesting depth.
#[derive(Debug, Clone)]
pub struct ScopedTable {
    pub table: Arc<TableMetadata>,
    pub start_index: usize,
    /// Lexical nesting level; zero is the current SELECT and larger values
    /// are successively enclosing SELECT scopes.
    pub scope_level: usize,
    /// Columns coalesced by a JOIN ... USING or NATURAL JOIN. They remain
    /// addressable by a qualified right-hand reference, but are not candidates
    /// for an unqualified reference because the merged output column owns
    /// the name.
    pub hidden_unqualified_columns: HashSet<String>,
    /// For a column merged by USING or NATURAL, the output indexes of every
    /// other side. An unqualified reference to a merged name resolves to
    /// `COALESCE(left, right, ...)` so that RIGHT and FULL joins report the key
    /// from whichever joined input is present.
    pub merged_column_partners: HashMap<String, Vec<usize>>,
    /// Column name to position in `table.columns`, built once when the table
    /// enters scope. Resolution looks a name up once per reference, so scanning
    /// the column list made a wide projection cost the square of its width.
    /// Shared alongside the metadata it indexes so the two cannot drift apart.
    ///
    /// `None` for narrow tables, where building the map costs more than the
    /// scans it saves; see [`COLUMN_INDEX_THRESHOLD`].
    column_index: Option<Arc<HashMap<String, usize>>>,
}

/// Column count above which a scoped table gets a hash index.
///
/// Below this a linear scan of the column list wins: the map allocation is paid
/// once per table per scope, and measurement showed narrow tables getting 10-15%
/// slower when every table was indexed unconditionally.
const COLUMN_INDEX_THRESHOLD: usize = 32;

impl ScopedTable {
    pub fn new(table: impl Into<Arc<TableMetadata>>, start_index: usize) -> Self {
        let table = table.into();
        let column_index = (table.columns.len() > COLUMN_INDEX_THRESHOLD).then(|| {
            // On a duplicate name the first position wins, matching the linear
            // scan this replaces.
            let mut index = HashMap::with_capacity(table.columns.len());
            for (position, column) in table.columns.iter().enumerate() {
                index.entry(column.name.clone()).or_insert(position);
            }
            Arc::new(index)
        });
        Self {
            table,
            start_index,
            scope_level: 0,
            hidden_unqualified_columns: HashSet::new(),
            merged_column_partners: HashMap::new(),
            column_index,
        }
    }

    /// Position of `column` in this table, or `None` if it has no such column.
    pub fn column_position(&self, column: &str) -> Option<usize> {
        match &self.column_index {
            Some(index) => index.get(column).copied(),
            None => self.table.get_column_index(column),
        }
    }

    pub fn hide_unqualified_columns(&mut self, columns: &[String]) {
        self.hidden_unqualified_columns
            .extend(columns.iter().cloned());
    }

    /// Record that `column` is merged with the output column at `partner_index`.
    pub fn merge_column_with(&mut self, column: &str, partner_index: usize) {
        let partners = self
            .merged_column_partners
            .entry(column.to_string())
            .or_default();
        if !partners.contains(&partner_index) {
            partners.push(partner_index);
        }
    }
}

pub type SubqueryPlanner<'p> = dyn Fn(&Statement, &[ScopedTable]) -> Result<(LogicalPlan, Vec<ColumnMetadata>), PlannerError>
    + 'p;

/// Type checker for SQL expressions.
///
/// Performs type inference and validation for expressions, ensuring that
/// operations are valid for the types involved and that constraints are met.
///
/// # Examples
///
/// ```
/// use alopex_sql::catalog::MemoryCatalog;
/// use alopex_sql::planner::type_checker::TypeChecker;
///
/// let catalog = MemoryCatalog::new();
/// let type_checker = TypeChecker::new(&catalog);
/// ```
pub struct TypeChecker<'a, C: Catalog + ?Sized> {
    catalog: &'a C,
}

impl<'a, C: Catalog + ?Sized> TypeChecker<'a, C> {
    /// Create a new TypeChecker with the given catalog.
    pub fn new(catalog: &'a C) -> Self {
        Self { catalog }
    }

    /// Get a reference to the catalog.
    pub fn catalog(&self) -> &'a C {
        self.catalog
    }

    /// Infer the type of an expression within a table context.
    ///
    /// Recursively analyzes the expression to determine its type, resolving
    /// column references against the provided table metadata.
    ///
    /// # Errors
    ///
    /// Returns an error if:
    /// - A column reference cannot be resolved
    /// - A binary operation is invalid for the operand types
    /// - A function call has invalid arguments
    pub fn infer_type(
        &self,
        expr: &Expr,
        table: &TableMetadata,
    ) -> Result<TypedExpr, PlannerError> {
        let scope = [ScopedTable::new(table.clone(), 0)];
        self.infer_type_with_scope(expr, &scope, &|stmt, _outer| {
            let planner = crate::planner::Planner::new(self.catalog);
            let plan = planner.plan(stmt)?;
            Ok((plan, Vec::new()))
        })
    }

    pub fn infer_type_with_scope(
        &self,
        expr: &Expr,
        scope: &[ScopedTable],
        plan_subquery: &SubqueryPlanner<'_>,
    ) -> Result<TypedExpr, PlannerError> {
        let span = expr.span;
        match &expr.kind {
            ExprKind::Literal { literal: lit } => self.infer_literal_type(lit, span),

            ExprKind::ColumnRef {
                table: table_qualifier,
                column,
            } => self.infer_column_ref_type_with_scope(
                scope,
                table_qualifier.as_deref(),
                column,
                span,
            ),

            ExprKind::BinaryOp { left, op, right } => {
                self.infer_binary_op_type_with_scope(left, *op, right, scope, plan_subquery, span)
            }

            ExprKind::UnaryOp { op, operand } => {
                self.infer_unary_op_type_with_scope(*op, operand, scope, plan_subquery, span)
            }

            ExprKind::FunctionCall {
                name,
                args,
                distinct,
                star,
            } => self.infer_function_call_type_with_scope(
                name,
                args,
                *distinct,
                *star,
                scope,
                plan_subquery,
                span,
            ),

            ExprKind::Cast { expr, target_type } => {
                let typed_expr = self.infer_type_with_scope(expr, scope, plan_subquery)?;
                Ok(TypedExpr::cast(
                    typed_expr,
                    ResolvedType::from_ast(target_type),
                    span,
                ))
            }

            ExprKind::Between {
                expr,
                low,
                high,
                negated,
            } => self.infer_between_type_with_scope(
                expr,
                low,
                high,
                *negated,
                scope,
                plan_subquery,
                span,
            ),

            ExprKind::Like {
                expr,
                pattern,
                escape,
                negated,
                kind,
            } => self.infer_like_type_with_scope(
                expr,
                pattern,
                escape.as_deref(),
                *negated,
                *kind,
                scope,
                plan_subquery,
                span,
            ),

            ExprKind::InList {
                expr,
                list,
                negated,
            } => {
                self.infer_in_list_type_with_scope(expr, list, *negated, scope, plan_subquery, span)
            }

            ExprKind::IsNull { expr, negated } => {
                self.infer_is_null_type_with_scope(expr, *negated, scope, plan_subquery, span)
            }

            ExprKind::VectorLiteral { values } => self.infer_vector_literal_type(values, span),

