prometheus/promql/bench_test.go

583 lines
16 KiB
Go

// Copyright 2015 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package promql_test
import (
"context"
"fmt"
"strconv"
"strings"
"testing"
"time"
"github.com/stretchr/testify/require"
"github.com/prometheus/prometheus/model/histogram"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/promql"
"github.com/prometheus/prometheus/promql/parser"
"github.com/prometheus/prometheus/promql/promqltest"
"github.com/prometheus/prometheus/storage"
"github.com/prometheus/prometheus/tsdb/tsdbutil"
"github.com/prometheus/prometheus/util/teststorage"
)
func setupRangeQueryTestData(stor *teststorage.TestStorage, _ *promql.Engine, interval, numIntervals int) error {
ctx := context.Background()
metrics := []labels.Labels{}
// Generating test series: a_X, b_X, and h_X, where X can take values of one, ten, or hundred,
// representing the number of series each metric name contains.
// Metric a_X and b_X are simple metrics where h_X is a histogram.
// These metrics will have data for all test time range
metrics = append(metrics, labels.FromStrings("__name__", "a_one"))
metrics = append(metrics, labels.FromStrings("__name__", "b_one"))
for j := 0; j < 10; j++ {
metrics = append(metrics, labels.FromStrings("__name__", "h_one", "le", strconv.Itoa(j)))
}
metrics = append(metrics, labels.FromStrings("__name__", "h_one", "le", "+Inf"))
for i := 0; i < 10; i++ {
metrics = append(metrics, labels.FromStrings("__name__", "a_ten", "l", strconv.Itoa(i)))
metrics = append(metrics, labels.FromStrings("__name__", "b_ten", "l", strconv.Itoa(i)))
for j := 0; j < 10; j++ {
metrics = append(metrics, labels.FromStrings("__name__", "h_ten", "l", strconv.Itoa(i), "le", strconv.Itoa(j)))
}
metrics = append(metrics, labels.FromStrings("__name__", "h_ten", "l", strconv.Itoa(i), "le", "+Inf"))
}
for i := 0; i < 100; i++ {
metrics = append(metrics, labels.FromStrings("__name__", "a_hundred", "l", strconv.Itoa(i)))
metrics = append(metrics, labels.FromStrings("__name__", "b_hundred", "l", strconv.Itoa(i)))
for j := 0; j < 10; j++ {
metrics = append(metrics, labels.FromStrings("__name__", "h_hundred", "l", strconv.Itoa(i), "le", strconv.Itoa(j)))
}
metrics = append(metrics, labels.FromStrings("__name__", "h_hundred", "l", strconv.Itoa(i), "le", "+Inf"))
}
refs := make([]storage.SeriesRef, len(metrics))
// Number points for each different label value of "l" for the sparse series
pointsPerSparseSeries := numIntervals / 50
for s := 0; s < numIntervals; s++ {
a := stor.Appender(context.Background())
ts := int64(s * interval)
for i, metric := range metrics {
ref, _ := a.Append(refs[i], metric, ts, float64(s)+float64(i)/float64(len(metrics)))
refs[i] = ref
}
// Generating a sparse time series: each label value of "l" will contain data only for
// pointsPerSparseSeries points
metric := labels.FromStrings("__name__", "sparse", "l", strconv.Itoa(s/pointsPerSparseSeries))
_, err := a.Append(0, metric, ts, float64(s)/float64(len(metrics)))
if err != nil {
return err
}
if err := a.Commit(); err != nil {
return err
}
}
stor.DB.ForceHeadMMap() // Ensure we have at most one head chunk for every series.
stor.DB.Compact(ctx)
return nil
}
type benchCase struct {
expr string
steps int
}
func rangeQueryCases() []benchCase {
cases := []benchCase{
// Plain retrieval.
{
expr: "a_X",
},
// Simple rate.
{
expr: "rate(a_X[1m])",
},
{
expr: "rate(a_X[1m])",
steps: 10000,
},
{
expr: "rate(sparse[1m])",
steps: 10000,
},
// Holt-Winters and long ranges.
{
expr: "holt_winters(a_X[1d], 0.3, 0.3)",
},
{
expr: "changes(a_X[1d])",
},
{
expr: "rate(a_X[1d])",
},
{
expr: "absent_over_time(a_X[1d])",
},
// Unary operators.
