Enum datafusion_python::datafusion_expr::logical_plan::Partitioning

pub enum Partitioning {
    RoundRobinBatch(usize),
    Hash(Vec<Expr>, usize),
    DistributeBy(Vec<Expr>),
}

Logical partitioning schemes supported by the repartition operator.

Variants

RoundRobinBatch(usize)

Allocate batches using a round-robin algorithm and the specified number of partitions

Hash(Vec<Expr>, usize)

Allocate rows based on a hash of one of more expressions and the specified number of partitions.

DistributeBy(Vec<Expr>)

The DISTRIBUTE BY clause is used to repartition the data based on the input expressions

Trait Implementations

impl Clone for Partitioning

fn clone(&self) -> Partitioning

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Partitioning

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

Formats the value using the given formatter.

impl From<Partitioning> for PyPartitioning

fn from(partitioning: Partitioning) -> Self

Converts to this type from the input type.

impl From<PyPartitioning> for Partitioning

fn from(partitioning: PyPartitioning) -> Self

Converts to this type from the input type.

impl Hash for Partitioning

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 Partitioning

fn eq(&self, other: &Partitioning) -> 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 Partitioning

impl StructuralPartialEq for Partitioning