mirror of
https://github.com/prometheus/prometheus.git
synced 2024-11-09 23:24:05 -08:00
ef8e6ae780
Signed-off-by: Arthur Silva Sens <arthur.sens@coralogix.com>
600 lines
19 KiB
Go
600 lines
19 KiB
Go
// Copyright 2021 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package textparse
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import (
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"bytes"
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"encoding/binary"
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"fmt"
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"io"
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"math"
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"strings"
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"unicode/utf8"
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"github.com/gogo/protobuf/proto"
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"github.com/gogo/protobuf/types"
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"github.com/pkg/errors"
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"github.com/prometheus/common/model"
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"github.com/prometheus/prometheus/model/exemplar"
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"github.com/prometheus/prometheus/model/histogram"
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"github.com/prometheus/prometheus/model/labels"
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dto "github.com/prometheus/prometheus/prompb/io/prometheus/client"
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)
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// ProtobufParser is a very inefficient way of unmarshaling the old Prometheus
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// protobuf format and then present it as it if were parsed by a
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// Prometheus-2-style text parser. This is only done so that we can easily plug
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// in the protobuf format into Prometheus 2. For future use (with the final
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// format that will be used for native histograms), we have to revisit the
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// parsing. A lot of the efficiency tricks of the Prometheus-2-style parsing
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// could be used in a similar fashion (byte-slice pointers into the raw
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// payload), which requires some hand-coded protobuf handling. But the current
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// parsers all expect the full series name (metric name plus label pairs) as one
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// string, which is not how things are represented in the protobuf format. If
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// the re-arrangement work is actually causing problems (which has to be seen),
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// that expectation needs to be changed.
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type ProtobufParser struct {
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in []byte // The intput to parse.
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inPos int // Position within the input.
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metricPos int // Position within Metric slice.
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// fieldPos is the position within a Summary or (legacy) Histogram. -2
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// is the count. -1 is the sum. Otherwise it is the index within
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// quantiles/buckets.
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fieldPos int
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fieldsDone bool // true if no more fields of a Summary or (legacy) Histogram to be processed.
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redoClassic bool // true after parsing a native histogram if we need to parse it again as a classic histogram.
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// exemplarReturned is set to true each time an exemplar has been
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// returned, and set back to false upon each Next() call.
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exemplarReturned bool
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// state is marked by the entry we are processing. EntryInvalid implies
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// that we have to decode the next MetricFamily.
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state Entry
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builder labels.ScratchBuilder // held here to reduce allocations when building Labels
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mf *dto.MetricFamily
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// Wether to also parse a classic histogram that is also present as a
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// native histogram.
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parseClassicHistograms bool
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// The following are just shenanigans to satisfy the Parser interface.
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metricBytes *bytes.Buffer // A somewhat fluid representation of the current metric.
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}
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// NewProtobufParser returns a parser for the payload in the byte slice.
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func NewProtobufParser(b []byte, parseClassicHistograms bool) Parser {
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return &ProtobufParser{
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in: b,
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state: EntryInvalid,
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mf: &dto.MetricFamily{},
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metricBytes: &bytes.Buffer{},
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parseClassicHistograms: parseClassicHistograms,
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}
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}
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// Series returns the bytes of a series with a simple float64 as a
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// value, the timestamp if set, and the value of the current sample.
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func (p *ProtobufParser) Series() ([]byte, *int64, float64) {
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var (
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m = p.mf.GetMetric()[p.metricPos]
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ts = m.GetTimestampMs()
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v float64
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)
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switch p.mf.GetType() {
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case dto.MetricType_COUNTER:
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v = m.GetCounter().GetValue()
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case dto.MetricType_GAUGE:
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v = m.GetGauge().GetValue()
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case dto.MetricType_UNTYPED:
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v = m.GetUntyped().GetValue()
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case dto.MetricType_SUMMARY:
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s := m.GetSummary()
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switch p.fieldPos {
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case -2:
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v = float64(s.GetSampleCount())
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case -1:
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v = s.GetSampleSum()
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// Need to detect summaries without quantile here.
