mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
synced 2025-01-10 15:14:09 +00:00
28a9e92b5e
- 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
94 lines
2.3 KiB
Go
94 lines
2.3 KiB
Go
package streamaggr
|
|
|
|
import (
|
|
"strconv"
|
|
"strings"
|
|
"sync"
|
|
|
|
"github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil"
|
|
"github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime"
|
|
"github.com/valyala/histogram"
|
|
)
|
|
|
|
// quantilesAggrState calculates output=quantiles, e.g. the the given quantiles over the input samples.
|
|
type quantilesAggrState struct {
|
|
m sync.Map
|
|
|
|
phis []float64
|
|
}
|
|
|
|
type quantilesStateValue struct {
|
|
mu sync.Mutex
|
|
h *histogram.Fast
|
|
deleted bool
|
|
}
|
|
|
|
func newQuantilesAggrState(phis []float64) *quantilesAggrState {
|
|
return &quantilesAggrState{
|
|
phis: phis,
|
|
}
|
|
}
|
|
|
|
func (as *quantilesAggrState) pushSamples(samples []pushSample) {
|
|
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.
|
|
h := histogram.GetFast()
|
|
v = &quantilesStateValue{
|
|
h: h,
|
|
}
|
|
outputKey = strings.Clone(outputKey)
|
|
vNew, loaded := as.m.LoadOrStore(outputKey, v)
|
|
if loaded {
|
|
// Use the entry created by a concurrent goroutine.
|
|
histogram.PutFast(h)
|
|
v = vNew
|
|
}
|
|
}
|
|
sv := v.(*quantilesStateValue)
|
|
sv.mu.Lock()
|
|
deleted := sv.deleted
|
|
if !deleted {
|
|
sv.h.Update(s.value)
|
|
}
|
|
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 *quantilesAggrState) appendSeriesForFlush(ctx *flushCtx) {
|
|
currentTimeMsec := int64(fasttime.UnixTimestamp()) * 1000
|
|
m := &as.m
|
|
phis := as.phis
|
|
var quantiles []float64
|
|
var b []byte
|
|
m.Range(func(k, v interface{}) bool {
|
|
// Atomically delete the entry from the map, so new entry is created for the next flush.
|
|
m.Delete(k)
|
|
|
|
sv := v.(*quantilesStateValue)
|
|
sv.mu.Lock()
|
|
quantiles = sv.h.Quantiles(quantiles[:0], phis)
|
|
histogram.PutFast(sv.h)
|
|
// Mark the entry as deleted, so it won't be updated anymore by concurrent pushSample() calls.
|
|
sv.deleted = true
|
|
sv.mu.Unlock()
|
|
|
|
key := k.(string)
|
|
for i, quantile := range quantiles {
|
|
b = strconv.AppendFloat(b[:0], phis[i], 'g', -1, 64)
|
|
phiStr := bytesutil.InternBytes(b)
|
|
ctx.appendSeriesWithExtraLabel(key, "quantiles", currentTimeMsec, quantile, "quantile", phiStr)
|
|
}
|
|
return true
|
|
})
|
|
}
|