package streamaggr import ( "encoding/json" "fmt" "math" "slices" "sort" "strconv" "strings" "sync" "sync/atomic" "time" "github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil" "github.com/VictoriaMetrics/VictoriaMetrics/lib/cgroup" "github.com/VictoriaMetrics/VictoriaMetrics/lib/encoding" "github.com/VictoriaMetrics/VictoriaMetrics/lib/envtemplate" "github.com/VictoriaMetrics/VictoriaMetrics/lib/fs/fscore" "github.com/VictoriaMetrics/VictoriaMetrics/lib/logger" "github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal" "github.com/VictoriaMetrics/VictoriaMetrics/lib/promrelabel" "github.com/VictoriaMetrics/VictoriaMetrics/lib/promutils" "github.com/VictoriaMetrics/VictoriaMetrics/lib/timerpool" "github.com/VictoriaMetrics/metrics" "gopkg.in/yaml.v2" ) var supportedOutputs = []string{ "rate_sum", "rate_avg", "total", "total_prometheus", "increase", "increase_prometheus", "count_series", "count_samples", "unique_samples", "sum_samples", "last", "min", "max", "avg", "stddev", "stdvar", "histogram_bucket", "quantiles(phi1, ..., phiN)", } var ( // lc contains information about all compressed labels for streaming aggregation lc promutils.LabelsCompressor _ = metrics.NewGauge(`vm_streamaggr_labels_compressor_size_bytes`, func() float64 { return float64(lc.SizeBytes()) }) _ = metrics.NewGauge(`vm_streamaggr_labels_compressor_items_count`, func() float64 { return float64(lc.ItemsCount()) }) ) // LoadFromFile loads Aggregators from the given path and uses the given pushFunc for pushing the aggregated data. // // opts can contain additional options. If opts is nil, then default options are used. // // The returned Aggregators must be stopped with MustStop() when no longer needed. func LoadFromFile(path string, pushFunc PushFunc, opts *Options) (*Aggregators, error) { data, err := fscore.ReadFileOrHTTP(path) if err != nil { return nil, fmt.Errorf("cannot load aggregators: %w", err) } data, err = envtemplate.ReplaceBytes(data) if err != nil { return nil, fmt.Errorf("cannot expand environment variables in %q: %w", path, err) } as, err := newAggregatorsFromData(data, pushFunc, opts) if err != nil { return nil, fmt.Errorf("cannot initialize aggregators from %q: %w; see https://docs.victoriametrics.com/stream-aggregation/#stream-aggregation-config", path, err) } return as, nil } // Options contains optional settings for the Aggregators. type Options struct { // DedupInterval is deduplication interval for samples received for the same time series. // // The last sample per each series is left per each DedupInterval if DedupInterval > 0. // // By default deduplication is disabled. // // The deduplication can be set up individually per each aggregation via dedup_interval option. DedupInterval time.Duration // DropInputLabels is an optional list of labels to drop from samples before de-duplication and stream aggregation. DropInputLabels []string // NoAlignFlushToInterval disables alignment of flushes to the aggregation interval. // // By default flushes are aligned to aggregation interval. // // The alignment of flushes can be disabled individually per each aggregation via no_align_flush_to_interval option. NoAlignFlushToInterval bool // FlushOnShutdown enables flush of incomplete aggregation state on startup and shutdown. // // By default incomplete state is dropped. // // The flush of incomplete state can be enabled individually per each aggregation via flush_on_shutdown option. FlushOnShutdown bool // KeepMetricNames instructs to leave metric names as is for the output time series without adding any suffix. // // By default the following suffix is added to every output time series: // // input_name:[_by_][_without_]_ // // This option can be overridden individually per each aggregation via keep_metric_names option. KeepMetricNames bool // IgnoreOldSamples instructs to ignore samples with timestamps older than the current aggregation interval. // // By default all the samples are taken into account. // // This option can