grafeo_engine/query/planner/lpg/

mod.rs

//! LPG (Labeled Property Graph) planner.
//!
//! Converts logical plans with LPG operators (NodeScan, Expand, etc.) to
//! physical operators that execute against an LPG store.

mod aggregate;
mod expand;
mod expression;
mod filter;
mod join;
mod mutation;
mod project;
mod scan;

#[cfg(feature = "algos")]
use crate::query::plan::CallProcedureOp;
use crate::query::plan::{
    AddLabelOp, AggregateFunction as LogicalAggregateFunction, AggregateOp, AntiJoinOp, ApplyOp,
    BinaryOp, CreateEdgeOp, CreateNodeOp, DeleteEdgeOp, DeleteNodeOp, DistinctOp,
    EntityKind as LogicalEntityKind, ExceptOp, ExpandDirection, ExpandOp, FilterOp,
    HorizontalAggregateOp, IntersectOp, JoinOp, JoinType, LeftJoinOp, LimitOp, LogicalExpression,
    LogicalOperator, LogicalPlan, MapCollectOp, MergeOp, MergeRelationshipOp, MultiWayJoinOp,
    NodeScanOp, OtherwiseOp, PathMode, RemoveLabelOp, ReturnOp, SetPropertyOp, ShortestPathOp,
    SkipOp, SortOp, SortOrder, UnaryOp, UnionOp, UnwindOp,
};
use grafeo_common::types::{EpochId, TransactionId};
use grafeo_common::types::{LogicalType, Value};
use grafeo_common::utils::error::{Error, Result};
use grafeo_core::execution::AdaptiveContext;
use grafeo_core::execution::operators::{
    AddLabelOperator, AggregateExpr as PhysicalAggregateExpr, ApplyOperator, ConstraintValidator,
    CreateEdgeOperator, CreateNodeOperator, DeleteEdgeOperator, DeleteNodeOperator, EmptyOperator,
    EntityKind, ExecutionPathMode, ExpandOperator, ExpandStep, ExpressionPredicate,
    FactorizedAggregate, FactorizedAggregateOperator, FilterExpression, FilterOperator,
    HashAggregateOperator, HashJoinOperator, HorizontalAggregateOperator,
    JoinType as PhysicalJoinType, LazyFactorizedChainOperator, LeapfrogJoinOperator,
    MapCollectOperator, MergeOperator, MergeRelationshipConfig, MergeRelationshipOperator,
    NestedLoopJoinOperator, NodeListOperator, NullOrder, Operator, ParameterScanOperator,
    ProjectExpr, ProjectOperator, PropertySource, RemoveLabelOperator, ScanOperator,
    SetPropertyOperator, ShortestPathOperator, SimpleAggregateOperator, SortDirection,
    SortKey as PhysicalSortKey, SortOperator, UnwindOperator, VariableLengthExpandOperator,
};
use grafeo_core::graph::{Direction, GraphStore, GraphStoreMut};
use std::collections::HashMap;
use std::sync::Arc;

use crate::query::planner::common;
use crate::query::planner::common::expression_to_string;
use crate::query::planner::{
    PhysicalPlan, convert_aggregate_function, convert_binary_op, convert_filter_expression,
    convert_unary_op, value_to_logical_type,
};
use crate::transaction::TransactionManager;

/// Range bounds for property-based range queries.
struct RangeBounds<'a> {
    min: Option<&'a Value>,
    max: Option<&'a Value>,
    min_inclusive: bool,
    max_inclusive: bool,
}

/// Converts a logical plan to a physical operator tree for LPG stores.
pub struct Planner {
    /// The graph store (supports both read and write operations).
    pub(super) store: Arc<dyn GraphStoreMut>,
    /// Transaction manager for MVCC operations.
    pub(super) transaction_manager: Option<Arc<TransactionManager>>,
    /// Current transaction ID (if in a transaction).
    pub(super) transaction_id: Option<TransactionId>,
    /// Epoch to use for visibility checks.
    pub(super) viewing_epoch: EpochId,
    /// Counter for generating unique anonymous edge column names.
    pub(super) anon_edge_counter: std::cell::Cell<u32>,
    /// Whether to use factorized execution for multi-hop queries.
    pub(super) factorized_execution: bool,
    /// Variables that hold scalar values (from UNWIND/FOR), not node/edge IDs.
    /// Used by plan_return to assign `LogicalType::Any` instead of `Node`.
    pub(super) scalar_columns: std::cell::RefCell<std::collections::HashSet<String>>,
    /// Variables that hold edge IDs (from MATCH edge patterns).
    /// Used by plan_return to emit `EdgeResolve` instead of `NodeResolve`.
    pub(super) edge_columns: std::cell::RefCell<std::collections::HashSet<String>>,
    /// Optional constraint validator for schema enforcement during mutations.
    pub(super) validator: Option<Arc<dyn ConstraintValidator>>,
    /// Catalog for user-defined procedure lookup.
    pub(super) catalog: Option<Arc<crate::catalog::Catalog>>,
    /// Shared parameter state for the currently planning correlated Apply.
    /// Set by `plan_apply` before planning the inner operator, consumed by
    /// `plan_operator` when encountering `ParameterScan`.
    pub(super) correlated_param_state:
        std::cell::RefCell<Option<Arc<grafeo_core::execution::operators::ParameterState>>>,
    /// Variables from variable-length expand patterns (group-list variables).
    /// Used by the aggregate planner to detect horizontal aggregation (GE09).
    pub(super) group_list_variables: std::cell::RefCell<std::collections::HashSet<String>>,
}

impl Planner {
    /// Creates a new planner with the given store.
    ///
    /// This creates a planner without transaction context, using the current
    /// epoch from the store for visibility.
    #[must_use]
    pub fn new(store: Arc<dyn GraphStoreMut>) -> Self {
        let epoch = store.current_epoch();
        Self {
            store,
            transaction_manager: None,
            transaction_id: None,
            viewing_epoch: epoch,
            anon_edge_counter: std::cell::Cell::new(0),
            factorized_execution: true,
            scalar_columns: std::cell::RefCell::new(std::collections::HashSet::new()),
            edge_columns: std::cell::RefCell::new(std::collections::HashSet::new()),
            validator: None,
            catalog: None,
            correlated_param_state: std::cell::RefCell::new(None),
            group_list_variables: std::cell::RefCell::new(std::collections::HashSet::new()),
        }
    }

    /// Creates a new planner with transaction context for MVCC-aware planning.
    #[must_use]
    pub fn with_context(
        store: Arc<dyn GraphStoreMut>,
        transaction_manager: Arc<TransactionManager>,
        transaction_id: Option<TransactionId>,
        viewing_epoch: EpochId,
    ) -> Self {
        Self {
            store,
            transaction_manager: Some(transaction_manager),
            transaction_id,
            viewing_epoch,
            anon_edge_counter: std::cell::Cell::new(0),
            factorized_execution: true,
            scalar_columns: std::cell::RefCell::new(std::collections::HashSet::new()),
            edge_columns: std::cell::RefCell::new(std::collections::HashSet::new()),
            validator: None,
            catalog: None,
            correlated_param_state: std::cell::RefCell::new(None),
            group_list_variables: std::cell::RefCell::new(std::collections::HashSet::new()),
        }
    }

