forked from mirror/client_golang
Add support for histograms to parsers, extraction and creation.
This does not include a histogram metric usable from the go client. See https://docs.google.com/document/d/1uSenXRDjDaJLV3qnSD09GqgPdEEDPjER0mVsnGaCYF0/edit#
This commit is contained in:
Brian Brazil
parent
d5fe8ed656
commit
6f2f8f28e8
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@ -69,6 +69,10 @@ func extractMetricFamily(out Ingester, o *ProcessOptions, family *dto.MetricFami
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if err := extractUntyped(out, o, family); err != nil {
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return err
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}
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case dto.MetricType_HISTOGRAM:
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if err := extractHistogram(out, o, family); err != nil {
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return err
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}
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}
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return nil
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}
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@ -227,3 +231,65 @@ func extractUntyped(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error
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return out.Ingest(samples)
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}
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func extractHistogram(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
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samples := make(model.Samples, 0, len(f.Metric))
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for _, m := range f.Metric {
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if m.Histogram == nil {
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continue
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}
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timestamp := o.Timestamp
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if m.TimestampMs != nil {
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timestamp = model.TimestampFromUnixNano(*m.TimestampMs * 1000000)
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}
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for _, q := range m.Histogram.Bucket {
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sample := new(model.Sample)
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samples = append(samples, sample)
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sample.Timestamp = timestamp
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sample.Metric = model.Metric{}
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metric := sample.Metric
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.LabelName("le")] = model.LabelValue(fmt.Sprint(q.GetUpperBound()))
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_bucket")
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sample.Value = model.SampleValue(q.GetCumulativeCount())
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}
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// TODO: If +Inf bucket is missing, add it.
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if m.Histogram.SampleSum != nil {
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sum := new(model.Sample)
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sum.Timestamp = timestamp
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metric := model.Metric{}
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_sum")
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sum.Metric = metric
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sum.Value = model.SampleValue(m.Histogram.GetSampleSum())
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samples = append(samples, sum)
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}
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if m.Histogram.SampleCount != nil {
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count := new(model.Sample)
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count.Timestamp = timestamp
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metric := model.Metric{}
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_count")
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count.Metric = metric
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count.Value = model.SampleValue(m.Histogram.GetSampleCount())
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samples = append(samples, count)
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}
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}
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return out.Ingest(samples)
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}
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@ -103,6 +103,48 @@ func TestMetricFamilyProcessor(t *testing.T) {
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},
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},
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},
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{
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in: "\x8d\x01\n\x1drequest_duration_microseconds\x12\x15The response latency.\x18\x04\"S:Q\b\x85\x15\x11\xcd\xcc\xccL\x8f\xcb:A\x1a\v\b{\x11\x00\x00\x00\x00\x00\x00Y@\x1a\f\b\x9c\x03\x11\x00\x00\x00\x00\x00\x00^@\x1a\f\b\xd0\x04\x11\x00\x00\x00\x00\x00\x00b@\x1a\f\b\xf4\v\x11\x9a\x99\x99\x99\x99\x99e@\x1a\f\b\x85\x15\x11\x00\x00\x00\x00\x00\x00\xf0\u007f",
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expected: []model.Samples{
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model.Samples{
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_duration_microseconds_bucket", "le": "100"},
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Value: 123,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_duration_microseconds_bucket", "le": "120"},
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Value: 412,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_duration_microseconds_bucket", "le": "144"},
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Value: 592,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_duration_microseconds_bucket", "le": "172.8"},
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Value: 1524,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_duration_microseconds_bucket", "le": "+Inf"},
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Value: 2693,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_duration_microseconds_sum"},
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Value: 1756047.3,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_duration_microseconds_count"},
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Value: 2693,
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Timestamp: testTime,
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},
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},
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},
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},
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}
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for i, scenario := range scenarios {
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@ -139,6 +139,39 @@ func MetricFamilyToText(out io.Writer, in *dto.MetricFamily) (int, error) {
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float64(metric.Summary.GetSampleCount()),
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out,
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)
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case dto.MetricType_HISTOGRAM:
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if metric.Histogram == nil {
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return written, fmt.Errorf(
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"expected summary in metric %s", metric,
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)
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}
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for _, q := range metric.Histogram.Bucket {
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n, err = writeSample(
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name+"_bucket", metric,
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"le", fmt.Sprint(q.GetUpperBound()),
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float64(q.GetCumulativeCount()),
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out,
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)
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written += n
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if err != nil {
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return written, err
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}
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// TODO: Add +inf bucket if it's missing.