be overridden individually per each aggregation via ignore_old_samples option. IgnoreOldSamples bool // IgnoreFirstIntervals sets amount of aggregation intervals to ignore on start. // // By default, no intervals will be ignored. // // This option can be overridden individually per each aggregation via ignore_first_intervals option. IgnoreFirstIntervals int } // Config is a configuration for a single stream aggregation. type Config struct { // Match is a label selector for filtering time series for the given selector. // // If the match isn't set, then all the input time series are processed. Match *promrelabel.IfExpression `yaml:"match,omitempty"` // Interval is the interval between aggregations. Interval string `yaml:"interval"` // NoAlighFlushToInterval disables aligning of flushes to multiples of Interval. // By default flushes are aligned to Interval. // // See also FlushOnShutdown. NoAlignFlushToInterval *bool `yaml:"no_align_flush_to_interval,omitempty"` // FlushOnShutdown defines whether to flush incomplete aggregation state on startup and shutdown. // By default incomplete aggregation state is dropped, since it may confuse users. FlushOnShutdown *bool `yaml:"flush_on_shutdown,omitempty"` // DedupInterval is an optional interval for deduplication. DedupInterval string `yaml:"dedup_interval,omitempty"` // Staleness interval is interval after which the series state will be reset if no samples have been sent during it. // The parameter is only relevant for outputs: total, total_prometheus, increase, increase_prometheus and histogram_bucket. StalenessInterval string `yaml:"staleness_interval,omitempty"` // Outputs is a list of output aggregate functions to produce. // // The following names are allowed: // // - rate_sum - calculates sum of rate for input counters // - rate_avg - calculates average of rate for input counters // - total - aggregates input counters // - total_prometheus - aggregates input counters, ignoring the first sample in new time series // - increase - calculates the increase over input series // - increase_prometheus - calculates the increase over input series, ignoring the first sample in new time series // - count_series - counts the number of unique input series // - count_samples - counts the input samples // - unique_samples - counts the number of unique sample values // - sum_samples - sums the input sample values // - last - the last biggest sample value // - min - the minimum sample value // - max - the maximum sample value // - avg - the average value across all the samples // - stddev - standard deviation across all the samples // - stdvar - standard variance across all the samples // - histogram_bucket - creates VictoriaMetrics histogram for input samples // - quantiles(phi1, ..., phiN) - quantiles' estimation for phi in the range [0..1] // // The output time series will have the following names by default: // // input_name:[_by_][_without_]_ // // See also KeepMetricNames // Outputs []string `yaml:"outputs"` // KeepMetricNames instructs to leave metric names as is for the output time series without adding any suffix. KeepMetricNames *bool `yaml:"keep_metric_names,omitempty"` // IgnoreOldSamples instructs to ignore samples with old timestamps outside the current aggregation interval. IgnoreOldSamples *bool `yaml:"ignore_old_samples,omitempty"` // IgnoreFirstIntervals sets number of aggregation intervals to be ignored on start. IgnoreFirstIntervals *int `yaml:"ignore_first_intervals,omitempty"` // By is an optional list of labels for grouping input series. // // See also Without. // // If neither By nor Without are set, then the Outputs are calculated // individually per each input time series. By []string `yaml:"by,omitempty"` // Without is an optional list of labels, which must be excluded when grouping input series. // // See also By. // // If neither By nor Without are set, then the Outputs are calculated // individually per each input time series. Without []string `yaml:"without,omitempty"` // DropInputLabels is an optional list with labels, which must be dropped before further processing of input samples. // // Labels are dropped before de-duplication and aggregation. DropInputLabels *[]string `yaml:"drop_input_labels,omitempty"` // InputRelabelConfigs is an optional relabeling rules, which are applied on the input // before aggregation. InputRelabelConfigs []promrelabel.RelabelConfig `yaml:"input_relabel_configs,omitempty"` // OutputRelabelConfigs is an optional relabeling rules, which are applied // on the aggregated output before being sent to remote storage. OutputRelabelConfigs []promrelabel.RelabelConfig `yaml:"output_relabel_configs,omitempty"` } // Aggregators aggregates metrics passed to Push and calls pushFunc for aggregated data. type Aggregators struct { as []*aggregator // configData contains marshaled configs. // It is used in Equal() for comparing Aggregators. configData []byte ms *metrics.Set } func newAggregatorsFromData(data []byte, pushFunc PushFunc, opts *Options) (*Aggregators, error) { var cfgs []*Config if err := yaml.UnmarshalStrict(data, &cfgs); err != nil { return nil, fmt.Errorf("cannot parse stream aggregation config: %w", err) } ms := metrics.NewSet() as := make([]*aggregator, len(cfgs)) for i, cfg := range cfgs { a, err := newAggregator(cfg, pushFunc, ms, opts) if err != nil { // Stop already initialized aggregators before returning the error. for _, a := range as[:i] { a.MustStop() } return nil, fmt.Errorf("cannot initialize aggregator #%d: %w", i, err) } as[i] = a } configData, err := json.Marshal(cfgs) if err != nil { logger.Panicf("BUG: cannot marshal the provided configs: %s", err) } _ = ms.NewGauge(`vm_streamaggr_dedup_state_size_bytes`, func() float64 { n := uint64(0) for _, aggr := range as { if aggr.da != nil { n += aggr.da.sizeBytes() } } return float64(n) }) _ = ms.NewGauge(`vm_streamaggr_dedup_state_items_count`, func() float64 { n := uint64(0) for _, aggr := range as { if aggr.da != nil { n += aggr.da.itemsCount() } } return float64(n) }) metrics.RegisterSet(ms) return &Aggregators{ as: as, configData: configData, ms: ms, }, nil } // IsEnabled returns true if Aggregators has at least one configured aggregator func (a *Aggregators) IsEnabled() bool { if a == nil { return false } if len(a.as) == 0 { return false } return true } // MustStop stops a. func (a *Aggregators) MustStop() { if a == nil { return } metrics.UnregisterSet(a.ms) a.ms = nil for _, aggr := range a.as { aggr.MustStop() } a.as = nil } // Equal returns true if a and b are initialized from identical configs. func (a *Aggregators) Equal(b *Aggregators) bool { if a == nil || b == nil { return a == nil && b == nil } return string(a.configData) == string(b.configData) } // Push pushes tss to a. // // Push sets matchIdxs[idx] to 1 if the corresponding tss[idx] was used in aggregations. // Otherwise matchIdxs[idx] is set to 0. // // Push returns matchIdxs with len equal to len(tss). // It re-uses the matchIdxs if it has enough capacity to hold len(tss) items. // Otherwise it allocates new matchIdxs. func (a *Aggregators) Push(tss []prompbmarshal.TimeSeries, matchIdxs []byte) []byte { matchIdxs = bytesutil.ResizeNoCopyMayOverallocate(matchIdxs, len(tss)) for i := range matchIdxs { matchIdxs[i] = 0 } if a == nil { return matchIdxs } for _, aggr := range a.as { aggr.Push(tss, matchIdxs) } return matchIdxs } // aggregator aggregates input series according to the config passed to NewAggregator type aggregator struct { match *promrelabel.IfExpression dropInputLabels []string inputRelabeling *promrelabel.ParsedConfigs outputRelabeling *promrelabel.ParsedConfigs keepMetricNames bool ignoreOldSamples bool by []string without []string aggregateOnlyByTime bool // da is set to non-nil if input samples must be de-duplicated da *dedupAggr // aggrStates contains aggregate states for the given outputs aggrStates []aggrState // minTimestamp is used for ignoring old samples when ignoreOldSamples is set