// Copyright 2021 The Prometheus Authors // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. package textparse import ( "bytes" "encoding/binary" "errors" "fmt" "io" "math" "strconv" "strings" "sync" "unicode/utf8" "github.com/gogo/protobuf/proto" "github.com/gogo/protobuf/types" "github.com/prometheus/common/model" "github.com/prometheus/prometheus/model/exemplar" "github.com/prometheus/prometheus/model/histogram" "github.com/prometheus/prometheus/model/labels" dto "github.com/prometheus/prometheus/prompb/io/prometheus/client" ) // floatFormatBufPool is exclusively used in formatOpenMetricsFloat. var floatFormatBufPool = sync.Pool{ New: func() interface{} { // To contain at most 17 digits and additional syntax for a float64. b := make([]byte, 0, 24) return &b }, } // ProtobufParser is a very inefficient way of unmarshaling the old Prometheus // protobuf format and then present it as it if were parsed by a // Prometheus-2-style text parser. This is only done so that we can easily plug // in the protobuf format into Prometheus 2. For future use (with the final // format that will be used for native histograms), we have to revisit the // parsing. A lot of the efficiency tricks of the Prometheus-2-style parsing // could be used in a similar fashion (byte-slice pointers into the raw // payload), which requires some hand-coded protobuf handling. But the current // parsers all expect the full series name (metric name plus label pairs) as one // string, which is not how things are represented in the protobuf format. If // the re-arrangement work is actually causing problems (which has to be seen), // that expectation needs to be changed. type ProtobufParser struct { in []byte // The input to parse. inPos int // Position within the input. metricPos int // Position within Metric slice. // fieldPos is the position within a Summary or (legacy) Histogram. -2 // is the count. -1 is the sum. Otherwise it is the index within // quantiles/buckets. fieldPos int fieldsDone bool // true if no more fields of a Summary or (legacy) Histogram to be processed. redoClassic bool // true after parsing a native histogram if we need to parse it again as a classic histogram. // exemplarPos is the position within the exemplars slice of a native histogram. exemplarPos int // exemplarReturned is set to true each time an exemplar has been // returned, and set back to false upon each Next() call. exemplarReturned bool // state is marked by the entry we are processing. EntryInvalid implies // that we have to decode the next MetricFamily. state Entry builder labels.ScratchBuilder // held here to reduce allocations when building Labels mf *dto.MetricFamily // Whether to also parse a classic histogram that is also present as a // native histogram. parseClassicHistograms bool // The following are just shenanigans to satisfy the Parser interface. metricBytes *bytes.Buffer // A somewhat fluid representation of the current metric. } // NewProtobufParser returns a parser for the payload in the byte slice. func NewProtobufParser(b []byte, parseClassicHistograms bool, st *labels.SymbolTable) Parser { return &ProtobufParser{ in: b, state: EntryInvalid, mf: &dto.MetricFamily{}, metricBytes: &bytes.Buffer{}, parseClassicHistograms: parseClassicHistograms, builder: labels.NewScratchBuilderWithSymbolTable(st, 16), } } // Series returns the bytes of a series with a simple float64 as a // value, the timestamp if set, and the value of the current sample. func (p *ProtobufParser) Series() ([]byte, *int64, float64) { var ( m = p.mf.GetMetric()[p.metricPos] ts = m.GetTimestampMs() v float64 ) switch p.mf.GetType() { case dto.MetricType_COUNTER: v = m.GetCounter().GetValue() case dto.MetricType_GAUGE: v = m.GetGauge().GetValue() case dto.MetricType_UNTYPED: v = m.GetUntyped().GetValue() case dto.MetricType_SUMMARY: s := m.GetSummary() switch p.fieldPos { case -2: v = float64(s.GetSampleCount()) case -1: v = s.GetSampleSum() // Need to detect summaries without quantile here. if len(s.GetQuantile()) == 0 { p.fieldsDone = true } default: v = s.GetQuantile()[p.fieldPos].GetValue() } case dto.MetricType_HISTOGRAM, dto.MetricType_GAUGE_HISTOGRAM: // This should only happen for a classic histogram. h := m.GetHistogram() switch p.fieldPos { case -2: v = h.GetSampleCountFloat() if v == 0 { v = float64(h.GetSampleCount()) } case -1: v = h.GetSampleSum() default: bb := h.GetBucket() if p.fieldPos >= len(bb) { v = h.GetSampleCountFloat() if v == 0 { v = float64(h.GetSampleCount()) } } else { v = bb[p.fieldPos].GetCumulativeCountFloat() if v == 0 { v = float64(bb[p.fieldPos].GetCumulativeCount()) } } } default: panic("encountered unexpected metric type, this is a bug") } if ts != 0 { return p.metricBytes.Bytes(), &ts, v } // TODO(beorn7): We assume here that ts==0 means no timestamp. That's // not true in general, but proto3 originally has no distinction between // unset and default. At a later stage, the `optional` keyword was // (re-)introduced in proto3, but gogo-protobuf never got updated to // support it. (Note that setting `[(gogoproto.nullable) = true]` for // the `timestamp_ms` field doesn't help, either.) We plan to migrate // away from gogo-protobuf to an actively maintained protobuf // implementation. Once that's done, we can simply use the `optional` // keyword and check for the unset state explicitly. return p.metricBytes.Bytes(), nil, v } // Histogram returns the bytes of a series with a native histogram as a value, // the timestamp if set, and the native histogram in the current sample. // // The Compact method is called before returning the Histogram (or FloatHistogram). // // If the SampleCountFloat or the ZeroCountFloat in the proto message is > 0, // the histogram is parsed and returned as a FloatHistogram and nil is returned // as the (integer) Histogram return value. Otherwise, it is parsed and returned // as an (integer) Histogram and nil is returned as the FloatHistogram return // value. func (p *ProtobufParser) Histogram() ([]byte, *int64, *histogram.Histogram, *histogram.FloatHistogram) { var ( m = p.mf.GetMetric()[p.metricPos] ts = m.GetTimestampMs() h = m.GetHistogram() ) if p.parseClassicHistograms && len(h.GetBucket()) > 0 { p.redoClassic = true } if h.GetSampleCountFloat() > 0 || h.GetZeroCountFloat() > 0 { // It is a float histogram. fh := histogram.FloatHistogram{ Count: h.GetSampleCountFloat(), Sum: h.GetSampleSum(), ZeroThreshold: h.GetZeroThreshold(), ZeroCount: h.GetZeroCountFloat(), Schema: h.GetSchema(), PositiveSpans: make([]histogram.Span, len(h.GetPositiveSpan())), PositiveBuckets: h.GetPositiveCount(), NegativeSpans: make([]histogram.Span, len(h.GetNegativeSpan())), NegativeBuckets: h.GetNegativeCount(), } for i, span := range h.GetPositiveSpan() { fh.PositiveSpans[i].Offset = span.GetOffset() fh.PositiveSpans[i].Length = span.GetLength() } for i, span := range h.GetNegativeSpan() { fh.NegativeSpans[i].Offset = span.GetOffset() fh.NegativeSpans[i].Length = span.GetLength() } if p.mf.GetType() == dto.MetricType_GAUGE_HISTOGRAM { fh.CounterResetHint = histogram.GaugeType } fh.Compact(0) if ts != 0 { return p.metricBytes.Bytes(), &ts, nil, &fh } // Nasty hack: Assume that ts==0 means no timestamp. That's not true in // general, but proto3 has no distinction between unset and // default. Need to avoid in the final format. return p.metricBytes.Bytes(), nil, nil, &fh } sh := histogram.Histogram{ Count: h.GetSampleCount(), Sum: h.GetSampleSum(), ZeroThreshold: h.GetZeroThreshold(), ZeroCount: h.GetZeroCount(), Schema: h.GetSchema(), PositiveSpans: make([]histogram.Span, len(h.GetPositiveSpan())), PositiveBuckets: h.GetPositiveDelta(), NegativeSpans: make([]histogram.Span, len(h.GetNegativeSpan())), NegativeBuckets: h.GetNegativeDelta(), } for i, span := range h.GetPositiveSpan() { sh.PositiveSpans[i].Offset = span.GetOffset() sh.PositiveSpans[i].Length = span.GetLength() } for i, span := range h.GetNegativeSpan() { sh.NegativeSpans[i].Offset = span.GetOffset() sh.NegativeSpans[i].Length = span.GetLength() } if p.mf.GetType() == dto.MetricType_GAUGE_HISTOGRAM { sh.CounterResetHint = histogram.GaugeType } sh.Compact(0) if ts != 0 { return p.metricBytes.Bytes(), &ts, &sh, nil } return p.metricBytes.Bytes(), nil, &sh, nil } // Help returns the metric name and help text in the current entry. // Must only be called after Next returned a help entry. // The returned byte slices become invalid after the next call to Next. func (p *ProtobufParser) Help() ([]byte, []byte) { return p.metricBytes.Bytes(), []byte(p.mf.GetHelp()) } // Type returns the metric name and type in the current entry. // Must only be called after Next returned a type entry. // The returned byte slices