Aggregation class

Describes how to combine multiple time series to provide a different view of the data.

Aggregation of time series is done in two steps. First, each time series in the set is aligned to the same time interval boundaries, then the set of time series is optionally reduced in number.Alignment consists of applying the per_series_aligner operation to each time series after its data has been divided into regular alignment_period time intervals. This process takes all of the data points in an alignment period, applies a mathematical transformation such as averaging, minimum, maximum, delta, etc., and converts them into a single data point per period.Reduction is when the aligned and transformed time series can optionally be combined, reducing the number of time series through similar mathematical transformations. Reduction involves applying a cross_series_reducer to all the time series, optionally sorting the time series into subsets with group_by_fields, and applying the reducer to each subset.The raw time series data can contain a huge amount of information from multiple sources. Alignment and reduction transforms this mass of data into a more manageable and representative collection of data, for example "the 95% latency across the average of all tasks in a cluster". This representative data can be more easily graphed and comprehended, and the individual time series data is still available for later drilldown. For more details, see Filtering and aggregation (https://cloud.google.com/monitoring/api/v3/aggregation).

Constructors

Aggregation({String? alignmentPeriod, String? crossSeriesReducer, List<String>? groupByFields, String? perSeriesAligner})
Aggregation.fromJson(Map json_)

Properties

alignmentPeriod String?
The alignment_period specifies a time interval, in seconds, that is used to divide the data in all the time series into consistent blocks of time.
getter/setter pair
crossSeriesReducer String?
The reduction operation to be used to combine 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.Not all reducer operations can be applied to all time series.
getter/setter pair
groupByFields List<String>?
The set of fields to preserve when cross_series_reducer is specified.
getter/setter pair
hashCode int
The hash code for this object.
no setterinherited
perSeriesAligner String?
An Aligner describes how to bring the data points in a single time series into temporal alignment.
getter/setter pair
runtimeType Type
A representation of the runtime type of the object.
no setterinherited

Methods

noSuchMethod(Invocation invocation) → dynamic
Invoked when a nonexistent method or property is accessed.
inherited
toJson() Map<String, dynamic>
toString() String
A string representation of this object.
inherited

Operators

operator ==(Object other) bool
The equality operator.
inherited