            ExprKind::ScalarSubquery { subquery } => {
                let (plan, schema) = plan_subquery(subquery, scope)?;
                let value_type = single_column_type(&schema, span)?;
                Ok(TypedExpr {
                    kind: TypedExprKind::ScalarSubquery(Box::new(plan)),
                    resolved_type: value_type,
                    span,
                })
            }
            ExprKind::InSubquery {
                expr,
                subquery,
                negated,
            } => {
                let expr_typed = self.infer_type_with_scope(expr, scope, plan_subquery)?;
                let (plan, schema) = plan_subquery(subquery, scope)?;
                let value_type = single_column_type(&schema, span)?;
                self.check_comparison_op(&expr_typed.resolved_type, &value_type, span)?;
                Ok(TypedExpr {
                    kind: TypedExprKind::InSubquery {
                        expr: Box::new(expr_typed),
                        subquery: Box::new(plan),
                        negated: *negated,
                    },
                    resolved_type: ResolvedType::Boolean,
                    span,
                })
            }
            ExprKind::Exists { subquery, negated } => {
                let (plan, _schema) = plan_subquery(subquery, scope)?;
                Ok(TypedExpr {
                    kind: TypedExprKind::Exists {
                        subquery: Box::new(plan),
                        negated: *negated,
                    },
                    resolved_type: ResolvedType::Boolean,
                    span,
                })
            }
            ExprKind::Quantified {
                expr,
                op,
                quantifier,
                subquery,
            } => {
                let expr_typed = self.infer_type_with_scope(expr, scope, plan_subquery)?;
                let (plan, schema) = plan_subquery(subquery, scope)?;
                let value_type = single_column_type(&schema, span)?;
                self.check_binary_op(*op, &expr_typed.resolved_type, &value_type, span)?;
                Ok(TypedExpr {
                    kind: TypedExprKind::Quantified {
                        expr: Box::new(expr_typed),
                        op: *op,
                        quantifier: match quantifier {
                            AstQuantifier::Any => Quantifier::Any,
                            AstQuantifier::All => Quantifier::All,
                        },
                        subquery: Box::new(plan),
                    },
                    resolved_type: ResolvedType::Boolean,
                    span,
                })
            }
        }
    }

    /// Infer the type of a literal value.
    fn infer_literal_type(&self, lit: &Literal, span: Span) -> Result<TypedExpr, PlannerError> {
        let (kind, resolved_type) = match lit {
            Literal::Number(s) => {
                // Determine if it's integer or floating point
                let resolved_type = if s.contains('.') || s.contains('e') || s.contains('E') {
                    ResolvedType::Double
                } else {
                    // Check if it fits in i32 or needs i64
                    if s.parse::<i32>().is_ok() {
                        ResolvedType::Integer
                    } else {
                        ResolvedType::BigInt
                    }
                };
                (TypedExprKind::Literal(lit.clone()), resolved_type)
            }
            Literal::String(_) => (TypedExprKind::Literal(lit.clone()), ResolvedType::Text),
            Literal::Interval(_) => {
                return Err(PlannerError::unsupported_feature(
                    "INTERVAL literals require a SQL-TS semantic layer",
                    "0.9.0",
                    span,
                ));
            }
            Literal::Boolean(_) => (TypedExprKind::Literal(lit.clone()), ResolvedType::Boolean),
            Literal::Null => (TypedExprKind::Literal(lit.clone()), ResolvedType::Null),
        };

        Ok(TypedExpr {
            kind,
            resolved_type,
            span,
        })
    }

    /// Infer the type of a column reference.
    #[allow(dead_code)]
    fn infer_column_ref_type(
        &self,
        table: &TableMetadata,
        column_name: &str,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        // Find the column in the table
        let (column_index, column) = table
            .columns
            .iter()
            .enumerate()
            .find(|(_, c)| c.name == column_name)
            .ok_or_else(|| PlannerError::ColumnNotFound {
                column: column_name.to_string(),
                table: table.name.clone(),
                line: span.start.line,
                col: span.start.column,
            })?;

        Ok(TypedExpr {
            kind: TypedExprKind::ColumnRef {
                table: table.name.clone(),
                column: column_name.to_string(),
                column_index,
            },
            resolved_type: column.data_type.clone(),
            span,
        })
    }

    fn infer_column_ref_type_with_scope(
        &self,
        scope: &[ScopedTable],
        table_qualifier: Option<&str>,
        column_name: &str,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let levels = scope
            .iter()
            .map(|table| table.scope_level)
            .collect::<BTreeSet<_>>();
        let mut qualifier_found = false;

        for level in levels {
            let candidates = scope
                .iter()
                .filter(|table| table.scope_level == level)
                .filter(|table| {
                    table_qualifier.is_some()
                        || !table.hidden_unqualified_columns.contains(column_name)
                })
                .collect::<Vec<_>>();
            if candidates.is_empty() {
                continue;
            }
            if let Some(qualifier) = table_qualifier {
                let qualified = candidates
                    .iter()
                    .filter(|table| table.table.name == qualifier)
                    .collect::<Vec<_>>();
                match qualified.len() {
                    0 => continue,
                    1 => qualifier_found = true,
                    _ => {
                        return Err(PlannerError::ambiguous_column(
                            column_name,
                            qualified
                                .iter()
                                .map(|table| table.table.name.clone())
                                .collect(),
                            span,
                        ));
                    }
                }
            }

            // Resolution happens through each table's own column index rather
            // than by scanning its column list, because this runs once per
            // column reference and the scan made a wide projection quadratic.
            let mut matches = candidates.iter().filter(|table| {
                table_qualifier.is_none_or(|qualifier| table.table.name == qualifier)
                    && table.column_position(column_name).is_some()
            });
            let found = matches.next();
            let second = matches.next();

            match (found, second) {
                (Some(_), Some(_)) => {
                    return Err(PlannerError::ambiguous_column(
                        column_name,
                        candidates
                            .iter()
                            .filter(|table| table.column_position(column_name).is_some())
                            .map(|table| table.table.name.clone())
                            .collect(),
                        span,
                    ));
                }
                (None, _) => {
                    if table_qualifier.is_some() {
                        // A qualified name that the named table does not have is
                        // an error here; it cannot be a correlated reference.
                        return Err(PlannerError::column_not_found(
                            column_name,
                            candidates
                                .first()
                                .map(|table| table.table.name.as_str())
                                .unwrap_or("unknown"),
                            span,
                        ));
                    }
                    // A missing local name may be a correlated reference. Only
                    // this case falls back to the next enclosing scope.
                    continue;
                }
                (Some(scoped), None) => {
                    let column_index = scoped
                        .column_position(column_name)
                        .expect("filtered on the column being present");
                    let column = &scoped.table.columns[column_index];
                    let own_ref = TypedExpr {
                        kind: TypedExprKind::ColumnRef {
                            table: scoped.table.name.clone(),
                            column: column_name.to_string(),
                            column_index: scoped.start_index + column_index,
                        },
                        resolved_type: column.data_type.clone(),
                        span,
                    };

                    // A USING/NATURAL common column is one output column formed
                    // from both inputs. An unqualified reference must see the
                    // merged value, otherwise a RIGHT or FULL join reports the
                    // left side's NULL for rows that only exist on the right.
                    if table_qualifier.is_none()
                        && let Some(partner_indices) =
                            scoped.merged_column_partners.get(column_name)
                    {
                        let mut args = Vec::with_capacity(partner_indices.len() + 1);
                        args.push(own_ref);
                        args.extend(partner_indices.iter().map(|&partner_index| TypedExpr {
                            kind: TypedExprKind::ColumnRef {
                                table: scoped.table.name.clone(),
                                column: column_name.to_string(),
                                column_index: partner_index,
                            },
                            resolved_type: column.data_type.clone(),
                            span,
                        }));
                        return Ok(TypedExpr {
                            kind: TypedExprKind::FunctionCall {
                                name: "coalesce".to_string(),
                                args,
                                distinct: false,
                                star: false,
                            },
                            resolved_type: column.data_type.clone(),
                            span,
                        });
                    }

                    return Ok(own_ref);
                }
            }
        }

        let table = scope
            .iter()
            .min_by_key(|table| table.scope_level)
            .map(|table| table.table.name.clone())
            .unwrap_or_else(|| "unknown".to_string());
        if let Some(qualifier) = table_qualifier
            && !qualifier_found
        {
            return Err(PlannerError::table_not_found(qualifier, span));
        }
        Err(PlannerError::column_not_found(column_name, table, span))
    }