{
expr: "-a_X",
},
// Binary operators.
{
expr: "a_X - b_X",
},
{
expr: "a_X - b_X",
steps: 10000,
},
{
expr: "a_X and b_X{l=~'.*[0-4]$'}",
},
{
expr: "a_X or b_X{l=~'.*[0-4]$'}",
},
{
expr: "a_X unless b_X{l=~'.*[0-4]$'}",
},
{
expr: "a_X and b_X{l='notfound'}",
},
// Simple functions.
{
expr: "abs(a_X)",
},
{
expr: "label_replace(a_X, 'l2', '$1', 'l', '(.*)')",
},
{
expr: "label_join(a_X, 'l2', '-', 'l', 'l')",
},
// Simple aggregations.
{
expr: "sum(a_X)",
},
{
expr: "avg(a_X)",
},
{
expr: "sum without (l)(h_X)",
},
{
expr: "sum without (le)(h_X)",
},
{
expr: "sum by (l)(h_X)",
},
{
expr: "sum by (le)(h_X)",
},
{
expr: "count_values('value', h_X)",
steps: 100,
},
{
expr: "topk(1, a_X)",
},
{
expr: "topk(5, a_X)",
},
{
expr: "limitk(1, a_X)",
},
{
expr: "limitk(5, a_X)",
},
{
expr: "limit_ratio(0.1, a_X)",
},
{
expr: "limit_ratio(0.5, a_X)",
},
{
expr: "limit_ratio(-0.5, a_X)",
},
// Combinations.
{
expr: "rate(a_X[1m]) + rate(b_X[1m])",
},
{
expr: "sum without (l)(rate(a_X[1m]))",
},
{
expr: "sum without (l)(rate(a_X[1m])) / sum without (l)(rate(b_X[1m]))",
},
{
expr: "histogram_quantile(0.9, rate(h_X[5m]))",
},
// Many-to-one join.
{
expr: "a_X + on(l) group_right a_one",
},
// Label compared to blank string.
{
expr: "count({__name__!=\"\"})",
steps: 1,
},
{
expr: "count({__name__!=\"\",l=\"\"})",
steps: 1,
},
// Functions which have special handling inside eval()
{
expr: "timestamp(a_X)",
},
}
// X in an expr will be replaced by different metric sizes.
tmp := []benchCase{}
for _, c := range cases {
if !strings.Contains(c.expr, "X") {
tmp = append(tmp, c)
} else {
tmp = append(tmp, benchCase{expr: strings.ReplaceAll(c.expr, "X", "one"), steps: c.steps})
tmp = append(tmp, benchCase{expr: strings.ReplaceAll(c.expr, "X", "ten"), steps: c.steps})
tmp = append(tmp, benchCase{expr: strings.ReplaceAll(c.expr, "X", "hundred"), steps: c.steps})
}
}
cases = tmp
// No step will be replaced by cases with the standard step.
tmp = []benchCase{}
for _, c := range cases {
if c.steps != 0 {
tmp = append(tmp, c)
} else {
tmp = append(tmp, benchCase{expr: c.expr, steps: 1})
tmp = append(tmp, benchCase{expr: c.expr, steps: 100})
tmp = append(tmp, benchCase{expr: c.expr, steps: 1000})
}
}
return tmp
}
func BenchmarkRangeQuery(b *testing.B) {
stor := teststorage.New(b)
stor.DB.DisableCompactions() // Don't want auto-compaction disrupting timings.
defer stor.Close()
opts := promql.EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 50000000,
Timeout: 100 * time.Second,
}
engine := promqltest.NewTestEngineWithOpts(b, opts)
const interval = 10000 // 10s interval.
// A day of data plus 10k steps.
