Struct NetworkShuffleExec 

pub struct NetworkShuffleExec { /* private fields */ }

ExecutionPlan implementation that shuffles data across the network in a distributed context.

The easiest way of thinking about this node is as a plan RepartitionExec node that is capable of fanning out the different produced partitions to different tasks. This allows redistributing data across different tasks in different stages, so that different physical machines can make progress on different non-overlapping sets of data.

This node allows fanning out of data from N tasks to M tasks, with N and M being arbitrary non-zero positive numbers. Here are some examples of how data can be shuffled in different scenarios:

1 to many

┌───────────────────────────┐  ┌───────────────────────────┐ ┌───────────────────────────┐     ■
│    NetworkShuffleExec     │  │    NetworkShuffleExec     │ │    NetworkShuffleExec     │     │
│         (task 1)          │  │         (task 2)          │ │         (task 3)          │     │
└┬─┬┬─┬┬─┬──────────────────┘  └─────────┬─┬┬─┬┬─┬─────────┘ └──────────────────┬─┬┬─┬┬─┬┘  Stage N+1
 │1││2││3│                               │4││5││6│                              │7││8││9│      │
 └─┘└─┘└─┘                               └─┘└─┘└─┘                              └─┘└─┘└─┘      │
  ▲  ▲  ▲                                 ▲  ▲  ▲                                ▲  ▲  ▲       ■
  └──┴──┴────────────────────────┬──┬──┐  │  │  │  ┌──┬──┬───────────────────────┴──┴──┘
                                 │  │  │  │  │  │  │  │  │                                     ■
                                ┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐                                    │
                                │1││2││3││4││5││6││7││8││9│                                    │
                               ┌┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┐                                Stage N
                               │      RepartitionExec      │                                   │
                               │         (task 1)          │                                   │
                               └───────────────────────────┘                                   ■

many to 1

                               ┌───────────────────────────┐                                   ■
                               │    NetworkShuffleExec     │                                   │
                               │         (task 1)          │                                   │
                               └┬─┬┬─┬┬─┬┬─┬┬─┬┬─┬┬─┬┬─┬┬─┬┘                                Stage N+1
                                │1││2││3││4││5││6││7││8││9│                                    │
                                └─┘└─┘└─┘└─┘└─┘└─┘└─┘└─┘└─┘                                    │
                                ▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲▲                                    ■
  ┌──┬──┬──┬──┬──┬──┬──┬──┬─────┴┼┴┴┼┴┴┼┴┴┼┴┴┼┴┴┼┴┴┼┴┴┼┴┴┼┴────┬──┬──┬──┬──┬──┬──┬──┬──┐
  │  │  │  │  │  │  │  │  │      │  │  │  │  │  │  │  │  │     │  │  │  │  │  │  │  │  │       ■
 ┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐    ┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐   ┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐      │
 │1││2││3││4││5││6││7││8││9│    │1││2││3││4││5││6││7││8││9│   │1││2││3││4││5││6││7││8││9│      │
┌┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┐  ┌┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┐ ┌┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┐  Stage N
│      RepartitionExec      │  │      RepartitionExec      │ │      RepartitionExec      │     │
│         (task 1)          │  │         (task 2)          │ │         (task 3)          │     │
└───────────────────────────┘  └───────────────────────────┘ └───────────────────────────┘     ■

