mirror of
https://github.com/prometheus/prometheus.git
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31eb3b286d
Previously, BenchmarkRangeQuery would run each case with three data sizes (1, 10, 100) and three range lengths (1, 100, 1000) for nine variations. With 36 cases, running with `-count=6` to get dependable results, would take 40-50 minutes in total. This PR removes the middle option in both dimensions, thus shrinking to four variations and about 20 minutes to run everything. Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
671 lines
18 KiB
Go
671 lines
18 KiB
Go
// Copyright 2015 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package promql_test
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import (
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"context"
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"fmt"
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"strconv"
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"strings"
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"testing"
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"time"
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"github.com/stretchr/testify/require"
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"github.com/prometheus/prometheus/model/histogram"
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"github.com/prometheus/prometheus/model/labels"
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"github.com/prometheus/prometheus/promql"
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"github.com/prometheus/prometheus/promql/parser"
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"github.com/prometheus/prometheus/promql/promqltest"
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"github.com/prometheus/prometheus/storage"
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"github.com/prometheus/prometheus/tsdb/tsdbutil"
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"github.com/prometheus/prometheus/util/teststorage"
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)
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func setupRangeQueryTestData(stor *teststorage.TestStorage, _ *promql.Engine, interval, numIntervals int) error {
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ctx := context.Background()
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metrics := []labels.Labels{}
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// Generating test series: a_X, b_X, and h_X, where X can take values of one, ten, or hundred,
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// representing the number of series each metric name contains.
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// Metric a_X and b_X are simple metrics where h_X is a histogram.
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// These metrics will have data for all test time range
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metrics = append(metrics, labels.FromStrings("__name__", "a_one"))
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metrics = append(metrics, labels.FromStrings("__name__", "b_one"))
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for j := 0; j < 10; j++ {
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metrics = append(metrics, labels.FromStrings("__name__", "h_one", "le", strconv.Itoa(j)))
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}
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metrics = append(metrics, labels.FromStrings("__name__", "h_one", "le", "+Inf"))
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for i := 0; i < 10; i++ {
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metrics = append(metrics, labels.FromStrings("__name__", "a_ten", "l", strconv.Itoa(i)))
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metrics = append(metrics, labels.FromStrings("__name__", "b_ten", "l", strconv.Itoa(i)))
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for j := 0; j < 10; j++ {
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metrics = append(metrics, labels.FromStrings("__name__", "h_ten", "l", strconv.Itoa(i), "le", strconv.Itoa(j)))
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}
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metrics = append(metrics, labels.FromStrings("__name__", "h_ten", "l", strconv.Itoa(i), "le", "+Inf"))
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}
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for i := 0; i < 100; i++ {
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metrics = append(metrics, labels.FromStrings("__name__", "a_hundred", "l", strconv.Itoa(i)))
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metrics = append(metrics, labels.FromStrings("__name__", "b_hundred", "l", strconv.Itoa(i)))
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for j := 0; j < 10; j++ {
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metrics = append(metrics, labels.FromStrings("__name__", "h_hundred", "l", strconv.Itoa(i), "le", strconv.Itoa(j)))
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}
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metrics = append(metrics, labels.FromStrings("__name__", "h_hundred", "l", strconv.Itoa(i), "le", "+Inf"))
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}
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refs := make([]storage.SeriesRef, len(metrics))
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// Number points for each different label value of "l" for the sparse series
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pointsPerSparseSeries := numIntervals / 50
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for s := 0; s < numIntervals; s++ {
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a := stor.Appender(context.Background())
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ts := int64(s * interval)
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for i, metric := range metrics {
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ref, _ := a.Append(refs[i], metric, ts, float64(s)+float64(i)/float64(len(metrics)))
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refs[i] = ref
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}
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// Generating a sparse time series: each label value of "l" will contain data only for
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// pointsPerSparseSeries points
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metric := labels.FromStrings("__name__", "sparse", "l", strconv.Itoa(s/pointsPerSparseSeries))
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_, err := a.Append(0, metric, ts, float64(s)/float64(len(metrics)))
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if err != nil {
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return err
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}
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if err := a.Commit(); err != nil {
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return err
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}
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}
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stor.ForceHeadMMap() // Ensure we have at most one head chunk for every series.
