Struct CumeDistEvaluator 

pub(crate) struct CumeDistEvaluator;

Trait Implementations

impl Debug for CumeDistEvaluator

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

Formats the value using the given formatter.

impl Default for CumeDistEvaluator

fn default() -> CumeDistEvaluator

Returns the “default value” for a type.

impl PartitionEvaluator for CumeDistEvaluator

fn evaluate_all_with_rank( &self, num_rows: usize, ranks_in_partition: &[Range<usize>], ) -> Result<ArrayRef>

Computes the cumulative distribution for all rows in the partition

fn include_rank(&self) -> bool

Can this function be evaluated with (only) rank

fn memoize( &mut self, _state: &mut WindowAggState, ) -> Result<(), DataFusionError>

When the window frame has a fixed beginning (e.g UNBOUNDED PRECEDING), some functions such as FIRST_VALUE, LAST_VALUE and NTH_VALUE do not need the (unbounded) input once they have seen a certain amount of input.

fn get_range( &self, idx: usize, _n_rows: usize, ) -> Result<Range<usize>, DataFusionError>

If uses_window_frame flag is false. This method is used to calculate required range for the window function during stateful execution.

fn is_causal(&self) -> bool

Get whether evaluator needs future data for its result (if so returns false) or not

fn evaluate_all( &mut self, values: &[Arc<dyn Array>], num_rows: usize, ) -> Result<Arc<dyn Array>, DataFusionError>

Evaluate a window function on an entire input partition.

fn evaluate( &mut self, _values: &[Arc<dyn Array>], _range: &Range<usize>, ) -> Result<ScalarValue, DataFusionError>

Evaluate window function on a range of rows in an input partition.x

fn supports_bounded_execution(&self) -> bool

Can the window function be incrementally computed using bounded memory?

fn uses_window_frame(&self) -> bool

Does the window function use the values from the window frame, if one is specified?