many to many

                   ┌───────────────────────────┐  ┌───────────────────────────┐                ■
                   │    NetworkShuffleExec     │  │    NetworkShuffleExec     │                │
                   │         (task 1)          │  │         (task 2)          │                │
                   └┬─┬┬─┬┬─┬┬─┬───────────────┘  └───────────────┬─┬┬─┬┬─┬┬─┬┘             Stage N+1
                    │1││2││3││4│                                  │5││6││7││8│                 │
                    └─┘└─┘└─┘└─┘                                  └─┘└─┘└─┘└─┘                 │
                    ▲▲▲▲▲▲▲▲▲▲▲▲                                  ▲▲▲▲▲▲▲▲▲▲▲▲                 ■
    ┌──┬──┬──┬──┬──┬┴┴┼┴┴┼┴┴┴┴┴┴───┬──┬──┬──┬──┬──┬──┬──┬────────┬┴┴┼┴┴┼┴┴┼┴┴┼──┬──┬──┐
    │  │  │  │  │  │  │  │         │  │  │  │  │  │  │  │        │  │  │  │  │  │  │  │        ■
   ┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐       ┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐      ┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐┌─┐       │
   │1││2││3││4││5││6││7││8│       │1││2││3││4││5││6││7││8│      │1││2││3││4││5││6││7││8│       │
┌──┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴─┐  ┌──┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴─┐ ┌──┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴┴─┴─┐  Stage N
│      RepartitionExec      │  │      RepartitionExec      │ │      RepartitionExec      │     │
│         (task 1)          │  │         (task 2)          │ │         (task 3)          │     │
└───────────────────────────┘  └───────────────────────────┘ └───────────────────────────┘     ■

The communication between two stages across a NetworkShuffleExec has two implications:

• Each task in Stage N+1 gathers data from all tasks in Stage N
• The total number of partitions across all tasks in Stage N+1 is equal to the number of partitions in a single task in Stage N. (e.g. (1,2,3,4)+(5,6,7,8) = (1,2,3,4,5,6,7,8) )

This node has two variants.

1. Pending: acts as a placeholder for the distributed optimization step to mark it as ready.
2. Ready: runs within a distributed stage and queries the next input stage over the network using Arrow Flight.

Implementations

impl NetworkShuffleExec

pub fn try_new( input: Arc<dyn ExecutionPlan>, query_id: Uuid, num: usize, task_count: usize, input_task_count: usize, ) -> Result<Self, DataFusionError>

Builds a new NetworkShuffleExec in “Pending” state.

Typically, the input to this node is a RepartitionExec with a Partitioning::Hash partition scheme.

Trait Implementations

impl Clone for NetworkShuffleExec

fn clone(&self) -> NetworkShuffleExec

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for NetworkShuffleExec

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

Formats the value using the given formatter.

impl DisplayAs for NetworkShuffleExec

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

Format according to DisplayFormatType, used when verbose representation looks different from the default one

impl ExecutionPlan for NetworkShuffleExec

fn name(&self) -> &str

Short name for the ExecutionPlan, such as ‘DataSourceExec’.

fn as_any(&self) -> &dyn Any

Returns the execution plan as Any so that it can be downcast to a specific implementation.

fn properties(&self) -> &Arc<PlanProperties>

Return properties of the output of the ExecutionPlan, such as output ordering(s), partitioning information etc.

fn children(&self) -> Vec<&Arc<dyn ExecutionPlan>>

Get a list of children ExecutionPlans that act as inputs to this plan. The returned list will be empty for leaf nodes such as scans, will contain a single value for unary nodes, or two values for binary nodes (such as joins).

fn with_new_children( self: Arc<Self>, children: Vec<Arc<dyn ExecutionPlan>>, ) -> Result<Arc<dyn ExecutionPlan>, DataFusionError>

Returns a new ExecutionPlan where all existing children were replaced by the children, in order

fn execute( &self, partition: usize, context: Arc<TaskContext>, ) -> Result<SendableRecordBatchStream, DataFusionError>

Begin execution of partition, returning a Stream of RecordBatches.

fn metrics(&self) -> Option<MetricsSet>

Return a snapshot of the set of Metrics for this ExecutionPlan. If no Metrics are available, return None.

fn static_name() -> &'static str

where Self: Sized,

Short name for the ExecutionPlan, such as ‘DataSourceExec’. Like name but can be called without an instance.

fn schema(&self) -> Arc<Schema>

Get the schema for this execution plan

fn check_invariants(&self, check: InvariantLevel) -> Result<(), DataFusionError>

Returns an error if this individual node does not conform to its invariants. These invariants are typically only checked in debug mode.