minTimestamp atomic.Int64 // suffix contains a suffix, which should be added to aggregate metric names // // It contains the interval, labels in (by, without), plus output name. // For example, foo_bar metric name is transformed to foo_bar:1m_by_job // for `interval: 1m`, `by: [job]` suffix string wg sync.WaitGroup stopCh chan struct{} flushDuration *metrics.Histogram dedupFlushDuration *metrics.Histogram flushTimeouts *metrics.Counter dedupFlushTimeouts *metrics.Counter } type aggrState interface { pushSamples(samples []pushSample) flushState(ctx *flushCtx, resetState bool) } // PushFunc is called by Aggregators when it needs to push its state to metrics storage type PushFunc func(tss []prompbmarshal.TimeSeries) // newAggregator creates new aggregator for the given cfg, which pushes the aggregate data to pushFunc. // // opts can contain additional options. If opts is nil, then default options are used. // // The returned aggregator must be stopped when no longer needed by calling MustStop(). func newAggregator(cfg *Config, pushFunc PushFunc, ms *metrics.Set, opts *Options) (*aggregator, error) { if opts == nil { opts = &Options{} } // check cfg.Interval if cfg.Interval == "" { return nil, fmt.Errorf("missing `interval` option") } interval, err := time.ParseDuration(cfg.Interval) if err != nil { return nil, fmt.Errorf("cannot parse `interval: %q`: %w", cfg.Interval, err) } if interval < time.Second { return nil, fmt.Errorf("aggregation interval cannot be smaller than 1s; got %s", interval) } // check cfg.DedupInterval dedupInterval := opts.DedupInterval if cfg.DedupInterval != "" { di, err := time.ParseDuration(cfg.DedupInterval) if err != nil { return nil, fmt.Errorf("cannot parse `dedup_interval: %q`: %w", cfg.DedupInterval, err) } dedupInterval = di } if dedupInterval > interval { return nil, fmt.Errorf("dedup_interval=%s cannot exceed interval=%s", dedupInterval, interval) } if dedupInterval > 0 && interval%dedupInterval != 0 { return nil, fmt.Errorf("interval=%s must be a multiple of dedup_interval=%s", interval, dedupInterval) } // check cfg.StalenessInterval stalenessInterval := interval * 2 if cfg.StalenessInterval != "" { stalenessInterval, err = time.ParseDuration(cfg.StalenessInterval) if err != nil { return nil, fmt.Errorf("cannot parse `staleness_interval: %q`: %w", cfg.StalenessInterval, err) } if stalenessInterval < interval { return nil, fmt.Errorf("staleness_interval=%s cannot be smaller than interval=%s", cfg.StalenessInterval, cfg.Interval) } } // Check cfg.DropInputLabels dropInputLabels := opts.DropInputLabels if v := cfg.DropInputLabels; v != nil { dropInputLabels = *v } // initialize input_relabel_configs and output_relabel_configs inputRelabeling, err := promrelabel.ParseRelabelConfigs(cfg.InputRelabelConfigs) if err != nil { return nil, fmt.Errorf("cannot parse input_relabel_configs: %w", err) } outputRelabeling, err := promrelabel.ParseRelabelConfigs(cfg.OutputRelabelConfigs) if err != nil { return nil, fmt.Errorf("cannot parse output_relabel_configs: %w", err) } // check by and without lists by := sortAndRemoveDuplicates(cfg.By) without := sortAndRemoveDuplicates(cfg.Without) if len(by) > 0 && len(without) > 0 { return nil, fmt.Errorf("`by: %s` and `without: %s` lists cannot be set simultaneously", by, without) } aggregateOnlyByTime := (len(by) == 0 && len(without) == 0) if !aggregateOnlyByTime && len(without) == 0 { by = addMissingUnderscoreName(by) } // check cfg.KeepMetricNames keepMetricNames := opts.KeepMetricNames if v := cfg.KeepMetricNames; v != nil { keepMetricNames = *v } if keepMetricNames { if len(cfg.Outputs) != 1 { return nil, fmt.Errorf("`ouputs` list must contain only a single entry if `keep_metric_names` is set; got %q", cfg.Outputs) } if cfg.Outputs[0] == "histogram_bucket" || strings.HasPrefix(cfg.Outputs[0], "quantiles(") && strings.Contains(cfg.Outputs[0], ",") { return nil, fmt.Errorf("`keep_metric_names` cannot be applied to `outputs: %q`, since they can generate multiple