    /// Returns the viewing epoch for this planner.
    #[must_use]
    pub fn viewing_epoch(&self) -> EpochId {
        self.viewing_epoch
    }

    /// Returns the transaction ID for this planner, if any.
    #[must_use]
    pub fn transaction_id(&self) -> Option<TransactionId> {
        self.transaction_id
    }

    /// Returns a reference to the transaction manager, if available.
    #[must_use]
    pub fn transaction_manager(&self) -> Option<&Arc<TransactionManager>> {
        self.transaction_manager.as_ref()
    }

    /// Enables or disables factorized execution for multi-hop queries.
    #[must_use]
    pub fn with_factorized_execution(mut self, enabled: bool) -> Self {
        self.factorized_execution = enabled;
        self
    }

    /// Sets the constraint validator for schema enforcement during mutations.
    #[must_use]
    pub fn with_validator(mut self, validator: Arc<dyn ConstraintValidator>) -> Self {
        self.validator = Some(validator);
        self
    }

    /// Sets the catalog for user-defined procedure lookup.
    #[must_use]
    pub fn with_catalog(mut self, catalog: Arc<crate::catalog::Catalog>) -> Self {
        self.catalog = Some(catalog);
        self
    }

    /// Counts consecutive single-hop expand operations.
    ///
    /// Returns the count and the deepest non-expand operator (the base of the chain).
    fn count_expand_chain(op: &LogicalOperator) -> (usize, &LogicalOperator) {
        match op {
            LogicalOperator::Expand(expand) => {
                let is_single_hop = expand.min_hops == 1 && expand.max_hops == Some(1);

                if is_single_hop {
                    let (inner_count, base) = Self::count_expand_chain(&expand.input);
                    (inner_count + 1, base)
                } else {
                    (0, op)
                }
            }
            _ => (0, op),
        }
    }

    /// Collects expand operations from the outermost down to the base.
    ///
    /// Returns expands in order from innermost (base) to outermost.
    fn collect_expand_chain(op: &LogicalOperator) -> Vec<&ExpandOp> {
        let mut chain = Vec::new();
        let mut current = op;

        while let LogicalOperator::Expand(expand) = current {
            let is_single_hop = expand.min_hops == 1 && expand.max_hops == Some(1);
            if !is_single_hop {
                break;
            }
            chain.push(expand);
            current = &expand.input;
        }

        chain.reverse();
        chain
    }

    /// Plans a logical plan into a physical operator.
    pub fn plan(&self, logical_plan: &LogicalPlan) -> Result<PhysicalPlan> {
        let (operator, columns) = self.plan_operator(&logical_plan.root)?;
        Ok(PhysicalPlan {
            operator,
            columns,
            adaptive_context: None,
        })
    }

    /// Plans a logical plan with adaptive execution support.
    pub fn plan_adaptive(&self, logical_plan: &LogicalPlan) -> Result<PhysicalPlan> {
        let (operator, columns) = self.plan_operator(&logical_plan.root)?;

        let mut adaptive_context = AdaptiveContext::new();
        self.collect_cardinality_estimates(&logical_plan.root, &mut adaptive_context, 0);

        Ok(PhysicalPlan {
            operator,
            columns,
            adaptive_context: Some(adaptive_context),
        })
    }

    /// Collects cardinality estimates from the logical plan into an adaptive context.
    fn collect_cardinality_estimates(
        &self,
        op: &LogicalOperator,
        ctx: &mut AdaptiveContext,
        depth: usize,
    ) {
        match op {
            LogicalOperator::NodeScan(scan) => {
                let estimate = if let Some(label) = &scan.label {
                    self.store.nodes_by_label(label).len() as f64
                } else {
                    self.store.node_count() as f64
                };
                let id = format!("scan_{}", scan.variable);
                ctx.set_estimate(&id, estimate);

                if let Some(input) = &scan.input {
                    self.collect_cardinality_estimates(input, ctx, depth + 1);
                }
            }
            LogicalOperator::Filter(filter) => {
                let input_estimate = self.estimate_cardinality(&filter.input);
                let estimate = input_estimate * 0.3;
                let id = format!("filter_{depth}");
                ctx.set_estimate(&id, estimate);

                self.collect_cardinality_estimates(&filter.input, ctx, depth + 1);
            }
            LogicalOperator::Expand(expand) => {
                let input_estimate = self.estimate_cardinality(&expand.input);
                let stats = self.store.statistics();
                let avg_degree = self.estimate_expand_degree(&stats, expand);
                let estimate = input_estimate * avg_degree;
                let id = format!("expand_{}", expand.to_variable);
                ctx.set_estimate(&id, estimate);

                self.collect_cardinality_estimates(&expand.input, ctx, depth + 1);
            }
            LogicalOperator::Join(join) => {
                let left_est = self.estimate_cardinality(&join.left);
                let right_est = self.estimate_cardinality(&join.right);
                let estimate = (left_est * right_est).sqrt();
                let id = format!("join_{depth}");
                ctx.set_estimate(&id, estimate);

                self.collect_cardinality_estimates(&join.left, ctx, depth + 1);
                self.collect_cardinality_estimates(&join.right, ctx, depth + 1);
            }
            LogicalOperator::Aggregate(agg) => {
                let input_estimate = self.estimate_cardinality(&agg.input);
                let estimate = if agg.group_by.is_empty() {
                    1.0
                } else {
                    (input_estimate * 0.1).max(1.0)
                };
                let id = format!("aggregate_{depth}");
                ctx.set_estimate(&id, estimate);

                self.collect_cardinality_estimates(&agg.input, ctx, depth + 1);
            }
            LogicalOperator::Distinct(distinct) => {
                let input_estimate = self.estimate_cardinality(&distinct.input);
                let estimate = (input_estimate * 0.5).max(1.0);
                let id = format!("distinct_{depth}");
                ctx.set_estimate(&id, estimate);

                self.collect_cardinality_estimates(&distinct.input, ctx, depth + 1);
            }
            LogicalOperator::Return(ret) => {
                self.collect_cardinality_estimates(&ret.input, ctx, depth + 1);
            }
            LogicalOperator::Limit(limit) => {
                let input_estimate = self.estimate_cardinality(&limit.input);
                let estimate = (input_estimate).min(limit.count.estimate());
                let id = format!("limit_{depth}");
                ctx.set_estimate(&id, estimate);

                self.collect_cardinality_estimates(&limit.input, ctx, depth + 1);
            }
            LogicalOperator::Skip(skip) => {
                let input_estimate = self.estimate_cardinality(&skip.input);
                let estimate = (input_estimate - skip.count.estimate()).max(0.0);
                let id = format!("skip_{depth}");
                ctx.set_estimate(&id, estimate);

                self.collect_cardinality_estimates(&skip.input, ctx, depth + 1);
            }
            LogicalOperator::Sort(sort) => {
                self.collect_cardinality_estimates(&sort.input, ctx, depth + 1);
            }
            LogicalOperator::Union(union) => {
                let estimate: f64 = union
                    .inputs
                    .iter()
                    .map(|input| self.estimate_cardinality(input))
                    .sum();
                let id = format!("union_{depth}");
                ctx.set_estimate(&id, estimate);

                for input in &union.inputs {
                    self.collect_cardinality_estimates(input, ctx, depth + 1);
                }
            }
            _ => {
                // For other operators, try to recurse into known input patterns
            }
        }
    }