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}
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n, err = writeSample(
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name+"_sum", metric, "", "",
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metric.Histogram.GetSampleSum(),
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out,
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)
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if err != nil {
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return written, err
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}
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written += n
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n, err = writeSample(
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name+"_count", metric, "", "",
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float64(metric.Histogram.GetSampleCount()),
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out,
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)
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default:
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return written, fmt.Errorf(
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"unexpected type in metric %s", metric,
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@ -219,6 +219,54 @@ summary_name{name_1="value 1",name_2="value 2",quantile="0.9"} 2
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summary_name{name_1="value 1",name_2="value 2",quantile="0.99"} 3
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summary_name_sum{name_1="value 1",name_2="value 2"} 2010.1971
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summary_name_count{name_1="value 1",name_2="value 2"} 4711
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`,
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},
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// 4: Histogram
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{
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in: &dto.MetricFamily{
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Name: proto.String("request_duration_microseconds"),
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Help: proto.String("The response latency."),
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Type: dto.MetricType_HISTOGRAM.Enum(),
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Metric: []*dto.Metric{
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&dto.Metric{
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Histogram: &dto.Histogram{
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SampleCount: proto.Uint64(2693),
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SampleSum: proto.Float64(1756047.3),
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Bucket: []*dto.Bucket{
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&dto.Bucket{
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UpperBound: proto.Float64(100),
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CumulativeCount: proto.Uint64(123),
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},
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&dto.Bucket{
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UpperBound: proto.Float64(120),
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CumulativeCount: proto.Uint64(412),
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},
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&dto.Bucket{
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UpperBound: proto.Float64(144),
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CumulativeCount: proto.Uint64(592),
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},
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&dto.Bucket{
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UpperBound: proto.Float64(172.8),
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CumulativeCount: proto.Uint64(1524),
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},
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&dto.Bucket{
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UpperBound: proto.Float64(math.Inf(+1)),
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CumulativeCount: proto.Uint64(2693),
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},
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},
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},
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},
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},
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},
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out: `# HELP request_duration_microseconds The response latency.
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# TYPE request_duration_microseconds histogram
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request_duration_microseconds_bucket{le="100"} 123
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request_duration_microseconds_bucket{le="120"} 412
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request_duration_microseconds_bucket{le="144"} 592
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request_duration_microseconds_bucket{le="172.8"} 1524
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request_duration_microseconds_bucket{le="+Inf"} 2693
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request_duration_microseconds_sum 1.7560473e+06
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request_duration_microseconds_count 2693
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`,
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},
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}
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110
text/parse.go
110
text/parse.go
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@ -59,14 +59,19 @@ type Parser struct {
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currentMetric *dto.Metric
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currentLabelPair *dto.LabelPair
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// The remaining member variables are only used for summaries.
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// The remaining member variables are only used for summaries/histograms.
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currentLabels map[string]string // All labels including '__name__' but excluding 'quantile'/'le'
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// Summary specific.
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summaries map[uint64]*dto.Metric // Key is created with LabelsToSignature.
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currentLabels map[string]string // All labels including '__name__' but excluding 'quantile'.
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currentQuantile float64
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// Histogram specific.
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histograms map[uint64]*dto.Metric // Key is created with LabelsToSignature.
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currentBucket float64
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// These tell us if the currently processed line ends on '_count' or
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// '_sum' respectively and belong to a summary, representing the sample
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// count and sum of that summary.
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currentIsSummaryCount, currentIsSummarySum bool
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// '_sum' respectively and belong to a summary/histogram, representing the sample
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// count and sum of that summary/histogram.
