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Module executors

reddb_server::storage::query

Module executors

Expand description

Multi-Mode Query Executors

Specialized executors for each query language mode:

Gremlin: Traverser-based execution with path state tracking
SPARQL: Pattern matching with variable bindings
Natural: Translation + execution with explanation
Vector: HNSW-based similarity search with metadata filtering
Hybrid: Combined structured + vector search with fusion strategies

Each executor converts its native AST to execution operations, leveraging the unified executor for common operations.

Re-exports§

pub use cte::inline_ctes;
pub use cte::split_union_parts;
pub use cte::CteContext;
pub use cte::CteExecutor;
pub use cte::CteStats;
pub use gremlin::GremlinExecutor;
pub use hybrid::HybridExecutor;
pub use hybrid::InMemoryHybridExecutor;
pub use natural::NaturalExecutor;
pub use sparql::SparqlExecutor;
pub use vector::InMemoryVectorExecutor;
pub use vector::VectorExecutor;

Modules§

agg_spill: Hash-aggregation spill helper — Fase 4 P4 building block.
aggregation: Aggregation Framework
bitmap_scan: Bitmap heap scan — Fase 5 P6 consumer of TidBitmap.
cte: CTE (Common Table Expression) executor.
gremlin: Gremlin Traversal Executor
hybrid: Hybrid Query Executor
join: JOIN Executor Algorithms
natural: Natural Language Query Executor
parallel_scan: Parallel scan coordinator — Fase 4 P5 building block.
set_ops: Set Operations Executor
sparql: SPARQL Query Executor
subquery: Subquery Executor
vector: Vector Query Executor
window: Window Functions Executor

Structs§

AggregationDef: Definition of an aggregation to compute
AvgAggregator: AVG aggregator
CountAggregator: COUNT aggregator
CountDistinctAggregator: COUNT DISTINCT aggregator
ExecuteResult: Result of executing a query with mode information
FrameSpec: Frame specification for window function
GroupConcatAggregator: GROUP_CONCAT aggregator
JoinStats: Statistics for choosing join strategy
MaxAggregator: MAX aggregator
MinAggregator: MIN aggregator
MultiModeExecutor: Multi-mode executor that routes to specialized executors
PercentileAggregator: Percentile aggregator
SampleAggregator: SAMPLE aggregator (returns first non-null value)
SetOpStats: Statistics for set operations
StdDevAggregator: Standard deviation aggregator
SubqueryDef: A subquery definition
SubqueryExecutor: Subquery executor handles evaluation of nested queries
SumAggregator: SUM aggregator
ValueHash: Hashable wrapper for Value (for HashSet storage)
VarianceAggregator: Variance aggregator
WindowDef: Complete window definition
WindowExecutor: Window function executor
WindowFunc: A window function to apply
WindowOrderBy: Order-by specification for window

Enums§

CompareOp: Comparison operator for ANY/ALL
FrameBound: Frame boundary specification
FrameExclude: Frame exclusion option
FrameType: Frame type for window functions
JoinCondition: Join condition for filtering matches
JoinStrategy: Strategy to use for executing the join
JoinType: Type of JOIN operation
NullsOrder: Null handling in sorting
SetOpType: Type of set operation
SortDirection: Sort direction
SubqueryCache: Cached result of a non-correlated subquery
SubqueryType: Type of subquery
WindowFuncType: Type of window function

Traits§

Aggregator: Trait for aggregation functions

Functions§

bind_outer_refs: Check if a binding satisfies correlation constraints
choose_strategy: Choose optimal join strategy based on statistics
create_aggregator: Create an aggregator by name
detect_correlation: Detect outer variable references in a subquery
execute_group_by: 1-pass streaming GROUP BY.
execute_having: Execute HAVING clause (filter on aggregated results)
execute_join: Execute a join operation using the optimal strategy
execute_set_op: Execute a set operation on two binding vectors
hash_join: Execute a hash join
merge_join: Execute a merge join (for sorted inputs)
nested_loop_join: Execute a nested loop join (O(n*m) but works with any condition)
set_except: EXCEPT operation (set difference)
set_intersect: INTERSECT operation
set_union: UNION operation