    /// Estimates cardinality for a logical operator subtree.
    fn estimate_cardinality(&self, op: &LogicalOperator) -> f64 {
        match op {
            LogicalOperator::NodeScan(scan) => {
                if let Some(label) = &scan.label {
                    self.store.nodes_by_label(label).len() as f64
                } else {
                    self.store.node_count() as f64
                }
            }
            LogicalOperator::Filter(filter) => self.estimate_cardinality(&filter.input) * 0.3,
            LogicalOperator::Expand(expand) => {
                let stats = self.store.statistics();
                let avg_degree = self.estimate_expand_degree(&stats, expand);
                self.estimate_cardinality(&expand.input) * avg_degree
            }
            LogicalOperator::Join(join) => {
                let left = self.estimate_cardinality(&join.left);
                let right = self.estimate_cardinality(&join.right);
                (left * right).sqrt()
            }
            LogicalOperator::Aggregate(agg) => {
                if agg.group_by.is_empty() {
                    1.0
                } else {
                    (self.estimate_cardinality(&agg.input) * 0.1).max(1.0)
                }
            }
            LogicalOperator::Distinct(distinct) => {
                (self.estimate_cardinality(&distinct.input) * 0.5).max(1.0)
            }
            LogicalOperator::Return(ret) => self.estimate_cardinality(&ret.input),
            LogicalOperator::Limit(limit) => self
                .estimate_cardinality(&limit.input)
                .min(limit.count.estimate()),
            LogicalOperator::Skip(skip) => {
                (self.estimate_cardinality(&skip.input) - skip.count.estimate()).max(0.0)
            }
            LogicalOperator::Sort(sort) => self.estimate_cardinality(&sort.input),
            LogicalOperator::Union(union) => union
                .inputs
                .iter()
                .map(|input| self.estimate_cardinality(input))
                .sum(),
            LogicalOperator::Except(except) => {
                let left = self.estimate_cardinality(&except.left);
                let right = self.estimate_cardinality(&except.right);
                (left - right).max(0.0)
            }
            LogicalOperator::Intersect(intersect) => {
                let left = self.estimate_cardinality(&intersect.left);
                let right = self.estimate_cardinality(&intersect.right);
                left.min(right)
            }
            LogicalOperator::Otherwise(otherwise) => self
                .estimate_cardinality(&otherwise.left)
                .max(self.estimate_cardinality(&otherwise.right)),
            _ => 1000.0,
        }
    }

    /// Estimates the average edge degree for an expand operation using store statistics.
    fn estimate_expand_degree(
        &self,
        stats: &grafeo_core::statistics::Statistics,
        expand: &ExpandOp,
    ) -> f64 {
        let outgoing = !matches!(expand.direction, ExpandDirection::Incoming);
        if expand.edge_types.len() == 1 {
            stats.estimate_avg_degree(&expand.edge_types[0], outgoing)
        } else if stats.total_nodes > 0 {
            (stats.total_edges as f64 / stats.total_nodes as f64).max(1.0)
        } else {
            10.0
        }
    }

    /// Plans a single logical operator.
    fn plan_operator(&self, op: &LogicalOperator) -> Result<(Box<dyn Operator>, Vec<String>)> {
        match op {
            LogicalOperator::NodeScan(scan) => self.plan_node_scan(scan),
            LogicalOperator::Expand(expand) => {
                if self.factorized_execution {
                    let (chain_len, _base) = Self::count_expand_chain(op);
                    if chain_len >= 2 {
                        return self.plan_expand_chain(op);
                    }
                }
                self.plan_expand(expand)
            }
            LogicalOperator::Return(ret) => self.plan_return(ret),
            LogicalOperator::Filter(filter) => self.plan_filter(filter),
            LogicalOperator::Project(project) => self.plan_project(project),
            LogicalOperator::Limit(limit) => self.plan_limit(limit),
            LogicalOperator::Skip(skip) => self.plan_skip(skip),
            LogicalOperator::Sort(sort) => self.plan_sort(sort),
            LogicalOperator::Aggregate(agg) => self.plan_aggregate(agg),
            LogicalOperator::Join(join) => self.plan_join(join),
            LogicalOperator::Union(union) => self.plan_union(union),
            LogicalOperator::Except(except) => self.plan_except(except),
            LogicalOperator::Intersect(intersect) => self.plan_intersect(intersect),
            LogicalOperator::Otherwise(otherwise) => self.plan_otherwise(otherwise),
            LogicalOperator::Apply(apply) => self.plan_apply(apply),
            LogicalOperator::Distinct(distinct) => self.plan_distinct(distinct),
            LogicalOperator::CreateNode(create) => self.plan_create_node(create),
            LogicalOperator::CreateEdge(create) => self.plan_create_edge(create),
            LogicalOperator::DeleteNode(delete) => self.plan_delete_node(delete),
            LogicalOperator::DeleteEdge(delete) => self.plan_delete_edge(delete),
            LogicalOperator::LeftJoin(left_join) => self.plan_left_join(left_join),
            LogicalOperator::AntiJoin(anti_join) => self.plan_anti_join(anti_join),
            LogicalOperator::Unwind(unwind) => self.plan_unwind(unwind),
            LogicalOperator::Merge(merge) => self.plan_merge(merge),
            LogicalOperator::MergeRelationship(merge_rel) => {
                self.plan_merge_relationship(merge_rel)
            }
            LogicalOperator::AddLabel(add_label) => self.plan_add_label(add_label),
            LogicalOperator::RemoveLabel(remove_label) => self.plan_remove_label(remove_label),
            LogicalOperator::SetProperty(set_prop) => self.plan_set_property(set_prop),
            LogicalOperator::ShortestPath(sp) => self.plan_shortest_path(sp),
            LogicalOperator::MapCollect(mc) => self.plan_map_collect(mc),
            #[cfg(feature = "algos")]
            LogicalOperator::CallProcedure(call) => self.plan_call_procedure(call),
            #[cfg(not(feature = "algos"))]
            LogicalOperator::CallProcedure(_) => Err(Error::Internal(
                "CALL procedures require the 'algos' feature".to_string(),
            )),
            LogicalOperator::ParameterScan(param_scan) => {
                let state = self
                    .correlated_param_state
                    .borrow()
                    .clone()
                    .ok_or_else(|| {
                        Error::Internal(
                            "ParameterScan without correlated Apply context".to_string(),
                        )
                    })?;
                let columns = param_scan.columns.clone();
                let operator: Box<dyn Operator> = Box::new(ParameterScanOperator::new(state));
                Ok((operator, columns))
            }
            LogicalOperator::MultiWayJoin(mwj) => self.plan_multi_way_join(mwj),
            LogicalOperator::HorizontalAggregate(ha) => self.plan_horizontal_aggregate(ha),
            LogicalOperator::Empty => Err(Error::Internal("Empty plan".to_string())),
            LogicalOperator::VectorScan(_) => Err(Error::Internal(
                "VectorScan requires vector-index feature".to_string(),
            )),
            LogicalOperator::VectorJoin(_) => Err(Error::Internal(
                "VectorJoin requires vector-index feature".to_string(),
            )),
            _ => Err(Error::Internal(format!(
                "Unsupported operator: {:?}",
                std::mem::discriminant(op)
            ))),
        }
    }

