Struct datafusion_python::datafusion_expr::expr::AggregateUDF

pub struct AggregateUDF {
    pub fun: Arc<AggregateUDF>,
    pub args: Vec<Expr>,
    pub filter: Option<Box<Expr>>,
    pub order_by: Option<Vec<Expr>>,
}

User Defined Aggregate Function

See udaf::AggregateUDF for more information.

Fields

fun: Arc<AggregateUDF>

The function

args: Vec<Expr>

List of expressions to feed to the functions as arguments

filter: Option<Box<Expr>>

Optional filter

order_by: Option<Vec<Expr>>

Optional ORDER BY applied prior to aggregating

Implementations

impl AggregateUDF

pub fn new( fun: Arc<AggregateUDF>, args: Vec<Expr>, filter: Option<Box<Expr>>, order_by: Option<Vec<Expr>>, ) -> AggregateUDF

Create a new AggregateUDF expression

Trait Implementations

impl Clone for AggregateUDF

fn clone(&self) -> AggregateUDF

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for AggregateUDF

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

Formats the value using the given formatter.

impl Hash for AggregateUDF

fn hash<__H>(&self, state: &mut __H)

where __H: Hasher,

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl PartialEq for AggregateUDF

fn eq(&self, other: &AggregateUDF) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Eq for AggregateUDF

impl StructuralPartialEq for AggregateUDF