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if len(s.GetQuantile()) == 0 {
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p.fieldsDone = true
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}
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default:
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v = s.GetQuantile()[p.fieldPos].GetValue()
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}
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case dto.MetricType_HISTOGRAM, dto.MetricType_GAUGE_HISTOGRAM:
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// This should only happen for a classic histogram.
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h := m.GetHistogram()
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switch p.fieldPos {
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case -2:
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v = h.GetSampleCountFloat()
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if v == 0 {
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v = float64(h.GetSampleCount())
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}
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case -1:
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v = h.GetSampleSum()
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default:
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bb := h.GetBucket()
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if p.fieldPos >= len(bb) {
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v = h.GetSampleCountFloat()
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if v == 0 {
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v = float64(h.GetSampleCount())
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}
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} else {
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v = bb[p.fieldPos].GetCumulativeCountFloat()
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if v == 0 {
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v = float64(bb[p.fieldPos].GetCumulativeCount())
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}
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}
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}
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default:
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panic("encountered unexpected metric type, this is a bug")
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}
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if ts != 0 {
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return p.metricBytes.Bytes(), &ts, v
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}
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// Nasty hack: Assume that ts==0 means no timestamp. That's not true in
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// general, but proto3 has no distinction between unset and
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// default. Need to avoid in the final format.
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return p.metricBytes.Bytes(), nil, v
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}
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// Histogram returns the bytes of a series with a native histogram as a value,
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// the timestamp if set, and the native histogram in the current sample.
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//
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// The Compact method is called before returning the Histogram (or FloatHistogram).
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//
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// If the SampleCountFloat or the ZeroCountFloat in the proto message is > 0,
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// the histogram is parsed and returned as a FloatHistogram and nil is returned
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// as the (integer) Histogram return value. Otherwise, it is parsed and returned
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// as an (integer) Histogram and nil is returned as the FloatHistogram return
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// value.
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func (p *ProtobufParser) Histogram() ([]byte, *int64, *histogram.Histogram, *histogram.FloatHistogram) {
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var (
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m = p.mf.GetMetric()[p.metricPos]
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ts = m.GetTimestampMs()
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h = m.GetHistogram()
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)
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if p.parseClassicHistograms && len(h.GetBucket()) > 0 {
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p.redoClassic = true
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}
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if h.GetSampleCountFloat() > 0 || h.GetZeroCountFloat() > 0 {
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// It is a float histogram.
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fh := histogram.FloatHistogram{
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Count: h.GetSampleCountFloat(),
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Sum: h.GetSampleSum(),
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ZeroThreshold: h.GetZeroThreshold(),
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ZeroCount: h.GetZeroCountFloat(),
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Schema: h.GetSchema(),
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PositiveSpans: make([]histogram.Span, len(h.GetPositiveSpan())),
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PositiveBuckets: h.GetPositiveCount(),
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NegativeSpans: make([]histogram.Span, len(h.GetNegativeSpan())),
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NegativeBuckets: h.GetNegativeCount(),
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}
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for i, span := range h.GetPositiveSpan() {
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fh.PositiveSpans[i].Offset = span.GetOffset()
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fh.PositiveSpans[i].Length = span.GetLength()
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}
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for i, span := range h.GetNegativeSpan() {
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fh.NegativeSpans[i].Offset = span.GetOffset()
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fh.NegativeSpans[i].Length = span.GetLength()
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}
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if p.mf.GetType() == dto.MetricType_GAUGE_HISTOGRAM {
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fh.CounterResetHint = histogram.GaugeType
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}
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fh.Compact(0)
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if ts != 0 {
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return p.metricBytes.Bytes(), &ts, nil, &fh
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}
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// Nasty hack: Assume that ts==0 means no timestamp. That's not true in
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// general, but proto3 has no distinction between unset and
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// default. Need to avoid in the final format.
