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cloudpods/vendor/github.com/influxdata/promql/v2/functions.go

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// Copyright 2015 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package promql
import (
"math"
)
// Function represents a function of the expression language and is
// used by function nodes.
type Function struct {
Name string
ArgTypes []ValueType
Variadic int
ReturnType ValueType
}
// Calculate the trend value at the given index i in raw data d.
// This is somewhat analogous to the slope of the trend at the given index.
// The argument "s" is the set of computed smoothed values.
// The argument "b" is the set of computed trend factors.
// The argument "d" is the set of raw input values.
func calcTrendValue(i int, sf, tf, s0, s1, b float64) float64 {
if i == 0 {
return b
}
x := tf * (s1 - s0)
y := (1 - tf) * b
return x + y
}
// linearRegression performs a least-square linear regression analysis on the
// provided SamplePairs. It returns the slope, and the intercept value at the
// provided time.
func linearRegression(samples []Point, interceptTime int64) (slope, intercept float64) {
var (
n float64
sumX, sumY float64
sumXY, sumX2 float64
)
for _, sample := range samples {
x := float64(sample.T-interceptTime) / 1e3
n += 1.0
sumY += sample.V
sumX += x
sumXY += x * sample.V
sumX2 += x * x
}
covXY := sumXY - sumX*sumY/n
varX := sumX2 - sumX*sumX/n
slope = covXY / varX
intercept = sumY/n - slope*sumX/n
return slope, intercept
}
var functions = map[string]*Function{
"abs": {
Name: "abs",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"absent": {
Name: "absent",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"avg_over_time": {
Name: "avg_over_time",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"ceil": {
Name: "ceil",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"changes": {
Name: "changes",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"clamp_max": {
Name: "clamp_max",
ArgTypes: []ValueType{ValueTypeVector, ValueTypeScalar},
ReturnType: ValueTypeVector,
},
"clamp_min": {
Name: "clamp_min",
ArgTypes: []ValueType{ValueTypeVector, ValueTypeScalar},
ReturnType: ValueTypeVector,
},
"count_over_time": {
Name: "count_over_time",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"days_in_month": {
Name: "days_in_month",
ArgTypes: []ValueType{ValueTypeVector},
Variadic: 1,
ReturnType: ValueTypeVector,
},
"day_of_month": {
Name: "day_of_month",
ArgTypes: []ValueType{ValueTypeVector},
Variadic: 1,
ReturnType: ValueTypeVector,
},
"day_of_week": {
Name: "day_of_week",
ArgTypes: []ValueType{ValueTypeVector},
Variadic: 1,
ReturnType: ValueTypeVector,
},
"delta": {
Name: "delta",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"deriv": {
Name: "deriv",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"exp": {
Name: "exp",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"floor": {
Name: "floor",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"histogram_quantile": {
Name: "histogram_quantile",
ArgTypes: []ValueType{ValueTypeScalar, ValueTypeVector},
ReturnType: ValueTypeVector,
},
"holt_winters": {
Name: "holt_winters",
ArgTypes: []ValueType{ValueTypeMatrix, ValueTypeScalar, ValueTypeScalar},
ReturnType: ValueTypeVector,
},
"hour": {
Name: "hour",
ArgTypes: []ValueType{ValueTypeVector},
Variadic: 1,
ReturnType: ValueTypeVector,
},
"idelta": {
Name: "idelta",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"increase": {
Name: "increase",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"irate": {
Name: "irate",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"label_replace": {
Name: "label_replace",
ArgTypes: []ValueType{ValueTypeVector, ValueTypeString, ValueTypeString, ValueTypeString, ValueTypeString},
ReturnType: ValueTypeVector,
},
"label_join": {
Name: "label_join",
ArgTypes: []ValueType{ValueTypeVector, ValueTypeString, ValueTypeString, ValueTypeString},
Variadic: -1,
ReturnType: ValueTypeVector,
},
"ln": {
Name: "ln",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"log10": {
Name: "log10",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"log2": {
Name: "log2",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"max_over_time": {
Name: "max_over_time",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"min_over_time": {
Name: "min_over_time",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"minute": {
Name: "minute",
ArgTypes: []ValueType{ValueTypeVector},
Variadic: 1,
ReturnType: ValueTypeVector,
},
"month": {
Name: "month",
ArgTypes: []ValueType{ValueTypeVector},
Variadic: 1,
ReturnType: ValueTypeVector,
},
"predict_linear": {
Name: "predict_linear",
ArgTypes: []ValueType{ValueTypeMatrix, ValueTypeScalar},
ReturnType: ValueTypeVector,
},
"quantile_over_time": {
Name: "quantile_over_time",
ArgTypes: []ValueType{ValueTypeScalar, ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"rate": {
Name: "rate",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"resets": {
Name: "resets",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"round": {
Name: "round",
ArgTypes: []ValueType{ValueTypeVector, ValueTypeScalar},
Variadic: 1,
ReturnType: ValueTypeVector,
},
"scalar": {
Name: "scalar",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeScalar,
},
"sort": {
Name: "sort",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"sort_desc": {
Name: "sort_desc",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"sqrt": {
Name: "sqrt",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"stddev_over_time": {
Name: "stddev_over_time",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"stdvar_over_time": {
Name: "stdvar_over_time",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"sum_over_time": {
Name: "sum_over_time",
ArgTypes: []ValueType{ValueTypeMatrix},
ReturnType: ValueTypeVector,
},
"time": {
Name: "time",
ArgTypes: []ValueType{},
ReturnType: ValueTypeScalar,
},
"timestamp": {
Name: "timestamp",
ArgTypes: []ValueType{ValueTypeVector},
ReturnType: ValueTypeVector,
},
"vector": {
Name: "vector",
ArgTypes: []ValueType{ValueTypeScalar},
ReturnType: ValueTypeVector,
},
"year": {
Name: "year",
ArgTypes: []ValueType{ValueTypeVector},
Variadic: 1,
ReturnType: ValueTypeVector,
},
}
// getFunction returns a predefined Function object for the given name.
func getFunction(name string) (*Function, bool) {
function, ok := functions[name]
return function, ok
}
type vectorByValueHeap Vector
func (s vectorByValueHeap) Len() int {
return len(s)
}
func (s vectorByValueHeap) Less(i, j int) bool {
if math.IsNaN(s[i].V) {
return true
}
return s[i].V < s[j].V
}
func (s vectorByValueHeap) Swap(i, j int) {
s[i], s[j] = s[j], s[i]
}
func (s *vectorByValueHeap) Push(x interface{}) {
*s = append(*s, *(x.(*Sample)))
}
func (s *vectorByValueHeap) Pop() interface{} {
old := *s
n := len(old)
el := old[n-1]
*s = old[0 : n-1]
return el
}
type vectorByReverseValueHeap Vector
func (s vectorByReverseValueHeap) Len() int {
return len(s)
}
func (s vectorByReverseValueHeap) Less(i, j int) bool {
if math.IsNaN(s[i].V) {
return true
}
return s[i].V > s[j].V
}
func (s vectorByReverseValueHeap) Swap(i, j int) {
s[i], s[j] = s[j], s[i]
}
func (s *vectorByReverseValueHeap) Push(x interface{}) {
*s = append(*s, *(x.(*Sample)))
}
func (s *vectorByReverseValueHeap) Pop() interface{} {
old := *s
n := len(old)
el := old[n-1]
*s = old[0 : n-1]
return el
}