    /// Infer the type of a binary operation.
    #[allow(dead_code)]
    fn infer_binary_op_type(
        &self,
        left: &Expr,
        op: BinaryOp,
        right: &Expr,
        table: &TableMetadata,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let left_typed = self.infer_type(left, table)?;
        let right_typed = self.infer_type(right, table)?;

        let result_type = self.check_binary_op(
            op,
            &left_typed.resolved_type,
            &right_typed.resolved_type,
            span,
        )?;

        Ok(TypedExpr {
            kind: TypedExprKind::BinaryOp {
                left: Box::new(left_typed),
                op,
                right: Box::new(right_typed),
            },
            resolved_type: result_type,
            span,
        })
    }

    fn infer_binary_op_type_with_scope(
        &self,
        left: &Expr,
        op: BinaryOp,
        right: &Expr,
        scope: &[ScopedTable],
        plan_subquery: &SubqueryPlanner<'_>,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let left_typed = self.infer_type_with_scope(left, scope, plan_subquery)?;
        let right_typed = self.infer_type_with_scope(right, scope, plan_subquery)?;

        let result_type = self.check_binary_op(
            op,
            &left_typed.resolved_type,
            &right_typed.resolved_type,
            span,
        )?;

        Ok(TypedExpr {
            kind: TypedExprKind::BinaryOp {
                left: Box::new(left_typed),
                op,
                right: Box::new(right_typed),
            },
            resolved_type: result_type,
            span,
        })
    }

    /// Check binary operation and return the result type.
    ///
    /// Validates that the operator is valid for the given operand types
    /// and returns the result type.
    ///
    /// # Type Rules
    ///
    /// - Arithmetic operators (+, -, *, /, %): Require numeric operands
    /// - Comparison operators (=, <>, <, >, <=, >=): Require compatible types
    /// - Logical operators (AND, OR): Require boolean operands
    /// - String concatenation (||): Requires text operands
    pub fn check_binary_op(
        &self,
        op: BinaryOp,
        left: &ResolvedType,
        right: &ResolvedType,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        use BinaryOp::*;
        use ResolvedType::*;

        match op {
            // Arithmetic operators: require numeric types
            Add | Sub | Mul | Div => {
                let result = self.check_arithmetic_op(left, right, span)?;
                Ok(result)
            }

            // Remainder is defined only for integral operands.
            Mod => self.check_modulo_op(left, right, span),

            // Comparison operators: require compatible types, return boolean
            Eq | Neq | Lt | Gt | LtEq | GtEq => {
                self.check_comparison_op(left, right, span)?;
                Ok(Boolean)
            }

            // Logical operators: require boolean types
            And | Or => {
                self.check_logical_op(left, right, span)?;
                Ok(Boolean)
            }

            // String concatenation: requires text types
            StringConcat => {
                self.check_string_concat_op(left, right, span)?;
                Ok(Text)
            }
        }
    }

    /// Check arithmetic operation and return the result type.
    fn check_arithmetic_op(
        &self,
        left: &ResolvedType,
        right: &ResolvedType,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        use ResolvedType::*;

        // Handle NULL propagation
        if matches!(left, Null) || matches!(right, Null) {
            return Ok(Null);
        }

        // Determine result type based on numeric type hierarchy
        match (left, right) {
            // Integer operations
            (Integer, Integer) => Ok(Integer),
            (Integer, BigInt) | (BigInt, Integer) | (BigInt, BigInt) => Ok(BigInt),
            (Float, Float) => Ok(Float),
            // f32 has 24 bits of mantissa and cannot hold the whole i32 range,
            // so an INTEGER mixed with FLOAT widens to DOUBLE.
            (Integer, Float)
            | (Float, Integer)
            | (Integer, Double)
            | (Double, Integer)
            | (BigInt, Float)
            | (Float, BigInt)
            | (BigInt, Double)
            | (Double, BigInt)
            | (Float, Double)
            | (Double, Float)
            | (Double, Double) => Ok(Double),

            _ => Err(PlannerError::InvalidOperator {
                op: "arithmetic".to_string(),
                type_name: format!("{} and {}", left.type_name(), right.type_name()),
                line: span.start.line,
                column: span.start.column,
            }),
        }
    }

    /// Check remainder operands and return the integral result type.
    fn check_modulo_op(
        &self,
        left: &ResolvedType,
        right: &ResolvedType,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        use ResolvedType::*;

        if matches!(left, Null) || matches!(right, Null) {
            return Ok(Null);
        }

        match (left, right) {
            (Integer, Integer) => Ok(Integer),
            (Integer, BigInt) | (BigInt, Integer) | (BigInt, BigInt) => Ok(BigInt),
            _ => Err(PlannerError::InvalidOperator {
                op: "modulo".to_string(),
                type_name: format!("{} and {}", left.type_name(), right.type_name()),
                line: span.start.line,
                column: span.start.column,
            }),
        }
    }

    /// Check comparison operation for compatible types.
    pub(crate) fn check_comparison_op(
        &self,
        left: &ResolvedType,
        right: &ResolvedType,
        span: Span,
    ) -> Result<(), PlannerError> {
        use ResolvedType::*;

        // NULL can be compared with anything
        if matches!(left, Null) || matches!(right, Null) {
            return Ok(());
        }

        // Check type compatibility
        let compatible = match (left, right) {
            // Same types are always comparable
            (a, b) if a == b => true,

            // Numeric types are comparable with each other
            (Integer | BigInt | Float | Double, Integer | BigInt | Float | Double) => true,

            // Text types
            (Text, Text) => true,

            // Boolean types
            (Boolean, Boolean) => true,

            // Timestamp types
            (Timestamp, Timestamp) => true,

            // Vector types (for equality only, dimension must match)
            (Vector { dimension: d1, .. }, Vector { dimension: d2, .. }) => d1 == d2,

            _ => false,
        };

        if compatible {
            Ok(())
        } else {
            Err(PlannerError::TypeMismatch {
                expected: left.type_name().to_string(),
                found: right.type_name().to_string(),
                line: span.start.line,
                column: span.start.column,
            })
        }
    }

    /// Check logical operation for boolean types.
    fn check_logical_op(
        &self,
        left: &ResolvedType,
        right: &ResolvedType,
        span: Span,
    ) -> Result<(), PlannerError> {
        use ResolvedType::*;

        // NULL is allowed (three-valued logic)
        let left_ok = matches!(left, Boolean | Null);
        let right_ok = matches!(right, Boolean | Null);

        if !left_ok {
            return Err(PlannerError::TypeMismatch {
                expected: "Boolean".to_string(),
                found: left.type_name().to_string(),
                line: span.start.line,
                column: span.start.column,
            });
        }

        if !right_ok {
            return Err(PlannerError::TypeMismatch {
                expected: "Boolean".to_string(),
                found: right.type_name().to_string(),
                line: span.start.line,
                column: span.start.column,
            });
        }

        Ok(())
    }

    /// Check string concatenation operation.
    fn check_string_concat_op(
        &self,
        left: &ResolvedType,
        right: &ResolvedType,
        span: Span,
    ) -> Result<(), PlannerError> {
        use ResolvedType::*;

        // NULL is allowed
        let left_ok = matches!(left, Text | Null);
        let right_ok = matches!(right, Text | Null);

        if !left_ok {
            return Err(PlannerError::TypeMismatch {
                expected: "Text".to_string(),
                found: left.type_name().to_string(),
                line: span.start.line,
                column: span.start.column,
            });
        }

        if !right_ok {
            return Err(PlannerError::TypeMismatch {
                expected: "Text".to_string(),
                found: right.type_name().to_string(),
                line: span.start.line,
                column: span.start.column,
            });
        }

