Enum polars_lazy::logical_plan::LogicalPlan
source · [−]pub enum LogicalPlan {
Show 19 variants
Selection {
input: Box<LogicalPlan>,
predicate: Expr,
},
Cache {
input: Box<LogicalPlan>,
},
CsvScan {
path: PathBuf,
schema: SchemaRef,
options: CsvParserOptions,
predicate: Option<Expr>,
aggregate: Vec<Expr>,
},
ParquetScan {
path: PathBuf,
schema: SchemaRef,
predicate: Option<Expr>,
aggregate: Vec<Expr>,
options: ParquetOptions,
},
IpcScan {
path: PathBuf,
schema: SchemaRef,
options: IpcScanOptions,
predicate: Option<Expr>,
aggregate: Vec<Expr>,
},
DataFrameScan {
df: Arc<DataFrame>,
schema: SchemaRef,
projection: Option<Vec<Expr>>,
selection: Option<Expr>,
},
LocalProjection {
expr: Vec<Expr>,
input: Box<LogicalPlan>,
schema: SchemaRef,
},
Projection {
expr: Vec<Expr>,
input: Box<LogicalPlan>,
schema: SchemaRef,
},
Aggregate {
input: Box<LogicalPlan>,
keys: Arc<Vec<Expr>>,
aggs: Vec<Expr>,
schema: SchemaRef,
apply: Option<Arc<dyn DataFrameUdf>>,
maintain_order: bool,
options: GroupbyOptions,
},
Join {
input_left: Box<LogicalPlan>,
input_right: Box<LogicalPlan>,
schema: SchemaRef,
left_on: Vec<Expr>,
right_on: Vec<Expr>,
options: JoinOptions,
},
HStack {
input: Box<LogicalPlan>,
exprs: Vec<Expr>,
schema: SchemaRef,
},
Distinct {
input: Box<LogicalPlan>,
options: DistinctOptions,
},
Sort {
input: Box<LogicalPlan>,
by_column: Vec<Expr>,
args: SortArguments,
},
Explode {
input: Box<LogicalPlan>,
columns: Vec<String>,
},
Slice {
input: Box<LogicalPlan>,
offset: i64,
len: u32,
},
Melt {
input: Box<LogicalPlan>,
id_vars: Arc<Vec<String>>,
value_vars: Arc<Vec<String>>,
schema: SchemaRef,
},
Udf {
input: Box<LogicalPlan>,
function: Arc<dyn DataFrameUdf>,
options: LogicalPlanUdfOptions,
schema: Option<SchemaRef>,
},
Union {
inputs: Vec<LogicalPlan>,
options: UnionOptions,
},
Error {
input: Box<LogicalPlan>,
err: Arc<Mutex<Option<PolarsError>>>,
},
}
Variants
Selection
Filter on a boolean mask
Cache
Fields
input: Box<LogicalPlan>
Cache the input at this point in the LP
CsvScan
Scan a CSV file
ParquetScan
Scan a Parquet file
IpcScan
DataFrameScan
In memory DataFrame
LocalProjection
Projection
Column selection
Aggregate
Groupby aggregation
Join
Fields
input_left: Box<LogicalPlan>
input_right: Box<LogicalPlan>
schema: SchemaRef
options: JoinOptions
Join operation
HStack
Adding columns to the table without a Join
Distinct
Remove duplicates from the table
Sort
Sort the table
Explode
An explode operation
Slice
Slice the table
Melt
A Melt operation
Udf
A User Defined Function
Union
Error
Catches errors and throws them later
Implementations
sourceimpl LogicalPlan
impl LogicalPlan
Trait Implementations
sourceimpl Clone for LogicalPlan
impl Clone for LogicalPlan
sourcefn clone(&self) -> LogicalPlan
fn clone(&self) -> LogicalPlan
Returns a copy of the value. Read more
1.0.0 · sourcefn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from source
. Read more
sourceimpl Debug for LogicalPlan
impl Debug for LogicalPlan
sourceimpl Default for LogicalPlan
impl Default for LogicalPlan
sourceimpl From<LogicalPlan> for LazyFrame
impl From<LogicalPlan> for LazyFrame
sourcefn from(plan: LogicalPlan) -> Self
fn from(plan: LogicalPlan) -> Self
Performs the conversion.
Auto Trait Implementations
impl !RefUnwindSafe for LogicalPlan
impl Send for LogicalPlan
impl Sync for LogicalPlan
impl Unpin for LogicalPlan
impl !UnwindSafe for LogicalPlan
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcefn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
sourceimpl<T> Pointable for T
impl<T> Pointable for T
sourceimpl<T> ToOwned for T where
T: Clone,
impl<T> ToOwned for T where
T: Clone,
type Owned = T
type Owned = T
The resulting type after obtaining ownership.
sourcefn clone_into(&self, target: &mut T)
fn clone_into(&self, target: &mut T)
🔬 This is a nightly-only experimental API. (
toowned_clone_into
)Uses borrowed data to replace owned data, usually by cloning. Read more