    /// Plans a horizontal aggregate operator (per-row aggregation over a list column).
    fn plan_horizontal_aggregate(
        &self,
        ha: &HorizontalAggregateOp,
    ) -> Result<(Box<dyn Operator>, Vec<String>)> {
        let (child_op, child_columns) = self.plan_operator(&ha.input)?;

        let list_col_idx = child_columns
            .iter()
            .position(|c| c == &ha.list_column)
            .ok_or_else(|| {
                Error::Internal(format!(
                    "HorizontalAggregate list column '{}' not found in {:?}",
                    ha.list_column, child_columns
                ))
            })?;

        let entity_kind = match ha.entity_kind {
            LogicalEntityKind::Edge => EntityKind::Edge,
            LogicalEntityKind::Node => EntityKind::Node,
        };

        let function = convert_aggregate_function(ha.function);
        let input_column_count = child_columns.len();

        let operator: Box<dyn Operator> = Box::new(HorizontalAggregateOperator::new(
            child_op,
            list_col_idx,
            entity_kind,
            function,
            ha.property.clone(),
            Arc::clone(&self.store) as Arc<dyn GraphStore>,
            input_column_count,
        ));

        let mut columns = child_columns;
        columns.push(ha.alias.clone());
        // Mark the result as a scalar column
        self.scalar_columns.borrow_mut().insert(ha.alias.clone());

        Ok((operator, columns))
    }

    /// Plans a `MapCollect` operator that collapses grouped rows into a single Map value.
    fn plan_map_collect(&self, mc: &MapCollectOp) -> Result<(Box<dyn Operator>, Vec<String>)> {
        let (child_op, child_columns) = self.plan_operator(&mc.input)?;
        let key_idx = child_columns
            .iter()
            .position(|c| c == &mc.key_var)
            .ok_or_else(|| {
                Error::Internal(format!(
                    "MapCollect key '{}' not in columns {:?}",
                    mc.key_var, child_columns
                ))
            })?;
        let value_idx = child_columns
            .iter()
            .position(|c| c == &mc.value_var)
            .ok_or_else(|| {
                Error::Internal(format!(
                    "MapCollect value '{}' not in columns {:?}",
                    mc.value_var, child_columns
                ))
            })?;
        let operator = Box::new(MapCollectOperator::new(child_op, key_idx, value_idx));
        self.scalar_columns.borrow_mut().insert(mc.alias.clone());
        Ok((operator, vec![mc.alias.clone()]))
    }
}

/// An operator that yields a static set of rows (for `grafeo.procedures()` etc.).
#[cfg(feature = "algos")]
struct StaticResultOperator {
    rows: Vec<Vec<Value>>,
    column_indices: Vec<usize>,
    row_index: usize,
}

#[cfg(feature = "algos")]
impl Operator for StaticResultOperator {
    fn next(&mut self) -> grafeo_core::execution::operators::OperatorResult {
        use grafeo_core::execution::DataChunk;

        if self.row_index >= self.rows.len() {
            return Ok(None);
        }

        let remaining = self.rows.len() - self.row_index;
        let chunk_rows = remaining.min(1024);
        let col_count = self.column_indices.len();

        let col_types: Vec<LogicalType> = vec![LogicalType::Any; col_count];
        let mut chunk = DataChunk::with_capacity(&col_types, chunk_rows);

        for row_offset in 0..chunk_rows {
            let row = &self.rows[self.row_index + row_offset];
            for (col_idx, &src_idx) in self.column_indices.iter().enumerate() {
                let value = row.get(src_idx).cloned().unwrap_or(Value::Null);
                if let Some(col) = chunk.column_mut(col_idx) {
                    col.push_value(value);
                }
            }
        }
        chunk.set_count(chunk_rows);

        self.row_index += chunk_rows;
        Ok(Some(chunk))
    }

    fn reset(&mut self) {
        self.row_index = 0;
    }

    fn name(&self) -> &'static str {
        "StaticResult"
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::query::plan::{
        AggregateExpr as LogicalAggregateExpr, CreateEdgeOp, CreateNodeOp, DeleteNodeOp,
        DistinctOp as LogicalDistinctOp, ExpandOp, FilterOp, JoinCondition, JoinOp,
        LimitOp as LogicalLimitOp, NodeScanOp, PathMode, ReturnItem, ReturnOp,
        SkipOp as LogicalSkipOp, SortKey, SortOp,
    };
    use grafeo_common::types::Value;
    use grafeo_core::execution::operators::AggregateFunction as PhysicalAggregateFunction;
    use grafeo_core::graph::GraphStoreMut;
    use grafeo_core::graph::lpg::LpgStore;

    fn create_test_store() -> Arc<dyn GraphStoreMut> {
        let store = Arc::new(LpgStore::new().unwrap());
        store.create_node(&["Person"]);
        store.create_node(&["Person"]);
        store.create_node(&["Company"]);
        store
    }

    // ==================== Simple Scan Tests ====================

    #[test]
    fn test_plan_simple_scan() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n:Person) RETURN n
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: Some("Person".to_string()),
                input: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_scan_without_label() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n) RETURN n
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: None,
                input: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_return_with_alias() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n:Person) RETURN n AS person
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: Some("person".to_string()),
            }],
            distinct: false,
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: Some("Person".to_string()),
                input: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["person"]);
    }

    #[test]
    fn test_plan_return_property() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n:Person) RETURN n.name
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Property {
                    variable: "n".to_string(),
                    property: "name".to_string(),
                },
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: Some("Person".to_string()),
                input: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n.name"]);
    }