        Ok(())
    }

    /// Infer the type of a unary operation.
    #[allow(dead_code)]
    fn infer_unary_op_type(
        &self,
        op: UnaryOp,
        operand: &Expr,
        table: &TableMetadata,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let operand_typed = self.infer_type(operand, table)?;

        let result_type = match op {
            UnaryOp::Not => {
                // NOT requires boolean operand
                if !matches!(
                    operand_typed.resolved_type,
                    ResolvedType::Boolean | ResolvedType::Null
                ) {
                    return Err(PlannerError::TypeMismatch {
                        expected: "Boolean".to_string(),
                        found: operand_typed.resolved_type.type_name().to_string(),
                        line: span.start.line,
                        column: span.start.column,
                    });
                }
                ResolvedType::Boolean
            }
            UnaryOp::Minus => {
                // Unary minus requires numeric operand
                match &operand_typed.resolved_type {
                    ResolvedType::Integer => ResolvedType::Integer,
                    ResolvedType::BigInt => ResolvedType::BigInt,
                    ResolvedType::Float => ResolvedType::Float,
                    ResolvedType::Double => ResolvedType::Double,
                    ResolvedType::Null => ResolvedType::Null,
                    other => {
                        return Err(PlannerError::InvalidOperator {
                            op: "unary minus".to_string(),
                            type_name: other.type_name().to_string(),
                            line: span.start.line,
                            column: span.start.column,
                        });
                    }
                }
            }
        };

        Ok(TypedExpr {
            kind: TypedExprKind::UnaryOp {
                op,
                operand: Box::new(operand_typed),
            },
            resolved_type: result_type,
            span,
        })
    }

    fn infer_unary_op_type_with_scope(
        &self,
        op: UnaryOp,
        operand: &Expr,
        scope: &[ScopedTable],
        plan_subquery: &SubqueryPlanner<'_>,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let operand_typed = self.infer_type_with_scope(operand, scope, plan_subquery)?;

        let result_type = match op {
            UnaryOp::Not => {
                if !matches!(
                    operand_typed.resolved_type,
                    ResolvedType::Boolean | ResolvedType::Null
                ) {
                    return Err(PlannerError::TypeMismatch {
                        expected: "Boolean".to_string(),
                        found: operand_typed.resolved_type.type_name().to_string(),
                        line: span.start.line,
                        column: span.start.column,
                    });
                }
                ResolvedType::Boolean
            }
            UnaryOp::Minus => match &operand_typed.resolved_type {
                ResolvedType::Integer => ResolvedType::Integer,
                ResolvedType::BigInt => ResolvedType::BigInt,
                ResolvedType::Float => ResolvedType::Float,
                ResolvedType::Double => ResolvedType::Double,
                ResolvedType::Null => ResolvedType::Null,
                other => {
                    return Err(PlannerError::InvalidOperator {
                        op: "unary minus".to_string(),
                        type_name: other.type_name().to_string(),
                        line: span.start.line,
                        column: span.start.column,
                    });
                }
            },
        };

        Ok(TypedExpr {
            kind: TypedExprKind::UnaryOp {
                op,
                operand: Box::new(operand_typed),
            },
            resolved_type: result_type,
            span,
        })
    }

    /// Infer the type of a function call.
    #[allow(dead_code)]
    fn infer_function_call_type(
        &self,
        name: &str,
        args: &[Expr],
        distinct: bool,
        star: bool,
        table: &TableMetadata,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        // Type-check all arguments first
        let typed_args: Vec<TypedExpr> = args
            .iter()
            .map(|arg| self.infer_type(arg, table))
            .collect::<Result<Vec<_>, _>>()?;

        // Delegate to check_function_call for validation and return type
        let result_type = self.check_function_call(name, &typed_args, distinct, star, span)?;

        Ok(TypedExpr {
            kind: TypedExprKind::FunctionCall {
                name: name.to_string(),
                args: typed_args,
                distinct,
                star,
            },
            resolved_type: result_type,
            span,
        })
    }

    #[allow(clippy::too_many_arguments)]
    fn infer_function_call_type_with_scope(
        &self,
        name: &str,
        args: &[Expr],
        distinct: bool,
        star: bool,
        scope: &[ScopedTable],
        plan_subquery: &SubqueryPlanner<'_>,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let typed_args: Vec<TypedExpr> = args
            .iter()
            .map(|arg| self.infer_type_with_scope(arg, scope, plan_subquery))
            .collect::<Result<Vec<_>, _>>()?;
        let result_type = self.check_function_call(name, &typed_args, distinct, star, span)?;

        Ok(TypedExpr {
            kind: TypedExprKind::FunctionCall {
                name: name.to_string(),
                args: typed_args,
                distinct,
                star,
            },
            resolved_type: result_type,
            span,
        })
    }

    /// Infer the type of a BETWEEN expression.
    #[allow(dead_code)]
    fn infer_between_type(
        &self,
        expr: &Expr,
        low: &Expr,
        high: &Expr,
        negated: bool,
        table: &TableMetadata,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let expr_typed = self.infer_type(expr, table)?;
        let low_typed = self.infer_type(low, table)?;
        let high_typed = self.infer_type(high, table)?;

        // Check that all three expressions have compatible types
        self.check_comparison_op(&expr_typed.resolved_type, &low_typed.resolved_type, span)?;
        self.check_comparison_op(&expr_typed.resolved_type, &high_typed.resolved_type, span)?;

        Ok(TypedExpr {
            kind: TypedExprKind::Between {
                expr: Box::new(expr_typed),
                low: Box::new(low_typed),
                high: Box::new(high_typed),
                negated,
            },
            resolved_type: ResolvedType::Boolean,
            span,
        })
    }

    #[allow(clippy::too_many_arguments)]
    fn infer_between_type_with_scope(
        &self,
        expr: &Expr,
        low: &Expr,
        high: &Expr,
        negated: bool,
        scope: &[ScopedTable],
        plan_subquery: &SubqueryPlanner<'_>,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let expr_typed = self.infer_type_with_scope(expr, scope, plan_subquery)?;
        let low_typed = self.infer_type_with_scope(low, scope, plan_subquery)?;
        let high_typed = self.infer_type_with_scope(high, scope, plan_subquery)?;
        self.check_comparison_op(&expr_typed.resolved_type, &low_typed.resolved_type, span)?;
        self.check_comparison_op(&expr_typed.resolved_type, &high_typed.resolved_type, span)?;

        Ok(TypedExpr {
            kind: TypedExprKind::Between {
                expr: Box::new(expr_typed),
                low: Box::new(low_typed),
                high: Box::new(high_typed),
                negated,
            },
            resolved_type: ResolvedType::Boolean,
            span,
        })
    }

    /// Infer the type of a LIKE expression.
    #[allow(dead_code)]
    #[allow(clippy::too_many_arguments)]
    fn infer_like_type(
        &self,
        expr: &Expr,
        pattern: &Expr,
        escape: Option<&Expr>,
        negated: bool,
        kind: PatternMatchKind,
        table: &TableMetadata,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let expr_typed = self.infer_type(expr, table)?;
        let pattern_typed = self.infer_type(pattern, table)?;

        // Expression must be text
        if !matches!(
            expr_typed.resolved_type,
            ResolvedType::Text | ResolvedType::Null
        ) {
            return Err(PlannerError::TypeMismatch {
                expected: "Text".to_string(),
                found: expr_typed.resolved_type.type_name().to_string(),
                line: expr.span.start.line,
                column: expr.span.start.column,
            });
        }

        // Pattern must be text
        if !matches!(
            pattern_typed.resolved_type,
            ResolvedType::Text | ResolvedType::Null
        ) {
            return Err(PlannerError::TypeMismatch {
                expected: "Text".to_string(),
                found: pattern_typed.resolved_type.type_name().to_string(),
                line: pattern.span.start.line,
                column: pattern.span.start.column,
            });
        }

        let escape_typed = if let Some(esc) = escape {
            let typed = self.infer_type(esc, table)?;
            if !matches!(typed.resolved_type, ResolvedType::Text | ResolvedType::Null) {
                return Err(PlannerError::TypeMismatch {
                    expected: "Text".to_string(),
                    found: typed.resolved_type.type_name().to_string(),
                    line: esc.span.start.line,
                    column: esc.span.start.column,
                });
            }
            Some(Box::new(typed))
        } else {
            None
        };

