telegraf/metric.go

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package telegraf
import (
"time"
"github.com/influxdata/influxdb/client/v2"
"github.com/influxdata/influxdb/models"
)
// ValueType is an enumeration of metric types that represent a simple value.
type ValueType int
// Possible values for the ValueType enum.
const (
_ ValueType = iota
Counter
Gauge
Untyped
)
type Metric interface {
// Name returns the measurement name of the metric
Name() string
// Name returns the tags associated with the metric
Tags() map[string]string
// Time return the timestamp for the metric
Time() time.Time
// Type returns the metric type. Can be either telegraf.Gauge or telegraf.Counter
Type() ValueType
// UnixNano returns the unix nano time of the metric
UnixNano() int64
// HashID returns a non-cryptographic hash of the metric (name + tags)
// NOTE: do not persist & depend on this value to disk.
HashID() uint64
// Fields returns the fields for the metric
Fields() map[string]interface{}
// String returns a line-protocol string of the metric
String() string
// PrecisionString returns a line-protocol string of the metric, at precision
PrecisionString(precison string) string
// Point returns a influxdb client.Point object
Point() *client.Point
// SetAggregate sets the metric's aggregate status
// This is so that aggregate metrics don't get re-sent to aggregator plugins
SetAggregate(bool)
// IsAggregate returns true if the metric is an aggregate
IsAggregate() bool
// Copy copies the metric
Copy() Metric
}
// metric is a wrapper of the influxdb client.Point struct
type metric struct {
pt models.Point
mType ValueType
isaggregate bool
}
func NewMetricFromPoint(pt models.Point) Metric {
return &metric{
pt: pt,
mType: Untyped,
}
}
// NewMetric returns an untyped metric.
func NewMetric(
name string,
tags map[string]string,
fields map[string]interface{},
t time.Time,
) (Metric, error) {
pt, err := models.NewPoint(name, models.NewTags(tags), fields, t)
if err != nil {
return nil, err
}
return &metric{
pt: pt,
mType: Untyped,
}, nil
}
// NewGaugeMetric returns a gauge metric.
// Gauge metrics should be used when the metric is can arbitrarily go up and
// down. ie, temperature, memory usage, cpu usage, etc.
func NewGaugeMetric(
name string,
tags map[string]string,
fields map[string]interface{},
t time.Time,
) (Metric, error) {
pt, err := models.NewPoint(name, models.NewTags(tags), fields, t)
if err != nil {
return nil, err
}
return &metric{
pt: pt,
mType: Gauge,
}, nil
}
// NewCounterMetric returns a Counter metric.
// Counter metrics should be used when the metric being created is an
// always-increasing counter. ie, net bytes received, requests served, errors, etc.
func NewCounterMetric(
name string,
tags map[string]string,
fields map[string]interface{},
t time.Time,
) (Metric, error) {
pt, err := models.NewPoint(name, models.NewTags(tags), fields, t)
if err != nil {
return nil, err
}
return &metric{
pt: pt,
mType: Counter,
}, nil
}
func (m *metric) Name() string {
return m.pt.Name()
}
func (m *metric) Tags() map[string]string {
return m.pt.Tags().Map()
}
func (m *metric) Time() time.Time {
return m.pt.Time()
}
func (m *metric) Type() ValueType {
return m.mType
}
func (m *metric) HashID() uint64 {
return m.pt.HashID()
}
func (m *metric) UnixNano() int64 {
return m.pt.UnixNano()
}
func (m *metric) Fields() map[string]interface{} {
return m.pt.Fields()
}
func (m *metric) String() string {
return m.pt.String()
}
func (m *metric) PrecisionString(precison string) string {
return m.pt.PrecisionString(precison)
}
func (m *metric) Point() *client.Point {
return client.NewPointFrom(m.pt)
}
func (m *metric) IsAggregate() bool {
return m.isaggregate
}
func (m *metric) SetAggregate(b bool) {
m.isaggregate = b
}
func (m *metric) Copy() Metric {
t := time.Time(m.Time())
tags := make(map[string]string)
fields := make(map[string]interface{})
for k, v := range m.Tags() {
tags[k] = v
}
for k, v := range m.Fields() {
fields[k] = v
}
out, _ := NewMetric(m.Name(), tags, fields, t)
return out
}