    #[test]
    fn test_plan_return_literal() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n) RETURN 42 AS answer
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Literal(Value::Int64(42)),
                alias: Some("answer".to_string()),
            }],
            distinct: false,
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: None,
                input: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["answer"]);
    }

    // ==================== Filter Tests ====================

    #[test]
    fn test_plan_filter_equality() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n:Person) WHERE n.age = 30 RETURN n
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Filter(FilterOp {
                predicate: LogicalExpression::Binary {
                    left: Box::new(LogicalExpression::Property {
                        variable: "n".to_string(),
                        property: "age".to_string(),
                    }),
                    op: BinaryOp::Eq,
                    right: Box::new(LogicalExpression::Literal(Value::Int64(30))),
                },
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: Some("Person".to_string()),
                    input: None,
                })),
                pushdown_hint: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_filter_compound_and() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // WHERE n.age > 20 AND n.age < 40
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Filter(FilterOp {
                predicate: LogicalExpression::Binary {
                    left: Box::new(LogicalExpression::Binary {
                        left: Box::new(LogicalExpression::Property {
                            variable: "n".to_string(),
                            property: "age".to_string(),
                        }),
                        op: BinaryOp::Gt,
                        right: Box::new(LogicalExpression::Literal(Value::Int64(20))),
                    }),
                    op: BinaryOp::And,
                    right: Box::new(LogicalExpression::Binary {
                        left: Box::new(LogicalExpression::Property {
                            variable: "n".to_string(),
                            property: "age".to_string(),
                        }),
                        op: BinaryOp::Lt,
                        right: Box::new(LogicalExpression::Literal(Value::Int64(40))),
                    }),
                },
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
                pushdown_hint: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_filter_unary_not() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // WHERE NOT n.active
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Filter(FilterOp {
                predicate: LogicalExpression::Unary {
                    op: UnaryOp::Not,
                    operand: Box::new(LogicalExpression::Property {
                        variable: "n".to_string(),
                        property: "active".to_string(),
                    }),
                },
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
                pushdown_hint: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_filter_is_null() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // WHERE n.email IS NULL
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Filter(FilterOp {
                predicate: LogicalExpression::Unary {
                    op: UnaryOp::IsNull,
                    operand: Box::new(LogicalExpression::Property {
                        variable: "n".to_string(),
                        property: "email".to_string(),
                    }),
                },
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
                pushdown_hint: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_filter_function_call() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // WHERE size(n.friends) > 0
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Filter(FilterOp {
                predicate: LogicalExpression::Binary {
                    left: Box::new(LogicalExpression::FunctionCall {
                        name: "size".to_string(),
                        args: vec![LogicalExpression::Property {
                            variable: "n".to_string(),
                            property: "friends".to_string(),
                        }],
                        distinct: false,
                    }),
                    op: BinaryOp::Gt,
                    right: Box::new(LogicalExpression::Literal(Value::Int64(0))),
                },
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
                pushdown_hint: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    // ==================== Expand Tests ====================

    #[test]
    fn test_plan_expand_outgoing() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (a:Person)-[:KNOWS]->(b) RETURN a, b
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("b".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::Expand(ExpandOp {
                from_variable: "a".to_string(),
                to_variable: "b".to_string(),
                edge_variable: None,
                direction: ExpandDirection::Outgoing,
                edge_types: vec!["KNOWS".to_string()],
                min_hops: 1,
                max_hops: Some(1),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: Some("Person".to_string()),
                    input: None,
                })),
                path_alias: None,
                path_mode: PathMode::Walk,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        // The return should have columns [a, b]
        assert!(physical.columns().contains(&"a".to_string()));
        assert!(physical.columns().contains(&"b".to_string()));
    }

    #[test]
    fn test_plan_expand_with_edge_variable() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (a)-[r:KNOWS]->(b) RETURN a, r, b
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("r".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("b".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::Expand(ExpandOp {
                from_variable: "a".to_string(),
                to_variable: "b".to_string(),
                edge_variable: Some("r".to_string()),
                direction: ExpandDirection::Outgoing,
                edge_types: vec!["KNOWS".to_string()],
                min_hops: 1,
                max_hops: Some(1),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: None,
                    input: None,
                })),
                path_alias: None,
                path_mode: PathMode::Walk,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"a".to_string()));
        assert!(physical.columns().contains(&"r".to_string()));
        assert!(physical.columns().contains(&"b".to_string()));
    }

    // ==================== Limit/Skip/Sort Tests ====================

    #[test]
    fn test_plan_limit() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n) RETURN n LIMIT 10
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Limit(LogicalLimitOp {
                count: 10.into(),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_skip() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n) RETURN n SKIP 5
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Skip(LogicalSkipOp {
                count: 5.into(),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_sort() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n) RETURN n ORDER BY n.name ASC
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Sort(SortOp {
                keys: vec![SortKey {
                    expression: LogicalExpression::Variable("n".to_string()),
                    order: SortOrder::Ascending,
                    nulls: None,
                }],
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_sort_descending() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // ORDER BY n DESC
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Sort(SortOp {
                keys: vec![SortKey {
                    expression: LogicalExpression::Variable("n".to_string()),
                    order: SortOrder::Descending,
                    nulls: None,
                }],
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_distinct() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n) RETURN DISTINCT n
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Distinct(LogicalDistinctOp {
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
                columns: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_distinct_with_columns() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // DISTINCT on specific columns (column-specific dedup)
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Distinct(LogicalDistinctOp {
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
                columns: Some(vec!["n".to_string()]),
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    #[test]
    fn test_plan_distinct_with_nonexistent_columns() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // When distinct columns don't match any output columns,
        // it falls back to full-row distinct.
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Distinct(LogicalDistinctOp {
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
                columns: Some(vec!["nonexistent".to_string()]),
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
    }

    // ==================== Aggregate Tests ====================

    #[test]
    fn test_plan_aggregate_count() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n) RETURN count(n)
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("cnt".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Aggregate(AggregateOp {
                group_by: vec![],
                aggregates: vec![LogicalAggregateExpr {
                    function: LogicalAggregateFunction::Count,
                    expression: Some(LogicalExpression::Variable("n".to_string())),
                    expression2: None,
                    distinct: false,
                    alias: Some("cnt".to_string()),
                    percentile: None,
                    separator: None,
                }],
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
                having: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"cnt".to_string()));
    }

    #[test]
    fn test_plan_aggregate_with_group_by() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n:Person) RETURN n.city, count(n) GROUP BY n.city
        let logical = LogicalPlan::new(LogicalOperator::Aggregate(AggregateOp {
            group_by: vec![LogicalExpression::Property {
                variable: "n".to_string(),
                property: "city".to_string(),
            }],
            aggregates: vec![LogicalAggregateExpr {
                function: LogicalAggregateFunction::Count,
                expression: Some(LogicalExpression::Variable("n".to_string())),
                expression2: None,
                distinct: false,
                alias: Some("cnt".to_string()),
                percentile: None,
                separator: None,
            }],
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: Some("Person".to_string()),
                input: None,
            })),
            having: None,
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns().len(), 2);
    }