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currentIsSummaryCount, currentIsSummarySum bool
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currentIsHistogramCount, currentIsHistogramSum bool
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}
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// TextToMetricFamilies reads 'in' as the simple and flat text-based exchange
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@ -111,7 +116,11 @@ func (p *Parser) reset(in io.Reader) {
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if p.summaries == nil || len(p.summaries) > 0 {
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p.summaries = map[uint64]*dto.Metric{}
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}
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if p.histograms == nil || len(p.histograms) > 0 {
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p.histograms = map[uint64]*dto.Metric{}
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}
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p.currentQuantile = math.NaN()
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p.currentBucket = math.NaN()
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}
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// startOfLine represents the state where the next byte read from p.buf is the
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@ -224,13 +233,14 @@ func (p *Parser) readingMetricName() stateFn {
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// p.currentByte) is either the first byte of the label set (i.e. a '{'), or the
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// first byte of the value (otherwise).
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func (p *Parser) readingLabels() stateFn {
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// Alas, summaries are really special... We have to reset the
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// currentLabels map and the currentQuantile before starting to
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// Summaries/histograms are special. We have to reset the
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// currentLabels map, currentQuantile and currentBucket before starting to
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// read labels.
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if p.currentMF.GetType() == dto.MetricType_SUMMARY {
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if p.currentMF.GetType() == dto.MetricType_SUMMARY || p.currentMF.GetType() == dto.MetricType_HISTOGRAM {
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p.currentLabels = map[string]string{}
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p.currentLabels[string(model.MetricNameLabel)] = p.currentMF.GetName()
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p.currentQuantile = math.NaN()
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p.currentBucket = math.NaN()
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}
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if p.currentByte != '{' {
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return p.readingValue
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@ -262,10 +272,10 @@ func (p *Parser) startLabelName() stateFn {
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p.parseError(fmt.Sprintf("label name %q is reserved", model.MetricNameLabel))
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return nil
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}
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// Once more, special summary treatment... Don't add 'quantile'
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// Special summary/histogram treatment. Don't add 'quantile' and 'le'
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// labels to 'real' labels.
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if p.currentMF.GetType() != dto.MetricType_SUMMARY ||
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p.currentLabelPair.GetName() != "quantile" {
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if !(p.currentMF.GetType() == dto.MetricType_SUMMARY && p.currentLabelPair.GetName() == "quantile") &&
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!(p.currentMF.GetType() == dto.MetricType_HISTOGRAM && p.currentLabelPair.GetName() == "le") {
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p.currentMetric.Label = append(p.currentMetric.Label, p.currentLabelPair)
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}
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if p.skipBlankTabIfCurrentBlankTab(); p.err != nil {
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@ -292,14 +302,26 @@ func (p *Parser) startLabelValue() stateFn {
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return nil
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}
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p.currentLabelPair.Value = proto.String(p.currentToken.String())
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// Once more, special treatment of summaries:
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// Special treatment of summaries:
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// - Quantile labels are special, will result in dto.Quantile later.
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// - Other labels have to be added to currentLabels for signature calculation.
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if p.currentMF.GetType() == dto.MetricType_SUMMARY {
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if p.currentLabelPair.GetName() == "quantile" {
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if p.currentQuantile, p.err = strconv.ParseFloat(p.currentLabelPair.GetValue(), 64); p.err != nil {
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// Create a more helpful error message.
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p.parseError(fmt.Sprintf("expected float as value for quantile label, got %q", p.currentLabelPair.GetValue()))
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p.parseError(fmt.Sprintf("expected float as value for 'quantile' label, got %q", p.currentLabelPair.GetValue()))
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return nil
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}
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} else {
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p.currentLabels[p.currentLabelPair.GetName()] = p.currentLabelPair.GetValue()
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}
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}
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// Similar special treatment of histograms.
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if p.currentMF.GetType() == dto.MetricType_HISTOGRAM {
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if p.currentLabelPair.GetName() == "le" {
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if p.currentBucket, p.err = strconv.ParseFloat(p.currentLabelPair.GetValue(), 64); p.err != nil {
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// Create a more helpful error message.