time series", cfg.Outputs) } } // check cfg.IgnoreOldSamples ignoreOldSamples := opts.IgnoreOldSamples if v := cfg.IgnoreOldSamples; v != nil { ignoreOldSamples = *v } // check cfg.IgnoreFirstIntervals ignoreFirstIntervals := opts.IgnoreFirstIntervals if v := cfg.IgnoreFirstIntervals; v != nil { ignoreFirstIntervals = *v } // initialize outputs list if len(cfg.Outputs) == 0 { return nil, fmt.Errorf("`outputs` list must contain at least a single entry from the list %s; "+ "see https://docs.victoriametrics.com/stream-aggregation/", supportedOutputs) } aggrStates := make([]aggrState, len(cfg.Outputs)) for i, output := range cfg.Outputs { if strings.HasPrefix(output, "quantiles(") { if !strings.HasSuffix(output, ")") { return nil, fmt.Errorf("missing closing brace for `quantiles()` output") } argsStr := output[len("quantiles(") : len(output)-1] if len(argsStr) == 0 { return nil, fmt.Errorf("`quantiles()` must contain at least one phi") } args := strings.Split(argsStr, ",") phis := make([]float64, len(args)) for j, arg := range args { arg = strings.TrimSpace(arg) phi, err := strconv.ParseFloat(arg, 64) if err != nil { return nil, fmt.Errorf("cannot parse phi=%q for quantiles(%s): %w", arg, argsStr, err) } if phi < 0 || phi > 1 { return nil, fmt.Errorf("phi inside quantiles(%s) must be in the range [0..1]; got %v", argsStr, phi) } phis[j] = phi } aggrStates[i] = newQuantilesAggrState(phis) continue } switch output { case "total": aggrStates[i] = newTotalAggrState(stalenessInterval, false, true) case "total_prometheus": aggrStates[i] = newTotalAggrState(stalenessInterval, false, false) case "increase": aggrStates[i] = newTotalAggrState(stalenessInterval, true, true) case "increase_prometheus": aggrStates[i] = newTotalAggrState(stalenessInterval, true, false) case "rate_sum": aggrStates[i] = newRateAggrState(stalenessInterval, "rate_sum") case "rate_avg": aggrStates[i] = newRateAggrState(stalenessInterval, "rate_avg") case "count_series": aggrStates[i] = newCountSeriesAggrState() case "count_samples": aggrStates[i] = newCountSamplesAggrState() case "unique_samples": aggrStates[i] = newUniqueSamplesAggrState() case "sum_samples": aggrStates[i] = newSumSamplesAggrState() case "last": aggrStates[i] = newLastAggrState() case "min": aggrStates[i] = newMinAggrState() case "max": aggrStates[i] = newMaxAggrState() case "avg": aggrStates[i] = newAvgAggrState() case "stddev": aggrStates[i] = newStddevAggrState() case "stdvar": aggrStates[i] = newStdvarAggrState() case "histogram_bucket": aggrStates[i] = newHistogramBucketAggrState(stalenessInterval) default: return nil, fmt.Errorf("unsupported output=%q; supported values: %s; "+ "see https://docs.victoriametrics.com/stream-aggregation/", output, supportedOutputs) } } // initialize suffix to add to metric names after aggregation suffix := ":" + cfg.Interval if labels := removeUnderscoreName(by); len(labels) > 0 { suffix += fmt.Sprintf("_by_%s", strings.Join(labels, "_")) } if labels := removeUnderscoreName(without); len(labels) > 0 { suffix += fmt.Sprintf("_without_%s", strings.Join(labels, "_")) } suffix += "_" // initialize the aggregator a := &aggregator{ match: cfg.Match, dropInputLabels: dropInputLabels, inputRelabeling: inputRelabeling, outputRelabeling: outputRelabeling, keepMetricNames: keepMetricNames, ignoreOldSamples: ignoreOldSamples, by: by, without: without, aggregateOnlyByTime: aggregateOnlyByTime, aggrStates: aggrStates, suffix: suffix, stopCh: make(chan struct{}), flushDuration: ms.GetOrCreateHistogram(`vm_streamaggr_flush_duration_seconds`), dedupFlushDuration: ms.GetOrCreateHistogram(`vm_streamaggr_dedup_flush_duration_seconds`), flushTimeouts: ms.GetOrCreateCounter(`vm_streamaggr_flush_timeouts_total`), dedupFlushTimeouts: ms.GetOrCreateCounter(`vm_streamaggr_dedup_flush_timeouts_total`), } if dedupInterval > 0 { a.da = newDedupAggr() } alignFlushToInterval := !opts.NoAlignFlushToInterval if v := cfg.NoAlignFlushToInterval; v != nil { alignFlushToInterval = !