VictoriaMetrics/lib/streamaggr/streamaggr.go
Ivan Yurochko 5dd879cd17
lib/streamaggr: add ignore_first_sample_interval param for streamaggr cfg (#7313)
### Describe Your Changes

As of right now by default aggregated output in streaming aggregation
takes a staleness interval and only starts sending first samples after
the staleness interval passes. We have a use case where we prefer to
start sending data as soon as we have any. This adds the option to
configure when we start sending first samples

https://github.com/VictoriaMetrics/VictoriaMetrics/issues/7116

### Checklist

The following checks are **mandatory**:

- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).

---------

Co-authored-by: hagen1778 <roman@victoriametrics.com>
2024-11-21 16:20:22 +01:00

1297 lines
39 KiB
Go

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{
"avg",
"count_samples",
"count_series",
"histogram_bucket",
"increase",
"increase_prometheus",
"last",
"max",
"min",
"quantiles(phi1, ..., phiN)",
"rate_avg",
"rate_sum",
"stddev",
"stdvar",
"sum_samples",
"total",
"total_prometheus",
"unique_samples",
}
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.
//
// alias is used as url label in metrics exposed for the returned Aggregators.
//
// The returned Aggregators must be stopped with MustStop() when no longer needed.
func LoadFromFile(path string, pushFunc PushFunc, opts *Options, alias string) (*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 := loadFromData(data, path, pushFunc, opts, alias)
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:<interval>[_by_<by_labels>][_without_<without_labels>]_<output>
//
// 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 the number of aggregation intervals to be ignored on start.
//
// By default, zero intervals are ignored.
//
// This option can be overridden individually per each aggregation via ignore_first_intervals option.
IgnoreFirstIntervals int
// KeepInput enables keeping all the input samples after the aggregation.
//
// By default, aggregates samples are dropped, while the remaining samples are written to the corresponding -remoteWrite.url.
KeepInput bool
}
// Config is a configuration for a single stream aggregation.
type Config struct {
// Name is an optional name of the Config.
//
// It is used as `name` label in the exposed metrics for the given Config.
Name string `yaml:"name,omitempty"`
// 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"`
// IgnoreFirstSampleInterval specifies the interval after which the agent begins sending samples.
// By default, it is set to the staleness interval, and it helps reduce the initial sample load after an agent restart.
// This parameter is relevant only for the following outputs: total, total_prometheus, increase, increase_prometheus, and histogram_bucket.
IgnoreFirstSampleInterval string `yaml:"ignore_first_sample_interval,omitempty"`
// Outputs is a list of output aggregate functions to produce.
//
// The following names are allowed:
//
// - avg - the average value across all the samples
// - count_samples - counts the input samples
// - count_series - counts the number of unique input series
// - histogram_bucket - creates VictoriaMetrics histogram for input samples
// - increase - calculates the increase over input series
// - increase_prometheus - calculates the increase over input series, ignoring the first sample in new time series
// - last - the last biggest sample value
// - max - the maximum sample value
// - min - the minimum sample value
// - quantiles(phi1, ..., phiN) - quantiles' estimation for phi in the range [0..1]
// - rate_avg - calculates average of rate for input counters
// - rate_sum - calculates sum of rate for input counters
// - stddev - standard deviation across all the samples
// - stdvar - standard variance across all the samples
// - sum_samples - sums the input sample values
// - total - aggregates input counters
// - total_prometheus - aggregates input counters, ignoring the first sample in new time series
// - unique_samples - counts the number of unique sample values
//
// The output time series will have the following names by default:
//
// input_name:<interval>[_by_<by_labels>][_without_<without_labels>]_<output>
//
// 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
// filePath is the path to config file used for creating the Aggregators.
