Struct datafusion::physical_plan::memory::MemoryExec

pub struct MemoryExec { /* private fields */ }

Execution plan for reading in-memory batches of data

Implementations

impl MemoryExec

pub fn try_new(
    partitions: &[Vec<RecordBatch>],
    schema: SchemaRef,
    projection: Option<Vec<usize>>
) -> Result<Self>

Create a new execution plan for reading in-memory record batches The provided schema should not have the projection applied.

Trait Implementations

impl Debug for MemoryExec

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

Formats the value using the given formatter.

impl ExecutionPlan for MemoryExec

fn as_any(&self) -> &dyn Any

Return a reference to Any that can be used for downcasting

fn schema(&self) -> SchemaRef

Get the schema for this execution plan

fn output_partitioning(&self) -> Partitioning

Get the output partitioning of this plan

fn statistics(&self) -> Statistics

We recompute the statistics dynamically from the arrow metadata as it is pretty cheap to do so

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

Get a list of child execution plans that provide the input for this plan. The returned list will be empty for leaf nodes, will contain a single value for unary nodes, or two values for binary nodes (such as joins).

fn output_ordering(&self) -> Option<&[PhysicalSortExpr]>

If the output of this operator is sorted, returns Some(keys) with the description of how it was sorted.

fn relies_on_input_order(&self) -> bool

Returns true if this operator relies on its inputs being produced in a certain order (for example that they are sorted a particular way) for correctness.

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

Returns a new plan where all children were replaced by new plans.

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

creates an iterator

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

Format this ExecutionPlan to f in the specified type.

fn required_child_distribution(&self) -> Distribution

Specifies the data distribution requirements of all the children for this operator

fn maintains_input_order(&self) -> bool

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

fn benefits_from_input_partitioning(&self) -> bool

Returns true if this operator would benefit from partitioning its input (and thus from more parallelism). For operators that do very little work the overhead of extra parallelism may outweigh any benefits

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

Return a snapshot of the set of Metrics for this ExecutionPlan.