Struct elasticsearch_dsl::search::aggregations::metrics::BoxplotAggregation

pub struct BoxplotAggregation { /* private fields */ }

A boxplot metrics aggregation that computes boxplot of numeric values extracted from the aggregated documents. These values can be generated from specific numeric or histogram fields in the documents.

The boxplot aggregation returns essential information for making a box plot: minimum, maximum median, first quartile (25th percentile) and third quartile (75th percentile) values.

The algorithm used by the boxplot metric is called TDigest (introduced by Ted Dunning in Computing Accurate Quantiles using T-Digests).

Boxplot as other percentile aggregations are also non-deterministic. This means you can get slightly different results using the same data.

https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-metrics-boxplot-aggregation.html

Implementations

impl BoxplotAggregation

pub fn compression<T>(self, compression: T) -> Selfwhere
    T: Into<Number>,

Approximate algorithms must balance memory utilization with estimation accuracy.

The TDigest algorithm uses a number of “nodes” to approximate percentiles —— the more nodes available, the higher the accuracy (and large memory footprint) proportional to the volume of data. The compression parameter limits the maximum number of nodes to 20 * compression.

Therefore, by increasing the compression value, you can increase the accuracy of your percentiles at the cost of more memory. Larger compression values also make the algorithm slower since the underlying tree data structure grows in size, resulting in more expensive operations. The default compression value is 100.

A “node” uses roughly 32 bytes of memory, so under worst-case scenarios (large amount of data which arrives sorted and in-order) the default settings will produce a TDigest roughly 64KB in size. In practice data tends to be more random and the TDigest will use less memory.

pub fn missing<T>(self, missing: T) -> Selfwhere
    T: Into<Number>,

The missing parameter defines how documents that are missing a value should be treated. By default they will be ignored but it is also possible to treat them as if they had a value.

Trait Implementations

impl Clone for BoxplotAggregation

fn clone(&self) -> BoxplotAggregation

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for BoxplotAggregation

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

Formats the value using the given formatter.

impl From<BoxplotAggregation> for Aggregation

fn from(q: BoxplotAggregation) -> Self

Converts to this type from the input type.

impl PartialEq<BoxplotAggregation> for BoxplotAggregation

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

This method tests for self and other values to be equal, and is used by ==.

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

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

impl Serialize for BoxplotAggregation

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>where
    __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for BoxplotAggregation