filePath string
// ms contains metrics associated with the Aggregators.
ms *metrics.Set
}
// FilePath returns path to file with the configuration used for creating the given Aggregators.
func (a *Aggregators) FilePath() string {
return a.filePath
}
// LoadFromData loads aggregators from data.
//
// opts can contain additional options. If opts is nil, then default options are used.
func LoadFromData(data []byte, pushFunc PushFunc, opts *Options, alias string) (*Aggregators, error) {
return loadFromData(data, "inmemory", pushFunc, opts, alias)
}
func loadFromData(data []byte, filePath string, pushFunc PushFunc, opts *Options, alias string) (*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, filePath, pushFunc, ms, opts, alias, i+1)
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)
}
metrics.RegisterSet(ms)
return &Aggregators{
as: as,
configData: configData,
filePath: filePath,
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, true)
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
// interval is the interval between flushes
interval time.Duration
// dedupInterval is optional deduplication interval for incoming samples
dedupInterval time.Duration
// da is set to non-nil if input samples must be de-duplicated
da *dedupAggr
// aggrOutputs contains aggregate states for the given outputs
aggrOutputs []aggrOutput
// 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
samplesLag *metrics.Histogram
flushTimeouts *metrics.Counter
dedupFlushTimeouts *metrics.Counter
ignoredOldSamples *metrics.Counter
ignoredNaNSamples *metrics.Counter
matchedSamples *metrics.Counter
}
type aggrOutput struct {
as aggrState
outputSamples *metrics.Counter
}
type aggrState interface {
// pushSamples must push samples to the aggrState.
//
// samples[].key must be cloned by aggrState, since it may change after returning from pushSamples.
pushSamples(samples []pushSample)
// flushState must flush aggrState data to ctx.
flushState(ctx *flushCtx)
}
// 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, path string, pushFunc PushFunc, ms *metrics.Set, opts *Options, alias string, aggrID int) (*aggregator, error) {
// 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)
}
if opts == nil {
opts = &Options{}
}
// 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.IgnoreFirstSampleInterval
// by default, it equals to the staleness interval to have backward compatibility, see https://github.com/VictoriaMetrics/VictoriaMetrics/issues/7116
ignoreFirstSampleInterval := stalenessInterval
if cfg.IgnoreFirstSampleInterval != "" {
ignoreFirstSampleInterval, err = time.ParseDuration(cfg.IgnoreFirstSampleInterval)
if err != nil {
return nil, fmt.Errorf("cannot parse `ignore_first_sample_interval: %q`: %w", cfg.IgnoreFirstSampleInterval, err)
}
}
// 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; see https://docs.victoriametrics.com/stream-aggregation/", 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 opts.KeepInput {
return nil, fmt.Errorf("`-streamAggr.keepInput` and `keep_metric_names` options can't be enabled in the same time," +
"as it may result in time series collision")
}
if len(cfg.Outputs) != 1 {
return nil, fmt.Errorf("`outputs` list must contain only a single entry if `keep_metric_names` is set; got %q; "+
"see https://docs.victoriametrics.com/stream-aggregation/#output-metric-names", 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; "+
"see https://docs.victoriametrics.com/stream-aggregation/#output-metric-names", 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 common metric labels
name := cfg.Name
if name == "" {
name = "none"
}
metricLabels := fmt.Sprintf(`name=%q,path=%q,url=%q,position="%d"`, name, path, alias, aggrID)
// initialize aggrOutputs
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)
}
aggrOutputs := make([]aggrOutput, len(cfg.Outputs))
outputsSeen := make(map[string]struct{}, len(cfg.Outputs))
for i, output := range cfg.Outputs {
as, err := newAggrState(output, outputsSeen, stalenessInterval, ignoreFirstSampleInterval)
if err != nil {
return nil, err
}
aggrOutputs[i] = aggrOutput{
as: as,
outputSamples: ms.NewCounter(fmt.Sprintf(`vm_streamaggr_output_samples_total{output=%q,%s}`, output, metricLabels)),
}
}
// 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,
interval: interval,
dedupInterval: dedupInterval,
aggrOutputs: aggrOutputs,