    #[test]
    fn test_plan_aggregate_sum() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // SUM(n.value)
        let logical = LogicalPlan::new(LogicalOperator::Aggregate(AggregateOp {
            group_by: vec![],
            aggregates: vec![LogicalAggregateExpr {
                function: LogicalAggregateFunction::Sum,
                expression: Some(LogicalExpression::Property {
                    variable: "n".to_string(),
                    property: "value".to_string(),
                }),
                expression2: None,
                distinct: false,
                alias: Some("total".to_string()),
                percentile: None,
                separator: None,
            }],
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: None,
                input: None,
            })),
            having: None,
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"total".to_string()));
    }

    #[test]
    fn test_plan_aggregate_avg() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // AVG(n.score)
        let logical = LogicalPlan::new(LogicalOperator::Aggregate(AggregateOp {
            group_by: vec![],
            aggregates: vec![LogicalAggregateExpr {
                function: LogicalAggregateFunction::Avg,
                expression: Some(LogicalExpression::Property {
                    variable: "n".to_string(),
                    property: "score".to_string(),
                }),
                expression2: None,
                distinct: false,
                alias: Some("average".to_string()),
                percentile: None,
                separator: None,
            }],
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: None,
                input: None,
            })),
            having: None,
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"average".to_string()));
    }

    #[test]
    fn test_plan_aggregate_min_max() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MIN(n.age), MAX(n.age)
        let logical = LogicalPlan::new(LogicalOperator::Aggregate(AggregateOp {
            group_by: vec![],
            aggregates: vec![
                LogicalAggregateExpr {
                    function: LogicalAggregateFunction::Min,
                    expression: Some(LogicalExpression::Property {
                        variable: "n".to_string(),
                        property: "age".to_string(),
                    }),
                    expression2: None,
                    distinct: false,
                    alias: Some("youngest".to_string()),
                    percentile: None,
                    separator: None,
                },
                LogicalAggregateExpr {
                    function: LogicalAggregateFunction::Max,
                    expression: Some(LogicalExpression::Property {
                        variable: "n".to_string(),
                        property: "age".to_string(),
                    }),
                    expression2: None,
                    distinct: false,
                    alias: Some("oldest".to_string()),
                    percentile: None,
                    separator: None,
                },
            ],
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: None,
                input: None,
            })),
            having: None,
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"youngest".to_string()));
        assert!(physical.columns().contains(&"oldest".to_string()));
    }

    // ==================== Join Tests ====================

    #[test]
    fn test_plan_inner_join() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // Inner join between two scans
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("b".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::Join(JoinOp {
                left: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: Some("Person".to_string()),
                    input: None,
                })),
                right: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "b".to_string(),
                    label: Some("Company".to_string()),
                    input: None,
                })),
                join_type: JoinType::Inner,
                conditions: vec![JoinCondition {
                    left: LogicalExpression::Variable("a".to_string()),
                    right: LogicalExpression::Variable("b".to_string()),
                }],
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"a".to_string()));
        assert!(physical.columns().contains(&"b".to_string()));
    }

    #[test]
    fn test_plan_cross_join() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // Cross join (no conditions)
        let logical = LogicalPlan::new(LogicalOperator::Join(JoinOp {
            left: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "a".to_string(),
                label: None,
                input: None,
            })),
            right: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "b".to_string(),
                label: None,
                input: None,
            })),
            join_type: JoinType::Cross,
            conditions: vec![],
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns().len(), 2);
    }

    #[test]
    fn test_plan_left_join() {
        let store = create_test_store();
        let planner = Planner::new(store);

        let logical = LogicalPlan::new(LogicalOperator::Join(JoinOp {
            left: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "a".to_string(),
                label: None,
                input: None,
            })),
            right: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "b".to_string(),
                label: None,
                input: None,
            })),
            join_type: JoinType::Left,
            conditions: vec![],
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns().len(), 2);
    }

    // ==================== Mutation Tests ====================

    #[test]
    fn test_plan_create_node() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // CREATE (n:Person {name: 'Alix'})
        let logical = LogicalPlan::new(LogicalOperator::CreateNode(CreateNodeOp {
            variable: "n".to_string(),
            labels: vec!["Person".to_string()],
            properties: vec![(
                "name".to_string(),
                LogicalExpression::Literal(Value::String("Alix".into())),
            )],
            input: None,
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"n".to_string()));
    }

    #[test]
    fn test_plan_create_edge() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (a), (b) CREATE (a)-[:KNOWS]->(b)
        let logical = LogicalPlan::new(LogicalOperator::CreateEdge(CreateEdgeOp {
            variable: Some("r".to_string()),
            from_variable: "a".to_string(),
            to_variable: "b".to_string(),
            edge_type: "KNOWS".to_string(),
            properties: vec![],
            input: Box::new(LogicalOperator::Join(JoinOp {
                left: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: None,
                    input: None,
                })),
                right: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "b".to_string(),
                    label: None,
                    input: None,
                })),
                join_type: JoinType::Cross,
                conditions: vec![],
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"r".to_string()));
    }

    #[test]
    fn test_plan_delete_node() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n) DELETE n
        let logical = LogicalPlan::new(LogicalOperator::DeleteNode(DeleteNodeOp {
            variable: "n".to_string(),
            detach: false,
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: None,
                input: None,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"deleted_count".to_string()));
    }

    // ==================== Error Cases ====================

    #[test]
    fn test_plan_empty_errors() {
        let store = create_test_store();
        let planner = Planner::new(store);

        let logical = LogicalPlan::new(LogicalOperator::Empty);
        let result = planner.plan(&logical);
        assert!(result.is_err());
    }

    #[test]
    fn test_plan_missing_variable_in_return() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // Return variable that doesn't exist in input
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("missing".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: None,
                input: None,
            })),
        }));

        let result = planner.plan(&logical);
        assert!(result.is_err());
    }

    // ==================== Helper Function Tests ====================

    #[test]
    fn test_convert_binary_ops() {
        assert!(convert_binary_op(BinaryOp::Eq).is_ok());
        assert!(convert_binary_op(BinaryOp::Ne).is_ok());
        assert!(convert_binary_op(BinaryOp::Lt).is_ok());
        assert!(convert_binary_op(BinaryOp::Le).is_ok());
        assert!(convert_binary_op(BinaryOp::Gt).is_ok());
        assert!(convert_binary_op(BinaryOp::Ge).is_ok());
        assert!(convert_binary_op(BinaryOp::And).is_ok());
        assert!(convert_binary_op(BinaryOp::Or).is_ok());
        assert!(convert_binary_op(BinaryOp::Add).is_ok());
        assert!(convert_binary_op(BinaryOp::Sub).is_ok());
        assert!(convert_binary_op(BinaryOp::Mul).is_ok());
        assert!(convert_binary_op(BinaryOp::Div).is_ok());
    }