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return p.metricBytes.Bytes(), nil, nil, &fh
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}
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sh := histogram.Histogram{
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Count: h.GetSampleCount(),
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Sum: h.GetSampleSum(),
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ZeroThreshold: h.GetZeroThreshold(),
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ZeroCount: h.GetZeroCount(),
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Schema: h.GetSchema(),
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PositiveSpans: make([]histogram.Span, len(h.GetPositiveSpan())),
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PositiveBuckets: h.GetPositiveDelta(),
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NegativeSpans: make([]histogram.Span, len(h.GetNegativeSpan())),
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NegativeBuckets: h.GetNegativeDelta(),
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}
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for i, span := range h.GetPositiveSpan() {
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sh.PositiveSpans[i].Offset = span.GetOffset()
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sh.PositiveSpans[i].Length = span.GetLength()
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}
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for i, span := range h.GetNegativeSpan() {
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sh.NegativeSpans[i].Offset = span.GetOffset()
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sh.NegativeSpans[i].Length = span.GetLength()
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}
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if p.mf.GetType() == dto.MetricType_GAUGE_HISTOGRAM {
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sh.CounterResetHint = histogram.GaugeType
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}
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sh.Compact(0)
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if ts != 0 {
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return p.metricBytes.Bytes(), &ts, &sh, nil
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}
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return p.metricBytes.Bytes(), nil, &sh, nil
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}
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// Help returns the metric name and help text in the current entry.
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// Must only be called after Next returned a help entry.
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// The returned byte slices become invalid after the next call to Next.
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func (p *ProtobufParser) Help() ([]byte, []byte) {
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return p.metricBytes.Bytes(), []byte(p.mf.GetHelp())
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}
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// Type returns the metric name and type in the current entry.
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// Must only be called after Next returned a type entry.
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// The returned byte slices become invalid after the next call to Next.
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func (p *ProtobufParser) Type() ([]byte, MetricType) {
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n := p.metricBytes.Bytes()
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switch p.mf.GetType() {
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case dto.MetricType_COUNTER:
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return n, MetricTypeCounter
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case dto.MetricType_GAUGE:
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return n, MetricTypeGauge
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case dto.MetricType_HISTOGRAM:
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return n, MetricTypeHistogram
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case dto.MetricType_GAUGE_HISTOGRAM:
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return n, MetricTypeGaugeHistogram
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case dto.MetricType_SUMMARY:
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return n, MetricTypeSummary
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}
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return n, MetricTypeUnknown
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}
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// Unit always returns (nil, nil) because units aren't supported by the protobuf
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// format.
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func (p *ProtobufParser) Unit() ([]byte, []byte) {
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return nil, nil
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}
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// Comment always returns nil because comments aren't supported by the protobuf
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// format.
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func (p *ProtobufParser) Comment() []byte {
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return nil
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}
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// Metric writes the labels of the current sample into the passed labels.
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// It returns the string from which the metric was parsed.
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func (p *ProtobufParser) Metric(l *labels.Labels) string {
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p.builder.Reset()
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p.builder.Add(labels.MetricName, p.getMagicName())
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for _, lp := range p.mf.GetMetric()[p.metricPos].GetLabel() {
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p.builder.Add(lp.GetName(), lp.GetValue())
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}
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if needed, name, value := p.getMagicLabel(); needed {
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p.builder.Add(name, value)
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}
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// Sort labels to maintain the sorted labels invariant.
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p.builder.Sort()
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*l = p.builder.Labels()
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return p.metricBytes.String()
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}
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// Exemplar writes the exemplar of the current sample into the passed
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// exemplar. It returns if an exemplar exists or not. In case of a native
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// histogram, the legacy bucket section is still used for exemplars. To ingest
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// all exemplars, call the Exemplar method repeatedly until it returns false.
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func (p *ProtobufParser) Exemplar(ex *exemplar.Exemplar) bool {
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if p.exemplarReturned && p.state == EntrySeries {
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// We only ever return one exemplar per (non-native-histogram) series.
