VictoriaMetrics/app/vminsert/common/streamaggr.go
Aliaksandr Valialkin 2da7dfc754
Revert c6c5a5a186 and b2765c45d0
Reason for revert:

There are many statsd servers exist:

- https://github.com/statsd/statsd - classical statsd server
- https://docs.datadoghq.com/developers/dogstatsd/ - statsd server from DataDog built into DatDog Agent ( https://docs.datadoghq.com/agent/ )
- https://github.com/avito-tech/bioyino - high-performance statsd server
- https://github.com/atlassian/gostatsd - statsd server in Go
- https://github.com/prometheus/statsd_exporter - statsd server, which exposes the aggregated data as Prometheus metrics

These servers can be used for efficient aggregating of statsd data and sending it to VictoriaMetrics
according to https://docs.victoriametrics.com/#how-to-send-data-from-graphite-compatible-agents-such-as-statsd (
the https://github.com/prometheus/statsd_exporter can be scraped as usual Prometheus target
according to https://docs.victoriametrics.com/#how-to-scrape-prometheus-exporters-such-as-node-exporter ).

Adding support for statsd data ingestion protocol into VictoriaMetrics makes sense only if it provides
significant advantages over the existing statsd servers, while has no significant drawbacks comparing
to existing statsd servers.

The main advantage of statsd server built into VictoriaMetrics and vmagent - getting rid of additional statsd server.
The main drawback is non-trivial and inconvenient streaming aggregation configs, which must be used for the ingested statsd metrics (
see https://docs.victoriametrics.com/stream-aggregation/ ). These configs are incompatible with the configs for standalone statsd servers.
So you need to manually translate configs of the used statsd server to stream aggregation configs when migrating
from standalone statsd server to statsd server built into VictoriaMetrics (or vmagent).

Another important drawback is that it is very easy to shoot yourself in the foot when using built-in statsd server
with the -statsd.disableAggregationEnforcement command-line flag or with improperly configured streaming aggregation.
In this case the ingested statsd metrics will be stored to VictoriaMetrics as is without any aggregation.
This may result in high CPU usage during data ingestion, high disk space usage for storing all the unaggregated
statsd metrics and high CPU usage during querying, since all the unaggregated metrics must be read, unpacked and processed
during querying.

P.S. Built-in statsd server can be added to VictoriaMetrics and vmagent after figuring out more ergonomic
specialized configuration for aggregating of statsd metrics. The main requirements for this configuration:

- easy to write, read and update (ideally it should work out of the box for most cases without additional configuration)
- hard to misconfigure (e.g. hard to shoot yourself in the foot)

It would be great if this configuration will be compatible with the configuration of the most widely used statsd server.

In the mean time it is recommended continue using external statsd server.

Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6265
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5053
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5052
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/206
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4600
2024-07-03 23:51:56 +02:00

