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https://github.com/prometheus/prometheus.git
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web: Add NHCB support to federation
This simply fills the classic buckets of the histogram protobuf with the content of the custom buckets. Signed-off-by: beorn7 <beorn@grafana.com>
This commit is contained in:
beorn7
parent
aac5cc3d99
commit
62eda08a6c
100
web/federate.go
100
web/federate.go
@ -190,10 +190,13 @@ Loop:
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isHistogram := s.H != nil
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formatType := format.FormatType()
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if isHistogram &&
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!s.H.UsesCustomBuckets() &&
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formatType != expfmt.TypeProtoDelim &&
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formatType != expfmt.TypeProtoText &&
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formatType != expfmt.TypeProtoCompact {
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// Can't serve the native histogram.
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// Can't serve a native histogram with a non-protobuf format.
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// (We can serve an NHCB, though, as it is converted to a
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// classic histogram for federation.)
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// TODO(codesome): Serve them when other protocols get the native histogram support.
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continue
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}
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@ -290,32 +293,10 @@ Loop:
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}
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} else {
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lastHistogramWasGauge = s.H.CounterResetHint == histogram.GaugeType
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protMetric.Histogram = &dto.Histogram{
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SampleCountFloat: proto.Float64(s.H.Count),
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SampleSum: proto.Float64(s.H.Sum),
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Schema: proto.Int32(s.H.Schema),
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ZeroThreshold: proto.Float64(s.H.ZeroThreshold),
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ZeroCountFloat: proto.Float64(s.H.ZeroCount),
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NegativeCount: s.H.NegativeBuckets,
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PositiveCount: s.H.PositiveBuckets,
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}
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if len(s.H.PositiveSpans) > 0 {
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protMetric.Histogram.PositiveSpan = make([]*dto.BucketSpan, len(s.H.PositiveSpans))
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for i, sp := range s.H.PositiveSpans {
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protMetric.Histogram.PositiveSpan[i] = &dto.BucketSpan{
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Offset: proto.Int32(sp.Offset),
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Length: proto.Uint32(sp.Length),
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}
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}
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}
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if len(s.H.NegativeSpans) > 0 {
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protMetric.Histogram.NegativeSpan = make([]*dto.BucketSpan, len(s.H.NegativeSpans))
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for i, sp := range s.H.NegativeSpans {
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protMetric.Histogram.NegativeSpan[i] = &dto.BucketSpan{
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Offset: proto.Int32(sp.Offset),
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Length: proto.Uint32(sp.Length),
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}
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}
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if s.H.UsesCustomBuckets() {
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protMetric.Histogram = makeClassicHistogram(s.H)
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} else {
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protMetric.Histogram = makeNativeHistogram(s.H)
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}
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}
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lastWasHistogram = isHistogram
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@ -329,3 +310,68 @@ Loop:
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}
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}
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}
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// makeNativeHistogram creates a dto.Histogram representing a native histogram.
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// Use only for standard exponential schemas.
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func makeNativeHistogram(h *histogram.FloatHistogram) *dto.Histogram {
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result := &dto.Histogram{
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SampleCountFloat: proto.Float64(h.Count),
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SampleSum: proto.Float64(h.Sum),
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Schema: proto.Int32(h.Schema),
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ZeroThreshold: proto.Float64(h.ZeroThreshold),
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ZeroCountFloat: proto.Float64(h.ZeroCount),
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NegativeCount: h.NegativeBuckets,
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PositiveCount: h.PositiveBuckets,
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}
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if len(h.PositiveSpans) > 0 {
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result.PositiveSpan = make([]*dto.BucketSpan, len(h.PositiveSpans))
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for i, sp := range h.PositiveSpans {
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result.PositiveSpan[i] = &dto.BucketSpan{
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Offset: proto.Int32(sp.Offset),
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Length: proto.Uint32(sp.Length),
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}
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}
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}
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if len(h.NegativeSpans) > 0 {
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result.NegativeSpan = make([]*dto.BucketSpan, len(h.NegativeSpans))
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for i, sp := range h.NegativeSpans {
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result.NegativeSpan[i] = &dto.BucketSpan{
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Offset: proto.Int32(sp.Offset),
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Length: proto.Uint32(sp.Length),
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}
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}
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}
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return result
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}
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// makeClassicHistogram creates a dto.Histogram representing a classic
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// histogram. Use only for NHCB (schema -53).