fn required_input_distribution(&self) -> Vec<Distribution>

Specifies the data distribution requirements for all the children for this ExecutionPlan, By default it’s [Distribution::UnspecifiedDistribution] for each child,

fn required_input_ordering(&self) -> Vec<Option<OrderingRequirements>>

Specifies the ordering required for all of the children of this ExecutionPlan.

fn maintains_input_order(&self) -> Vec<bool>

Returns false if this ExecutionPlan’s implementation may reorder rows within or between partitions.

fn benefits_from_input_partitioning(&self) -> Vec<bool>

Specifies whether the ExecutionPlan benefits from increased parallelization at its input for each child.

fn reset_state( self: Arc<Self>, ) -> Result<Arc<dyn ExecutionPlan>, DataFusionError>

Reset any internal state within this ExecutionPlan.

fn repartitioned( &self, _target_partitions: usize, _config: &ConfigOptions, ) -> Result<Option<Arc<dyn ExecutionPlan>>, DataFusionError>

If supported, attempt to increase the partitioning of this ExecutionPlan to produce target_partitions partitions.

fn partition_statistics( &self, partition: Option<usize>, ) -> Result<Statistics, DataFusionError>

Returns statistics for a specific partition of this ExecutionPlan node. If statistics are not available, should return Statistics::new_unknown (the default), not an error. If partition is None, it returns statistics for the entire plan.

fn supports_limit_pushdown(&self) -> bool

Returns true if a limit can be safely pushed down through this ExecutionPlan node.

fn with_fetch(&self, _limit: Option<usize>) -> Option<Arc<dyn ExecutionPlan>>

Returns a fetching variant of this ExecutionPlan node, if it supports fetch limits. Returns None otherwise.

fn fetch(&self) -> Option<usize>

Gets the fetch count for the operator, None means there is no fetch.

fn cardinality_effect(&self) -> CardinalityEffect

Gets the effect on cardinality, if known

fn try_swapping_with_projection( &self, _projection: &ProjectionExec, ) -> Result<Option<Arc<dyn ExecutionPlan>>, DataFusionError>

Attempts to push down the given projection into the input of this ExecutionPlan.

fn gather_filters_for_pushdown( &self, _phase: FilterPushdownPhase, parent_filters: Vec<Arc<dyn PhysicalExpr>>, _config: &ConfigOptions, ) -> Result<FilterDescription, DataFusionError>

Collect filters that this node can push down to its children. Filters that are being pushed down from parents are passed in, and the node may generate additional filters to push down. For example, given the plan FilterExec -> HashJoinExec -> DataSourceExec, what will happen is that we recurse down the plan calling ExecutionPlan::gather_filters_for_pushdown:

fn handle_child_pushdown_result( &self, _phase: FilterPushdownPhase, child_pushdown_result: ChildPushdownResult, _config: &ConfigOptions, ) -> Result<FilterPushdownPropagation<Arc<dyn ExecutionPlan>>, DataFusionError>

Handle the result of a child pushdown.

fn with_new_state( &self, _state: Arc<dyn Any + Send + Sync>, ) -> Option<Arc<dyn ExecutionPlan>>

Injects arbitrary run-time state into this execution plan, returning a new plan instance that incorporates that state if it is relevant to the concrete node implementation.

fn try_pushdown_sort( &self, _order: &[PhysicalSortExpr], ) -> Result<SortOrderPushdownResult<Arc<dyn ExecutionPlan>>, DataFusionError>

Try to push down sort ordering requirements to this node.

fn with_preserve_order( &self, _preserve_order: bool, ) -> Option<Arc<dyn ExecutionPlan>>

Returns a variant of this ExecutionPlan that is aware of order-sensitivity.

impl NetworkBoundary for NetworkShuffleExec

fn input_stage(&self) -> &Stage

Returns the assigned input Stage, if any.

fn with_input_stage(&self, input_stage: Stage) -> Result<Arc<dyn ExecutionPlan>>

Called when a Stage is correctly formed. The NetworkBoundary can use this information to perform any internal transformations necessary for distributed execution.