numIntervals := 8640 + 10000
err := setupRangeQueryTestData(stor, engine, interval, numIntervals)
if err != nil {
b.Fatal(err)
}
cases := rangeQueryCases()
for _, c := range cases {
name := fmt.Sprintf("expr=%s,steps=%d", c.expr, c.steps)
b.Run(name, func(b *testing.B) {
ctx := context.Background()
b.ReportAllocs()
for i := 0; i < b.N; i++ {
qry, err := engine.NewRangeQuery(
ctx, stor, nil, c.expr,
time.Unix(int64((numIntervals-c.steps)*10), 0),
time.Unix(int64(numIntervals*10), 0), time.Second*10)
if err != nil {
b.Fatal(err)
}
res := qry.Exec(ctx)
if res.Err != nil {
b.Fatal(res.Err)
}
qry.Close()
}
})
}
}
func BenchmarkNativeHistograms(b *testing.B) {
testStorage := teststorage.New(b)
defer testStorage.Close()
app := testStorage.Appender(context.TODO())
if err := generateNativeHistogramSeries(app, 3000); err != nil {
b.Fatal(err)
}
if err := app.Commit(); err != nil {
b.Fatal(err)
}
start := time.Unix(0, 0)
end := start.Add(2 * time.Hour)
step := time.Second * 30
cases := []struct {
name string
query string
}{
{
name: "sum",
query: "sum(native_histogram_series)",
},
{
name: "sum rate with short rate interval",
query: "sum(rate(native_histogram_series[2m]))",
},
{
name: "sum rate with long rate interval",
query: "sum(rate(native_histogram_series[20m]))",
},
{
name: "histogram_count with short rate interval",
query: "histogram_count(sum(rate(native_histogram_series[2m])))",
},
{
name: "histogram_count with long rate interval",
query: "histogram_count(sum(rate(native_histogram_series[20m])))",
},
}
opts := promql.EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 50000000,
Timeout: 100 * time.Second,
EnableAtModifier: true,
EnableNegativeOffset: true,
}
b.ResetTimer()
b.ReportAllocs()
for _, tc := range cases {
b.Run(tc.name, func(b *testing.B) {
ng := promqltest.NewTestEngineWithOpts(b, opts)
for i := 0; i < b.N; i++ {
qry, err := ng.NewRangeQuery(context.Background(), testStorage, nil, tc.query, start, end, step)
if err != nil {
b.Fatal(err)
}
if result := qry.Exec(context.Background()); result.Err != nil {
b.Fatal(result.Err)
}
}
})
}
}
func BenchmarkInfoFunction(b *testing.B) {
// Initialize test storage and generate test series data.
testStorage := teststorage.New(b)
defer testStorage.Close()
start := time.Unix(0, 0)
end := start.Add(2 * time.Hour)
step := 30 * time.Second
// Generate time series data for the benchmark.
generateInfoFunctionTestSeries(b, testStorage, 100, 2000, 3600)
// Define test cases with queries to benchmark.
cases := []struct {
name string
query string
}{
{
name: "Joining info metrics with other metrics with group_left example 1",
query: "rate(http_server_request_duration_seconds_count[2m]) * on (job, instance) group_left (k8s_cluster_name) target_info{k8s_cluster_name=\"us-east\"}",
},
{
name: "Joining info metrics with other metrics with info() example 1",
query: `info(rate(http_server_request_duration_seconds_count[2m]), {k8s_cluster_name="us-east"})`,
},
{
name: "Joining info metrics with other metrics with group_left example 2",
query: "sum by (k8s_cluster_name, http_status_code) (rate(http_server_request_duration_seconds_count[2m]) * on (job, instance) group_left (k8s_cluster_name) target_info)",
},
{
name: "Joining info metrics with other metrics with info() example 2",
query: `sum by (k8s_cluster_name, http_status_code) (info(rate(http_server_request_duration_seconds_count[2m]), {k8s_cluster_name=~".+"}))`,
},
}
// Benchmark each query type.
for _, tc := range cases {
// Initialize the PromQL engine once for all benchmarks.
opts := promql.EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 50000000,
Timeout: 100 * time.Second,
EnableAtModifier: true,
EnableNegativeOffset: true,
}
engine := promql.NewEngine(opts)
b.Run(tc.name, func(b *testing.B) {
b.ResetTimer()
for i := 0; i < b.N; i++ {
b.StopTimer() // Stop the timer to exclude setup time.
qry, err := engine.NewRangeQuery(context.Background(), testStorage, nil, tc.query, start, end, step)
require.NoError(b, err)
b.StartTimer()
result := qry.Exec(context.Background())
require.NoError(b, result.Err)
}
})
}
// Report allocations.
b.ReportAllocs()
}
// Helper function to generate target_info and http_server_request_duration_seconds_count series for info function benchmarking.
func generateInfoFunctionTestSeries(tb testing.TB, stor *teststorage.TestStorage, infoSeriesNum, interval, numIntervals int) {
tb.Helper()
ctx := context.Background()
statusCodes := []string{"200", "400", "500"}
// Generate target_info metrics with instance and job labels, and k8s_cluster_name label.
