Enum opentelemetry_sdk::metrics::Aggregation

#[non_exhaustive]
pub enum Aggregation {
    Drop,
    Default,
    Sum,
    LastValue,
    ExplicitBucketHistogram {
        boundaries: Vec<f64>,
        record_min_max: bool,
    },
    Base2ExponentialHistogram {
        max_size: u32,
        max_scale: i8,
        record_min_max: bool,
    },
}

The way recorded measurements are summarized.

Variants (Non-exhaustive)

Non-exhaustive enums could have additional variants added in future. Therefore, when matching against variants of non-exhaustive enums, an extra wildcard arm must be added to account for any future variants.

Drop

An aggregation that drops all recorded data.

Default

An aggregation that uses the default instrument kind selection mapping to select another aggregation.

A metric reader can be configured to make an aggregation selection based on instrument kind that differs from the default. This aggregation ensures the default is used.

See the DefaultAggregationSelector for information about the default instrument kind selection mapping.

Sum

An aggregation that summarizes a set of measurements as their arithmetic sum.

LastValue

An aggregation that summarizes a set of measurements as the last one made.

ExplicitBucketHistogram

An aggregation that summarizes a set of measurements as a histogram with explicitly defined buckets.

Fields

boundaries: Vec<f64>

The increasing bucket boundary values.

Boundary values define bucket upper bounds. Buckets are exclusive of their lower boundary and inclusive of their upper bound (except at positive infinity). A measurement is defined to fall into the greatest-numbered bucket with a boundary that is greater than or equal to the measurement. As an example, boundaries defined as:

vec![0.0, 5.0, 10.0, 25.0, 50.0, 75.0, 100.0, 250.0, 500.0, 750.0, 1000.0, 2500.0, 5000.0, 7500.0, 10000.0];

Will define these buckets:

(-∞, 0], (0, 5.0], (5.0, 10.0], (10.0, 25.0], (25.0, 50.0], (50.0, 75.0], (75.0, 100.0], (100.0, 250.0], (250.0, 500.0], (500.0, 750.0], (750.0, 1000.0], (1000.0, 2500.0], (2500.0, 5000.0], (5000.0, 7500.0], (7500.0, 10000.0], (10000.0, +∞)

record_min_max: bool

Indicates whether to not record the min and max of the distribution.

By default, these values are recorded.

Recording these values for cumulative data is expected to have little value, they will represent the entire life of the instrument instead of just the current collection cycle. It is recommended to set this to false for that type of data to avoid computing the low-value instances.

Base2ExponentialHistogram

An aggregation that summarizes a set of measurements as a histogram with bucket widths that grow exponentially.

Fields

max_size: u32

The maximum number of buckets to use for the histogram.

max_scale: i8

The maximum resolution scale to use for the histogram.

The maximum value is 20, in which case the maximum number of buckets that can fit within the range of a signed 32-bit integer index could be used.

The minimum value is -10 in which case only two buckets will be used.

record_min_max: bool

Indicates whether to not record the min and max of the distribution.

By default, these values are recorded.

It is generally not valuable to record min and max for cumulative data as they will represent the entire life of the instrument instead of just the current collection cycle, you can opt out by setting this value to false

Implementations

impl Aggregation

pub fn validate(&self) -> Result<()>

Validate that this aggregation has correct configuration

Trait Implementations

impl Clone for Aggregation

fn clone(&self) -> Aggregation

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Aggregation

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

Formats the value using the given formatter.

impl Display for Aggregation

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

Formats the value using the given formatter.

impl PartialEq for Aggregation

fn eq(&self, other: &Aggregation) -> 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 StructuralPartialEq for Aggregation