Documentation ¶
Index ¶
Constants ¶
This section is empty.
Variables ¶
var ( ErrInvalidQuantile = fmt.Errorf("the requested quantile is out of range") ErrNegativeInput = fmt.Errorf("negative value is out of range for this instrument") ErrNaNInput = fmt.Errorf("NaN value is an invalid input") ErrInconsistentType = fmt.Errorf("inconsistent aggregator types") ErrNoSubtraction = fmt.Errorf("aggregator does not subtract") // ErrNoData is returned when (due to a race with collection) // the Aggregator is check-pointed before the first value is set. // The aggregator should simply be skipped in this case. ErrNoData = fmt.Errorf("no data collected by this aggregator") )
Functions ¶
This section is empty.
Types ¶
type Aggregation ¶
type Aggregation interface { // Kind returns a short identifying string to identify // the Aggregator that was used to produce the // Aggregation (e.g., "Sum"). Kind() Kind }
Aggregation is an interface returned by the Aggregator containing an interval of metric data.
type Buckets ¶
type Buckets struct { // Boundaries are floating point numbers, even when // aggregating integers. Boundaries []float64 // Counts are floating point numbers to account for // the possibility of sampling which allows for // non-integer count values. Counts []float64 }
Buckets represents histogram buckets boundaries and counts.
For a Histogram with N defined boundaries, e.g, [x, y, z]. There are N+1 counts: [-inf, x), [x, y), [y, z), [z, +inf]
type Count ¶
type Count interface { Aggregation Count() (int64, error) }
Sum returns the number of values that were aggregated.
type Distribution ¶
type Distribution interface { Aggregation Min() (metric.Number, error) Max() (metric.Number, error) Sum() (metric.Number, error) Count() (int64, error) Quantile(float64) (metric.Number, error) }
Distribution supports the Min, Max, Sum, Count, and Quantile interfaces.
type Kind ¶
type Kind string
Kind is a short name for the Aggregator that produces an Aggregation, used for descriptive purpose only. Kind is a string to allow user-defined Aggregators.
When deciding how to handle an Aggregation, Exporters are encouraged to decide based on conversion to the above interfaces based on strength, not on Kind value, when deciding how to expose metric data. This enables user-supplied Aggregators to replace builtin Aggregators.
For example, test for a Distribution before testing for a MinMaxSumCount, test for a Histogram before testing for a Sum, and so on.
type Max ¶
type Max interface { Aggregation Max() (metric.Number, error) }
Max returns the maximum value over the set of values that were aggregated.
type Min ¶
type Min interface { Aggregation Min() (metric.Number, error) }
Min returns the minimum value over the set of values that were aggregated.
type MinMaxSumCount ¶
type MinMaxSumCount interface { Aggregation Min() (metric.Number, error) Max() (metric.Number, error) Sum() (metric.Number, error) Count() (int64, error) }
MinMaxSumCount supports the Min, Max, Sum, and Count interfaces.
type Points ¶
type Points interface { Aggregation Points() ([]metric.Number, error) }
Points returns the raw set of values that were aggregated.