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DistributedLeafExec

Struct DistributedLeafExec 

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pub struct DistributedLeafExec { /* private fields */ }
Expand description

Represents a leaf node ready to be distributed across N tasks, where the variant of the node belonging to each task is stored in a Vec of N positions.

While sending this plan over the wire to a remote worker, only the appropriate variant is sent.

This ExecutionPlan implementation is typically returned by crate::TaskEstimator::scale_up_leaf_node, which will be called for scaling up a node for distribution. The process typically looks like this:

  1. The distributed planner calls crate::TaskEstimator::scale_up_leaf_node providing a leaf node and the amount of tasks in which it should be distributed:
┌──────────────┐
│DataSourceExec│ + 3 tasks
└──────────────┘
  1. The crate::TaskEstimator implementation, either user provided or a default one, returns a DistributedLeafExec adhering to this task count:
┌────────────────────────────────────────────────┐
│              DistributedLeafExec               │
│                                                │
│┌──────────────┐┌──────────────┐┌──────────────┐│
││DataSourceExec││DataSourceExec││DataSourceExec││
││  for task 0  ││  for task 1  ││  for task 2  ││
│└──────────────┘└──────────────┘└──────────────┘│
└────────────────────────────────────────────────┘
  1. The crate::DistributedExec node, upon being executed, will send the different variants of the leaf node to the respective workers, instead of sending the full DistributedLeafExec:
┌──────────────────┐┌──────────────────┐┌──────────────────┐
│     Worker 0     ││     Worker 1     ││     Worker 2     │
│                  ││                  ││                  │
│       ...        ││       ...        ││       ...        │
│                  ││                  ││                  │
│ ┌──────────────┐ ││ ┌──────────────┐ ││ ┌──────────────┐ │
│ │   SomeExec   │ ││ │   SomeExec   │ ││ │   SomeExec   │ │
│ │              │ ││ │              │ ││ │              │ │
│ └──────────────┘ ││ └──────────────┘ ││ └──────────────┘ │
│ ┌──────────────┐ ││ ┌──────────────┐ ││ ┌──────────────┐ │
│ │DataSourceExec│ ││ │DataSourceExec│ ││ │DataSourceExec│ │
│ │  for task 0  │ ││ │  for task 1  │ ││ │  for task 2  │ │
│ └──────────────┘ ││ └──────────────┘ ││ └──────────────┘ │
└──────────────────┘└──────────────────┘└──────────────────┘

This way, the different workers get to execute different versions of the same plan, each handling its own range of non-overlapping data.

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impl DistributedLeafExec

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pub fn try_new( original: Arc<dyn ExecutionPlan>, variants: impl IntoIterator<Item = Arc<dyn ExecutionPlan>>, ) -> Result<Self>

Builds a new DistributedLeafExec based on the provided original plan and its per-task variants. Provided variants must expose the same partition count as the original plan.

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pub fn original(&self) -> &Arc<dyn ExecutionPlan>

The plan this leaf was built from (the leaf passed to crate::TaskEstimator::scale_up_leaf_node). Useful for recognising which DistributedLeafExec you are looking at — e.g. by downcasting it to your own leaf type — before inspecting its DistributedLeafExec::variants.

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pub fn variants(&self) -> &[Arc<dyn ExecutionPlan>]

The per-task variants, in task order: variants()[i] is the plan sent to task i. Useful for inspecting per-task information (e.g. data locality) when routing tasks to workers via crate::TaskEstimator::route_tasks.

Trait Implementations§

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impl Debug for DistributedLeafExec

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

Formats the value using the given formatter. Read more
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impl DisplayAs for DistributedLeafExec

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fn fmt_as(&self, t: DisplayFormatType, f: &mut Formatter<'_>) -> Result

Format according to DisplayFormatType, used when verbose representation looks different from the default one Read more
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impl ExecutionPlan for DistributedLeafExec

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fn name(&self) -> &str

Short name for the ExecutionPlan, such as ‘DataSourceExec’. Read more
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fn properties(&self) -> &Arc<PlanProperties>

Return properties of the output of the ExecutionPlan, such as output ordering(s), partitioning information etc. Read more
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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).
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fn with_new_children( self: Arc<Self>, _children: Vec<Arc<dyn ExecutionPlan>>, ) -> Result<Arc<dyn ExecutionPlan>>

Returns a new ExecutionPlan where all existing children were replaced by the children, in order
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fn execute( &self, partition: usize, context: Arc<TaskContext>, ) -> Result<SendableRecordBatchStream>

Begin execution of partition, returning a Stream of RecordBatches. Read more
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fn metrics(&self) -> Option<MetricsSet>

Return a snapshot of the set of Metrics for this ExecutionPlan. If no Metrics are available, return None. Read more
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fn partition_statistics( &self, partition: Option<usize>, ) -> Result<Arc<Statistics>>

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.
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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.
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fn downcast_delegate(&self) -> Option<&(dyn ExecutionPlan + 'static)>

Returns the plan that provides this plan’s public ExecutionPlan downcast identity. Read more
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fn schema(&self) -> Arc<Schema>

Get the schema for this execution plan
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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. Read more
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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,
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fn required_input_ordering(&self) -> Vec<Option<OrderingRequirements>>

Specifies the ordering required for all of the children of this ExecutionPlan. Read more
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fn maintains_input_order(&self) -> Vec<bool>

Returns false if this ExecutionPlan’s implementation may reorder rows within or between partitions. Read more
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fn benefits_from_input_partitioning(&self) -> Vec<bool>

Specifies whether the ExecutionPlan benefits from increased parallelization at its input for each child. Read more
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fn reset_state( self: Arc<Self>, ) -> Result<Arc<dyn ExecutionPlan>, DataFusionError>

Reset any internal state within this ExecutionPlan. Read more
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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. Read more
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fn supports_limit_pushdown(&self) -> bool

Returns true if a limit can be safely pushed down through this ExecutionPlan node. Read more
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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. Read more
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fn fetch(&self) -> Option<usize>

Gets the fetch count for the operator, None means there is no fetch.
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fn cardinality_effect(&self) -> CardinalityEffect

Gets the effect on cardinality, if known
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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. Read more
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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: Read more
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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. Read more
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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. Read more
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fn try_pushdown_sort( &self, _order: &[PhysicalSortExpr], ) -> Result<SortOrderPushdownResult<Arc<dyn ExecutionPlan>>, DataFusionError>

Try to push down sort ordering requirements to this node. Read more
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fn with_preserve_order( &self, _preserve_order: bool, ) -> Option<Arc<dyn ExecutionPlan>>

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

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