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stor.Compact(ctx)
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return nil
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}
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type benchCase struct {
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expr string
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steps int
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}
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func rangeQueryCases() []benchCase {
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cases := []benchCase{
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// Plain retrieval.
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{
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expr: "a_X",
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},
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// Simple rate.
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{
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expr: "rate(a_X[1m])",
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},
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{
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expr: "rate(a_X[1m])",
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steps: 10000,
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},
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{
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expr: "rate(sparse[1m])",
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steps: 10000,
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},
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// Holt-Winters and long ranges.
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{
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expr: "double_exponential_smoothing(a_X[1d], 0.3, 0.3)",
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},
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{
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expr: "changes(a_X[1d])",
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},
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{
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expr: "rate(a_X[1d])",
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},
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{
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expr: "absent_over_time(a_X[1d])",
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},
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// Unary operators.
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{
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expr: "-a_X",
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},
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// Binary operators.
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{
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expr: "a_X - b_X",
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},
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{
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expr: "a_X - b_X",
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steps: 10000,
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},
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{
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expr: "a_X and b_X{l=~'.*[0-4]$'}",
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},
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{
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expr: "a_X or b_X{l=~'.*[0-4]$'}",
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},
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{
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expr: "a_X unless b_X{l=~'.*[0-4]$'}",
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},
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{
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expr: "a_X and b_X{l='notfound'}",
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},
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// Simple functions.
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{
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expr: "abs(a_X)",
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},
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{
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expr: "label_replace(a_X, 'l2', '$1', 'l', '(.*)')",
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},
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{
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expr: "label_join(a_X, 'l2', '-', 'l', 'l')",
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},
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// Simple aggregations.
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{
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expr: "sum(a_X)",
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},
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{
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expr: "avg(a_X)",
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},
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{
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expr: "sum without (l)(h_X)",
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},
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{
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expr: "sum without (le)(h_X)",
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},
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{
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expr: "sum by (l)(h_X)",
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},
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{
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expr: "sum by (le)(h_X)",
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},
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{
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expr: "count_values('value', h_X)",
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steps: 100,
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},
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{
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expr: "topk(1, a_X)",
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},
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{
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expr: "topk(5, a_X)",
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},
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{
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expr: "limitk(1, a_X)",
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},
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{
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expr: "limitk(5, a_X)",
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},
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{
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expr: "limit_ratio(0.1, a_X)",
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},
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{
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expr: "limit_ratio(0.5, a_X)",
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},
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{
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expr: "limit_ratio(-0.5, a_X)",
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},
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// Combinations.
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{
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expr: "rate(a_X[1m]) + rate(b_X[1m])",
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},
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{
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expr: "sum without (l)(rate(a_X[1m]))",
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},
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{
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expr: "sum without (l)(rate(a_X[1m])) / sum without (l)(rate(b_X[1m]))",
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},
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{
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expr: "histogram_quantile(0.9, rate(h_X[5m]))",
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},
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// Many-to-one join.
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{
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expr: "a_X + on(l) group_right a_one",
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},
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// Label compared to blank string.
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{
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expr: "count({__name__!=\"\"})",
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steps: 1,
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},
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{
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expr: "count({__name__!=\"\",l=\"\"})",
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steps: 1,
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},
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// Functions which have special handling inside eval()
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{
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expr: "timestamp(a_X)",
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},
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}
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// X in an expr will be replaced by different metric sizes.
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tmp := []benchCase{}
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for _, c := range cases {
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if !strings.Contains(c.expr, "X") {
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tmp = append(tmp, c)
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} else {
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tmp = append(tmp, benchCase{expr: strings.ReplaceAll(c.expr, "X", "one"), steps: c.steps})
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tmp = append(tmp, benchCase{expr: strings.ReplaceAll(c.expr, "X", "hundred"), steps: c.steps})
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}
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}
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cases = tmp
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// No step will be replaced by cases with the standard step.
