VictoriaMetrics/lib/streamaggr/avg.go
Roman Khavronenko 7cb894a777
lib/streamaggr: reduce number of inuse objects (#6402)
The main change is getting rid of interning of sample key. It was
discovered that for cases with many unique time series aggregated by
vmagent interned keys could grow up to hundreds of millions of objects.
This has negative impact on the following aspects:
1. It slows down garbage collection cycles, as GC has to scan all inuse
objects periodically. The higher is the number of inuse objects, the
longer it takes/the more CPU it takes.
2. It slows down the hot path of samples aggregation where each key
needs to be looked up in the map first.

The change makes code more fragile, but suppose to provide performance
optimization for heavy-loaded vmagents with stream aggregation enabled.

---------

Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2024-06-07 15:45:52 +02:00

85 lines
1.8 KiB
Go

package streamaggr
import (
"strings"
"sync"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime"
)
// avgAggrState calculates output=avg, e.g. the average value over input samples.
type avgAggrState struct {
m sync.Map
}
type avgStateValue struct {
mu sync.Mutex
sum float64
count int64
deleted bool
}
func newAvgAggrState() *avgAggrState {
return &avgAggrState{}
}
func (as *avgAggrState) 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.
v = &avgStateValue{
sum: s.value,
count: 1,
}
vNew, loaded := as.m.LoadOrStore(strings.Clone(outputKey), v)
if !loaded {
// The entry has been successfully stored
continue
}
// Update the entry created by a concurrent goroutine.
v = vNew
}
sv := v.(*avgStateValue)
sv.mu.Lock()
deleted := sv.deleted
if !deleted {
sv.sum += s.value
sv.count++
}
sv.mu.Unlock()
if deleted {
// The entry has been deleted by the concurrent call to flushState
// Try obtaining and updating the entry again.
goto again
}
}
}
func (as *avgAggrState) flushState(ctx *flushCtx, resetState bool) {
currentTimeMsec := int64(fasttime.UnixTimestamp()) * 1000
m := &as.m
m.Range(func(k, v interface{}) bool {
if resetState {
// Atomically delete the entry from the map, so new entry is created for the next flush.
m.Delete(k)
}
sv := v.(*avgStateValue)
sv.mu.Lock()
avg := sv.sum / float64(sv.count)
if resetState {
// 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)
ctx.appendSeries(key, "avg", currentTimeMsec, avg)
return true
})
}