286 lines
9.5 KiB
Go

package common
import (
"flag"
"fmt"
"sync"
"sync/atomic"
"github.com/VictoriaMetrics/VictoriaMetrics/app/vmstorage"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/flagutil"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/logger"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/procutil"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/storage"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/streamaggr"
"github.com/VictoriaMetrics/metrics"
)
var (
streamAggrConfig = flag.String("streamAggr.config", "", "Optional path to file with stream aggregation config. "+
"See https://docs.victoriametrics.com/stream-aggregation/ . "+
"See also -streamAggr.keepInput, -streamAggr.dropInput and -streamAggr.dedupInterval")
streamAggrKeepInput = flag.Bool("streamAggr.keepInput", false, "Whether to keep all the input samples after the aggregation with -streamAggr.config. "+
"By default, only aggregated samples are dropped, while the remaining samples are stored in the database. "+
"See also -streamAggr.dropInput and https://docs.victoriametrics.com/stream-aggregation/")
streamAggrDropInput = flag.Bool("streamAggr.dropInput", false, "Whether to drop all the input samples after the aggregation with -streamAggr.config. "+
"By default, only aggregated samples are dropped, while the remaining samples are stored in the database. "+
"See also -streamAggr.keepInput and https://docs.victoriametrics.com/stream-aggregation/")
streamAggrDedupInterval = flag.Duration("streamAggr.dedupInterval", 0, "Input samples are de-duplicated with this interval before optional aggregation with -streamAggr.config . "+
"See also -streamAggr.dropInputLabels and -dedup.minScrapeInterval and https://docs.victoriametrics.com/stream-aggregation/#deduplication")
streamAggrDropInputLabels = flagutil.NewArrayString("streamAggr.dropInputLabels", "An optional list of labels to drop from samples "+
"before stream de-duplication and aggregation . See https://docs.victoriametrics.com/stream-aggregation/#dropping-unneeded-labels")
streamAggrIgnoreOldSamples = flag.Bool("streamAggr.ignoreOldSamples", false, "Whether to ignore input samples with old timestamps outside the current aggregation interval. "+
"See https://docs.victoriametrics.com/stream-aggregation/#ignoring-old-samples")
streamAggrIgnoreFirstIntervals = flag.Int("streamAggr.ignoreFirstIntervals", 0, "Number of aggregation intervals to skip after the start. Increase this value if you observe incorrect aggregation results after restarts. It could be caused by receiving unordered delayed data from clients pushing data into the database. "+
"See https://docs.victoriametrics.com/stream-aggregation/#ignore-aggregation-intervals-on-start")
)
var (
saCfgReloaderStopCh chan struct{}
saCfgReloaderWG sync.WaitGroup
saCfgReloads = metrics.NewCounter(`vminsert_streamagg_config_reloads_total`)
saCfgReloadErr = metrics.NewCounter(`vminsert_streamagg_config_reloads_errors_total`)
saCfgSuccess = metrics.NewGauge(`vminsert_streamagg_config_last_reload_successful`, nil)
saCfgTimestamp = metrics.NewCounter(`vminsert_streamagg_config_last_reload_success_timestamp_seconds`)
sasGlobal atomic.Pointer[streamaggr.Aggregators]
deduplicator *streamaggr.Deduplicator
)
// CheckStreamAggrConfig checks config pointed by -stramaggr.config
func CheckStreamAggrConfig() error {
if *streamAggrConfig == "" {
return nil
}
pushNoop := func(_ []prompbmarshal.TimeSeries) {}
opts := streamaggr.Options{
DedupInterval: *streamAggrDedupInterval,
DropInputLabels: *streamAggrDropInputLabels,
IgnoreOldSamples: *streamAggrIgnoreOldSamples,
IgnoreFirstIntervals: *streamAggrIgnoreFirstIntervals,
Alias: "global",
}
sas, err := streamaggr.LoadFromFile(*streamAggrConfig, pushNoop, opts)
if err != nil {
return fmt.Errorf("error when loading -streamAggr.config=%q: %w", *streamAggrConfig, err)
}
sas.MustStop()
return nil
}
// InitStreamAggr must be called after flag.Parse and before using the common package.
//
// MustStopStreamAggr must be called when stream aggr is no longer needed.
func InitStreamAggr() {
saCfgReloaderStopCh = make(chan struct{})
rwctx := "global"
if *streamAggrConfig == "" {
if *streamAggrDedupInterval > 0 {
deduplicator = streamaggr.NewDeduplicator(pushAggregateSeries, *streamAggrDedupInterval, *streamAggrDropInputLabels, rwctx)
}
return
}
sighupCh := procutil.NewSighupChan()
opts := streamaggr.Options{
DedupInterval: *streamAggrDedupInterval,
DropInputLabels: *streamAggrDropInputLabels,
IgnoreOldSamples: *streamAggrIgnoreOldSamples,
