Files

377 lines
10 KiB
Go

package remotewrite
import (
"fmt"
"math"
"reflect"
"strconv"
"sync/atomic"
"testing"
"time"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/consistenthash"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/fs"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/persistentqueue"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompb"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/promrelabel"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/prometheus"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/streamaggr"
"github.com/VictoriaMetrics/metrics"
)
func TestGetLabelsHash_Distribution(t *testing.T) {
f := func(bucketsCount int) {
t.Helper()
// Distribute itemsCount hashes returned by getLabelsHash() across bucketsCount buckets.
itemsCount := 1_000 * bucketsCount
m := make([]int, bucketsCount)
var labels []prompb.Label
for i := range itemsCount {
labels = append(labels[:0], prompb.Label{
Name: "__name__",
Value: fmt.Sprintf("some_name_%d", i),
})
for j := range 10 {
labels = append(labels, prompb.Label{
Name: fmt.Sprintf("label_%d", j),
Value: fmt.Sprintf("value_%d_%d", i, j),
})
}
h := getLabelsHash(labels)
m[h%uint64(bucketsCount)]++
}
// Verify that the distribution is even
expectedItemsPerBucket := itemsCount / bucketsCount
for _, n := range m {
if math.Abs(1-float64(n)/float64(expectedItemsPerBucket)) > 0.04 {
t.Fatalf("unexpected items in the bucket for %d buckets; got %d; want around %d", bucketsCount, n, expectedItemsPerBucket)
}
}
}
f(2)
f(3)
f(4)
f(5)
f(10)
}
func TestRemoteWriteContext_TryPushTimeSeries(t *testing.T) {
f := func(streamAggrConfig, relabelConfig string, enableWindows bool, dedupInterval time.Duration, keepInput, dropInput bool, input string, expectedRowsPushedAfterRelabel, expectedPushedSample int) {
t.Helper()
perURLRelabel, err := promrelabel.ParseRelabelConfigsData([]byte(relabelConfig))
if err != nil {
t.Fatalf("cannot load relabel configs: %s", err)
}
rcs := &relabelConfigs{
perURL: []*promrelabel.ParsedConfigs{
perURLRelabel,
},
}
allRelabelConfigs.Store(rcs)
path := "fast-queue-write-test"
fs.MustRemoveDir(path)
fq := persistentqueue.MustOpenFastQueue(path, "test", 100, 0, false)
defer fs.MustRemoveDir(path)
defer fq.MustClose()
pss := make([]*pendingSeries, 1)
isVMProto := &atomic.Bool{}
isVMProto.Store(true)
pss[0] = newPendingSeries(fq, isVMProto, 0, 100)
rwctx := &remoteWriteCtx{
idx: 0,
streamAggrKeepInput: keepInput,
streamAggrDropInput: dropInput,
pss: pss,
rowsPushedAfterRelabel: metrics.GetOrCreateCounter(`foo`),
rowsDroppedByRelabel: metrics.GetOrCreateCounter(`bar`),
}
defer metrics.UnregisterAllMetrics()
if dedupInterval > 0 {
rwctx.deduplicator = streamaggr.NewDeduplicator(nil, enableWindows, dedupInterval, nil, "dedup-global")
}
if streamAggrConfig != "" {
pushNoop := func(_ []prompb.TimeSeries) {}
opts := streamaggr.Options{
EnableWindows: enableWindows,
}
sas, err := streamaggr.LoadFromData([]byte(streamAggrConfig), pushNoop, &opts, "global")
if err != nil {
t.Fatalf("cannot load streamaggr configs: %s", err)
}
defer sas.MustStop()
rwctx.sas.Store(sas)
}
offsetMsecs := time.Now().UnixMilli()
inputTss := prometheus.MustParsePromMetrics(input, offsetMsecs)