    #[test]
    fn test_convert_unary_ops() {
        assert!(convert_unary_op(UnaryOp::Not).is_ok());
        assert!(convert_unary_op(UnaryOp::IsNull).is_ok());
        assert!(convert_unary_op(UnaryOp::IsNotNull).is_ok());
        assert!(convert_unary_op(UnaryOp::Neg).is_ok());
    }

    #[test]
    fn test_convert_aggregate_functions() {
        assert!(matches!(
            convert_aggregate_function(LogicalAggregateFunction::Count),
            PhysicalAggregateFunction::Count
        ));
        assert!(matches!(
            convert_aggregate_function(LogicalAggregateFunction::Sum),
            PhysicalAggregateFunction::Sum
        ));
        assert!(matches!(
            convert_aggregate_function(LogicalAggregateFunction::Avg),
            PhysicalAggregateFunction::Avg
        ));
        assert!(matches!(
            convert_aggregate_function(LogicalAggregateFunction::Min),
            PhysicalAggregateFunction::Min
        ));
        assert!(matches!(
            convert_aggregate_function(LogicalAggregateFunction::Max),
            PhysicalAggregateFunction::Max
        ));
    }

    #[test]
    fn test_planner_accessors() {
        let store = create_test_store();
        let planner = Planner::new(Arc::clone(&store));

        assert!(planner.transaction_id().is_none());
        assert!(planner.transaction_manager().is_none());
        let _ = planner.viewing_epoch(); // Just ensure it's accessible
    }

    #[test]
    fn test_physical_plan_accessors() {
        let store = create_test_store();
        let planner = Planner::new(store);

        let logical = LogicalPlan::new(LogicalOperator::NodeScan(NodeScanOp {
            variable: "n".to_string(),
            label: None,
            input: None,
        }));

        let physical = planner.plan(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);

        // Test into_operator
        let _ = physical.into_operator();
    }

    // ==================== Adaptive Planning Tests ====================

    #[test]
    fn test_plan_adaptive_with_scan() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n:Person) RETURN n
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: Some("Person".to_string()),
                input: None,
            })),
        }));

        let physical = planner.plan_adaptive(&logical).unwrap();
        assert_eq!(physical.columns(), &["n"]);
        // Should have adaptive context with estimates
        assert!(physical.adaptive_context.is_some());
    }

    #[test]
    fn test_plan_adaptive_with_filter() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n) WHERE n.age > 30 RETURN n
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Filter(FilterOp {
                predicate: LogicalExpression::Binary {
                    left: Box::new(LogicalExpression::Property {
                        variable: "n".to_string(),
                        property: "age".to_string(),
                    }),
                    op: BinaryOp::Gt,
                    right: Box::new(LogicalExpression::Literal(Value::Int64(30))),
                },
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
                pushdown_hint: None,
            })),
        }));

        let physical = planner.plan_adaptive(&logical).unwrap();
        assert!(physical.adaptive_context.is_some());
    }

    #[test]
    fn test_plan_adaptive_with_expand() {
        let store = create_test_store();
        let planner = Planner::new(Arc::clone(&store)).with_factorized_execution(false);

        // MATCH (a)-[:KNOWS]->(b) RETURN a, b
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("b".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::Expand(ExpandOp {
                from_variable: "a".to_string(),
                to_variable: "b".to_string(),
                edge_variable: None,
                direction: ExpandDirection::Outgoing,
                edge_types: vec!["KNOWS".to_string()],
                min_hops: 1,
                max_hops: Some(1),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: None,
                    input: None,
                })),
                path_alias: None,
                path_mode: PathMode::Walk,
            })),
        }));

        let physical = planner.plan_adaptive(&logical).unwrap();
        assert!(physical.adaptive_context.is_some());
    }

    #[test]
    fn test_plan_adaptive_with_join() {
        let store = create_test_store();
        let planner = Planner::new(store);

        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("b".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::Join(JoinOp {
                left: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: None,
                    input: None,
                })),
                right: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "b".to_string(),
                    label: None,
                    input: None,
                })),
                join_type: JoinType::Cross,
                conditions: vec![],
            })),
        }));

        let physical = planner.plan_adaptive(&logical).unwrap();
        assert!(physical.adaptive_context.is_some());
    }

    #[test]
    fn test_plan_adaptive_with_aggregate() {
        let store = create_test_store();
        let planner = Planner::new(store);

        let logical = LogicalPlan::new(LogicalOperator::Aggregate(AggregateOp {
            group_by: vec![],
            aggregates: vec![LogicalAggregateExpr {
                function: LogicalAggregateFunction::Count,
                expression: Some(LogicalExpression::Variable("n".to_string())),
                expression2: None,
                distinct: false,
                alias: Some("cnt".to_string()),
                percentile: None,
                separator: None,
            }],
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "n".to_string(),
                label: None,
                input: None,
            })),
            having: None,
        }));

        let physical = planner.plan_adaptive(&logical).unwrap();
        assert!(physical.adaptive_context.is_some());
    }

    #[test]
    fn test_plan_adaptive_with_distinct() {
        let store = create_test_store();
        let planner = Planner::new(store);

        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Distinct(LogicalDistinctOp {
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
                columns: None,
            })),
        }));

        let physical = planner.plan_adaptive(&logical).unwrap();
        assert!(physical.adaptive_context.is_some());
    }

    #[test]
    fn test_plan_adaptive_with_limit() {
        let store = create_test_store();
        let planner = Planner::new(store);

        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Limit(LogicalLimitOp {
                count: 10.into(),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
            })),
        }));

        let physical = planner.plan_adaptive(&logical).unwrap();
        assert!(physical.adaptive_context.is_some());
    }

    #[test]
    fn test_plan_adaptive_with_skip() {
        let store = create_test_store();
        let planner = Planner::new(store);

        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Skip(LogicalSkipOp {
                count: 5.into(),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
            })),
        }));

        let physical = planner.plan_adaptive(&logical).unwrap();
        assert!(physical.adaptive_context.is_some());
    }

    #[test]
    fn test_plan_adaptive_with_sort() {
        let store = create_test_store();
        let planner = Planner::new(store);

        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Sort(SortOp {
                keys: vec![SortKey {
                    expression: LogicalExpression::Variable("n".to_string()),
                    order: SortOrder::Ascending,
                    nulls: None,
                }],
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
            })),
        }));

        let physical = planner.plan_adaptive(&logical).unwrap();
        assert!(physical.adaptive_context.is_some());
    }

    #[test]
    fn test_plan_adaptive_with_union() {
        let store = create_test_store();
        let planner = Planner::new(store);