// Generate http_server_request_duration_seconds_count metrics with instance and job labels, and http_status_code label.
// the classic target_info metrics is gauge type.
metrics := make([]labels.Labels, 0, infoSeriesNum+len(statusCodes))
for i := 0; i < infoSeriesNum; i++ {
clusterName := "us-east"
if i >= infoSeriesNum/2 {
clusterName = "eu-south"
}
metrics = append(metrics, labels.FromStrings(
"__name__", "target_info",
"instance", "instance"+strconv.Itoa(i),
"job", "job"+strconv.Itoa(i),
"k8s_cluster_name", clusterName,
))
}
for _, statusCode := range statusCodes {
metrics = append(metrics, labels.FromStrings(
"__name__", "http_server_request_duration_seconds_count",
"instance", "instance0",
"job", "job0",
"http_status_code", statusCode,
))
}
// Append the generated metrics and samples to the storage.
refs := make([]storage.SeriesRef, len(metrics))
for i := 0; i < numIntervals; i++ {
a := stor.Appender(context.Background())
ts := int64(i * interval)
for j, metric := range metrics[:infoSeriesNum] {
ref, _ := a.Append(refs[j], metric, ts, 1)
refs[j] = ref
}
for j, metric := range metrics[infoSeriesNum:] {
ref, _ := a.Append(refs[j+infoSeriesNum], metric, ts, float64(i))
refs[j+infoSeriesNum] = ref
}
require.NoError(tb, a.Commit())
}
stor.DB.ForceHeadMMap() // Ensure we have at most one head chunk for every series.
stor.DB.Compact(ctx)
}
func generateNativeHistogramSeries(app storage.Appender, numSeries int) error {
commonLabels := []string{labels.MetricName, "native_histogram_series", "foo", "bar"}
series := make([][]*histogram.Histogram, numSeries)
for i := range series {
series[i] = tsdbutil.GenerateTestHistograms(2000)
}
higherSchemaHist := &histogram.Histogram{
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: -5, Length: 2}, // -5 -4
{Offset: 2, Length: 3}, // -1 0 1
{Offset: 2, Length: 2}, // 4 5
},
PositiveBuckets: []int64{1, 2, -2, 1, -1, 0, 3},
Count: 13,
}
for sid, histograms := range series {
seriesLabels := labels.FromStrings(append(commonLabels, "h", strconv.Itoa(sid))...)
for i := range histograms {
ts := time.Unix(int64(i*15), 0).UnixMilli()
if i == 0 {
// Inject a histogram with a higher schema.
if _, err := app.AppendHistogram(0, seriesLabels, ts, higherSchemaHist, nil); err != nil {
return err
}
}
if _, err := app.AppendHistogram(0, seriesLabels, ts, histograms[i], nil); err != nil {
return err
}
}
}
return nil
}
func BenchmarkParser(b *testing.B) {
cases := []string{
"a",
"metric",
"1",
"1 >= bool 1",
"1 + 2/(3*1)",
"foo or bar",
"foo and bar unless baz or qux",
"bar + on(foo) bla / on(baz, buz) group_right(test) blub",
"foo / ignoring(test,blub) group_left(blub) bar",
"foo - ignoring(test,blub) group_right(bar,foo) bar",
`foo{a="b", foo!="bar", test=~"test", bar!~"baz"}`,
`min_over_time(rate(foo{bar="baz"}[2s])[5m:])[4m:3s]`,
"sum without(and, by, avg, count, alert, annotations)(some_metric) [30m:10s]",
}
errCases := []string{
"(",
"}",
"1 or 1",
"1 or on(bar) foo",
"foo unless on(bar) group_left(baz) bar",
"test[5d] OFFSET 10s [10m:5s]",
}
for _, c := range cases {
b.Run(c, func(b *testing.B) {
b.ReportAllocs()
for i := 0; i < b.N; i++ {
parser.ParseExpr(c)
}
})
}
for _, c := range errCases {
name := fmt.Sprintf("%s (should fail)", c)
b.Run(name, func(b *testing.B) {
b.ReportAllocs()
for i := 0; i < b.N; i++ {
parser.ParseExpr(c)
}
})
}
}