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.
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.
ReduceCountFalse
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.
ReduceCountTrue
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.
ReduceFractionTrue
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_typeDOUBLE.
ReduceMax
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.
ReduceMean
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
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.
ReduceNone
No cross-time series reduction. The output of the Aligner is
returned.
ReducePercentile05
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.
ReducePercentile50
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.
ReducePercentile95
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.
ReducePercentile99
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.
ReduceStddev
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.
ReduceSum
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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-04-17 UTC."],[[["This page details the `Reducer` enum within the `Google.Cloud.Monitoring.V3` namespace, which is used to aggregate data points from multiple time series into a single time series."],["The `Reducer` enum offers various operations, including counting, finding maximums, minimums, means, percentiles, sums, and standard deviations."],["The operations can be performed across time series for each alignment period, and the supported metric types include `DELTA` and `GAUGE` metrics with numeric, Boolean, or distribution values."],["The latest version available for the `Reducer` is 3.15.0, while the current version that this document references is version 2.5.0, with several prior versions also being available."],["The different types of reduction operations are listed in a table, describing the name of each and their functionalities."]]],[]]