        Ok(TypedExpr {
            kind: TypedExprKind::Like {
                expr: Box::new(expr_typed),
                pattern: Box::new(pattern_typed),
                escape: escape_typed,
                negated,
                kind,
            },
            resolved_type: ResolvedType::Boolean,
            span,
        })
    }

    #[allow(clippy::too_many_arguments)]
    #[allow(clippy::too_many_arguments)]
    fn infer_like_type_with_scope(
        &self,
        expr: &Expr,
        pattern: &Expr,
        escape: Option<&Expr>,
        negated: bool,
        kind: PatternMatchKind,
        scope: &[ScopedTable],
        plan_subquery: &SubqueryPlanner<'_>,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let expr_typed = self.infer_type_with_scope(expr, scope, plan_subquery)?;
        let pattern_typed = self.infer_type_with_scope(pattern, scope, plan_subquery)?;

        if !matches!(
            expr_typed.resolved_type,
            ResolvedType::Text | ResolvedType::Null
        ) {
            return Err(PlannerError::TypeMismatch {
                expected: "Text".to_string(),
                found: expr_typed.resolved_type.type_name().to_string(),
                line: expr.span.start.line,
                column: expr.span.start.column,
            });
        }

        if !matches!(
            pattern_typed.resolved_type,
            ResolvedType::Text | ResolvedType::Null
        ) {
            return Err(PlannerError::TypeMismatch {
                expected: "Text".to_string(),
                found: pattern_typed.resolved_type.type_name().to_string(),
                line: pattern.span.start.line,
                column: pattern.span.start.column,
            });
        }

        let escape_typed = if let Some(esc) = escape {
            let typed = self.infer_type_with_scope(esc, scope, plan_subquery)?;
            if !matches!(typed.resolved_type, ResolvedType::Text | ResolvedType::Null) {
                return Err(PlannerError::TypeMismatch {
                    expected: "Text".to_string(),
                    found: typed.resolved_type.type_name().to_string(),
                    line: esc.span.start.line,
                    column: esc.span.start.column,
                });
            }
            Some(Box::new(typed))
        } else {
            None
        };

        Ok(TypedExpr {
            kind: TypedExprKind::Like {
                expr: Box::new(expr_typed),
                pattern: Box::new(pattern_typed),
                escape: escape_typed,
                negated,
                kind,
            },
            resolved_type: ResolvedType::Boolean,
            span,
        })
    }

    /// Infer the type of an IN list expression.
    #[allow(dead_code)]
    fn infer_in_list_type(
        &self,
        expr: &Expr,
        list: &[Expr],
        negated: bool,
        table: &TableMetadata,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let expr_typed = self.infer_type(expr, table)?;

        let typed_list: Vec<TypedExpr> = list
            .iter()
            .map(|item| {
                let typed = self.infer_type(item, table)?;
                // Check each item is compatible with the expression
                self.check_comparison_op(
                    &expr_typed.resolved_type,
                    &typed.resolved_type,
                    item.span,
                )?;
                Ok(typed)
            })
            .collect::<Result<Vec<_>, PlannerError>>()?;

        Ok(TypedExpr {
            kind: TypedExprKind::InList {
                expr: Box::new(expr_typed),
                list: typed_list,
                negated,
            },
            resolved_type: ResolvedType::Boolean,
            span,
        })
    }

    fn infer_in_list_type_with_scope(
        &self,
        expr: &Expr,
        list: &[Expr],
        negated: bool,
        scope: &[ScopedTable],
        plan_subquery: &SubqueryPlanner<'_>,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let expr_typed = self.infer_type_with_scope(expr, scope, plan_subquery)?;

        let typed_list: Vec<TypedExpr> = list
            .iter()
            .map(|item| {
                let typed = self.infer_type_with_scope(item, scope, plan_subquery)?;
                self.check_comparison_op(
                    &expr_typed.resolved_type,
                    &typed.resolved_type,
                    item.span,
                )?;
                Ok(typed)
            })
            .collect::<Result<Vec<_>, PlannerError>>()?;

        Ok(TypedExpr {
            kind: TypedExprKind::InList {
                expr: Box::new(expr_typed),
                list: typed_list,
                negated,
            },
            resolved_type: ResolvedType::Boolean,
            span,
        })
    }

    /// Infer the type of an IS NULL expression.
    #[allow(dead_code)]
    fn infer_is_null_type(
        &self,
        expr: &Expr,
        negated: bool,
        table: &TableMetadata,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let expr_typed = self.infer_type(expr, table)?;

        Ok(TypedExpr {
            kind: TypedExprKind::IsNull {
                expr: Box::new(expr_typed),
                negated,
            },
            resolved_type: ResolvedType::Boolean,
            span,
        })
    }

    fn infer_is_null_type_with_scope(
        &self,
        expr: &Expr,
        negated: bool,
        scope: &[ScopedTable],
        plan_subquery: &SubqueryPlanner<'_>,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        let expr_typed = self.infer_type_with_scope(expr, scope, plan_subquery)?;

        Ok(TypedExpr {
            kind: TypedExprKind::IsNull {
                expr: Box::new(expr_typed),
                negated,
            },
            resolved_type: ResolvedType::Boolean,
            span,
        })
    }

    /// Infer the type of a vector literal.
    fn infer_vector_literal_type(
        &self,
        values: &[f64],
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        Ok(TypedExpr {
            kind: TypedExprKind::VectorLiteral(values.to_vec()),
            resolved_type: ResolvedType::Vector {
                dimension: values.len() as u32,
                metric: VectorMetric::Cosine, // Default metric for literals
            },
            span,
        })
    }

    /// Normalize a metric string to VectorMetric enum (case-insensitive).
    ///
    /// # Valid Values
    ///
    /// - "cosine" (case-insensitive) → `VectorMetric::Cosine`
    /// - "l2" (case-insensitive) → `VectorMetric::L2`
    /// - "inner" (case-insensitive) → `VectorMetric::Inner`
    ///
    /// # Errors
    ///
    /// Returns `PlannerError::InvalidMetric` if the value is not recognized.
    pub fn normalize_metric(&self, metric: &str, span: Span) -> Result<VectorMetric, PlannerError> {
        match metric.to_lowercase().as_str() {
            "cosine" => Ok(VectorMetric::Cosine),
            "l2" => Ok(VectorMetric::L2),
            "inner" => Ok(VectorMetric::Inner),
            _ => Err(PlannerError::InvalidMetric {
                value: metric.to_string(),
                line: span.start.line,
                column: span.start.column,
            }),
        }
    }

    /// Check function call and return the result type.
    ///
    /// Validates that the function arguments have correct types and returns
    /// the result type.
    pub fn check_function_call(
        &self,
        name: &str,
        args: &[TypedExpr],
        distinct: bool,
        star: bool,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        let lower_name = name.to_ascii_lowercase();

        match lower_name.as_str() {
            "count" => self.check_count(args, distinct, star, span),
            "sum" => self.check_sum(args, distinct, star, span),
            "total" => self.check_total(args, distinct, star, span),
            "avg" => self.check_avg(args, distinct, star, span),
            "min" => self.check_min_max(args, distinct, star, span),
            "max" => self.check_min_max(args, distinct, star, span),
            "group_concat" => self.check_group_concat(args, distinct, star, span),
            "string_agg" => self.check_string_agg(args, distinct, star, span),
            _ => {
                let Some(signature) = crate::scalar::signature(&lower_name) else {
                    return Err(PlannerError::unsupported_feature(
                        format!("function '{name}'"),
                        "future",
                        span,
                    ));
                };
                if distinct || star {
                    return Err(PlannerError::invalid_expression(format!(
                        "scalar function '{name}' does not support DISTINCT or *"
                    )));
                }
                signature.arity.validate(name, args.len(), span)?;
                (signature.check)(args)?;
                let types: Vec<_> = args.iter().map(|arg| arg.resolved_type.clone()).collect();
                match &signature.ret {
                    crate::scalar::ReturnRule::Fixed(ty) => Ok(ty.clone()),
                    crate::scalar::ReturnRule::FromArgs(rule) => rule(&types),
                }
            }
        }
    }

