Module: Google::Cloud::Monitoring::V3::Aggregation::Reducer
- Defined in:
- proto_docs/google/monitoring/v3/common.rb
Overview
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.
Constant Summary collapse
- REDUCE_NONE =
No cross-time series reduction. The output of the
Aligner
is returned. 0
- REDUCE_MEAN =
1
- REDUCE_MIN =
Reduce by computing the minimum value across time series for each alignment period. This reducer is valid for
DELTA
andGAUGE
metrics with numeric values. Thevalue_type
of the output is the same as thevalue_type
of the input. 2
- REDUCE_MAX =
Reduce by computing the maximum value across time series for each alignment period. This reducer is valid for
DELTA
andGAUGE
metrics with numeric values. Thevalue_type
of the output is the same as thevalue_type
of the input. 3
- REDUCE_SUM =
Reduce by computing the sum across time series for each alignment period. This reducer is valid for
DELTA
andGAUGE
metrics with numeric and distribution values. Thevalue_type
of the output is the same as thevalue_type
of the input. 4
- REDUCE_STDDEV =
Reduce by computing the standard deviation across time series for each alignment period. This reducer is valid for
DELTA
andGAUGE
metrics with numeric or distribution values. Thevalue_type
of the output isDOUBLE
. 5
- REDUCE_COUNT =
Reduce by computing the number of data points across time series for each alignment period. This reducer is valid for
DELTA
andGAUGE
metrics of numeric, Boolean, distribution, and stringvalue_type
. Thevalue_type
of the output isINT64
. 6
- REDUCE_COUNT_TRUE =
Reduce by computing the number of
True
-valued data points across time series for each alignment period. This reducer is valid forDELTA
andGAUGE
metrics of Booleanvalue_type
. Thevalue_type
of the output isINT64
. 7
- REDUCE_COUNT_FALSE =
Reduce by computing the number of
False
-valued data points across time series for each alignment period. This reducer is valid forDELTA
andGAUGE
metrics of Booleanvalue_type
. Thevalue_type
of the output isINT64
. 15
- REDUCE_FRACTION_TRUE =
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 forDELTA
andGAUGE
metrics of Booleanvalue_type
. The output value is in the range [0.0, 1.0] and hasvalue_type
DOUBLE
. 8
- REDUCE_PERCENTILE_99 =
Reduce by computing the 99th percentile of data points across time series for each alignment period. This reducer is valid for
GAUGE
andDELTA
metrics of numeric and distribution type. The value of the output isDOUBLE
. 9
- REDUCE_PERCENTILE_95 =
Reduce by computing the 95th percentile of data points across time series for each alignment period. This reducer is valid for
GAUGE
andDELTA
metrics of numeric and distribution type. The value of the output isDOUBLE
. 10
- REDUCE_PERCENTILE_50 =
Reduce by computing the 50th percentile of data points across time series for each alignment period. This reducer is valid for
GAUGE
andDELTA
metrics of numeric and distribution type. The value of the output isDOUBLE
. 11
- REDUCE_PERCENTILE_05 =
Reduce by computing the 5th percentile of data points across time series for each alignment period. This reducer is valid for
GAUGE
andDELTA
metrics of numeric and distribution type. The value of the output isDOUBLE
. 12