expectedTss := make([]prompb.TimeSeries, len(inputTss))
// check inputTss is not modified after TryPushTimeSeries
copy(expectedTss, inputTss)
if !rwctx.TryPushTimeSeries(inputTss, false) {
t.Fatalf("cannot push samples to rwctx")
}
if int(rwctx.rowsPushedAfterRelabel.Get()) != expectedRowsPushedAfterRelabel {
t.Fatalf("unexpected number of rows after relabel; got %d; want %d", rwctx.rowsPushedAfterRelabel.Get(), expectedRowsPushedAfterRelabel)
}
if len(pss[0].wr.tss) != expectedPushedSample {
t.Fatalf("unexpected number of pushed samples; got %d; want %d", len(pss[0].wr.tss), expectedPushedSample)
}
if !reflect.DeepEqual(expectedTss, inputTss) {
t.Fatalf("unexpected samples;\ngot\n%v\nwant\n%v", inputTss, expectedTss)
}
}
// relabeling
f(``, `
- action: keep
source_labels: [env]
regex: "dev"
`, false, 0, false, false, `
metric{env="dev"} 10
metric{env="bar"} 20
metric{env="dev"} 15
metric{env="bar"} 25
`, 2, 2)
// relabeling + aggregation
f(`
- match: '{env="dev"}'
interval: 1m
outputs: [sum_samples]
`, `
- action: keep
source_labels: [env]
regex: ".*"
`, false, 0, false, false, `
metric{env="dev"} 10
metric{env="bar"} 20
metric{env="dev"} 15
metric{env="bar"} 25
`, 4, 2)
// aggregation + keepInput
f(`
- match: '{env="dev"}'
interval: 1m
outputs: [sum_samples]
`, ``, false, 0, true, false, `
metric{env="dev"} 10
metric{env="bar"} 20
metric{env="dev"} 15
metric{env="bar"} 25
`, 4, 4)
// aggregation + dropInput
f(`
- match: '{env="dev"}'
interval: 1m
outputs: [sum_samples]
`, ``, false, 0, false, true, `
metric{env="dev"} 10
metric{env="bar"} 20
metric{env="dev"} 15
metric{env="bar"} 25
`, 4, 0)
// aggregation + keepInput + dropInput
f(`
- match: '{env="dev"}'
interval: 1m
outputs: [sum_samples]
`, ``, false, 0, true, true, `
metric{env="dev"} 10
metric{env="bar"} 20
metric{env="bar"} 25
`, 3, 1)
// aggregation + deduplication
f(``, ``, true, time.Hour, false, false, `
metric{env="dev"} 10
metric{env="foo"} 20
metric{env="dev"} 15
metric{env="foo"} 25
`, 4, 0)
}
func TestShardAmountRemoteWriteCtx(t *testing.T) {
// 1. distribute 100000 series to n nodes.
// 2. remove the last node from healthy list.
// 3. distribute the same 10000 series to (n-1) node again.
// 4. check active time series change rate:
// change rate must < (3/total nodes). e.g. +30% if 10 you have 10 nodes.
f := func(remoteWriteCount int, healthyIdx []int, replicas int) {
t.Helper()
defer func() {
rwctxsGlobal = nil
rwctxsGlobalIdx = nil
rwctxConsistentHashGlobal = nil
}()
rwctxsGlobal = make([]*remoteWriteCtx, remoteWriteCount)
rwctxsGlobalIdx = make([]int, remoteWriteCount)
rwctxs := make([]*remoteWriteCtx, 0, len(healthyIdx))
for i := range remoteWriteCount {
rwCtx := &remoteWriteCtx{
idx: i,
}
rwctxsGlobalIdx[i] = i
if i >= len(healthyIdx) {
rwctxsGlobal[i] = rwCtx
continue
}
hIdx := healthyIdx[i]
if hIdx != i {
rwctxs = append(rwctxs, &remoteWriteCtx{
idx: hIdx,
})
} else {
rwctxs = append(rwctxs, rwCtx)
}
rwctxsGlobal[i] = rwCtx
}
seriesCount := 100000
// build 1000000 series
tssBlock := make([]prompb.TimeSeries, 0, seriesCount)
for i := range seriesCount {
tssBlock = append(tssBlock, prompb.TimeSeries{
Labels: []prompb.Label{
{
Name: "label",
Value: strconv.Itoa(i),
},
},
Samples: []prompb.Sample{
{
Timestamp: 0,