suffix: suffix,
stopCh: make(chan struct{}),
flushDuration: ms.NewHistogram(fmt.Sprintf(`vm_streamaggr_flush_duration_seconds{%s}`, metricLabels)),
dedupFlushDuration: ms.NewHistogram(fmt.Sprintf(`vm_streamaggr_dedup_flush_duration_seconds{%s}`, metricLabels)),
samplesLag: ms.NewHistogram(fmt.Sprintf(`vm_streamaggr_samples_lag_seconds{%s}`, metricLabels)),
matchedSamples: ms.NewCounter(fmt.Sprintf(`vm_streamaggr_matched_samples_total{%s}`, metricLabels)),
flushTimeouts: ms.NewCounter(fmt.Sprintf(`vm_streamaggr_flush_timeouts_total{%s}`, metricLabels)),
dedupFlushTimeouts: ms.NewCounter(fmt.Sprintf(`vm_streamaggr_dedup_flush_timeouts_total{%s}`, metricLabels)),
ignoredNaNSamples: ms.NewCounter(fmt.Sprintf(`vm_streamaggr_ignored_samples_total{reason="nan",%s}`, metricLabels)),
ignoredOldSamples: ms.NewCounter(fmt.Sprintf(`vm_streamaggr_ignored_samples_total{reason="too_old",%s}`, metricLabels)),
}
if dedupInterval > 0 {
a.da = newDedupAggr()
_ = ms.NewGauge(fmt.Sprintf(`vm_streamaggr_dedup_state_size_bytes{%s}`, metricLabels), func() float64 {
n := a.da.sizeBytes()
return float64(n)
})
_ = ms.NewGauge(fmt.Sprintf(`vm_streamaggr_dedup_state_items_count{%s}`, metricLabels), func() float64 {
n := a.da.itemsCount()
return float64(n)
})
}
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, ignoreFirstIntervals)
a.wg.Done()
}()
return a, nil
}
func newAggrState(output string, outputsSeen map[string]struct{}, stalenessInterval, ignoreFirstSampleInterval time.Duration) (aggrState, error) {
// check for duplicated output
if _, ok := outputsSeen[output]; ok {
return nil, fmt.Errorf("`outputs` list contains duplicate aggregation function: %s", output)
}
outputsSeen[output] = struct{}{}
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 i, 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[i] = phi
}
if _, ok := outputsSeen["quantiles"]; ok {
return nil, fmt.Errorf("`outputs` list contains duplicated `quantiles()` function, please combine multiple phi* like `quantiles(0.5, 0.9)`")
}
outputsSeen["quantiles"] = struct{}{}
return newQuantilesAggrState(phis), nil
}
switch output {
case "avg":
return newAvgAggrState(), nil
case "count_samples":
return newCountSamplesAggrState(), nil
case "count_series":
return newCountSeriesAggrState(), nil
case "histogram_bucket":
return newHistogramBucketAggrState(stalenessInterval), nil
case "increase":
return newTotalAggrState(stalenessInterval, ignoreFirstSampleInterval, true, true), nil
case "increase_prometheus":
return newTotalAggrState(stalenessInterval, ignoreFirstSampleInterval, true, false), nil
case "last":
return newLastAggrState(), nil
case "max":
return newMaxAggrState(), nil
case "min":
return newMinAggrState(), nil
case "rate_avg":
return newRateAggrState(stalenessInterval, true), nil
case "rate_sum":
return newRateAggrState(stalenessInterval, false), nil
case "stddev":
return newStddevAggrState(), nil
case "stdvar":
return newStdvarAggrState(), nil
case "sum_samples":
return newSumSamplesAggrState(), nil
case "total":
return newTotalAggrState(stalenessInterval, ignoreFirstSampleInterval, false, true), nil
case "total_prometheus":
return newTotalAggrState(stalenessInterval, ignoreFirstSampleInterval, false, false), nil
case "unique_samples":
return newUniqueSamplesAggrState(), nil
default:
return nil, fmt.Errorf("unsupported output=%q; supported values: %s; see https://docs.victoriametrics.com/stream-aggregation/", output, supportedOutputs)
}
}
func (a *aggregator) runFlusher(pushFunc PushFunc, alignFlushToInterval, skipIncompleteFlush bool, 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:
}
}
var flushTimeMsec int64
tickerWait := func(t *time.Ticker) bool {
select {
case <-a.stopCh:
flushTimeMsec = time.Now().UnixMilli()
return false
case ct := <-t.C:
flushTimeMsec = ct.UnixMilli()
return true
}
}
if a.dedupInterval <= 0 {
alignedSleep(a.interval)
t := time.NewTicker(a.interval)
defer t.Stop()
if alignFlushToInterval && skipIncompleteFlush {
a.flush(nil, 0)
ignoreFirstIntervals--
}
for tickerWait(t) {
if ignoreFirstIntervals > 0 {
a.flush(nil, 0)
ignoreFirstIntervals--
} else {
a.flush(pushFunc, flushTimeMsec)
}
if alignFlushToInterval {
select {
case <-t.C:
default:
}
}
}
} else {
alignedSleep(a.dedupInterval)
t := time.NewTicker(a.dedupInterval)
defer t.Stop()
flushDeadline := time.Now().Add(a.interval)
