Documentation ¶
Index ¶
Constants ¶
This section is empty.
Variables ¶
var ( 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 holds the count in each bucket. Counts []uint64 }
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() (uint64, error) }
Count returns the number of values that were aggregated.
type Histogram ¶
type Histogram interface { Aggregation Count() (uint64, error) Sum() (number.Number, error) Histogram() (Buckets, error) }
Histogram returns the count of events in pre-determined buckets.
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() (number.Number, error) }
Max returns the maximum value over the set of values that were aggregated.
type Min ¶
type Min interface { Aggregation Min() (number.Number, error) }
Min returns the minimum value over the set of values that were aggregated.
type MinMaxSumCount ¶
type MinMaxSumCount interface { Aggregation Min() (number.Number, error) Max() (number.Number, error) Sum() (number.Number, error) Count() (uint64, error) }
MinMaxSumCount supports the Min, Max, Sum, and Count interfaces.
type Points ¶
type Points interface { Aggregation // Points returns points in the order they were // recorded. Points are approximately ordered by // timestamp, but this is not guaranteed. Points() ([]Point, error) }
Points returns the raw values that were aggregated.