Value: 0,
},
},
})
}
// build consistent hash for x remote write context
// build active time series set
nodes := make([]string, 0, remoteWriteCount)
activeTimeSeriesByNodes := make([]map[string]struct{}, remoteWriteCount)
for i := range remoteWriteCount {
nodes = append(nodes, fmt.Sprintf("node%d", i))
activeTimeSeriesByNodes[i] = make(map[string]struct{})
}
rwctxConsistentHashGlobal = consistenthash.NewConsistentHash(nodes, 0)
// create shards
x := getTSSShards(len(rwctxs))
shards := x.shards
// execute
shardAmountRemoteWriteCtx(tssBlock, shards, rwctxs, replicas)
for i, nodeIdx := range healthyIdx {
for _, ts := range shards[i] {
// add it to node[nodeIdx]'s active time series
activeTimeSeriesByNodes[nodeIdx][prompb.LabelsToString(ts.Labels)] = struct{}{}
}
}
totalActiveTimeSeries := 0
for _, activeTimeSeries := range activeTimeSeriesByNodes {
totalActiveTimeSeries += len(activeTimeSeries)
}
avgActiveTimeSeries1 := totalActiveTimeSeries / remoteWriteCount
putTSSShards(x)
// removed last node
rwctxs = rwctxs[:len(rwctxs)-1]
healthyIdx = healthyIdx[:len(healthyIdx)-1]
x = getTSSShards(len(rwctxs))
shards = x.shards
// execute
shardAmountRemoteWriteCtx(tssBlock, shards, rwctxs, replicas)
for i, nodeIdx := range healthyIdx {
for _, ts := range shards[i] {
// add it to node[nodeIdx]'s active time series
activeTimeSeriesByNodes[nodeIdx][prompb.LabelsToString(ts.Labels)] = struct{}{}
}
}
totalActiveTimeSeries = 0
for _, activeTimeSeries := range activeTimeSeriesByNodes {
totalActiveTimeSeries += len(activeTimeSeries)
}
avgActiveTimeSeries2 := totalActiveTimeSeries / remoteWriteCount
changed := math.Abs(float64(avgActiveTimeSeries2-avgActiveTimeSeries1) / float64(avgActiveTimeSeries1))
threshold := 3 / float64(remoteWriteCount)
if changed >= threshold {
t.Fatalf("average active time series before: %d, after: %d, changed: %.2f. threshold: %.2f", avgActiveTimeSeries1, avgActiveTimeSeries2, changed, threshold)
}
}
f(5, []int{0, 1, 2, 3, 4}, 1)
f(5, []int{0, 1, 2, 3, 4}, 2)
f(10, []int{0, 1, 2, 3, 4, 5, 6, 7, 9}, 1)
f(10, []int{0, 1, 2, 3, 4, 5, 6, 7, 9}, 3)
}
func TestCalculateHealthyRwctxIdx(t *testing.T) {
f := func(total int, healthyIdx []int, unhealthyIdx []int) {
t.Helper()
healthyMap := make(map[int]bool)
for _, idx := range healthyIdx {
healthyMap[idx] = true
}
rwctxsGlobal = make([]*remoteWriteCtx, total)
rwctxsGlobalIdx = make([]int, total)
rwctxs := make([]*remoteWriteCtx, 0, len(healthyIdx))
for i := range rwctxsGlobal {
rwctx := &remoteWriteCtx{idx: i}
rwctxsGlobal[i] = rwctx
if healthyMap[i] {
rwctxs = append(rwctxs, rwctx)
}
rwctxsGlobalIdx[i] = i
}
gotHealthyIdx, gotUnhealthyIdx := calculateHealthyRwctxIdx(rwctxs)
if !reflect.DeepEqual(healthyIdx, gotHealthyIdx) {
t.Errorf("calculateHealthyRwctxIdx want healthyIdx = %v, got %v", healthyIdx, gotHealthyIdx)
}
if !reflect.DeepEqual(unhealthyIdx, gotUnhealthyIdx) {
t.Errorf("calculateHealthyRwctxIdx want unhealthyIdx = %v, got %v", unhealthyIdx, gotUnhealthyIdx)
}
}
f(5, []int{0, 1, 2, 3, 4}, nil)
f(5, []int{0, 1, 2, 4}, []int{3})
f(5, []int{2, 4}, []int{0, 1, 3})
f(5, []int{0, 2, 4}, []int{1, 3})
f(5, []int{}, []int{0, 1, 2, 3, 4})
f(5, []int{4}, []int{0, 1, 2, 3})
f(1, []int{0}, nil)
f(1, []int{}, []int{0})
}