*v } skipIncompleteFlush := !opts.FlushOnShutdown if v := cfg.FlushOnShutdown; v != nil { skipIncompleteFlush = !*v } a.wg.Add(1) go func() { a.runFlusher(pushFunc, alignFlushToInterval, skipIncompleteFlush, interval, dedupInterval, ignoreFirstIntervals) a.wg.Done() }() return a, nil } func (a *aggregator) runFlusher(pushFunc PushFunc, alignFlushToInterval, skipIncompleteFlush bool, interval, dedupInterval time.Duration, ignoreFirstIntervals int) { alignedSleep := func(d time.Duration) { if !alignFlushToInterval { return } ct := time.Duration(time.Now().UnixNano()) dSleep := d - (ct % d) timer := timerpool.Get(dSleep) defer timer.Stop() select { case <-a.stopCh: case <-timer.C: } } tickerWait := func(t *time.Ticker) bool { select { case <-a.stopCh: return false case <-t.C: return true } } if dedupInterval <= 0 { alignedSleep(interval) t := time.NewTicker(interval) defer t.Stop() if alignFlushToInterval && skipIncompleteFlush { a.flush(nil, interval, true) } for tickerWait(t) { pf := pushFunc if ignoreFirstIntervals > 0 { pf = nil ignoreFirstIntervals-- } a.flush(pf, interval, true) if alignFlushToInterval { select { case <-t.C: default: } } } } else { alignedSleep(dedupInterval) t := time.NewTicker(dedupInterval) defer t.Stop() flushDeadline := time.Now().Add(interval) isSkippedFirstFlush := false for tickerWait(t) { a.dedupFlush(dedupInterval) ct := time.Now() if ct.After(flushDeadline) { pf := pushFunc if ignoreFirstIntervals > 0 { pf = nil ignoreFirstIntervals-- } // It is time to flush the aggregated state if alignFlushToInterval && skipIncompleteFlush && !isSkippedFirstFlush { pf = nil isSkippedFirstFlush = true } a.flush(pf, interval, true) for ct.After(flushDeadline) { flushDeadline = flushDeadline.Add(interval) } } if alignFlushToInterval { select { case <-t.C: default: } } } } if !skipIncompleteFlush && ignoreFirstIntervals == 0 { a.dedupFlush(dedupInterval) a.flush(pushFunc, interval, true) } } func (a *aggregator) dedupFlush(dedupInterval time.Duration) { if dedupInterval <= 0 { // The de-duplication is disabled. return } startTime := time.Now() a.da.flush(a.pushSamples, true) d := time.Since(startTime) a.dedupFlushDuration.Update(d.Seconds()) if d > dedupInterval { a.dedupFlushTimeouts.Inc() logger.Warnf("deduplication couldn't be finished in the configured dedup_interval=%s; it took %.03fs; "+ "possible solutions: increase dedup_interval; use match filter matching smaller number of series; "+ "reduce samples' ingestion rate to stream aggregation", dedupInterval, d.Seconds()) } } func (a *aggregator) flush(pushFunc PushFunc, interval time.Duration, resetState bool) { startTime := time.Now() // Update minTimestamp before flushing samples to the storage, // since the flush durtion can be quite long. // This should prevent from dropping samples with old timestamps when the flush takes long time. a.minTimestamp.Store(startTime.UnixMilli() - 5_000) var wg sync.WaitGroup for _, as := range a.aggrStates { flushConcurrencyCh <- struct{}{} wg.Add(1) go func(as aggrState) { defer func() { <-flushConcurrencyCh wg.Done() }() ctx := getFlushCtx(a, pushFunc) as.flushState(ctx, resetState) ctx.flushSeries() ctx.resetSeries() putFlushCtx(ctx) }(as) } wg.Wait() d := time.Since(startTime) a.flushDuration.Update(d.Seconds()) if d > interval { a.flushTimeouts.Inc() logger.Warnf("stream aggregation couldn't be finished in the configured interval=%s; it took %.03fs; "+ "possible solutions: increase interval; use match filter matching smaller number of series; "+ "reduce samples' ingestion rate to stream aggregation", interval, d.Seconds()) } } var flushConcurrencyCh = make(chan struct{}, cgroup.AvailableCPUs()) // MustStop stops the aggregator. // // The aggregator stops pushing the aggregated metrics after this call. func (a *aggregator) MustStop() { close(a.stopCh) a.wg.Wait() } // Push pushes tss to a. func (a *aggregator) Push(tss []prompbmarshal.TimeSeries, matchIdxs []byte) { ctx := getPushCtx() defer putPushCtx(ctx) samples := ctx.samples buf := ctx.buf labels := &ctx.labels inputLabels := &ctx.inputLabels outputLabels := &ctx.outputLabels dropLabels := a.dropInputLabels ignoreOldSamples := a.ignoreOldSamples minTimestamp := a.minTimestamp.Load() for idx, ts := range tss { if !a.match.Match(ts.Labels) { continue } matchIdxs[idx] = 1 if len(dropLabels) > 0 { labels.Labels = dropSeriesLabels(labels.Labels[:0], ts.Labels, dropLabels) } else { labels.Labels = append(labels.Labels[:0], ts.Labels...) } labels.Labels = a.inputRelabeling.Apply(labels.Labels, 0) if len(labels.Labels) == 0 { // The metric has been deleted by the relabeling continue } labels.Sort() inputLabels.Reset() outputLabels.Reset() if !a.aggregateOnlyByTime { inputLabels.Labels, outputLabels.Labels = getInputOutputLabels(inputLabels.Labels, outputLabels.Labels, labels.Labels, a.by, a.without) } else { outputLabels.Labels = append(outputLabels.Labels, labels.Labels...) } buf = compressLabels(buf[:0], inputLabels.Labels, outputLabels.Labels) key := bytesutil.InternBytes(buf) for _, sample := range ts.Samples { if math.IsNaN(sample.Value) { // Skip NaN values continue } if ignoreOldSamples && sample.Timestamp < minTimestamp { // Skip old samples outside the current aggregation interval continue } samples = append(samples, pushSample{ key: key, value: sample.Value, timestamp: sample.Timestamp, }) } } ctx.samples = samples ctx.buf = buf if a.da != nil { a.da.pushSamples(samples) } else { a.pushSamples(samples) } } func compressLabels(dst []byte, inputLabels, outputLabels []prompbmarshal.Label) []byte { bb := bbPool.Get() bb.B = lc.Compress(bb.B, inputLabels) dst = encoding.MarshalVarUint64(dst, uint64(len(bb.B))) dst = append(dst, bb.B...) bbPool.Put(bb) dst = lc.Compress(dst, outputLabels) return dst } func decompressLabels(dst []prompbmarshal.Label, key string) []prompbmarshal.Label { return lc.Decompress(dst, bytesutil.ToUnsafeBytes(key)) } func getOutputKey(key string) string { src := bytesutil.ToUnsafeBytes(key) inputKeyLen, nSize := encoding.UnmarshalVarUint64(src) if nSize <= 0 { logger.Panicf("BUG: cannot unmarshal inputKeyLen from uvarint") } src = src[nSize:] outputKey := src[inputKeyLen:] return bytesutil.ToUnsafeString(outputKey) } func getInputOutputKey(key string) (string, string) { src := bytesutil.ToUnsafeBytes(key) inputKeyLen, nSize := encoding.UnmarshalVarUint64(src) if nSize <= 0 { logger.Panicf("BUG: cannot unmarshal inputKeyLen from uvarint") } src = src[nSize:] inputKey := src[:inputKeyLen] outputKey := src[inputKeyLen:] return bytesutil.ToUnsafeString(inputKey), bytesutil.ToUnsafeString(outputKey) } func (a *aggregator) pushSamples(samples []pushSample) { for _, as := range a.aggrStates { as.pushSamples(samples) } } type pushCtx struct { samples []pushSample labels promutils.Labels inputLabels promutils.Labels outputLabels promutils.Labels buf []byte } func (ctx *pushCtx) reset() { clear(ctx.samples) ctx.samples = ctx.samples[:0] ctx.labels.Reset() ctx.inputLabels.Reset() ctx.outputLabels.Reset() ctx.buf = ctx.buf[:0] } type pushSample struct { key string value float64 timestamp int64 } func getPushCtx() *pushCtx { v := pushCtxPool.Get() if v == nil { return &pushCtx{} } return v.(*pushCtx) } func putPushCtx(ctx *pushCtx) { ctx.reset() pushCtxPool.Put(ctx) } var pushCtxPool sync.Pool func getInputOutputLabels(dstInput, dstOutput, labels []prompbmarshal.Label, by, without []string) ([]prompbmarshal.Label, []prompbmarshal.Label) { if len(without) > 0 { for _, label := range labels { if slices.Contains(without, label.Name) { dstInput = append(dstInput, label) } else { dstOutput = append(dstOutput, label) } } } else { for _, label := range labels { if !slices.Contains(by, label.Name) { dstInput = append(dstInput, label) } else { dstOutput = append(dstOutput, label) } } } return dstInput, dstOutput } func getFlushCtx(a *aggregator, pushFunc PushFunc) *flushCtx { v := flushCtxPool.Get() if v == nil { v = &flushCtx{} } ctx := v.