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return false
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}
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m := p.mf.GetMetric()[p.metricPos]
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var exProto *dto.Exemplar
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switch p.mf.GetType() {
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case dto.MetricType_COUNTER:
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exProto = m.GetCounter().GetExemplar()
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case dto.MetricType_HISTOGRAM, dto.MetricType_GAUGE_HISTOGRAM:
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bb := m.GetHistogram().GetBucket()
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if p.fieldPos < 0 {
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if p.state == EntrySeries {
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return false // At _count or _sum.
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}
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p.fieldPos = 0 // Start at 1st bucket for native histograms.
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}
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for p.fieldPos < len(bb) {
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exProto = bb[p.fieldPos].GetExemplar()
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if p.state == EntrySeries {
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break
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}
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p.fieldPos++
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if exProto != nil {
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break
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}
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}
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default:
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return false
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}
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if exProto == nil {
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return false
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}
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ex.Value = exProto.GetValue()
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if ts := exProto.GetTimestamp(); ts != nil {
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ex.HasTs = true
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ex.Ts = ts.GetSeconds()*1000 + int64(ts.GetNanos()/1_000_000)
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}
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p.builder.Reset()
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for _, lp := range exProto.GetLabel() {
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p.builder.Add(lp.GetName(), lp.GetValue())
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}
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p.builder.Sort()
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ex.Labels = p.builder.Labels()
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p.exemplarReturned = true
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return true
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}
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func (p *ProtobufParser) CreatedTimestamp(ct *types.Timestamp) bool {
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var foundCT *types.Timestamp
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switch p.mf.GetType() {
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case dto.MetricType_COUNTER:
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foundCT = p.mf.GetMetric()[p.metricPos].GetCounter().GetCreatedTimestamp()
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case dto.MetricType_SUMMARY:
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foundCT = p.mf.GetMetric()[p.metricPos].GetSummary().GetCreatedTimestamp()
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case dto.MetricType_HISTOGRAM, dto.MetricType_GAUGE_HISTOGRAM:
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foundCT = p.mf.GetMetric()[p.metricPos].GetHistogram().GetCreatedTimestamp()
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default:
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}
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if foundCT == nil {
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return false
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}
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*ct = *foundCT
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return true
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}
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// Next advances the parser to the next "sample" (emulating the behavior of a
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// text format parser). It returns (EntryInvalid, io.EOF) if no samples were
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// read.
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func (p *ProtobufParser) Next() (Entry, error) {
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p.exemplarReturned = false
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switch p.state {
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case EntryInvalid:
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p.metricPos = 0
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p.fieldPos = -2
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n, err := readDelimited(p.in[p.inPos:], p.mf)
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p.inPos += n
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if err != nil {
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return p.state, err
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}
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// Skip empty metric families.
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if len(p.mf.GetMetric()) == 0 {
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return p.Next()
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}
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// We are at the beginning of a metric family. Put only the name
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// into metricBytes and validate only name, help, and type for now.
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name := p.mf.GetName()
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if !model.IsValidMetricName(model.LabelValue(name)) {
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return EntryInvalid, errors.Errorf("invalid metric name: %s", name)
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}
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if help := p.mf.GetHelp(); !utf8.ValidString(help) {
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return EntryInvalid, errors.Errorf("invalid help for metric %q: %s", name, help)
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}
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switch p.mf.GetType() {
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case dto.MetricType_COUNTER,
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dto.MetricType_GAUGE,
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dto.MetricType_HISTOGRAM,
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dto.MetricType_GAUGE_HISTOGRAM,
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dto.MetricType_SUMMARY,
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dto.MetricType_UNTYPED:
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// All good.
