Module: Google::Monitoring::V3::Aggregation::Aligner

Defined in:: lib/google/cloud/monitoring/v3/doc/google/monitoring/v3/common.rb

Overview

The Aligner describes how to bring the data points in a single time series into temporal alignment.

Constant Summary collapse

ALIGN_NONE = No alignment. Raw data is returned. Not valid if cross-time series reduction is requested. The value type of the result is the same as the value type of the input.

ALIGN_DELTA = Align and convert to delta metric type. This alignment is valid for cumulative metrics and delta metrics. Aligning an existing delta metric to a delta metric requires that the alignment period be increased. The value type of the result is the same as the value type of the input. One can think of this aligner as a rate but without time units; that is, the output is conceptually (second_point - first_point).

ALIGN_RATE = Align and convert to a rate. This alignment is valid for cumulative metrics and delta metrics with numeric values. The output is a gauge metric with value type DOUBLE. One can think of this aligner as conceptually providing the slope of the line that passes through the value at the start and end of the window. In other words, this is conceptually ((y1 - y0)/(t1 - t0)), and the output unit is one that has a "/time" dimension. If, by rate, you are looking for percentage change, see the +ALIGN_PERCENT_CHANGE+ aligner option.

ALIGN_INTERPOLATE = Align by interpolating between adjacent points around the period boundary. This alignment is valid for gauge metrics with numeric values. The value type of the result is the same as the value type of the input.

ALIGN_NEXT_OLDER = Align by shifting the oldest data point before the period boundary to the boundary. This alignment is valid for gauge metrics. The value type of the result is the same as the value type of the input.

ALIGN_MIN = Align time series via aggregation. The resulting data point in the alignment period is the minimum of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the result is the same as the value type of the input.

ALIGN_MAX = Align time series via aggregation. The resulting data point in the alignment period is the maximum of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the result is the same as the value type of the input.

ALIGN_MEAN = Align time series via aggregation. The resulting data point in the alignment period is the average or arithmetic mean of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the output is DOUBLE.

ALIGN_COUNT = Align time series via aggregation. The resulting data point in the alignment period is the count of all data points in the period. This alignment is valid for gauge and delta metrics with numeric or Boolean values. The value type of the output is INT64.

ALIGN_SUM = Align time series via aggregation. The resulting data point in the alignment period is the sum of all data points in the period. This alignment is valid for gauge and delta metrics with numeric and distribution values. The value type of the output is the same as the value type of the input.

ALIGN_STDDEV = Align time series via aggregation. The resulting data point in the alignment period is the standard deviation of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the output is DOUBLE.

ALIGN_COUNT_TRUE = Align time series via aggregation. The resulting data point in the alignment period is the count of True-valued data points in the period. This alignment is valid for gauge metrics with Boolean values. The value type of the output is INT64.

ALIGN_COUNT_FALSE = Align time series via aggregation. The resulting data point in the alignment period is the count of False-valued data points in the period. This alignment is valid for gauge metrics with Boolean values. The value type of the output is INT64.

ALIGN_FRACTION_TRUE = Align time series via aggregation. The resulting data point in the alignment period is the fraction of True-valued data points in the period. This alignment is valid for gauge metrics with Boolean values. The output value is in the range [0, 1] and has value type DOUBLE.

ALIGN_PERCENTILE_99 = Align time series via aggregation. The resulting data point in the alignment period is the 99th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

ALIGN_PERCENTILE_95 = Align time series via aggregation. The resulting data point in the alignment period is the 95th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

ALIGN_PERCENTILE_50 = Align time series via aggregation. The resulting data point in the alignment period is the 50th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

ALIGN_PERCENTILE_05 = Align time series via aggregation. The resulting data point in the alignment period is the 5th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

ALIGN_PERCENT_CHANGE = Align and convert to a percentage change. This alignment is valid for gauge and delta metrics with numeric values. This alignment conceptually computes the equivalent of "((current - previous)/previous)*100" where previous value is determined based on the alignmentPeriod. In the event that previous is 0 the calculated value is infinity with the exception that if both (current - previous) and previous are 0 the calculated value is 0. A 10 minute moving mean is computed at each point of the time window prior to the above calculation to smooth the metric and prevent false positives from very short lived spikes. Only applicable for data that is >= 0. Any values < 0 are treated as no data. While delta metrics are accepted by this alignment special care should be taken that the values for the metric will always be positive. The output is a gauge metric with value type DOUBLE.