VictoriaMetrics/lib/streamaggr/histogram_bucket.go
Aliaksandr Valialkin 28a9e92b5e
lib/streamaggr: huge pile of changes
- Reduce memory usage by up to 5x when de-duplicating samples across big number of time series.
- Reduce memory usage by up to 5x when aggregating across big number of output time series.
- Add lib/promutils.LabelsCompressor, which is going to be used by other VictoriaMetrics components
  for reducing memory usage for marshaled []prompbmarshal.Label.
- Add `dedup_interval` option at aggregation config, which allows setting individual
  deduplication intervals per each aggregation.
- Add `keep_metric_names` option at aggregation config, which allows keeping the original
  metric names in the output samples.
- Add `unique_samples` output, which counts the number of unique sample values.
- Add `increase_prometheus` and `total_prometheus` outputs, which ignore the first sample
  per each newly encountered time series.
- Use 64-bit hashes instead of marshaled labels as map keys when calculating `count_series` output.
  This makes obsolete https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5579
- Expose various metrics, which may help debugging stream aggregation:
  - vm_streamaggr_dedup_state_size_bytes - the size of data structures responsible for deduplication
  - vm_streamaggr_dedup_state_items_count - the number of items in the deduplication data structures
  - vm_streamaggr_labels_compressor_size_bytes - the size of labels compressor data structures
  - vm_streamaggr_labels_compressor_items_count - the number of entries in the labels compressor
  - vm_streamaggr_flush_duration_seconds - a histogram, which shows the duration of stream aggregation flushes
  - vm_streamaggr_dedup_flush_duration_seconds - a histogram, which shows the duration of deduplication flushes
  - vm_streamaggr_flush_timeouts_total - counter for timed out stream aggregation flushes,
    which took longer than the configured interval
  - vm_streamaggr_dedup_flush_timeouts_total - counter for timed out deduplication flushes,
    which took longer than the configured dedup_interval
- Actualize docs/stream-aggregation.md

The memory usage reduction increases CPU usage during stream aggregation by up to 30%.

This commit is based on https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5850
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5898
2024-03-02 02:42:50 +02:00

117 lines
2.7 KiB
Go

package streamaggr
import (
"math"
"strings"
"sync"
"time"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime"
"github.com/VictoriaMetrics/metrics"
)
// histogramBucketAggrState calculates output=histogram_bucket, e.g. VictoriaMetrics histogram over input samples.
type histogramBucketAggrState struct {
m sync.Map
stalenessSecs uint64
}
type histogramBucketStateValue struct {
mu sync.Mutex
h metrics.Histogram
deleteDeadline uint64
deleted bool
}
func newHistogramBucketAggrState(stalenessInterval time.Duration) *histogramBucketAggrState {
stalenessSecs := roundDurationToSecs(stalenessInterval)
return &histogramBucketAggrState{
stalenessSecs: stalenessSecs,
}
}
func (as *histogramBucketAggrState) pushSamples(samples []pushSample) {
currentTime := fasttime.UnixTimestamp()
deleteDeadline := currentTime + as.stalenessSecs
for i := range samples {
s := &samples[i]
outputKey := getOutputKey(s.key)
again:
v, ok := as.m.Load(outputKey)
if !ok {
// The entry is missing in the map. Try creating it.
v = &histogramBucketStateValue{}
outputKey = strings.Clone(outputKey)
vNew, loaded := as.m.LoadOrStore(outputKey, v)
if loaded {
// Use the entry created by a concurrent goroutine.
v = vNew
}
}
sv := v.(*histogramBucketStateValue)
sv.mu.Lock()
deleted := sv.deleted
if !deleted {
sv.h.Update(s.value)
sv.deleteDeadline = deleteDeadline
}
sv.mu.Unlock()
if deleted {
// The entry has been deleted by the concurrent call to appendSeriesForFlush
// Try obtaining and updating the entry again.
goto again
}
}
}
func (as *histogramBucketAggrState) removeOldEntries(currentTime uint64) {
m := &as.m
m.Range(func(k, v interface{}) bool {
sv := v.(*histogramBucketStateValue)
sv.mu.Lock()
deleted := currentTime > sv.deleteDeadline
if deleted {
// Mark the current entry as deleted
sv.deleted = deleted
}
sv.mu.Unlock()
if deleted {
m.Delete(k)
}
return true
})
}
func (as *histogramBucketAggrState) appendSeriesForFlush(ctx *flushCtx) {
currentTime := fasttime.UnixTimestamp()
currentTimeMsec := int64(currentTime) * 1000
as.removeOldEntries(currentTime)
m := &as.m
m.Range(func(k, v interface{}) bool {
sv := v.(*histogramBucketStateValue)
sv.mu.Lock()
if !sv.deleted {
key := k.(string)
sv.h.VisitNonZeroBuckets(func(vmrange string, count uint64) {
ctx.appendSeriesWithExtraLabel(key, "histogram_bucket", currentTimeMsec, float64(count), "vmrange", vmrange)
})
}
sv.mu.Unlock()
return true
})
}
func roundDurationToSecs(d time.Duration) uint64 {
if d < 0 {
return 0
}
secs := d.Seconds()
return uint64(math.Ceil(secs))
}