    pub fn validate_having_expr(
        &self,
        expr: &TypedExpr,
        group_keys: &[TypedExpr],
        aggregates: &[AggregateExpr],
    ) -> Result<(), PlannerError> {
        use std::collections::HashSet;

        let group_key_indices: HashSet<usize> = group_keys
            .iter()
            .filter_map(|expr| match &expr.kind {
                TypedExprKind::ColumnRef { column_index, .. } => Some(*column_index),
                _ => None,
            })
            .collect();

        let aggregate_signatures: HashSet<AggregateSignature> = aggregates
            .iter()
            .map(aggregate_signature_from_expr)
            .collect();

        fn walk(
            expr: &TypedExpr,
            group_key_indices: &HashSet<usize>,
            aggregate_signatures: &HashSet<AggregateSignature>,
        ) -> Result<(), PlannerError> {
            match &expr.kind {
                TypedExprKind::ColumnRef { column_index, .. } => {
                    if group_key_indices.contains(column_index) {
                        Ok(())
                    } else {
                        Err(PlannerError::invalid_expression(
                            "column in HAVING must be in GROUP BY or be aggregated".to_string(),
                        ))
                    }
                }
                TypedExprKind::FunctionCall {
                    name,
                    args,
                    distinct,
                    star,
                } if is_aggregate_name(name) => {
                    let signature = aggregate_signature_from_call(name, args, *distinct, *star)?;
                    if aggregate_signatures.contains(&signature) {
                        Ok(())
                    } else {
                        Err(PlannerError::invalid_expression(
                            "aggregate in HAVING must appear in plan".to_string(),
                        ))
                    }
                }
                TypedExprKind::BinaryOp { left, right, .. } => {
                    walk(left, group_key_indices, aggregate_signatures)?;
                    walk(right, group_key_indices, aggregate_signatures)
                }
                TypedExprKind::UnaryOp { operand, .. } => {
                    walk(operand, group_key_indices, aggregate_signatures)
                }
                TypedExprKind::FunctionCall { args, .. } => {
                    for arg in args {
                        walk(arg, group_key_indices, aggregate_signatures)?;
                    }
                    Ok(())
                }
                TypedExprKind::Between {
                    expr, low, high, ..
                } => {
                    walk(expr, group_key_indices, aggregate_signatures)?;
                    walk(low, group_key_indices, aggregate_signatures)?;
                    walk(high, group_key_indices, aggregate_signatures)
                }
                TypedExprKind::Like {
                    expr,
                    pattern,
                    escape,
                    ..
                } => {
                    walk(expr, group_key_indices, aggregate_signatures)?;
                    walk(pattern, group_key_indices, aggregate_signatures)?;
                    if let Some(esc) = escape {
                        walk(esc, group_key_indices, aggregate_signatures)?;
                    }
                    Ok(())
                }
                TypedExprKind::InList { expr, list, .. } => {
                    walk(expr, group_key_indices, aggregate_signatures)?;
                    for item in list {
                        walk(item, group_key_indices, aggregate_signatures)?;
                    }
                    Ok(())
                }
                TypedExprKind::IsNull { expr, .. } => {
                    walk(expr, group_key_indices, aggregate_signatures)
                }
                _ => Ok(()),
            }
        }

        walk(expr, &group_key_indices, &aggregate_signatures)
    }

    fn check_count(
        &self,
        args: &[TypedExpr],
        distinct: bool,
        star: bool,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        if star {
            if distinct {
                return Err(PlannerError::unsupported_feature(
                    "COUNT(DISTINCT *)",
                    "future",
                    span,
                ));
            }
            if !args.is_empty() {
                return Err(PlannerError::type_mismatch(
                    "no arguments with COUNT(*)",
                    format!("{} arguments", args.len()),
                    span,
                ));
            }
            return Ok(ResolvedType::BigInt);
        }

        if args.len() != 1 {
            return Err(PlannerError::type_mismatch(
                "1 argument",
                format!("{} arguments", args.len()),
                span,
            ));
        }

        if distinct {
            return Ok(ResolvedType::BigInt);
        }

        Ok(ResolvedType::BigInt)
    }

    fn check_sum(
        &self,
        args: &[TypedExpr],
        _distinct: bool,
        star: bool,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        if star {
            return Err(PlannerError::type_mismatch(
                "numeric argument",
                "COUNT(*) style",
                span,
            ));
        }
        let arg = self.require_single_arg(args, span)?;
        if !is_numeric_type(&arg.resolved_type) && arg.resolved_type != ResolvedType::Null {
            return Err(PlannerError::type_mismatch(
                "numeric",
                arg.resolved_type.type_name().to_string(),
                arg.span,
            ));
        }
        Ok(crate::planner::aggregate_expr::sum_result_type(
            &arg.resolved_type,
        ))
    }

    fn check_total(
        &self,
        args: &[TypedExpr],
        distinct: bool,
        star: bool,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        if star {
            return Err(PlannerError::type_mismatch(
                "numeric argument",
                "COUNT(*) style",
                span,
            ));
        }
        if distinct {
            return Err(PlannerError::unsupported_feature(
                "TOTAL(DISTINCT ...)",
                "future",
                span,
            ));
        }
        let arg = self.require_single_arg(args, span)?;
        if !is_numeric_type(&arg.resolved_type) && arg.resolved_type != ResolvedType::Null {
            return Err(PlannerError::type_mismatch(
                "numeric",
                arg.resolved_type.type_name().to_string(),
                arg.span,
            ));
        }
        Ok(ResolvedType::Double)
    }

    fn check_avg(
        &self,
        args: &[TypedExpr],
        _distinct: bool,
        star: bool,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        if star {
            return Err(PlannerError::type_mismatch(
                "numeric argument",
                "COUNT(*) style",
                span,
            ));
        }
        let arg = self.require_single_arg(args, span)?;
        if !is_numeric_type(&arg.resolved_type) && arg.resolved_type != ResolvedType::Null {
            return Err(PlannerError::type_mismatch(
                "numeric",
                arg.resolved_type.type_name().to_string(),
                arg.span,
            ));
        }
        Ok(ResolvedType::Double)
    }

    fn check_min_max(
        &self,
        args: &[TypedExpr],
        _distinct: bool,
        star: bool,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        if star {
            return Err(PlannerError::type_mismatch(
                "argument",
                "COUNT(*) style",
                span,
            ));
        }
        let arg = self.require_single_arg(args, span)?;
        if matches!(arg.resolved_type, ResolvedType::Vector { .. }) {
            return Err(PlannerError::type_mismatch(
                "comparable",
                arg.resolved_type.type_name().to_string(),
                arg.span,
            ));
        }
        Ok(arg.resolved_type.clone())
    }

    fn check_group_concat(
        &self,
        args: &[TypedExpr],
        _distinct: bool,
        star: bool,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        if star {
            return Err(PlannerError::type_mismatch(
                "text argument",
                "COUNT(*) style",
                span,
            ));
        }
        if args.is_empty() || args.len() > 2 {
            return Err(PlannerError::type_mismatch(
                "1 or 2 arguments",
                format!("{} arguments", args.len()),
                span,
            ));
        }
        if !matches!(
            args[0].resolved_type,
            ResolvedType::Text | ResolvedType::Null
        ) {
            return Err(PlannerError::type_mismatch(
                "Text",
                args[0].resolved_type.type_name().to_string(),
                args[0].span,
            ));
        }
        if args.len() == 2
            && !matches!(
                args[1].resolved_type,
                ResolvedType::Text | ResolvedType::Null
            )
        {
            return Err(PlannerError::type_mismatch(
                "Text",
                args[1].resolved_type.type_name().to_string(),
                args[1].span,
            ));
        }
        Ok(ResolvedType::Text)
    }

