Struct datafusion::physical_plan::unnest::UnnestExec
source · pub struct UnnestExec { /* private fields */ }
Expand description
Unnest the given column by joining the row with each value in the nested type.
Implementations§
source§impl UnnestExec
impl UnnestExec
sourcepub fn new(
input: Arc<dyn ExecutionPlan>,
column: Column,
schema: SchemaRef
) -> Self
pub fn new( input: Arc<dyn ExecutionPlan>, column: Column, schema: SchemaRef ) -> Self
Create a new UnnestExec.
Trait Implementations§
source§impl Debug for UnnestExec
impl Debug for UnnestExec
source§impl ExecutionPlan for UnnestExec
impl ExecutionPlan for UnnestExec
source§fn unbounded_output(&self, children: &[bool]) -> Result<bool>
fn unbounded_output(&self, children: &[bool]) -> Result<bool>
Specifies whether this plan generates an infinite stream of records. If the plan does not support pipelining, but it its input(s) are infinite, returns an error to indicate this.
source§fn as_any(&self) -> &dyn Any
fn as_any(&self) -> &dyn Any
Returns the execution plan as
Any
so that it can be
downcast to a specific implementation.source§fn children(&self) -> Vec<Arc<dyn ExecutionPlan>>
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).
source§fn with_new_children(
self: Arc<Self>,
children: Vec<Arc<dyn ExecutionPlan>>
) -> Result<Arc<dyn ExecutionPlan>>
fn with_new_children( self: Arc<Self>, children: Vec<Arc<dyn ExecutionPlan>> ) -> Result<Arc<dyn ExecutionPlan>>
Returns a new plan where all children were replaced by new plans.
source§fn required_input_distribution(&self) -> Vec<Distribution>
fn required_input_distribution(&self) -> Vec<Distribution>
Specifies the data distribution requirements for all the
children for this operator, By default it’s [Distribution::UnspecifiedDistribution] for each child,
source§fn output_partitioning(&self) -> Partitioning
fn output_partitioning(&self) -> Partitioning
Specifies the output partitioning scheme of this plan
source§fn output_ordering(&self) -> Option<&[PhysicalSortExpr]>
fn output_ordering(&self) -> Option<&[PhysicalSortExpr]>
If the output of this operator within each partition is sorted,
returns
Some(keys)
with the description of how it was sorted. Read moresource§fn equivalence_properties(&self) -> EquivalenceProperties
fn equivalence_properties(&self) -> EquivalenceProperties
Get the EquivalenceProperties within the plan
source§fn execute(
&self,
partition: usize,
context: Arc<TaskContext>
) -> Result<SendableRecordBatchStream>
fn execute( &self, partition: usize, context: Arc<TaskContext> ) -> Result<SendableRecordBatchStream>
creates an iterator
source§fn statistics(&self) -> Statistics
fn statistics(&self) -> Statistics
Returns the global output statistics for this
ExecutionPlan
node.source§fn required_input_ordering(&self) -> Vec<Option<&[PhysicalSortExpr]>>
fn required_input_ordering(&self) -> Vec<Option<&[PhysicalSortExpr]>>
Specifies the ordering requirements for all of the children
For each child, it’s the local ordering requirement within
each partition rather than the global ordering Read more
source§fn maintains_input_order(&self) -> Vec<bool>
fn maintains_input_order(&self) -> Vec<bool>
Returns
false
if this operator’s implementation may reorder
rows within or between partitions. Read moresource§fn benefits_from_input_partitioning(&self) -> bool
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 Read more