Struct OptimizerEngine 

pub struct OptimizerEngine { /* private fields */ }

Implementations

impl OptimizerEngine

pub fn new(cost_config: CostModelConfig) -> Self

pub fn with_expression_context( expression_context: Arc<ExpressionAnalysisContext>, cost_config: CostModelConfig, ) -> Self

pub fn for_ssd() -> Self

pub fn for_in_memory() -> Self

pub fn cost_config(&self) -> &CostModelConfig

pub fn cost_calculator(&self) -> &Arc<CostCalculator>

pub fn cost_calculator_for(&self, space: Option<&str>) -> Arc<CostCalculator>

pub fn space_cost_configs(&self) -> HashMap<String, CostModelConfig>

pub fn set_space_cost_configs(&self, configs: HashMap<String, CostModelConfig>)

pub fn cost_epoch(&self) -> u64

pub fn stats_manager(&self) -> &Arc<StatisticsManager>

pub fn selectivity_estimator(&self) -> &Arc<SelectivityEstimator>

pub fn expression_context(&self) -> &Arc<ExpressionAnalysisContext>

pub fn feedback_history(&self) -> Arc<QueryFeedbackHistory>

pub fn selectivity_feedback(&self) -> &Arc<SelectivityFeedbackManager>

pub fn cardinality_feedback(&self) -> &Arc<CardinalityFeedbackManager>

pub fn decision_feedback(&self) -> &Arc<DecisionFeedbackStore>

pub fn set_enable_feedback(&mut self, enable: bool)

pub fn feedback_enabled(&self) -> bool

pub fn columnar_policy(&self) -> Arc<ColumnarPolicy>

pub fn set_metrics_stats(&mut self, stats: Arc<StatsManager>)

pub fn metrics_stats(&self) -> Option<Arc<StatsManager>>

pub fn batch_plan_analyzer(&self) -> &BatchPlanAnalyzer

pub fn subquery_unnesting_optimizer(&self) -> &SubqueryUnnestingOptimizer

pub fn cte_cache_manager(&self) -> &CteCacheManager

pub fn set_cte_cache_stats_manager(&self, stats_manager: Arc<StatsManager>)

pub fn set_cost_config(&mut self, config: CostModelConfig)

pub fn set_enable_heuristic(&mut self, enable: bool)

pub fn set_max_heuristic_iterations(&mut self, max: usize)

pub fn set_partitioning_config(&mut self, config: PartitioningConfig)

pub fn set_rule_selection(&mut self, disabled: &[String], enabled: &[String])

Apply the [optimizer.rules] selection to the physical heuristic phase. enabled non-empty keeps only those rules; disabled then removes rules. Names match rule type names with or without the Rule suffix.

pub fn partitioning_config(&self) -> &PartitioningConfig

pub fn heuristic_batch(&self) -> &BatchOptimizer

pub fn logical_heuristic(&self) -> &LogicalBatchOptimizer

pub fn physical_heuristic(&self) -> &PhysicalHeuristicOptimizer

pub fn last_batch_statistics(&self) -> Vec<(OptimizationBatch, BatchStatistics)>

impl OptimizerEngine

pub fn maybe_apply_feedback(&self)

Fold execution feedback into selectivity/cardinality corrections.

Consumes actual row counts from feedback_history, which execution populates via collect_execution_feedback from runtime operator profiles (estimated vs actual per shape/predicate). Observability portraits (QueryProfile in metrics) and optimizer corrections (QueryExecutionFeedback here) serve separate roles — human-facing diagnostics vs EWMA estimate correction — and are both fed from the same runtime profiles.

Each execution is folded exactly once (per-fingerprint sequence watermark): re-applying the retained history on every optimization would walk the corrections over identical samples again. Samples from starved operators or without a measurable input pairing are dropped instead of folded.

pub fn invalidate_space_feedback(&self, space: Option<&str>)

Drop all feedback corrections scoped to space (None clears all).

Called when a space’s statistics are invalidated (ANALYZE force or DDL commit) so stale corrections cannot mislead estimates after a schema or data change.

impl OptimizerEngine

pub fn optimize( &self, plan: ExecutionPlan, space: Option<&str>, ) -> OptimizeResult<ExecutionPlan>

pub fn optimize_with_layout( &self, plan: ExecutionPlan, space: Option<&str>, layout: &PartitioningLayoutInfo, ) -> OptimizeResult<ExecutionPlan>

Trait Implementations

impl Debug for OptimizerEngine

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for OptimizerEngine

fn default() -> Self

Returns the “default value” for a type.

impl From<&OptimizerEngine> for OptimizationContext

fn from(engine: &OptimizerEngine) -> Self

Converts to this type from the input type.