IgnoreFirstIntervals: *streamAggrIgnoreFirstIntervals,
Alias: rwctx,
}
sas, err := streamaggr.LoadFromFile(*streamAggrConfig, pushAggregateSeries, opts)
if err != nil {
logger.Fatalf("cannot load -streamAggr.config=%q: %s", *streamAggrConfig, err)
}
sasGlobal.Store(sas)
saCfgSuccess.Set(1)
saCfgTimestamp.Set(fasttime.UnixTimestamp())
// Start config reloader.
saCfgReloaderWG.Add(1)
go func() {
defer saCfgReloaderWG.Done()
for {
select {
case <-sighupCh:
case <-saCfgReloaderStopCh:
return
}
reloadStreamAggrConfig()
}
}()
}
func reloadStreamAggrConfig() {
logger.Infof("reloading -streamAggr.config=%q", *streamAggrConfig)
saCfgReloads.Inc()
opts := streamaggr.Options{
DedupInterval: *streamAggrDedupInterval,
DropInputLabels: *streamAggrDropInputLabels,
IgnoreOldSamples: *streamAggrIgnoreOldSamples,
IgnoreFirstIntervals: *streamAggrIgnoreFirstIntervals,
Alias: "global",
}
sasNew, err := streamaggr.LoadFromFile(*streamAggrConfig, pushAggregateSeries, opts)
if err != nil {
saCfgSuccess.Set(0)
saCfgReloadErr.Inc()
logger.Errorf("cannot reload -streamAggr.config=%q: use the previously loaded config; error: %s", *streamAggrConfig, err)
return
}
sas := sasGlobal.Load()
if !sasNew.Equal(sas) {
sasOld := sasGlobal.Swap(sasNew)
sasOld.MustStop()
logger.Infof("successfully reloaded stream aggregation config at -streamAggr.config=%q", *streamAggrConfig)
} else {
logger.Infof("nothing changed in -streamAggr.config=%q", *streamAggrConfig)
sasNew.MustStop()
}
saCfgSuccess.Set(1)
saCfgTimestamp.Set(fasttime.UnixTimestamp())
}
// MustStopStreamAggr stops stream aggregators.
func MustStopStreamAggr() {
close(saCfgReloaderStopCh)
saCfgReloaderWG.Wait()
sas := sasGlobal.Swap(nil)
sas.MustStop()
if deduplicator != nil {
deduplicator.MustStop()
deduplicator = nil
}
}
type streamAggrCtx struct {
mn storage.MetricName
tss []prompbmarshal.TimeSeries
labels []prompbmarshal.Label
samples []prompbmarshal.Sample
buf []byte
}
func (ctx *streamAggrCtx) Reset() {
ctx.mn.Reset()
clear(ctx.tss)
ctx.tss = ctx.tss[:0]
clear(ctx.labels)
ctx.labels = ctx.labels[:0]
ctx.samples = ctx.samples[:0]
ctx.buf = ctx.buf[:0]
}
func (ctx *streamAggrCtx) push(mrs []storage.MetricRow, matchIdxs []byte) []byte {
mn := &ctx.mn
tss := ctx.tss
labels := ctx.labels
samples := ctx.samples
buf := ctx.buf
tssLen := len(tss)
for _, mr := range mrs {
if err := mn.UnmarshalRaw(mr.MetricNameRaw); err != nil {
logger.Panicf("BUG: cannot unmarshal recently marshaled MetricName: %s", err)
}
labelsLen := len(labels)
bufLen := len(buf)
buf = append(buf, mn.MetricGroup...)
metricGroup := bytesutil.ToUnsafeString(buf[bufLen:])
labels = append(labels, prompbmarshal.Label{
Name: "__name__",
Value: metricGroup,
})
for _, tag := range mn.Tags {
bufLen = len(buf)
buf = append(buf, tag.Key...)
name := bytesutil.ToUnsafeString(buf[bufLen:])
bufLen = len(buf)
buf = append(buf, tag.Value...)
value := bytesutil.ToUnsafeString(buf[bufLen:])
labels = append(labels, prompbmarshal.Label{
Name: name,
Value: value,
})
}
samplesLen := len(samples)
samples = append(samples, prompbmarshal.Sample{
Timestamp: mr.Timestamp,
Value: mr.Value,
})
tss = append(tss, prompbmarshal.TimeSeries{
Labels: labels[labelsLen:],
Samples: samples[samplesLen:],
})
}
ctx.tss = tss
ctx.labels = labels
ctx.samples = samples
ctx.buf = buf
tss = tss[tssLen:]
sas := sasGlobal.Load()
if sas.IsEnabled() {
matchIdxs = sas.Push(tss, matchIdxs)
} else if deduplicator != nil {
matchIdxs = bytesutil.ResizeNoCopyMayOverallocate(matchIdxs, len(tss))
for i := range matchIdxs {
matchIdxs[i] = 1
}
deduplicator.Push(tss)
}
ctx.Reset()
return matchIdxs
}
func pushAggregateSeries(tss []prompbmarshal.TimeSeries) {
currentTimestamp := int64(fasttime.UnixTimestamp()) * 1000
var ctx InsertCtx
ctx.Reset(len(tss))
ctx.skipStreamAggr = true
for _, ts := range tss {
labels := ts.Labels
ctx.Labels = ctx.Labels[:0]
for _, label := range labels {
name := label.Name
if name == "__name__" {
name = ""
}
ctx.AddLabel(name, label.Value)
}
value := ts.Samples[0].Value
if err := ctx.WriteDataPoint(nil, ctx.Labels, currentTimestamp, value); err != nil {
logger.Errorf("cannot store aggregate series: %s", err)
// Do not continue pushing the remaining samples, since it is likely they will return the same error.
return
}
}
// There is no need in limiting the number of concurrent calls to vmstorage.AddRows() here,
// since the number of concurrent pushAggregateSeries() calls should be already limited by lib/streamaggr.
if err := vmstorage.AddRows(ctx.mrs); err != nil {
logger.Errorf("cannot flush aggregate series: %s", err)
}
}