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func makeClassicHistogram(h *histogram.FloatHistogram) *dto.Histogram {
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result := &dto.Histogram{
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SampleCountFloat: proto.Float64(h.Count),
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SampleSum: proto.Float64(h.Sum),
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}
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result.Bucket = make([]*dto.Bucket, len(h.CustomValues))
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var (
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cumulativeCount float64
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bucketIter = h.PositiveBucketIterator()
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bucketAvailable = bucketIter.Next()
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)
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for i, le := range h.CustomValues {
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for bucketAvailable && int(bucketIter.At().Index) < i {
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bucketAvailable = bucketIter.Next()
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}
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if bucketAvailable && int(bucketIter.At().Index) == i {
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cumulativeCount += bucketIter.At().Count
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}
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result.Bucket[i] = &dto.Bucket{
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UpperBound: proto.Float64(le),
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CumulativeCountFloat: proto.Float64(cumulativeCount),
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}
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}
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// Note that we do not add the +Inf bucket explicitly. In the protobuf
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// exposition format, it is optional. For other exposition formats, the
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// code converting the protobuf created here into the actual exposition
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// payload will add the +Inf bucket.
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return result
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}
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@ -340,8 +340,19 @@ func TestFederationWithNativeHistograms(t *testing.T) {
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},
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NegativeBuckets: []int64{2, 2, -2, 0},
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}
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nhcb := &histogram.Histogram{
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Count: 6,
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Sum: 1.234,
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Schema: -53,
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PositiveSpans: []histogram.Span{
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{Offset: 0, Length: 2},
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{Offset: 2, Length: 1},
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},
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PositiveBuckets: []int64{3, -1, -1},
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CustomValues: []float64{0.1, 0.2, 0.5, 1, 2},
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}
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app := db.Appender(context.Background())
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for i := range 6 {
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for i := range 7 {
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l := labels.FromStrings("__name__", "test_metric", "foo", strconv.Itoa(i))
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expL := labels.FromStrings("__name__", "test_metric", "instance", "", "foo", strconv.Itoa(i))
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var err error
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@ -360,6 +371,56 @@ func TestFederationWithNativeHistograms(t *testing.T) {
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H: histWithoutZeroBucket.ToFloat(nil),
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Metric: expL,
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})
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case 6:
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_, err = app.AppendHistogram(0, l, 100*60*1000, nhcb.Copy(), nil)
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expL = labels.FromStrings("__name__", "test_metric_count", "instance", "", "foo", strconv.Itoa(i))
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expVec = append(expVec, promql.Sample{
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T: 100 * 60 * 1000,
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F: 6,
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Metric: expL,
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})
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expL = labels.FromStrings("__name__", "test_metric_sum", "instance", "", "foo", strconv.Itoa(i))
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expVec = append(expVec, promql.Sample{
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T: 100 * 60 * 1000,
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F: 1.234,
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Metric: expL,
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})
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expL = labels.FromStrings("__name__", "test_metric_bucket", "instance", "", "foo", strconv.Itoa(i), "le", "0.1")
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expVec = append(expVec, promql.Sample{
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T: 100 * 60 * 1000,
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F: 3,
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Metric: expL,
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})
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expL = labels.FromStrings("__name__", "test_metric_bucket", "instance", "", "foo", strconv.Itoa(i), "le", "0.2")
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expVec = append(expVec, promql.Sample{
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T: 100 * 60 * 1000,
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F: 5,
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Metric: expL,
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})
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expL = labels.FromStrings("__name__", "test_metric_bucket", "instance", "", "foo", strconv.Itoa(i), "le", "0.5")
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expVec = append(expVec, promql.Sample{
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T: 100 * 60 * 1000,
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F: 5,
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Metric: expL,
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})
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expL = labels.FromStrings("__name__", "test_metric_bucket", "instance", "", "foo", strconv.Itoa(i), "le", "1.0")
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expVec = append(expVec, promql.Sample{
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T: 100 * 60 * 1000,
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F: 5,
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Metric: expL,
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})
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expL = labels.FromStrings("__name__", "test_metric_bucket", "instance", "", "foo", strconv.Itoa(i), "le", "2.0")
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expVec = append(expVec, promql.Sample{
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T: 100 * 60 * 1000,
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F: 6,
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Metric: expL,
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})
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expL = labels.FromStrings("__name__", "test_metric_bucket", "instance", "", "foo", strconv.Itoa(i), "le", "+Inf")
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expVec = append(expVec, promql.Sample{
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T: 100 * 60 * 1000,
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F: 6,
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Metric: expL,
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})
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default:
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hist.ZeroCount++
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hist.Count++
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