isSkippedFirstFlush := false
for tickerWait(t) {
a.dedupFlush()
ct := time.Now()
if ct.After(flushDeadline) {
// It is time to flush the aggregated state
if alignFlushToInterval && skipIncompleteFlush && !isSkippedFirstFlush {
a.flush(nil, 0)
ignoreFirstIntervals--
isSkippedFirstFlush = true
} else if ignoreFirstIntervals > 0 {
a.flush(nil, 0)
ignoreFirstIntervals--
} else {
a.flush(pushFunc, flushTimeMsec)
}
for ct.After(flushDeadline) {
flushDeadline = flushDeadline.Add(a.interval)
}
}
if alignFlushToInterval {
select {
case <-t.C:
default:
}
}
}
}
if !skipIncompleteFlush && ignoreFirstIntervals <= 0 {
a.dedupFlush()
a.flush(pushFunc, flushTimeMsec)
}
}
func (a *aggregator) dedupFlush() {
if a.dedupInterval <= 0 {
// The de-duplication is disabled.
return
}
startTime := time.Now()
a.da.flush(a.pushSamples)
d := time.Since(startTime)
a.dedupFlushDuration.Update(d.Seconds())
if d > a.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", a.dedupInterval, d.Seconds())
}
}
// flush flushes aggregator state to pushFunc.
//
// If pushFunc is nil, then the aggregator state is just reset.
func (a *aggregator) flush(pushFunc PushFunc, flushTimeMsec int64) {
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(flushTimeMsec - 5_000)
var wg sync.WaitGroup
for i := range a.aggrOutputs {
ao := &a.aggrOutputs[i]
flushConcurrencyCh <- struct{}{}
wg.Add(1)
go func(ao *aggrOutput) {
defer func() {
<-flushConcurrencyCh
wg.Done()
}()
ctx := getFlushCtx(a, ao, pushFunc, flushTimeMsec)
ao.as.flushState(ctx)
ctx.flushSeries()
putFlushCtx(ctx)
}(ao)
}
wg.Wait()
d := time.Since(startTime)
a.flushDuration.Update(d.Seconds())
if d > a.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", a.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()
nowMsec := time.Now().UnixMilli()
var maxLagMsec int64
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...)
}
bufLen := len(buf)
buf = compressLabels(buf, inputLabels.Labels, outputLabels.Labels)
// key remains valid only by the end of this function and can't be reused after
// do not intern key because number of unique keys could be too high
key := bytesutil.ToUnsafeString(buf[bufLen:])
for _, s := range ts.Samples {
if math.IsNaN(s.Value) {
a.ignoredNaNSamples.Inc()
// Skip NaN values
continue
}
if ignoreOldSamples && s.Timestamp < minTimestamp {
a.ignoredOldSamples.Inc()
// Skip old samples outside the current aggregation interval
continue
}
lagMsec := nowMsec - s.Timestamp
if lagMsec > maxLagMsec {
maxLagMsec = lagMsec
}
samples = append(samples, pushSample{
key: key,
value: s.Value,
timestamp: s.Timestamp,
})
}
}
if len(samples) > 0 {
a.matchedSamples.Add(len(samples))
a.samplesLag.Update(float64(maxLagMsec) / 1_000)
}
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 _, ao := range a.aggrOutputs {
ao.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 identifies a sample that belongs to unique series
// key value can't be re-used
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, ao *aggrOutput, pushFunc PushFunc, flushTimestamp int64) *flushCtx {
v := flushCtxPool.Get()
if v == nil {
v = &flushCtx{}
}
ctx := v.(*flushCtx)
ctx.a = a
ctx.ao = ao
ctx.pushFunc = pushFunc
ctx.flushTimestamp = flushTimestamp
return ctx
}
func putFlushCtx(ctx *flushCtx) {
ctx.reset()
flushCtxPool.Put(ctx)
}
var flushCtxPool sync.Pool
type flushCtx struct {
a *aggregator
ao *aggrOutput
pushFunc PushFunc
flushTimestamp int64
tss []prompbmarshal.TimeSeries
labels []prompbmarshal.Label
samples []prompbmarshal.Sample
}
func (ctx *flushCtx) reset() {
ctx.a = nil
ctx.ao = nil
ctx.pushFunc = nil
ctx.flushTimestamp = 0
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() {
defer ctx.resetSeries()
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)
ctx.ao.outputSamples.Add(len(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)
ctx.ao.outputSamples.Add(len(dst))
}
auxLabels.Labels = dstLabels
promutils.PutLabels(auxLabels)
}
func (ctx *flushCtx) appendSeries(key, suffix string, 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: ctx.flushTimestamp,
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()
}
}
func (ctx *flushCtx) appendSeriesWithExtraLabel(key, suffix string, 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: ctx.flushTimestamp,
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()
}
}
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