become invalid after the next call to Next. func (p *ProtobufParser) Type() ([]byte, model.MetricType) { n := p.metricBytes.Bytes() switch p.mf.GetType() { case dto.MetricType_COUNTER: return n, model.MetricTypeCounter case dto.MetricType_GAUGE: return n, model.MetricTypeGauge case dto.MetricType_HISTOGRAM: return n, model.MetricTypeHistogram case dto.MetricType_GAUGE_HISTOGRAM: return n, model.MetricTypeGaugeHistogram case dto.MetricType_SUMMARY: return n, model.MetricTypeSummary } return n, model.MetricTypeUnknown } // Unit returns the metric unit in the current entry. // Must only be called after Next returned a unit entry. // The returned byte slices become invalid after the next call to Next. func (p *ProtobufParser) Unit() ([]byte, []byte) { return p.metricBytes.Bytes(), []byte(p.mf.GetUnit()) } // Comment always returns nil because comments aren't supported by the protobuf // format. func (p *ProtobufParser) Comment() []byte { return nil } // Metric writes the labels of the current sample into the passed labels. // It returns the string from which the metric was parsed. func (p *ProtobufParser) Metric(l *labels.Labels) string { p.builder.Reset() p.builder.Add(labels.MetricName, p.getMagicName()) for _, lp := range p.mf.GetMetric()[p.metricPos].GetLabel() { p.builder.Add(lp.GetName(), lp.GetValue()) } if needed, name, value := p.getMagicLabel(); needed { p.builder.Add(name, value) } // Sort labels to maintain the sorted labels invariant. p.builder.Sort() *l = p.builder.Labels() return p.metricBytes.String() } // Exemplar writes the exemplar of the current sample into the passed // exemplar. It returns if an exemplar exists or not. In case of a native // histogram, the exemplars in the native histogram will be returned. // If this field is empty, the classic bucket section is still used for exemplars. // To ingest all exemplars, call the Exemplar method repeatedly until it returns false. func (p *ProtobufParser) Exemplar(ex *exemplar.Exemplar) bool { if p.exemplarReturned && p.state == EntrySeries { // We only ever return one exemplar per (non-native-histogram) series. return false } m := p.mf.GetMetric()[p.metricPos] var exProto *dto.Exemplar switch p.mf.GetType() { case dto.MetricType_COUNTER: exProto = m.GetCounter().GetExemplar() case dto.MetricType_HISTOGRAM, dto.MetricType_GAUGE_HISTOGRAM: isClassic := p.state == EntrySeries if !isClassic && len(m.GetHistogram().GetExemplars()) > 0 { exs := m.GetHistogram().GetExemplars() for p.exemplarPos < len(exs) { exProto = exs[p.exemplarPos] p.exemplarPos++ if exProto != nil && exProto.GetTimestamp() != nil { break } } if exProto != nil && exProto.GetTimestamp() == nil { return false } } else { bb := m.GetHistogram().GetBucket() if p.fieldPos < 0 { if isClassic { return false // At _count or _sum. } p.fieldPos = 0 // Start at 1st bucket for native histograms. } for p.fieldPos < len(bb) { exProto = bb[p.fieldPos].GetExemplar() if isClassic { break } p.fieldPos++ // We deliberately drop exemplars with no timestamp only for native histograms. if exProto != nil && (isClassic || exProto.GetTimestamp() != nil) { break // Found a classic histogram exemplar or a native histogram exemplar with a timestamp. } } // If the last exemplar for native histograms has no timestamp, ignore it. if !isClassic && exProto.GetTimestamp() == nil { return false } } default: return false } if exProto == nil { return false } ex.Value = exProto.GetValue() if ts := exProto.GetTimestamp(); ts != nil { ex.HasTs = true ex.Ts = ts.GetSeconds()*1000 + int64(ts.GetNanos()/1_000_000) } p.builder.Reset() for _, lp := range exProto.GetLabel() { p.builder.Add(lp.GetName(), lp.GetValue()) } p.builder.Sort() ex.Labels = p.builder.Labels() p.exemplarReturned = true return true } // CreatedTimestamp returns CT or nil if CT is not present or // invalid (as timestamp e.g. negative value) on counters, summaries or histograms. func (p *ProtobufParser) CreatedTimestamp() *int64 { var ct *types.Timestamp switch p.mf.GetType() { case dto.MetricType_COUNTER: ct = p.mf.GetMetric()[p.metricPos].GetCounter().GetCreatedTimestamp() case dto.MetricType_SUMMARY: ct = p.mf.GetMetric()[p.metricPos].GetSummary().GetCreatedTimestamp() case dto.MetricType_HISTOGRAM, dto.MetricType_GAUGE_HISTOGRAM: ct = p.mf.GetMetric()[p.metricPos].GetHistogram().GetCreatedTimestamp() default: } ctAsTime, err := types.TimestampFromProto(ct) if err != nil { // Errors means ct == nil or invalid timestamp, which we silently ignore. return nil } ctMilis := ctAsTime.UnixMilli() return &ctMilis } // Next advances the parser to the next "sample" (emulating the behavior of a // text format parser). It returns (EntryInvalid, io.EOF) if no samples were // read. func (p *ProtobufParser) Next() (Entry, error) { p.exemplarReturned = false switch p.state { case EntryInvalid: p.metricPos = 0 p.exemplarPos = 0 p.fieldPos = -2 n, err := readDelimited(p.in[p.inPos:], p.mf) p.inPos += n if err != nil { return p.state, err } // Skip empty metric families. if len(p.mf.GetMetric()) == 0 { return p.Next() } // We are at the beginning of a metric family. Put only the name // into metricBytes and validate only name, help, and type for now. name := p.mf.GetName() if !model.IsValidMetricName(model.LabelValue(name)) { return EntryInvalid, fmt.Errorf("invalid metric name: %s", name) } if help := p.mf.GetHelp(); !utf8.ValidString(help) { return EntryInvalid, fmt.Errorf("invalid help for metric %q: %s", name, help) } switch p.mf.GetType() { case dto.MetricType_COUNTER, dto.MetricType_GAUGE, dto.MetricType_HISTOGRAM, dto.MetricType_GAUGE_HISTOGRAM, dto.MetricType_SUMMARY, dto.MetricType_UNTYPED: // All good. default: return EntryInvalid, fmt.Errorf("unknown metric type for metric %q: %s", name, p.mf.GetType()) } unit := p.mf.GetUnit() if len(unit) > 0 { if p.mf.GetType() == dto.MetricType_COUNTER && strings.HasSuffix(name, "_total") { if !strings.HasSuffix(name[:len(name)-6], unit) || len(name)-6 < len(unit)+1 || name[len(name)-6-len(unit)-1] != '_' { return EntryInvalid, fmt.Errorf("unit %q not a suffix of counter %q", unit, name) } } else if !strings.HasSuffix(name, unit) || len(name) < len(unit)+1 || name[len(name)-len(unit)-1] != '_' { return EntryInvalid, fmt.Errorf("unit %q not a suffix of metric %q", unit, name) } } p.metricBytes.Reset() p.metricBytes.WriteString(name) p.state = EntryHelp case EntryHelp: if p.mf.Unit != "" { p.state = EntryUnit } else { p.state = EntryType } case EntryUnit: p.state = EntryType case EntryType: t := p.mf.GetType() if (t == dto.MetricType_HISTOGRAM || t == dto.MetricType_GAUGE_HISTOGRAM) && isNativeHistogram(p.mf.GetMetric()[0].GetHistogram()) { p.state = EntryHistogram } else { p.state = EntrySeries } if err := p.updateMetricBytes(); err != nil { return EntryInvalid, err } case EntryHistogram, EntrySeries: if p.redoClassic { p.redoClassic = false p.state = EntrySeries p.fieldPos = -3 p.fieldsDone = false } t := p.mf.GetType() if p.state == EntrySeries && !p.fieldsDone && (t == dto.MetricType_SUMMARY || t == dto.MetricType_HISTOGRAM || t == dto.MetricType_GAUGE_HISTOGRAM) { p.fieldPos++ } else { p.metricPos++ p.fieldPos = -2 p.fieldsDone = false p.exemplarPos = 0 // If this is a metric family containing native // histograms, we have to switch back to native // histograms after parsing a classic histogram. if p.state == EntrySeries && (t == dto.MetricType_HISTOGRAM || t == dto.MetricType_GAUGE_HISTOGRAM) && isNativeHistogram(p.mf.GetMetric()[0].GetHistogram()) { p.state = EntryHistogram } } if p.metricPos >= len(p.mf.GetMetric()) { p.state = EntryInvalid return p.Next() } if err := p.updateMetricBytes(); err != nil { return EntryInvalid, err } default: return EntryInvalid, fmt.Errorf("invalid protobuf parsing state: %d", p.state) } return p.state, nil } func (p *ProtobufParser) updateMetricBytes() error { b := p.metricBytes b.Reset() b.WriteString(p.getMagicName()) for _, lp := range p.mf.GetMetric()[p.metricPos].GetLabel() { b.WriteByte(model.SeparatorByte) n := lp.GetName() if !model.LabelName(n).IsValid() { return fmt.Errorf("invalid label name: %s", n) } b.WriteString(n) b.WriteByte(model.SeparatorByte) v := lp.GetValue() if !utf8.ValidString(v) { return fmt.Errorf("invalid label value: %s", v) } 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, fmt.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 float // 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" } bp := floatFormatBufPool.Get().(*[]byte) defer floatFormatBufPool.Put(bp) *bp = strconv.AppendFloat((*bp)[:0], f, 'g', -1, 64) if bytes.ContainsAny(*bp, "e.") { return string(*bp) } *bp = append(*bp, '.', '0') return string(*bp) } // 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 }