    fn check_string_agg(
        &self,
        args: &[TypedExpr],
        _distinct: bool,
        star: bool,
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        if star {
            return Err(PlannerError::type_mismatch(
                "text argument",
                "COUNT(*) style",
                span,
            ));
        }
        if args.len() != 2 {
            return Err(PlannerError::type_mismatch(
                "2 arguments",
                format!("{} arguments", args.len()),
                span,
            ));
        }
        if !matches!(
            args[0].resolved_type,
            ResolvedType::Text | ResolvedType::Null
        ) {
            return Err(PlannerError::type_mismatch(
                "Text",
                args[0].resolved_type.type_name().to_string(),
                args[0].span,
            ));
        }
        if !matches!(
            args[1].resolved_type,
            ResolvedType::Text | ResolvedType::Null
        ) {
            return Err(PlannerError::type_mismatch(
                "Text",
                args[1].resolved_type.type_name().to_string(),
                args[1].span,
            ));
        }
        Ok(ResolvedType::Text)
    }

    fn require_single_arg<'b>(
        &self,
        args: &'b [TypedExpr],
        span: Span,
    ) -> Result<&'b TypedExpr, PlannerError> {
        if args.len() != 1 {
            return Err(PlannerError::type_mismatch(
                "1 argument",
                format!("{} arguments", args.len()),
                span,
            ));
        }
        Ok(&args[0])
    }

    /// Check vector_distance function arguments.
    ///
    /// Signature: `vector_distance(column: Vector, vector: Vector, metric: Text) -> Double`
    ///
    /// # Requirements
    ///
    /// - First argument must be a Vector type (column reference)
    /// - Second argument must be a Vector type (vector literal)
    /// - Third argument must be a Text type (metric string)
    /// - Vector dimensions must match
    pub fn check_vector_distance(
        &self,
        args: &[TypedExpr],
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        if args.len() != 3 {
            return Err(PlannerError::TypeMismatch {
                expected: "3 arguments".to_string(),
                found: format!("{} arguments", args.len()),
                line: span.start.line,
                column: span.start.column,
            });
        }

        // First argument: Vector column
        let col_dim = match &args[0].resolved_type {
            ResolvedType::Vector { dimension, .. } => *dimension,
            other => {
                return Err(PlannerError::TypeMismatch {
                    expected: "Vector".to_string(),
                    found: other.type_name().to_string(),
                    line: args[0].span.start.line,
                    column: args[0].span.start.column,
                });
            }
        };

        // Second argument: Vector literal
        let vec_dim = match &args[1].resolved_type {
            ResolvedType::Vector { dimension, .. } => *dimension,
            other => {
                return Err(PlannerError::TypeMismatch {
                    expected: "Vector".to_string(),
                    found: other.type_name().to_string(),
                    line: args[1].span.start.line,
                    column: args[1].span.start.column,
                });
            }
        };

        // Check dimension match
        self.check_vector_dimension(col_dim, vec_dim, args[1].span)?;

        // Third argument: Metric string
        match &args[2].resolved_type {
            ResolvedType::Text => {
                // Validate metric value if it's a literal
                if let TypedExprKind::Literal(Literal::String(s)) = &args[2].kind {
                    self.normalize_metric(s, args[2].span)?;
                }
            }
            ResolvedType::Null => {
                // NULL metric is not allowed
                return Err(PlannerError::TypeMismatch {
                    expected: "Text (metric)".to_string(),
                    found: "Null".to_string(),
                    line: args[2].span.start.line,
                    column: args[2].span.start.column,
                });
            }
            other => {
                return Err(PlannerError::TypeMismatch {
                    expected: "Text (metric)".to_string(),
                    found: other.type_name().to_string(),
                    line: args[2].span.start.line,
                    column: args[2].span.start.column,
                });
            }
        }

        Ok(ResolvedType::Double)
    }

    /// Check vector_similarity function arguments.
    ///
    /// Signature: `vector_similarity(column: Vector, vector: Vector, metric: Text) -> Double`
    ///
    /// Same validation rules as vector_distance.
    pub fn check_vector_similarity(
        &self,
        args: &[TypedExpr],
        span: Span,
    ) -> Result<ResolvedType, PlannerError> {
        // Same validation as vector_distance
        self.check_vector_distance(args, span)
    }

    /// Check that two vector dimensions match.
    ///
    /// # Errors
    ///
    /// Returns `PlannerError::VectorDimensionMismatch` if dimensions don't match.
    pub fn check_vector_dimension(
        &self,
        expected: u32,
        found: u32,
        span: Span,
    ) -> Result<(), PlannerError> {
        if expected != found {
            Err(PlannerError::VectorDimensionMismatch {
                expected,
                found,
                line: span.start.line,
                column: span.start.column,
            })
        } else {
            Ok(())
        }
    }

    // ============================================================
    // INSERT/UPDATE Type Checking Methods (Task 13)
    // ============================================================

    /// Check INSERT values against table columns.
    ///
    /// Validates that:
    /// - The number of values matches the number of columns
    /// - Each value's type is compatible with the column type
    /// - NOT NULL constraints are satisfied
    /// - Vector dimensions match for vector columns
    ///
    /// # Column Order
    ///
    /// If `columns` is empty, uses `TableMetadata.column_names()` order (definition order).
    ///
    /// # Errors
    ///
    /// - `ColumnValueCountMismatch`: Number of values doesn't match columns
    /// - `TypeMismatch`: Value type incompatible with column type
    /// - `NullConstraintViolation`: NULL value for NOT NULL column
    /// - `VectorDimensionMismatch`: Vector dimension mismatch
    pub fn check_insert_values(
        &self,
        table: &TableMetadata,
        columns: &[String],
        values: &[Vec<Expr>],
        span: Span,
    ) -> Result<Vec<Vec<TypedExpr>>, PlannerError> {
        // Determine the target columns
        let target_columns: Vec<&str> = if columns.is_empty() {
            table.column_names()
        } else {
            columns.iter().map(|s| s.as_str()).collect()
        };

        let mut typed_rows = Vec::with_capacity(values.len());

        for row in values {
            // Check value count matches column count
            if row.len() != target_columns.len() {
                return Err(PlannerError::ColumnValueCountMismatch {
                    columns: target_columns.len(),
                    values: row.len(),
                    line: span.start.line,
                    column: span.start.column,
                });
            }

            let mut typed_values = Vec::with_capacity(row.len());

            for (value, col_name) in row.iter().zip(target_columns.iter()) {
                // Get column metadata
                let col_meta =
                    table
                        .get_column(col_name)
                        .ok_or_else(|| PlannerError::ColumnNotFound {
                            column: col_name.to_string(),
                            table: table.name.clone(),
                            line: span.start.line,
                            col: span.start.column,
                        })?;

                // Type-check the value expression
                let typed_value = self.infer_type(value, table)?;

                // Check NOT NULL constraint
                self.check_null_constraint(col_meta, &typed_value, value.span)?;

                // Check type compatibility
                self.check_type_compatibility(
                    &col_meta.data_type,
                    &typed_value.resolved_type,
                    value.span,
                )?;

                let typed_value =
                    self.coerce_column_value(&col_meta.data_type, typed_value, value.span);

