Struct datafusion_functions_aggregate::median::Median

pub struct Median { /* private fields */ }

MEDIAN aggregate expression. If using the non-distinct variation, then this uses a lot of memory because all values need to be stored in memory before a result can be computed. If an approximation is sufficient then APPROX_MEDIAN provides a much more efficient solution.

If using the distinct variation, the memory usage will be similarly high if the cardinality is high as it stores all distinct values in memory before computing the result, but if cardinality is low then memory usage will also be lower.

Implementations

impl Median

pub fn new() -> Self

Trait Implementations

impl AggregateUDFImpl for Median

fn as_any(&self) -> &dyn Any

Returns this object as an Any trait object

fn name(&self) -> &str

Returns this function’s name

fn signature(&self) -> &Signature

Returns the function’s Signature for information about what input types are accepted and the function’s Volatility.

fn return_type(&self, arg_types: &[DataType]) -> Result<DataType>

What DataType will be returned by this function, given the types of the arguments

fn state_fields(&self, args: StateFieldsArgs<'_>) -> Result<Vec<Field>>

Return the fields used to store the intermediate state of this accumulator.

fn accumulator( &self, acc_args: AccumulatorArgs<'_>, ) -> Result<Box<dyn Accumulator>>

Return a new Accumulator that aggregates values for a specific group during query execution.

fn aliases(&self) -> &[String]

Returns any aliases (alternate names) for this function.

fn groups_accumulator_supported(&self, _args: AccumulatorArgs<'_>) -> bool

If the aggregate expression has a specialized GroupsAccumulator implementation. If this returns true, [Self::create_groups_accumulator] will be called.

fn create_groups_accumulator( &self, _args: AccumulatorArgs<'_>, ) -> Result<Box<dyn GroupsAccumulator>, DataFusionError>

Return a specialized GroupsAccumulator that manages state for all groups.

fn create_sliding_accumulator( &self, args: AccumulatorArgs<'_>, ) -> Result<Box<dyn Accumulator>, DataFusionError>

Sliding accumulator is an alternative accumulator that can be used for window functions. It has retract method to revert the previous update.

fn with_beneficial_ordering( self: Arc<Self>, _beneficial_ordering: bool, ) -> Result<Option<Arc<dyn AggregateUDFImpl>>, DataFusionError>

Sets the indicator whether ordering requirements of the AggregateUDFImpl is satisfied by its input. If this is not the case, UDFs with order sensitivity AggregateOrderSensitivity::Beneficial can still produce the correct result with possibly more work internally.

fn order_sensitivity(&self) -> AggregateOrderSensitivity

Gets the order sensitivity of the UDF. See AggregateOrderSensitivity for possible options.

fn simplify( &self, ) -> Option<Box<dyn Fn(AggregateFunction, &dyn SimplifyInfo) -> Result<Expr, DataFusionError>>>

Optionally apply per-UDaF simplification / rewrite rules.

fn reverse_expr(&self) -> ReversedUDAF

Returns the reverse expression of the aggregate function.

fn coerce_types( &self, _arg_types: &[DataType], ) -> Result<Vec<DataType>, DataFusionError>

Coerce arguments of a function call to types that the function can evaluate.

fn equals(&self, other: &dyn AggregateUDFImpl) -> bool

Return true if this aggregate UDF is equal to the other.

fn hash_value(&self) -> u64

Returns a hash value for this aggregate UDF.

fn is_descending(&self) -> Option<bool>

If this function is max, return true if the function is min, return false otherwise return None (the default)

impl Debug for Median

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

Formats the value using the given formatter.

impl Default for Median

fn default() -> Self

Returns the “default value” for a type.