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default:
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return EntryInvalid, errors.Errorf("unknown metric type for metric %q: %s", name, p.mf.GetType())
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}
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p.metricBytes.Reset()
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p.metricBytes.WriteString(name)
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p.state = EntryHelp
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case EntryHelp:
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p.state = EntryType
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case EntryType:
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t := p.mf.GetType()
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if (t == dto.MetricType_HISTOGRAM || t == dto.MetricType_GAUGE_HISTOGRAM) &&
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isNativeHistogram(p.mf.GetMetric()[0].GetHistogram()) {
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p.state = EntryHistogram
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} else {
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p.state = EntrySeries
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}
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if err := p.updateMetricBytes(); err != nil {
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return EntryInvalid, err
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}
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case EntryHistogram, EntrySeries:
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if p.redoClassic {
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p.redoClassic = false
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p.state = EntrySeries
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p.fieldPos = -3
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p.fieldsDone = false
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}
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t := p.mf.GetType()
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if p.state == EntrySeries && !p.fieldsDone &&
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(t == dto.MetricType_SUMMARY ||
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t == dto.MetricType_HISTOGRAM ||
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t == dto.MetricType_GAUGE_HISTOGRAM) {
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p.fieldPos++
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} else {
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p.metricPos++
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p.fieldPos = -2
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p.fieldsDone = false
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// If this is a metric family containing native
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// histograms, we have to switch back to native
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// histograms after parsing a classic histogram.
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if p.state == EntrySeries &&
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(t == dto.MetricType_HISTOGRAM || t == dto.MetricType_GAUGE_HISTOGRAM) &&
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isNativeHistogram(p.mf.GetMetric()[0].GetHistogram()) {
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p.state = EntryHistogram
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}
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}
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if p.metricPos >= len(p.mf.GetMetric()) {
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p.state = EntryInvalid
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return p.Next()
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}
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if err := p.updateMetricBytes(); err != nil {
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return EntryInvalid, err
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}
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default:
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return EntryInvalid, errors.Errorf("invalid protobuf parsing state: %d", p.state)
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}
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return p.state, nil
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}
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func (p *ProtobufParser) updateMetricBytes() error {
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b := p.metricBytes
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b.Reset()
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b.WriteString(p.getMagicName())
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for _, lp := range p.mf.GetMetric()[p.metricPos].GetLabel() {
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b.WriteByte(model.SeparatorByte)
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n := lp.GetName()
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if !model.LabelName(n).IsValid() {
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return errors.Errorf("invalid label name: %s", n)
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}
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b.WriteString(n)
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b.WriteByte(model.SeparatorByte)
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v := lp.GetValue()
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if !utf8.ValidString(v) {
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return errors.Errorf("invalid label value: %s", v)
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}
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b.WriteString(v)
|
|
}
|
|
if needed, n, v := p.getMagicLabel(); needed {
|
|
b.WriteByte(model.SeparatorByte)
|
|
b.WriteString(n)
|
|
b.WriteByte(model.SeparatorByte)
|
|
b.WriteString(v)
|
|
}
|
|
return nil
|
|
}
|
|
|
|
// getMagicName usually just returns p.mf.GetType() but adds a magic suffix
|
|
// ("_count", "_sum", "_bucket") if needed according to the current parser
|
|
// state.
|
|
func (p *ProtobufParser) getMagicName() string {
|
|
t := p.mf.GetType()
|
|
if p.state == EntryHistogram || (t != dto.MetricType_HISTOGRAM && t != dto.MetricType_GAUGE_HISTOGRAM && t != dto.MetricType_SUMMARY) {
|
|
return p.mf.GetName()
|
|
}
|
|
if p.fieldPos == -2 {
|
|
return p.mf.GetName() + "_count"
|
|
}
|
|
if p.fieldPos == -1 {
|
|
return p.mf.GetName() + "_sum"
|
|
}
|
|
if t == dto.MetricType_HISTOGRAM || t == dto.MetricType_GAUGE_HISTOGRAM {
|
|
return p.mf.GetName() + "_bucket"
|
|
}
|
|
return p.mf.GetName()
|
|
}
|
|
|
|
// getMagicLabel returns if a magic label ("quantile" or "le") is needed and, if
|
|
// so, its name and value. It also sets p.fieldsDone if applicable.
