Struct HistogramFold

pub struct HistogramFold {
    le_column: String,
    ts_column: String,
    input: LogicalPlan,
    field_column: String,
    quantile: OrderedF64,
    output_schema: DFSchemaRef,
}

HistogramFold will fold the conventional (non-native) histogram (1) for later computing.

Specifically, it will transform the le and field column into a complex type, and samples on other tag columns:

• le will become a [ListArray] of f64. With each bucket bound parsed
• field will become a [ListArray] of f64
• other columns will be sampled every bucket_num element, but their types won’t change.

Due to the folding or sampling, the output rows number will become input_rows / bucket_num.

Requirement

• Input should be sorted on <tag list>, ts, le ASC.
• The value set of le should be same. I.e., buckets of every series should be same.

Fields

le_column: String

Name of the le column. It’s a special column in prometheus for implementing conventional histogram. It’s a string column with “literal” float value, like “+Inf”, “0.001” etc.

ts_column: String

input: LogicalPlan

field_column: String

quantile: OrderedF64

output_schema: DFSchemaRef

Implementations

impl HistogramFold

pub fn new( le_column: String, field_column: String, ts_column: String, quantile: f64, input: LogicalPlan, ) -> DataFusionResult<Self>

pub const fn name() -> &'static str

fn check_schema( input_schema: &DFSchemaRef, le_column: &str, field_column: &str, ts_column: &str, ) -> DataFusionResult<()>

pub fn to_execution_plan( &self, exec_input: Arc<dyn ExecutionPlan>, ) -> Arc<dyn ExecutionPlan>

fn convert_schema( input_schema: &DFSchemaRef, le_column: &str, ) -> DataFusionResult<DFSchemaRef>

Transform the schema

• le will be removed

Trait Implementations

impl Debug for HistogramFold

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

Formats the value using the given formatter.

impl Hash for HistogramFold

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

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 HistogramFold

fn eq(&self, other: &HistogramFold) -> 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 PartialOrd for HistogramFold

fn partial_cmp(&self, other: &Self) -> Option<Ordering>

This method returns an ordering between self and other values if one exists.

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

Tests less than (for self and other) and is used by the < operator.

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

Tests less than or equal to (for self and other) and is used by the <= operator.

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

Tests greater than (for self and other) and is used by the > operator.

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

Tests greater than or equal to (for self and other) and is used by the >= operator.

impl UserDefinedLogicalNodeCore for HistogramFold

fn name(&self) -> &str

Return the plan’s name.

fn inputs(&self) -> Vec<&LogicalPlan>

Return the logical plan’s inputs.

fn schema(&self) -> &DFSchemaRef

Return the output schema of this logical plan node.

fn expressions(&self) -> Vec<Expr>

Returns all expressions in the current logical plan node. This should not include expressions of any inputs (aka non-recursively). These expressions are used for optimizer passes and rewrites.

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

Write a single line, human readable string to f for use in explain plan.

fn with_exprs_and_inputs( &self, _exprs: Vec<Expr>, inputs: Vec<LogicalPlan>, ) -> DataFusionResult<Self>

Create a new UserDefinedLogicalNode with the specified children and expressions. This function is used during optimization when the plan is being rewritten and a new instance of the UserDefinedLogicalNode must be created.

fn prevent_predicate_push_down_columns(&self) -> HashSet<String>

A list of output columns (e.g. the names of columns in self.schema()) for which predicates can not be pushed below this node without changing the output.

fn from_template(&self, exprs: &[Expr], inputs: &[LogicalPlan]) -> Self

👎Deprecated since 39.0.0: use with_exprs_and_inputs instead

fn necessary_children_exprs( &self, _output_columns: &[usize], ) -> Option<Vec<Vec<usize>>>

Returns the necessary input columns for this node required to compute the columns in the output schema

fn supports_limit_pushdown(&self) -> bool

Returns true if a limit can be safely pushed down through this UserDefinedLogicalNode node.

impl Eq for HistogramFold

impl StructuralPartialEq for HistogramFold