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p.parseError(fmt.Sprintf("expected float as value for 'le' label, got %q", p.currentLabelPair.GetValue()))
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return nil
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}
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} else {
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@ -328,7 +350,7 @@ func (p *Parser) startLabelValue() stateFn {
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// p.currentByte) is the first byte of the sample value (i.e. a float).
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func (p *Parser) readingValue() stateFn {
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// When we are here, we have read all the labels, so for the
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// infamous special case of a summary, we can finally find out
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// special case of a summary/histogram, we can finally find out
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// if the metric already exists.
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if p.currentMF.GetType() == dto.MetricType_SUMMARY {
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signature := model.LabelsToSignature(p.currentLabels)
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@ -338,6 +360,14 @@ func (p *Parser) readingValue() stateFn {
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p.summaries[signature] = p.currentMetric
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p.currentMF.Metric = append(p.currentMF.Metric, p.currentMetric)
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}
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} else if p.currentMF.GetType() == dto.MetricType_HISTOGRAM {
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signature := model.LabelsToSignature(p.currentLabels)
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if histogram := p.histograms[signature]; histogram != nil {
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p.currentMetric = histogram
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} else {
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p.histograms[signature] = p.currentMetric
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p.currentMF.Metric = append(p.currentMF.Metric, p.currentMetric)
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}
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} else {
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p.currentMF.Metric = append(p.currentMF.Metric, p.currentMetric)
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}
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@ -376,6 +406,25 @@ func (p *Parser) readingValue() stateFn {
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},
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)
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}
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case dto.MetricType_HISTOGRAM:
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// *sigh*
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if p.currentMetric.Histogram == nil {
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p.currentMetric.Histogram = &dto.Histogram{}
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}
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switch {
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case p.currentIsHistogramCount:
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p.currentMetric.Histogram.SampleCount = proto.Uint64(uint64(value))
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case p.currentIsHistogramSum:
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p.currentMetric.Histogram.SampleSum = proto.Float64(value)
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case !math.IsNaN(p.currentBucket):
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p.currentMetric.Histogram.Bucket = append(
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p.currentMetric.Histogram.Bucket,
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&dto.Bucket{
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UpperBound: proto.Float64(p.currentBucket),
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CumulativeCount: proto.Uint64(uint64(value)),
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},
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)
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}
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default:
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p.err = fmt.Errorf("unexpected type for metric name %q", p.currentMF.GetName())
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}
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@ -598,11 +647,13 @@ func (p *Parser) readTokenAsLabelValue() {
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func (p *Parser) setOrCreateCurrentMF() {
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p.currentIsSummaryCount = false
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p.currentIsSummarySum = false
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p.currentIsHistogramCount = false
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p.currentIsHistogramSum = false
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name := p.currentToken.String()
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if p.currentMF = p.metricFamiliesByName[name]; p.currentMF != nil {
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return
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}
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// Try out if this is a _sum or _count for a summary.
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// Try out if this is a _sum or _count for a summary/histogram.
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summaryName := summaryMetricName(name)
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if p.currentMF = p.metricFamiliesByName[summaryName]; p.currentMF != nil {
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if p.currentMF.GetType() == dto.MetricType_SUMMARY {
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@ -615,6 +666,18 @@ func (p *Parser) setOrCreateCurrentMF() {
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return
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}
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}
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histogramName := histogramMetricName(name)
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if p.currentMF = p.metricFamiliesByName[histogramName]; p.currentMF != nil {
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if p.currentMF.GetType() == dto.MetricType_HISTOGRAM {
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if isCount(name) {
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p.currentIsHistogramCount = true
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}
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if isSum(name) {
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p.currentIsHistogramSum = true
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}
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return
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}
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}
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p.currentMF = &dto.MetricFamily{Name: proto.String(name)}
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p.metricFamiliesByName[name] = p.currentMF
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}
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@ -647,6 +710,10 @@ func isSum(name string) bool {
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return len(name) > 4 && name[len(name)-4:] == "_sum"
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}
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func isBucket(name string) bool {
|
||||
return len(name) > 7 && name[len(name)-7:] == "_bucket"
|
||||
}
|
||||
|
||||
func summaryMetricName(name string) string {
|
||||
switch {
|
||||
case isCount(name):
|
||||
|
|
@ -657,3 +724,16 @@ func summaryMetricName(name string) string {
|
|||
return name
|
||||
}
|
||||
}
|
||||
|
||||
func histogramMetricName(name string) string {
|
||||
switch {
|
||||
case isCount(name):
|
||||
return name[:len(name)-6]
|
||||
case isSum(name):
|
||||
return name[:len(name)-4]
|
||||
case isBucket(name):
|
||||
return name[:len(name)-7]
|
||||
default:
|
||||
return name
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -335,6 +335,57 @@ my_summary{n1="val3", quantile="0.2"} 4711
|
|||
},
|
||||
},
|
||||
},
|
||||
// 4: The histogram.
