Enum google_api_proto::google::monitoring::v3::aggregation::Reducer

#[repr(i32)]
pub enum Reducer {
    ReduceNone = 0,
    ReduceMean = 1,
    ReduceMin = 2,
    ReduceMax = 3,
    ReduceSum = 4,
    ReduceStddev = 5,
    ReduceCount = 6,
    ReduceCountTrue = 7,
    ReduceCountFalse = 15,
    ReduceFractionTrue = 8,
    ReducePercentile99 = 9,
    ReducePercentile95 = 10,
    ReducePercentile50 = 11,
    ReducePercentile05 = 12,
}

A Reducer operation describes how to aggregate data points from multiple time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.

Variants

ReduceNone = 0

No cross-time series reduction. The output of the Aligner is returned.

ReduceMean = 1

Reduce by computing the mean value across time series for each alignment period. This reducer is valid for [DELTA][google.api.MetricDescriptor.MetricKind.DELTA] and [GAUGE][google.api.MetricDescriptor.MetricKind.GAUGE] metrics with numeric or distribution values. The value_type of the output is [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].

ReduceMin = 2

Reduce by computing the minimum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.

ReduceMax = 3

Reduce by computing the maximum value across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric values. The value_type of the output is the same as the value_type of the input.

ReduceSum = 4

Reduce by computing the sum across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric and distribution values. The value_type of the output is the same as the value_type of the input.

ReduceStddev = 5

Reduce by computing the standard deviation across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics with numeric or distribution values. The value_type of the output is DOUBLE.

ReduceCount = 6

Reduce by computing the number of data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of numeric, Boolean, distribution, and string value_type. The value_type of the output is INT64.

ReduceCountTrue = 7

Reduce by computing the number of True-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.

ReduceCountFalse = 15

Reduce by computing the number of False-valued data points across time series for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The value_type of the output is INT64.

ReduceFractionTrue = 8

Reduce by computing the ratio of the number of True-valued data points to the total number of data points for each alignment period. This reducer is valid for DELTA and GAUGE metrics of Boolean value_type. The output value is in the range [0.0, 1.0] and has value_type DOUBLE.

ReducePercentile99 = 9

Reduce by computing the 99th percentile of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.

ReducePercentile95 = 10

Reduce by computing the 95th percentile of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.

ReducePercentile50 = 11

Reduce by computing the 50th percentile of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.

ReducePercentile05 = 12

Reduce by computing the 5th percentile of data points across time series for each alignment period. This reducer is valid for GAUGE and DELTA metrics of numeric and distribution type. The value of the output is DOUBLE.

Implementations

impl Reducer

pub fn is_valid(value: i32) -> bool

Returns true if value is a variant of Reducer.

pub fn from_i32(value: i32) -> Option<Reducer>

👎Deprecated: Use the TryFrom<i32> implementation instead

Converts an i32 to a Reducer, or None if value is not a valid variant.

impl Reducer

pub fn as_str_name(&self) -> &'static str

String value of the enum field names used in the ProtoBuf definition.

The values are not transformed in any way and thus are considered stable (if the ProtoBuf definition does not change) and safe for programmatic use.

pub fn from_str_name(value: &str) -> Option<Self>

Creates an enum from field names used in the ProtoBuf definition.

Trait Implementations

impl Clone for Reducer

fn clone(&self) -> Reducer

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Reducer

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

Formats the value using the given formatter.

impl Default for Reducer

fn default() -> Reducer

Returns the “default value” for a type.

impl From<Reducer> for i32

fn from(value: Reducer) -> i32

Converts to this type from the input type.

impl Hash for Reducer

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 Ord for Reducer

fn cmp(&self, other: &Reducer) -> Ordering

This method returns an Ordering between self and other.

fn max(self, other: Self) -> Self

where Self: Sized,

Compares and returns the maximum of two values.

fn min(self, other: Self) -> Self

where Self: Sized,

Compares and returns the minimum of two values.

fn clamp(self, min: Self, max: Self) -> Self

where Self: Sized + PartialOrd,

Restrict a value to a certain interval.

impl PartialEq for Reducer

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

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

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

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

This method tests less than (for self and other) and is used by the < operator.

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

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

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

This method tests greater than (for self and other) and is used by the > operator.

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

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

impl TryFrom<i32> for Reducer

type Error = DecodeError

The type returned in the event of a conversion error.

fn try_from(value: i32) -> Result<Reducer, DecodeError>

Performs the conversion.

impl Copy for Reducer

impl Eq for Reducer

impl StructuralPartialEq for Reducer