                // For vector types, also check dimension
                if let (
                    ResolvedType::Vector {
                        dimension: expected_dim,
                        ..
                    },
                    ResolvedType::Vector {
                        dimension: actual_dim,
                        ..
                    },
                ) = (&col_meta.data_type, &typed_value.resolved_type)
                {
                    self.check_vector_dimension(*expected_dim, *actual_dim, value.span)?;
                }

                typed_values.push(typed_value);
            }

            typed_rows.push(typed_values);
        }

        Ok(typed_rows)
    }

    /// Check UPDATE assignment type compatibility.
    ///
    /// Validates that the value's type is compatible with the column type.
    ///
    /// # Errors
    ///
    /// - `ColumnNotFound`: Column doesn't exist
    /// - `TypeMismatch`: Value type incompatible with column type
    /// - `NullConstraintViolation`: NULL value for NOT NULL column
    /// - `VectorDimensionMismatch`: Vector dimension mismatch
    pub fn check_assignment(
        &self,
        table: &TableMetadata,
        column: &str,
        value: &Expr,
        span: Span,
    ) -> Result<TypedExpr, PlannerError> {
        // Get column metadata
        let col_meta = table
            .get_column(column)
            .ok_or_else(|| PlannerError::ColumnNotFound {
                column: column.to_string(),
                table: table.name.clone(),
                line: span.start.line,
                col: span.start.column,
            })?;

        // Type-check the value expression
        let typed_value = self.infer_type(value, table)?;

        // Check NOT NULL constraint
        self.check_null_constraint(col_meta, &typed_value, value.span)?;

        // Check type compatibility
        self.check_type_compatibility(&col_meta.data_type, &typed_value.resolved_type, value.span)?;

        let typed_value = self.coerce_column_value(&col_meta.data_type, typed_value, value.span);

        // For vector types, also check dimension
        if let (
            ResolvedType::Vector {
                dimension: expected_dim,
                ..
            },
            ResolvedType::Vector {
                dimension: actual_dim,
                ..
            },
        ) = (&col_meta.data_type, &typed_value.resolved_type)
        {
            self.check_vector_dimension(*expected_dim, *actual_dim, value.span)?;
        }

        Ok(typed_value)
    }

    /// Check NOT NULL constraint for a value.
    ///
    /// # Errors
    ///
    /// Returns `PlannerError::NullConstraintViolation` if the column has NOT NULL
    /// constraint and the value is NULL.
    pub fn check_null_constraint(
        &self,
        column: &crate::catalog::ColumnMetadata,
        value: &TypedExpr,
        span: Span,
    ) -> Result<(), PlannerError> {
        if column.not_null && matches!(value.resolved_type, ResolvedType::Null) {
            Err(PlannerError::NullConstraintViolation {
                column: column.name.clone(),
                line: span.start.line,
                col: span.start.column,
            })
        } else {
            Ok(())
        }
    }

    /// Check type compatibility between expected and actual types.
    ///
    /// Uses implicit type conversion rules defined in `ResolvedType::can_cast_to`.
    ///
    /// # Errors
    ///
    /// Returns `PlannerError::TypeMismatch` if types are incompatible.
    fn check_type_compatibility(
        &self,
        expected: &ResolvedType,
        actual: &ResolvedType,
        span: Span,
    ) -> Result<(), PlannerError> {
        // Same type is always compatible
        if expected == actual {
            return Ok(());
        }

        // Check if implicit cast is allowed
        if actual.can_cast_to(expected) {
            return Ok(());
        }

        // Special case: Vector types with same dimension but different metric are compatible
        // (the column's metric is used)
        if let (
            ResolvedType::Vector {
                dimension: d1,
                metric: _,
            },
            ResolvedType::Vector {
                dimension: d2,
                metric: _,
            },
        ) = (expected, actual)
        {
            // Dimensions must match for vector compatibility
            if *d1 == *d2 {
                return Ok(());
            }
            // Different dimensions will fall through to TypeMismatch error
        }

        Err(PlannerError::TypeMismatch {
            expected: expected.type_name().to_string(),
            found: actual.type_name().to_string(),
            line: span.start.line,
            column: span.start.column,
        })
    }

    /// Insert an execution-time coercion where a column accepts a value whose
    /// source representation differs from its storage representation.
    fn coerce_column_value(
        &self,
        expected: &ResolvedType,
        value: TypedExpr,
        span: Span,
    ) -> TypedExpr {
        if value.resolved_type != *expected
            && value.resolved_type != ResolvedType::Null
            && matches!(
                expected,
                ResolvedType::Integer
                    | ResolvedType::BigInt
                    | ResolvedType::Float
                    | ResolvedType::Double
                    | ResolvedType::Timestamp
            )
        {
            TypedExpr::cast(value, expected.clone(), span)
        } else {
            value
        }
    }
}

fn is_numeric_type(ty: &ResolvedType) -> bool {
    matches!(
        ty,
        ResolvedType::Integer | ResolvedType::BigInt | ResolvedType::Float | ResolvedType::Double
    )
}

#[derive(Debug, Clone, PartialEq, Eq, Hash)]
struct AggregateSignature {
    name: String,
    distinct: bool,
    star: bool,
    arg_key: Option<String>,
    separator: Option<String>,
}

fn is_aggregate_name(name: &str) -> bool {
    matches!(
        name.to_ascii_lowercase().as_str(),
        "count" | "sum" | "total" | "avg" | "min" | "max" | "group_concat" | "string_agg"
    )
}

fn aggregate_signature_from_expr(expr: &AggregateExpr) -> AggregateSignature {
    let (name, separator, star, arg) = match &expr.function {
        AggregateFunction::Count => (
            "count".to_string(),
            None,
            expr.arg.is_none(),
            expr.arg.as_ref(),
        ),
        AggregateFunction::Sum => ("sum".to_string(), None, false, expr.arg.as_ref()),
        AggregateFunction::Total => ("total".to_string(), None, false, expr.arg.as_ref()),
        AggregateFunction::Avg => ("avg".to_string(), None, false, expr.arg.as_ref()),
        AggregateFunction::Min => ("min".to_string(), None, false, expr.arg.as_ref()),
        AggregateFunction::Max => ("max".to_string(), None, false, expr.arg.as_ref()),
        AggregateFunction::GroupConcat { separator } => (
            "group_concat".to_string(),
            separator.clone(),
            false,
            expr.arg.as_ref(),
        ),
        AggregateFunction::StringAgg { separator } => (
            "string_agg".to_string(),
            separator.clone(),
            false,
            expr.arg.as_ref(),
        ),
    };
    AggregateSignature {
        name,
        distinct: expr.distinct,
        star,
        arg_key: arg.map(typed_expr_signature),
        separator,
    }
}

fn aggregate_signature_from_call(
    name: &str,
    args: &[TypedExpr],
    distinct: bool,
    star: bool,
) -> Result<AggregateSignature, PlannerError> {
    let separator = if name.eq_ignore_ascii_case("group_concat") && args.len() == 2 {
        if let TypedExprKind::Literal(Literal::String(value)) = &args[1].kind {
            Some(value.clone())
        } else {
            return Err(PlannerError::invalid_expression(
                "GROUP_CONCAT separator must be a string literal".to_string(),
            ));
        }
    } else if name.eq_ignore_ascii_case("string_agg") && args.len() == 2 {
        if let TypedExprKind::Literal(Literal::String(value)) = &args[1].kind {
            Some(value.clone())
        } else {
            return Err(PlannerError::invalid_expression(
                "STRING_AGG separator must be a string literal".to_string(),
            ));
        }
    } else {
        None
    };
    Ok(AggregateSignature {
        name: name.to_ascii_lowercase(),
        distinct,
        star,
        arg_key: args.first().map(typed_expr_signature),
        separator,
    })
}

fn typed_expr_signature(expr: &TypedExpr) -> String {
    format!("{:?}", expr.kind)
}

fn single_column_type(schema: &[ColumnMetadata], span: Span) -> Result<ResolvedType, PlannerError> {
    match schema {
        [column] => Ok(column.data_type.clone()),
        [] => Err(PlannerError::type_mismatch(
            "one-column subquery",
            "zero-column subquery",
            span,
        )),
        _ => Err(PlannerError::type_mismatch(
            "one-column subquery",
            format!("{} columns", schema.len()),
            span,
        )),
    }
}

// Tests are in type_checker/tests.rs
#[cfg(test)]
#[path = "type_checker/tests.rs"]
mod tests;