Struct datafusion::physical_plan::joins::CrossJoinExec
source · pub struct CrossJoinExec { /* private fields */ }
Expand description
executes partitions in parallel and combines them into a set of partitions by combining all values from the left with all values on the right
Implementations§
source§impl CrossJoinExec
impl CrossJoinExec
sourcepub fn try_new(
left: Arc<dyn ExecutionPlan>,
right: Arc<dyn ExecutionPlan>
) -> Result<Self>
pub fn try_new(
left: Arc<dyn ExecutionPlan>,
right: Arc<dyn ExecutionPlan>
) -> Result<Self>
Tries to create a new CrossJoinExec.
Error
This function errors when left and right schema’s can’t be combined
sourcepub fn left(&self) -> &Arc<dyn ExecutionPlan>
pub fn left(&self) -> &Arc<dyn ExecutionPlan>
left (build) side which gets loaded in memory
sourcepub fn right(&self) -> &Arc<dyn ExecutionPlan>
pub fn right(&self) -> &Arc<dyn ExecutionPlan>
right side which gets combined with left side
Trait Implementations§
source§impl Debug for CrossJoinExec
impl Debug for CrossJoinExec
source§impl ExecutionPlan for CrossJoinExec
impl ExecutionPlan for CrossJoinExec
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). Read more
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, Read more
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 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 the
children for this operator. Read more
source§fn relies_on_input_order(&self) -> bool
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. Read moresource§fn maintains_input_order(&self) -> bool
fn maintains_input_order(&self) -> 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