Add stackdriver input plugin (#5406)
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86
metric/series_grouper.go
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86
metric/series_grouper.go
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@@ -0,0 +1,86 @@
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package metric
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import (
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"hash/fnv"
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"io"
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"sort"
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"strconv"
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"time"
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"github.com/influxdata/telegraf"
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)
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// NewSeriesGrouper returns a type that can be used to group fields by series
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// and time, so that fields which share these values will be combined into a
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// single telegraf.Metric.
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//
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// This is useful to build telegraf.Metric's when all fields for a series are
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// not available at once.
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//
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// ex:
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// - cpu,host=localhost usage_time=42
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// - cpu,host=localhost idle_time=42
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// + cpu,host=localhost idle_time=42,usage_time=42
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func NewSeriesGrouper() *SeriesGrouper {
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return &SeriesGrouper{
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metrics: make(map[uint64]telegraf.Metric),
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ordered: []telegraf.Metric{},
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}
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}
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type SeriesGrouper struct {
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metrics map[uint64]telegraf.Metric
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ordered []telegraf.Metric
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}
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// Add adds a field key and value to the series.
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func (g *SeriesGrouper) Add(
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measurement string,
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tags map[string]string,
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tm time.Time,
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field string,
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fieldValue interface{},
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) error {
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var err error
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id := groupID(measurement, tags, tm)
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metric := g.metrics[id]
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if metric == nil {
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metric, err = New(measurement, tags, map[string]interface{}{field: fieldValue}, tm)
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if err != nil {
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return err
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}
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g.metrics[id] = metric
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g.ordered = append(g.ordered, metric)
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} else {
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metric.AddField(field, fieldValue)
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}
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return nil
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}
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// Metrics returns the metrics grouped by series and time.
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func (g *SeriesGrouper) Metrics() []telegraf.Metric {
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return g.ordered
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}
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func groupID(measurement string, tags map[string]string, tm time.Time) uint64 {
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h := fnv.New64a()
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h.Write([]byte(measurement))
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h.Write([]byte("\n"))
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taglist := make([]*telegraf.Tag, 0, len(tags))
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for k, v := range tags {
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taglist = append(taglist,
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&telegraf.Tag{Key: k, Value: v})
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}
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sort.Slice(taglist, func(i, j int) bool { return taglist[i].Key < taglist[j].Key })
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for _, tag := range taglist {
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h.Write([]byte(tag.Key))
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h.Write([]byte("\n"))
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h.Write([]byte(tag.Value))
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h.Write([]byte("\n"))
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}
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h.Write([]byte("\n"))
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io.WriteString(h, strconv.FormatInt(tm.UnixNano(), 10))
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return h.Sum64()
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}
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