Adding upstream version 1.34.4.
Signed-off-by: Daniel Baumann <daniel@debian.org>
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136
plugins/processors/noise/noise.go
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136
plugins/processors/noise/noise.go
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//go:generate ../../../tools/readme_config_includer/generator
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package noise
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import (
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_ "embed"
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"fmt"
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"math"
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"reflect"
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"gonum.org/v1/gonum/stat/distuv"
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"github.com/influxdata/telegraf"
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"github.com/influxdata/telegraf/filter"
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"github.com/influxdata/telegraf/plugins/processors"
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)
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//go:embed sample.conf
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var sampleConfig string
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const (
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defaultScale = 1.0
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defaultMin = -1.0
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defaultMax = 1.0
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defaultMu = 0.0
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defaultNoiseType = "laplacian"
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)
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type Noise struct {
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Scale float64 `toml:"scale"`
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Min float64 `toml:"min"`
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Max float64 `toml:"max"`
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Mu float64 `toml:"mu"`
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IncludeFields []string `toml:"include_fields"`
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ExcludeFields []string `toml:"exclude_fields"`
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NoiseType string `toml:"type"`
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Log telegraf.Logger `toml:"-"`
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generator distuv.Rander
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fieldFilter filter.Filter
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}
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// generates a random noise value depending on the defined probability density
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// function and adds that to the original value. If any integer overflows
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// happen during the calculation, the result is set to MaxInt or 0 (for uint)
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func (p *Noise) addNoise(value interface{}) interface{} {
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n := p.generator.Rand()
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switch v := value.(type) {
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case int:
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case int8:
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case int16:
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case int32:
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case int64:
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if v > 0 && (n > math.Nextafter(float64(math.MaxInt64), 0) || int64(n) > math.MaxInt64-v) {
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p.Log.Debug("Int64 overflow, setting value to MaxInt64")
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return int64(math.MaxInt64)
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}
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if v < 0 && (n < math.Nextafter(float64(math.MinInt64), 0) || int64(n) < math.MinInt64-v) {
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p.Log.Debug("Int64 (negative) overflow, setting value to MinInt64")
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return int64(math.MinInt64)
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}
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return v + int64(n)
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case uint:
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case uint8:
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case uint16:
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case uint32:
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case uint64:
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if n < 0 {
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if uint64(-n) > v {
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p.Log.Debug("Uint64 (negative) overflow, setting value to 0")
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return uint64(0)
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}
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return v - uint64(-n)
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}
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if n > math.Nextafter(float64(math.MaxUint64), 0) || uint64(n) > math.MaxUint64-v {
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p.Log.Debug("Uint64 overflow, setting value to MaxUint64")
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return uint64(math.MaxUint64)
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}
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return v + uint64(n)
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case float32:
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return v + float32(n)
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case float64:
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return v + n
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default:
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p.Log.Debugf("Value (%v) type invalid: [%v] is not an int, uint or float", v, reflect.TypeOf(value))
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}
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return value
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}
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func (*Noise) SampleConfig() string {
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return sampleConfig
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}
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// Creates a filter for Include and Exclude fields and sets the desired noise
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// distribution
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func (p *Noise) Init() error {
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fieldFilter, err := filter.NewIncludeExcludeFilter(p.IncludeFields, p.ExcludeFields)
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if err != nil {
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return fmt.Errorf("creating fieldFilter failed: %w", err)
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}
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p.fieldFilter = fieldFilter
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switch p.NoiseType {
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case "", "laplacian":
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p.generator = &distuv.Laplace{Mu: p.Mu, Scale: p.Scale}
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case "uniform":
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p.generator = &distuv.Uniform{Min: p.Min, Max: p.Max}
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case "gaussian":
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p.generator = &distuv.Normal{Mu: p.Mu, Sigma: p.Scale}
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default:
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return fmt.Errorf("unknown distribution type %q", p.NoiseType)
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}
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return nil
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}
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func (p *Noise) Apply(metrics ...telegraf.Metric) []telegraf.Metric {
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for _, metric := range metrics {
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for _, field := range metric.FieldList() {
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if !p.fieldFilter.Match(field.Key) {
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continue
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}
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field.Value = p.addNoise(field.Value)
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}
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}
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return metrics
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}
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func init() {
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processors.Add("noise", func() telegraf.Processor {
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return &Noise{
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NoiseType: defaultNoiseType,
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Mu: defaultMu,
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Scale: defaultScale,
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Min: defaultMin,
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Max: defaultMax,
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}
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})
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}
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