(*flushCtx) ctx.a = a ctx.pushFunc = pushFunc return ctx } func putFlushCtx(ctx *flushCtx) { ctx.reset() flushCtxPool.Put(ctx) } var flushCtxPool sync.Pool type flushCtx struct { a *aggregator pushFunc PushFunc tss []prompbmarshal.TimeSeries labels []prompbmarshal.Label samples []prompbmarshal.Sample } func (ctx *flushCtx) reset() { ctx.a = nil ctx.pushFunc = nil ctx.resetSeries() } func (ctx *flushCtx) resetSeries() { clear(ctx.tss) ctx.tss = ctx.tss[:0] clear(ctx.labels) ctx.labels = ctx.labels[:0] ctx.samples = ctx.samples[:0] } func (ctx *flushCtx) flushSeries() { tss := ctx.tss if len(tss) == 0 { // nothing to flush return } outputRelabeling := ctx.a.outputRelabeling if outputRelabeling == nil { // Fast path - push the output metrics. if ctx.pushFunc != nil { ctx.pushFunc(tss) } return } // Slow path - apply output relabeling and then push the output metrics. auxLabels := promutils.GetLabels() dstLabels := auxLabels.Labels[:0] dst := tss[:0] for _, ts := range tss { dstLabelsLen := len(dstLabels) dstLabels = append(dstLabels, ts.Labels...) dstLabels = outputRelabeling.Apply(dstLabels, dstLabelsLen) if len(dstLabels) == dstLabelsLen { // The metric has been deleted by the relabeling continue } ts.Labels = dstLabels[dstLabelsLen:] dst = append(dst, ts) } if ctx.pushFunc != nil { ctx.pushFunc(dst) } auxLabels.Labels = dstLabels promutils.PutLabels(auxLabels) } func (ctx *flushCtx) appendSeries(key, suffix string, timestamp int64, value float64) { labelsLen := len(ctx.labels) samplesLen := len(ctx.samples) ctx.labels = decompressLabels(ctx.labels, key) if !ctx.a.keepMetricNames { ctx.labels = addMetricSuffix(ctx.labels, labelsLen, ctx.a.suffix, suffix) } ctx.samples = append(ctx.samples, prompbmarshal.Sample{ Timestamp: timestamp, Value: value, }) ctx.tss = append(ctx.tss, prompbmarshal.TimeSeries{ Labels: ctx.labels[labelsLen:], Samples: ctx.samples[samplesLen:], }) // Limit the maximum length of ctx.tss in order to limit memory usage. if len(ctx.tss) >= 10_000 { ctx.flushSeries() ctx.resetSeries() } } func (ctx *flushCtx) appendSeriesWithExtraLabel(key, suffix string, timestamp int64, value float64, extraName, extraValue string) { labelsLen := len(ctx.labels) samplesLen := len(ctx.samples) ctx.labels = decompressLabels(ctx.labels, key) if !ctx.a.keepMetricNames { ctx.labels = addMetricSuffix(ctx.labels, labelsLen, ctx.a.suffix, suffix) } ctx.labels = append(ctx.labels, prompbmarshal.Label{ Name: extraName, Value: extraValue, }) ctx.samples = append(ctx.samples, prompbmarshal.Sample{ Timestamp: timestamp, Value: value, }) ctx.tss = append(ctx.tss, prompbmarshal.TimeSeries{ Labels: ctx.labels[labelsLen:], Samples: ctx.samples[samplesLen:], }) } func addMetricSuffix(labels []prompbmarshal.Label, offset int, firstSuffix, lastSuffix string) []prompbmarshal.Label { src := labels[offset:] for i := range src { label := &src[i] if label.Name != "__name__" { continue } bb := bbPool.Get() bb.B = append(bb.B, label.Value...) bb.B = append(bb.B, firstSuffix...) bb.B = append(bb.B, lastSuffix...) label.Value = bytesutil.InternBytes(bb.B) bbPool.Put(bb) return labels } // The __name__ isn't found. Add it bb := bbPool.Get() bb.B = append(bb.B, firstSuffix...) bb.B = append(bb.B, lastSuffix...) labelValue := bytesutil.InternBytes(bb.B) labels = append(labels, prompbmarshal.Label{ Name: "__name__", Value: labelValue, }) return labels } func addMissingUnderscoreName(labels []string) []string { result := []string{"__name__"} for _, s := range labels { if s == "__name__" { continue } result = append(result, s) } return result } func removeUnderscoreName(labels []string) []string { var result []string for _, s := range labels { if s == "__name__" { continue } result = append(result, s) } return result } func sortAndRemoveDuplicates(a []string) []string { if len(a) == 0 { return nil } a = append([]string{}, a...) sort.Strings(a) dst := a[:1] for _, v := range a[1:] { if v != dst[len(dst)-1] { dst = append(dst, v) } } return dst } var bbPool bytesutil.ByteBufferPool