Module: Google::Cloud::Monitoring::V3::Aggregation::Aligner
- Defined in:
- proto_docs/google/monitoring/v3/common.rb
Overview
The Aligner
specifies the operation that will be applied to the data
points in each alignment period in a time series. Except for
ALIGN_NONE
, which specifies that no operation be applied, each alignment
operation replaces the set of data values in each alignment period with
a single value: the result of applying the operation to the data values.
An aligned time series has a single data value at the end of each
alignment_period
.
An alignment operation can change the data type of the values, too. For
example, if you apply a counting operation to boolean values, the data
value_type
in the original time series is BOOLEAN
, but the value_type
in the aligned result is INT64
.
Constant Summary collapse
- ALIGN_NONE =
No alignment. Raw data is returned. Not valid if cross-series reduction is requested. The
value_type
of the result is the same as thevalue_type
of the input. 0
- ALIGN_DELTA =
Align and convert to DELTA. The output is
delta = y1 - y0
.This alignment is valid for CUMULATIVE and
DELTA
metrics. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. Thevalue_type
of the aligned result is the same as thevalue_type
of the input. 1
- ALIGN_RATE =
Align and convert to a rate. The result is computed as
rate = (y1 - y0)/(t1 - t0)
, or "delta over time". Think of this aligner as providing the slope of the line that passes through the value at the start and at the end of thealignment_period
.This aligner is valid for
CUMULATIVE
andDELTA
metrics with numeric values. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The output is aGAUGE
metric withvalue_type
DOUBLE
.If, by "rate", you mean "percentage change", see the
ALIGN_PERCENT_CHANGE
aligner instead. 2
- ALIGN_INTERPOLATE =
Align by interpolating between adjacent points around the alignment period boundary. This aligner is valid for
GAUGE
metrics with numeric values. Thevalue_type
of the aligned result is the same as thevalue_type
of the input. 3
- ALIGN_NEXT_OLDER =
Align by moving the most recent data point before the end of the alignment period to the boundary at the end of the alignment period. This aligner is valid for
GAUGE
metrics. Thevalue_type
of the aligned result is the same as thevalue_type
of the input. 4
- ALIGN_MIN =
Align the time series by returning the minimum value in each alignment period. This aligner is valid for
GAUGE
andDELTA
metrics with numeric values. Thevalue_type
of the aligned result is the same as thevalue_type
of the input. 10
- ALIGN_MAX =
Align the time series by returning the maximum value in each alignment period. This aligner is valid for
GAUGE
andDELTA
metrics with numeric values. Thevalue_type
of the aligned result is the same as thevalue_type
of the input. 11
- ALIGN_MEAN =
Align the time series by returning the mean value in each alignment period. This aligner is valid for
GAUGE
andDELTA
metrics with numeric values. Thevalue_type
of the aligned result isDOUBLE
. 12
- ALIGN_COUNT =
Align the time series by returning the number of values in each alignment period. This aligner is valid for
GAUGE
andDELTA
metrics with numeric or Boolean values. Thevalue_type
of the aligned result isINT64
. 13
- ALIGN_SUM =
Align the time series by returning the sum of the values in each alignment period. This aligner is valid for
GAUGE
andDELTA
metrics with numeric and distribution values. Thevalue_type
of the aligned result is the same as thevalue_type
of the input. 14
- ALIGN_STDDEV =
Align the time series by returning the standard deviation of the values in each alignment period. This aligner is valid for
GAUGE
andDELTA
metrics with numeric values. Thevalue_type
of the output isDOUBLE
. 15
- ALIGN_COUNT_TRUE =
Align the time series by returning the number of
True
values in each alignment period. This aligner is valid forGAUGE
metrics with Boolean values. Thevalue_type
of the output isINT64
. 16
- ALIGN_COUNT_FALSE =
Align the time series by returning the number of
False
values in each alignment period. This aligner is valid forGAUGE
metrics with Boolean values. Thevalue_type
of the output isINT64
. 24
- ALIGN_FRACTION_TRUE =
Align the time series by returning the ratio of the number of
True
values to the total number of values in each alignment period. This aligner is valid forGAUGE
metrics with Boolean values. The output value is in the range [0.0, 1.0] and hasvalue_type
DOUBLE
. 17
- ALIGN_PERCENTILE_99 =
Align the time series by using percentile aggregation. The resulting data point in each alignment period is the 99th percentile of all data points in the period. This aligner is valid for
GAUGE
andDELTA
metrics with distribution values. The output is aGAUGE
metric withvalue_type
DOUBLE
. 18
- ALIGN_PERCENTILE_95 =
Align the time series by using percentile aggregation. The resulting data point in each alignment period is the 95th percentile of all data points in the period. This aligner is valid for
GAUGE
andDELTA
metrics with distribution values. The output is aGAUGE
metric withvalue_type
DOUBLE
. 19
- ALIGN_PERCENTILE_50 =
Align the time series by using percentile aggregation. The resulting data point in each alignment period is the 50th percentile of all data points in the period. This aligner is valid for
GAUGE
andDELTA
metrics with distribution values. The output is aGAUGE
metric withvalue_type
DOUBLE
. 20
- ALIGN_PERCENTILE_05 =
Align the time series by using percentile aggregation. The resulting data point in each alignment period is the 5th percentile of all data points in the period. This aligner is valid for
GAUGE
andDELTA
metrics with distribution values. The output is aGAUGE
metric withvalue_type
DOUBLE
. 21
- ALIGN_PERCENT_CHANGE =
Align and convert to a percentage change. This aligner is valid for
GAUGE
andDELTA
metrics with numeric values. This alignment returns((current - previous)/previous) * 100
, where the value ofprevious
is determined based on thealignment_period
.If the values of
current
andprevious
are both 0, then the returned value is 0. If onlyprevious
is 0, the returned value is infinity.A 10-minute moving mean is computed at each point of the alignment period prior to the above calculation to smooth the metric and prevent false positives from very short-lived spikes. The moving mean is only applicable for data whose values are
>= 0
. Any values< 0
are treated as a missing datapoint, and are ignored. WhileDELTA
metrics are accepted by this alignment, special care should be taken that the values for the metric will always be positive. The output is aGAUGE
metric withvalue_type
DOUBLE
. 23