VictoriaMetrics/lib/streamaggr/dedup.go
Aliaksandr Valialkin d269a95da3
lib/streamaggr: use strings.Clone() instead of bytesutil.InternString() for creating series key in dedupAggr
Our internal testing shows that this reduces GC overhead when deduplicating tens of millions of active series.
2024-06-10 16:08:47 +02:00

217 lines
4.3 KiB
Go

package streamaggr
import (
"strings"
"sync"
"sync/atomic"
"unsafe"
"github.com/cespare/xxhash/v2"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil"
)
const dedupAggrShardsCount = 128
type dedupAggr struct {
shards []dedupAggrShard
}
type dedupAggrShard struct {
dedupAggrShardNopad
// The padding prevents false sharing on widespread platforms with
// 128 mod (cache line size) = 0 .
_ [128 - unsafe.Sizeof(dedupAggrShardNopad{})%128]byte
}
type dedupAggrShardNopad struct {
mu sync.Mutex
m map[string]*dedupAggrSample
sizeBytes atomic.Uint64
itemsCount atomic.Uint64
}
type dedupAggrSample struct {
value float64
timestamp int64
}
func newDedupAggr() *dedupAggr {
shards := make([]dedupAggrShard, dedupAggrShardsCount)
return &dedupAggr{
shards: shards,
}
}
func (da *dedupAggr) sizeBytes() uint64 {
n := uint64(unsafe.Sizeof(*da))
for i := range da.shards {
n += da.shards[i].sizeBytes.Load()
}
return n
}
func (da *dedupAggr) itemsCount() uint64 {
n := uint64(0)
for i := range da.shards {
n += da.shards[i].itemsCount.Load()
}
return n
}
func (da *dedupAggr) pushSamples(samples []pushSample) {
pss := getPerShardSamples()
shards := pss.shards
for _, sample := range samples {
h := xxhash.Sum64(bytesutil.ToUnsafeBytes(sample.key))
idx := h % uint64(len(shards))
shards[idx] = append(shards[idx], sample)
}
for i, shardSamples := range shards {
if len(shardSamples) == 0 {
continue
}
da.shards[i].pushSamples(shardSamples)
}
putPerShardSamples(pss)
}
func getDedupFlushCtx() *dedupFlushCtx {
v := dedupFlushCtxPool.Get()
if v == nil {
return &dedupFlushCtx{}
}
return v.(*dedupFlushCtx)
}
func putDedupFlushCtx(ctx *dedupFlushCtx) {
ctx.reset()
dedupFlushCtxPool.Put(ctx)
}
var dedupFlushCtxPool sync.Pool
type dedupFlushCtx struct {
samples []pushSample
}
func (ctx *dedupFlushCtx) reset() {
clear(ctx.samples)
ctx.samples = ctx.samples[:0]
}
func (da *dedupAggr) flush(f func(samples []pushSample)) {
var wg sync.WaitGroup
for i := range da.shards {
flushConcurrencyCh <- struct{}{}
wg.Add(1)
go func(shard *dedupAggrShard) {
defer func() {
<-flushConcurrencyCh
wg.Done()
}()
ctx := getDedupFlushCtx()
shard.flush(ctx, f)
putDedupFlushCtx(ctx)
}(&da.shards[i])
}
wg.Wait()
}
type perShardSamples struct {
shards [][]pushSample
}
func (pss *perShardSamples) reset() {
shards := pss.shards
for i, shardSamples := range shards {
if len(shardSamples) > 0 {
clear(shardSamples)
shards[i] = shardSamples[:0]
}
}
}
func getPerShardSamples() *perShardSamples {
v := perShardSamplesPool.Get()
if v == nil {
return &perShardSamples{
shards: make([][]pushSample, dedupAggrShardsCount),
}
}
return v.(*perShardSamples)
}
func putPerShardSamples(pss *perShardSamples) {
pss.reset()
perShardSamplesPool.Put(pss)
}
var perShardSamplesPool sync.Pool
func (das *dedupAggrShard) pushSamples(samples []pushSample) {
das.mu.Lock()
defer das.mu.Unlock()
m := das.m
if m == nil {
m = make(map[string]*dedupAggrSample, len(samples))
das.m = m
}
for _, sample := range samples {
s, ok := m[sample.key]
if !ok {
key := strings.Clone(sample.key)
m[key] = &dedupAggrSample{
value: sample.value,
timestamp: sample.timestamp,
}
das.itemsCount.Add(1)
das.sizeBytes.Add(uint64(len(key)) + uint64(unsafe.Sizeof(key)+unsafe.Sizeof(s)))
continue
}
// Update the existing value according to logic described at https://docs.victoriametrics.com/#deduplication
if sample.timestamp > s.timestamp || (sample.timestamp == s.timestamp && sample.value > s.value) {
s.value = sample.value
s.timestamp = sample.timestamp
}
}
}
func (das *dedupAggrShard) flush(ctx *dedupFlushCtx, f func(samples []pushSample)) {
das.mu.Lock()
m := das.m
if len(m) > 0 {
das.m = make(map[string]*dedupAggrSample, len(m))
das.sizeBytes.Store(0)
das.itemsCount.Store(0)
}
das.mu.Unlock()
if len(m) == 0 {
return
}
dstSamples := ctx.samples
for key, s := range m {
dstSamples = append(dstSamples, pushSample{
key: key,
value: s.value,
timestamp: s.timestamp,
})
// Limit the number of samples per each flush in order to limit memory usage.
if len(dstSamples) >= 10_000 {
f(dstSamples)
clear(dstSamples)
dstSamples = dstSamples[:0]
}
}
f(dstSamples)
ctx.samples = dstSamples
}