Struct AggregateStrategySelector 

pub struct AggregateStrategySelector { /* private fields */ }

Aggregation Policy Selector

Selecting the optimal aggregation execution strategy based on a cost model

Implementations

impl AggregateStrategySelector

pub fn new(cost_calculator: Arc<CostCalculator>) -> Self

Create a new selector for aggregating policies.

pub fn select_strategy( &self, space: &str, context: &AggregateContext, ) -> AggregateStrategyDecision

Selecting the optimal aggregation strategy

Parameters

Context: Information about the context in which the aggregation operation is taking place.

Return

Aggregation policy decision-making, including the selected policy and the estimated cost.

pub fn select_strategy_with_memory_pressure( &self, space: &str, context: &AggregateContext, ) -> AggregateStrategyDecision

Selecting the optimal aggregation strategy with memory pressure awareness

This method considers the global memory pressure threshold from the cost model configuration to make more robust decisions for large-scale aggregations.

Parameters

• context: Information about the context in which the aggregation operation is taking place.

Return

Aggregation policy decision-making, including the selected policy and the estimated cost.

pub fn select_strategy_quick( &self, input_rows: u64, group_key_count: usize, _agg_function_count: usize, ) -> AggregateStrategy

Rapid selection strategy (simplified version, for use in decision-making caching)

pub fn update_decision( &self, space: &str, decision: &mut OptimizationDecision, context: &AggregateContext, )

Update and optimize the information on the aggregation strategies used in decision-making processes.

pub fn analyze_aggregation_complexity( &self, agg_functions: &[ContextualExpression], ) -> f64

Analyze aggregation expression complexity using expression cost

Returns the total expression cost for all aggregation functions. Higher cost indicates more complex expressions that benefit from HashAggregate (to avoid redundant computations).

pub fn select_strategy_comprehensive( &self, space: &str, context: &AggregateContext, agg_functions: &[ContextualExpression], ) -> AggregateStrategyDecision

Select strategy considering both memory pressure and expression complexity

This is the most comprehensive strategy selection method that considers:

• Input sorting
• Memory constraints and pressure
• Expression complexity
• Cost comparison

Trait Implementations

impl Debug for AggregateStrategySelector

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

Formats the value using the given formatter.