        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Union(UnionOp {
                inputs: vec![
                    LogicalOperator::NodeScan(NodeScanOp {
                        variable: "n".to_string(),
                        label: Some("Person".to_string()),
                        input: None,
                    }),
                    LogicalOperator::NodeScan(NodeScanOp {
                        variable: "n".to_string(),
                        label: Some("Company".to_string()),
                        input: None,
                    }),
                ],
            })),
        }));

        let physical = planner.plan_adaptive(&logical).unwrap();
        assert!(physical.adaptive_context.is_some());
    }

    // ==================== Variable Length Path Tests ====================

    #[test]
    fn test_plan_expand_variable_length() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (a)-[:KNOWS*1..3]->(b) RETURN a, b
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("b".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::Expand(ExpandOp {
                from_variable: "a".to_string(),
                to_variable: "b".to_string(),
                edge_variable: None,
                direction: ExpandDirection::Outgoing,
                edge_types: vec!["KNOWS".to_string()],
                min_hops: 1,
                max_hops: Some(3),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: None,
                    input: None,
                })),
                path_alias: None,
                path_mode: PathMode::Walk,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"a".to_string()));
        assert!(physical.columns().contains(&"b".to_string()));
    }

    #[test]
    fn test_plan_expand_with_path_alias() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH p = (a)-[:KNOWS*1..3]->(b) RETURN a, b
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("b".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::Expand(ExpandOp {
                from_variable: "a".to_string(),
                to_variable: "b".to_string(),
                edge_variable: None,
                direction: ExpandDirection::Outgoing,
                edge_types: vec!["KNOWS".to_string()],
                min_hops: 1,
                max_hops: Some(3),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: None,
                    input: None,
                })),
                path_alias: Some("p".to_string()),
                path_mode: PathMode::Walk,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        // Verify plan was created successfully with expected output columns
        assert!(physical.columns().contains(&"a".to_string()));
        assert!(physical.columns().contains(&"b".to_string()));
    }

    #[test]
    fn test_plan_expand_incoming() {
        let store = create_test_store();
        let planner = Planner::new(Arc::clone(&store)).with_factorized_execution(false);

        // MATCH (a)<-[:KNOWS]-(b) RETURN a, b
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("b".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::Expand(ExpandOp {
                from_variable: "a".to_string(),
                to_variable: "b".to_string(),
                edge_variable: None,
                direction: ExpandDirection::Incoming,
                edge_types: vec!["KNOWS".to_string()],
                min_hops: 1,
                max_hops: Some(1),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: None,
                    input: None,
                })),
                path_alias: None,
                path_mode: PathMode::Walk,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"a".to_string()));
        assert!(physical.columns().contains(&"b".to_string()));
    }

    #[test]
    fn test_plan_expand_both_directions() {
        let store = create_test_store();
        let planner = Planner::new(Arc::clone(&store)).with_factorized_execution(false);

        // MATCH (a)-[:KNOWS]-(b) RETURN a, b
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("b".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::Expand(ExpandOp {
                from_variable: "a".to_string(),
                to_variable: "b".to_string(),
                edge_variable: None,
                direction: ExpandDirection::Both,
                edge_types: vec!["KNOWS".to_string()],
                min_hops: 1,
                max_hops: Some(1),
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: None,
                    input: None,
                })),
                path_alias: None,
                path_mode: PathMode::Walk,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"a".to_string()));
        assert!(physical.columns().contains(&"b".to_string()));
    }

    // ==================== With Context Tests ====================

    #[test]
    fn test_planner_with_context() {
        use crate::transaction::TransactionManager;

        let store = create_test_store();
        let transaction_manager = Arc::new(TransactionManager::new());
        let transaction_id = transaction_manager.begin();
        let epoch = transaction_manager.current_epoch();

        let planner = Planner::with_context(
            Arc::clone(&store),
            Arc::clone(&transaction_manager),
            Some(transaction_id),
            epoch,
        );

        assert_eq!(planner.transaction_id(), Some(transaction_id));
        assert!(planner.transaction_manager().is_some());
        assert_eq!(planner.viewing_epoch(), epoch);
    }

    #[test]
    fn test_planner_with_factorized_execution_disabled() {
        let store = create_test_store();
        let planner = Planner::new(Arc::clone(&store)).with_factorized_execution(false);

        // Two consecutive expands - should NOT use factorized execution
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("c".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::Expand(ExpandOp {
                from_variable: "b".to_string(),
                to_variable: "c".to_string(),
                edge_variable: None,
                direction: ExpandDirection::Outgoing,
                edge_types: vec![],
                min_hops: 1,
                max_hops: Some(1),
                input: Box::new(LogicalOperator::Expand(ExpandOp {
                    from_variable: "a".to_string(),
                    to_variable: "b".to_string(),
                    edge_variable: None,
                    direction: ExpandDirection::Outgoing,
                    edge_types: vec![],
                    min_hops: 1,
                    max_hops: Some(1),
                    input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                        variable: "a".to_string(),
                        label: None,
                        input: None,
                    })),
                    path_alias: None,
                    path_mode: PathMode::Walk,
                })),
                path_alias: None,
                path_mode: PathMode::Walk,
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"a".to_string()));
        assert!(physical.columns().contains(&"c".to_string()));
    }

    // ==================== Sort with Property Tests ====================

    #[test]
    fn test_plan_sort_by_property() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // MATCH (n) RETURN n ORDER BY n.name ASC
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![ReturnItem {
                expression: LogicalExpression::Variable("n".to_string()),
                alias: None,
            }],
            distinct: false,
            input: Box::new(LogicalOperator::Sort(SortOp {
                keys: vec![SortKey {
                    expression: LogicalExpression::Property {
                        variable: "n".to_string(),
                        property: "name".to_string(),
                    },
                    order: SortOrder::Ascending,
                    nulls: None,
                }],
                input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "n".to_string(),
                    label: None,
                    input: None,
                })),
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        // Should have the property column projected
        assert!(physical.columns().contains(&"n".to_string()));
    }

    // ==================== Scan with Input Tests ====================

    #[test]
    fn test_plan_scan_with_input() {
        let store = create_test_store();
        let planner = Planner::new(store);

        // A scan with another scan as input (for chained patterns)
        let logical = LogicalPlan::new(LogicalOperator::Return(ReturnOp {
            items: vec![
                ReturnItem {
                    expression: LogicalExpression::Variable("a".to_string()),
                    alias: None,
                },
                ReturnItem {
                    expression: LogicalExpression::Variable("b".to_string()),
                    alias: None,
                },
            ],
            distinct: false,
            input: Box::new(LogicalOperator::NodeScan(NodeScanOp {
                variable: "b".to_string(),
                label: Some("Company".to_string()),
                input: Some(Box::new(LogicalOperator::NodeScan(NodeScanOp {
                    variable: "a".to_string(),
                    label: Some("Person".to_string()),
                    input: None,
                }))),
            })),
        }));

        let physical = planner.plan(&logical).unwrap();
        assert!(physical.columns().contains(&"a".to_string()));
        assert!(physical.columns().contains(&"b".to_string()));
    }
}