|
|
func (p *ProtobufParser) getMagicLabel() (bool, string, string) {
|
|
if p.state == EntryHistogram || p.fieldPos < 0 {
|
|
return false, "", ""
|
|
}
|
|
switch p.mf.GetType() {
|
|
case dto.MetricType_SUMMARY:
|
|
qq := p.mf.GetMetric()[p.metricPos].GetSummary().GetQuantile()
|
|
q := qq[p.fieldPos]
|
|
p.fieldsDone = p.fieldPos == len(qq)-1
|
|
return true, model.QuantileLabel, formatOpenMetricsFloat(q.GetQuantile())
|
|
case dto.MetricType_HISTOGRAM, dto.MetricType_GAUGE_HISTOGRAM:
|
|
bb := p.mf.GetMetric()[p.metricPos].GetHistogram().GetBucket()
|
|
if p.fieldPos >= len(bb) {
|
|
p.fieldsDone = true
|
|
return true, model.BucketLabel, "+Inf"
|
|
}
|
|
b := bb[p.fieldPos]
|
|
p.fieldsDone = math.IsInf(b.GetUpperBound(), +1)
|
|
return true, model.BucketLabel, formatOpenMetricsFloat(b.GetUpperBound())
|
|
}
|
|
return false, "", ""
|
|
}
|
|
|
|
var errInvalidVarint = errors.New("protobufparse: invalid varint encountered")
|
|
|
|
// readDelimited is essentially doing what the function of the same name in
|
|
// github.com/matttproud/golang_protobuf_extensions/pbutil is doing, but it is
|
|
// specific to a MetricFamily, utilizes the more efficient gogo-protobuf
|
|
// unmarshaling, and acts on a byte slice directly without any additional
|
|
// staging buffers.
|
|
func readDelimited(b []byte, mf *dto.MetricFamily) (n int, err error) {
|
|
if len(b) == 0 {
|
|
return 0, io.EOF
|
|
}
|
|
messageLength, varIntLength := proto.DecodeVarint(b)
|
|
if varIntLength == 0 || varIntLength > binary.MaxVarintLen32 {
|
|
return 0, errInvalidVarint
|
|
}
|
|
totalLength := varIntLength + int(messageLength)
|
|
if totalLength > len(b) {
|
|
return 0, errors.Errorf("protobufparse: insufficient length of buffer, expected at least %d bytes, got %d bytes", totalLength, len(b))
|
|
}
|
|
mf.Reset()
|
|
return totalLength, mf.Unmarshal(b[varIntLength:totalLength])
|
|
}
|
|
|
|
// formatOpenMetricsFloat works like the usual Go string formatting of a fleat
|
|
// but appends ".0" if the resulting number would otherwise contain neither a
|
|
// "." nor an "e".
|
|
func formatOpenMetricsFloat(f float64) string {
|
|
// A few common cases hardcoded.
|
|
switch {
|
|
case f == 1:
|
|
return "1.0"
|
|
case f == 0:
|
|
return "0.0"
|
|
case f == -1:
|
|
return "-1.0"
|
|
case math.IsNaN(f):
|
|
return "NaN"
|
|
case math.IsInf(f, +1):
|
|
return "+Inf"
|
|
case math.IsInf(f, -1):
|
|
return "-Inf"
|
|
}
|
|
s := fmt.Sprint(f)
|
|
if strings.ContainsAny(s, "e.") {
|
|
return s
|
|
}
|
|
return s + ".0"
|
|
}
|
|
|
|
// isNativeHistogram returns false iff the provided histograms has no spans at
|
|
// all (neither positive nor negative) and a zero threshold of 0 and a zero
|
|
// count of 0. In principle, this could still be meant to be a native histogram
|
|
// with a zero threshold of 0 and no observations yet. In that case,
|
|
// instrumentation libraries should add a "no-op" span (e.g. length zero, offset
|
|
// zero) to signal that the histogram is meant to be parsed as a native
|
|
// histogram. Failing to do so will cause Prometheus to parse it as a classic
|
|
// histogram as long as no observations have happened.
|
|
func isNativeHistogram(h *dto.Histogram) bool {
|
|
return len(h.GetPositiveSpan()) > 0 ||
|
|
len(h.GetNegativeSpan()) > 0 ||
|
|
h.GetZeroThreshold() > 0 ||
|
|
h.GetZeroCount() > 0
|
|
}
|