Struct datafusion_python::datafusion_expr::logical_plan::Analyze

pub struct Analyze {
    pub verbose: bool,
    pub input: Arc<LogicalPlan>,
    pub schema: Arc<DFSchema>,
}

Runs the actual plan, and then prints the physical plan with with execution metrics.

Fields

verbose: bool

Should extra detail be included?

input: Arc<LogicalPlan>

The logical plan that is being EXPLAIN ANALYZE’d

schema: Arc<DFSchema>

The output schema of the explain (2 columns of text)

Trait Implementations

impl Clone for Analyze

fn clone(&self) -> Analyze

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Analyze

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

Formats the value using the given formatter.

impl From<Analyze> for PyAnalyze

fn from(analyze: Analyze) -> PyAnalyze

Converts to this type from the input type.

impl From<PyAnalyze> for Analyze

fn from(analyze: PyAnalyze) -> Self

Converts to this type from the input type.

impl Hash for Analyze

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 Analyze

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

impl StructuralPartialEq for Analyze