|
||||
{
|
||||
in: `
|
||||
# HELP request_duration_microseconds The response latency.
|
||||
# TYPE request_duration_microseconds histogram
|
||||
request_duration_microseconds_bucket{le="100"} 123
|
||||
request_duration_microseconds_bucket{le="120"} 412
|
||||
request_duration_microseconds_bucket{le="144"} 592
|
||||
request_duration_microseconds_bucket{le="172.8"} 1524
|
||||
request_duration_microseconds_bucket{le="+Inf"} 2693
|
||||
request_duration_microseconds_sum 1.7560473e+06
|
||||
request_duration_microseconds_count 2693
|
||||
`,
|
||||
out: []*dto.MetricFamily{
|
||||
{
|
||||
Name: proto.String("request_duration_microseconds"),
|
||||
Help: proto.String("The response latency."),
|
||||
Type: dto.MetricType_HISTOGRAM.Enum(),
|
||||
Metric: []*dto.Metric{
|
||||
&dto.Metric{
|
||||
Histogram: &dto.Histogram{
|
||||
SampleCount: proto.Uint64(2693),
|
||||
SampleSum: proto.Float64(1756047.3),
|
||||
Bucket: []*dto.Bucket{
|
||||
&dto.Bucket{
|
||||
UpperBound: proto.Float64(100),
|
||||
CumulativeCount: proto.Uint64(123),
|
||||
},
|
||||
&dto.Bucket{
|
||||
UpperBound: proto.Float64(120),
|
||||
CumulativeCount: proto.Uint64(412),
|
||||
},
|
||||
&dto.Bucket{
|
||||
UpperBound: proto.Float64(144),
|
||||
CumulativeCount: proto.Uint64(592),
|
||||
},
|
||||
&dto.Bucket{
|
||||
UpperBound: proto.Float64(172.8),
|
||||
CumulativeCount: proto.Uint64(1524),
|
||||
},
|
||||
&dto.Bucket{
|
||||
UpperBound: proto.Float64(math.Inf(+1)),
|
||||
CumulativeCount: proto.Uint64(2693),
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
for i, scenario := range scenarios {
|
||||
|
|
@ -427,7 +478,7 @@ line"} 3.14
|
|||
# TYPE metric summary
|
||||
metric{quantile="bla"} 3.14
|
||||
`,
|
||||
err: "text format parsing error in line 3: expected float as value for quantile label",
|
||||
err: "text format parsing error in line 3: expected float as value for 'quantile' label",
|
||||
},
|
||||
// 8:
|
||||
{
|
||||
|
|
@ -500,6 +551,14 @@ metric 4.12
|
|||
in: `{label="bla"} 3.14 2`,
|
||||
err: "text format parsing error in line 1: invalid metric name",
|
||||
},
|
||||
// 18:
|
||||
{
|
||||
in: `
|
||||
# TYPE metric histogram
|
||||
metric_bucket{le="bla"} 3.14
|
||||
`,
|
||||
err: "text format parsing error in line 3: expected float as value for 'le' label",
|
||||
},
|
||||
}
|
||||
|
||||
for i, scenario := range scenarios {
|
||||
|
|
|
|||
Loading…
Reference in New Issue