temporal

package
v0.10.2 Latest Latest
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Published: Jun 14, 2019 License: Apache-2.0 Imports: 16 Imported by: 0

Documentation

Overview

Package temporal is a generated GoMock package.

Index

Constants

View Source
const (
	// AvgType calculates the average of all values in the specified interval.
	AvgType = "avg_over_time"

	// CountType calculates count of all values in the specified interval.
	CountType = "count_over_time"

	// MinType calculates the minimum of all values in the specified interval.
	MinType = "min_over_time"

	// MaxType calculates the maximum of all values in the specified interval.
	MaxType = "max_over_time"

	// SumType calculates the sum of all values in the specified interval.
	SumType = "sum_over_time"

	// StdDevType calculates the standard deviation of all values in the specified interval.
	StdDevType = "stddev_over_time"

	// StdVarType calculates the standard variance of all values in the specified interval.
	StdVarType = "stdvar_over_time"

	// QuantileType calculates the φ-quantile (0 ≤ φ ≤ 1) of the values in the specified interval.
	QuantileType = "quantile_over_time"
)
View Source
const (
	// ResetsType returns the number of counter resets within the provided time range as a time series.
	// Any decrease in the value between two consecutive datapoints is interpreted as a counter reset.
	// ResetsTemporalType should only be used with counters.
	ResetsType = "resets"

	// ChangesType returns the number of times a value changes within the provided time range for
	// a given time series.
	ChangesType = "changes"
)
View Source
const (
	// PredictLinearType predicts the value of time series t seconds from now, based on the input series, using simple linear regression.
	// PredictLinearType should only be used with gauges.
	PredictLinearType = "predict_linear"

	// DerivType calculates the per-second derivative of the time series, using simple linear regression.
	// DerivType should only be used with gauges.
	DerivType = "deriv"
)
View Source
const (
	// IRateType calculates the per-second rate of increase of the time series
	// across the specified time range. This is based on the last two data points.
	IRateType = "irate"

	// IDeltaType calculates the difference between the last two values in the time series.
	// IDeltaTemporalType should only be used with gauges.
	IDeltaType = "idelta"

	// RateType calculates the per-second average rate of increase of the time series.
	RateType = "rate"

	// DeltaType calculates the difference between the first and last value of each time series.
	DeltaType = "delta"

	// IncreaseType calculates the increase in the time series.
	IncreaseType = "increase"
)
View Source
const (
	// HoltWintersType produces a smoothed value for time series based on the specified interval.
	// The algorithm used comes from https://en.wikipedia.org/wiki/Exponential_smoothing#Double_exponential_smoothing.
	// Holt-Winters should only be used with gauges.
	HoltWintersType = "holt_winters"
)

Variables

This section is empty.

Functions

func NewAggOp added in v0.4.4

func NewAggOp(args []interface{}, optype string) (transform.Params, error)

NewAggOp creates a new base temporal transform with a specified node.

func NewFunctionOp added in v0.4.4

func NewFunctionOp(args []interface{}, optype string) (transform.Params, error)

NewFunctionOp creates a new base temporal transform for functions

func NewHoltWintersOp added in v0.4.7

func NewHoltWintersOp(args []interface{}) (transform.Params, error)

NewHoltWintersOp creates a new base Holt-Winters transform with a specified node.

func NewLinearRegressionOp added in v0.4.8

func NewLinearRegressionOp(args []interface{}, optype string) (transform.Params, error)

NewLinearRegressionOp creates a new base temporal transform for linear regression functions

func NewQuantileOp added in v0.6.0

func NewQuantileOp(args []interface{}, optype string) (transform.Params, error)

NewQuantileOp create a new base temporal transform for quantile_over_time func.

func NewRateOp added in v0.4.4

func NewRateOp(args []interface{}, optype string) (transform.Params, error)

NewRateOp creates a new base temporal transform for rate functions

Types

type MakeProcessor

type MakeProcessor interface {
	Init(op baseOp, controller *transform.Controller, opts transform.Options) Processor
}

MakeProcessor is a way to create a transform

type Mockcontroller added in v0.7.0

type Mockcontroller struct {
	// contains filtered or unexported fields
}

Mockcontroller is a mock of controller interface

func NewMockcontroller added in v0.7.0

func NewMockcontroller(ctrl *gomock.Controller) *Mockcontroller

NewMockcontroller creates a new mock instance

func (*Mockcontroller) BlockBuilder added in v0.7.0

func (m *Mockcontroller) BlockBuilder(queryCtx *models.QueryContext, blockMeta block.Metadata, seriesMeta []block.SeriesMeta) (block.Builder, error)

BlockBuilder mocks base method

func (*Mockcontroller) EXPECT added in v0.7.0

EXPECT returns an object that allows the caller to indicate expected use

func (*Mockcontroller) Process added in v0.7.0

func (m *Mockcontroller) Process(queryCtx *models.QueryContext, block block.Block) error

Process mocks base method

type MockcontrollerMockRecorder added in v0.7.0

type MockcontrollerMockRecorder struct {
	// contains filtered or unexported fields
}

MockcontrollerMockRecorder is the mock recorder for Mockcontroller

func (*MockcontrollerMockRecorder) BlockBuilder added in v0.7.0

func (mr *MockcontrollerMockRecorder) BlockBuilder(queryCtx, blockMeta, seriesMeta interface{}) *gomock.Call

BlockBuilder indicates an expected call of BlockBuilder

func (*MockcontrollerMockRecorder) Process added in v0.7.0

func (mr *MockcontrollerMockRecorder) Process(queryCtx, block interface{}) *gomock.Call

Process indicates an expected call of Process

type Processor

type Processor interface {
	Process(values ts.Datapoints, evaluationTime time.Time) float64
}

Processor is implemented by the underlying transforms

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