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tmp = []benchCase{}
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for _, c := range cases {
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if c.steps != 0 {
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tmp = append(tmp, c)
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} else {
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tmp = append(tmp, benchCase{expr: c.expr, steps: 1})
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tmp = append(tmp, benchCase{expr: c.expr, steps: 1000})
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}
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}
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return tmp
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}
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func BenchmarkRangeQuery(b *testing.B) {
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stor := teststorage.New(b)
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stor.DisableCompactions() // Don't want auto-compaction disrupting timings.
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defer stor.Close()
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opts := promql.EngineOpts{
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Logger: nil,
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Reg: nil,
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MaxSamples: 50000000,
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Timeout: 100 * time.Second,
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}
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engine := promqltest.NewTestEngineWithOpts(b, opts)
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const interval = 10000 // 10s interval.
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// A day of data plus 10k steps.
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numIntervals := 8640 + 10000
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err := setupRangeQueryTestData(stor, engine, interval, numIntervals)
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if err != nil {
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b.Fatal(err)
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}
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cases := rangeQueryCases()
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for _, c := range cases {
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name := fmt.Sprintf("expr=%s,steps=%d", c.expr, c.steps)
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b.Run(name, func(b *testing.B) {
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ctx := context.Background()
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b.ReportAllocs()
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for i := 0; i < b.N; i++ {
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qry, err := engine.NewRangeQuery(
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ctx, stor, nil, c.expr,
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time.Unix(int64((numIntervals-c.steps)*10), 0),
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time.Unix(int64(numIntervals*10), 0), time.Second*10)
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if err != nil {
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b.Fatal(err)
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}
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res := qry.Exec(ctx)
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if res.Err != nil {
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b.Fatal(res.Err)
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}
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qry.Close()
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}
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})
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}
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}
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func BenchmarkNativeHistograms(b *testing.B) {
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testStorage := teststorage.New(b)
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defer testStorage.Close()
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app := testStorage.Appender(context.TODO())
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if err := generateNativeHistogramSeries(app, 3000); err != nil {
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b.Fatal(err)
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}
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if err := app.Commit(); err != nil {
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b.Fatal(err)
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}
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start := time.Unix(0, 0)
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end := start.Add(2 * time.Hour)
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step := time.Second * 30
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cases := []struct {
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name string
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query string
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}{
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{
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name: "sum",
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query: "sum(native_histogram_series)",
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},
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{
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name: "sum rate with short rate interval",
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query: "sum(rate(native_histogram_series[2m]))",
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},
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{
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name: "sum rate with long rate interval",
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query: "sum(rate(native_histogram_series[20m]))",
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},
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{
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name: "histogram_count with short rate interval",
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query: "histogram_count(sum(rate(native_histogram_series[2m])))",
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},
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{
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name: "histogram_count with long rate interval",
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query: "histogram_count(sum(rate(native_histogram_series[20m])))",
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},
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}
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opts := promql.EngineOpts{
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Logger: nil,
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Reg: nil,
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MaxSamples: 50000000,
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Timeout: 100 * time.Second,
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EnableAtModifier: true,
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EnableNegativeOffset: true,
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}
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b.ResetTimer()
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b.ReportAllocs()
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for _, tc := range cases {
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b.Run(tc.name, func(b *testing.B) {
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ng := promqltest.NewTestEngineWithOpts(b, opts)
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for i := 0; i < b.N; i++ {
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qry, err := ng.NewRangeQuery(context.Background(), testStorage, nil, tc.query, start, end, step)
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if err != nil {
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b.Fatal(err)
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}
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if result := qry.Exec(context.Background()); result.Err != nil {
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b.Fatal(result.Err)
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}
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}
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})
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}
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}
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func BenchmarkNativeHistogramsCustomBuckets(b *testing.B) {
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testStorage := teststorage.New(b)
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defer testStorage.Close()
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app := testStorage.Appender(context.TODO())
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if err := generateNativeHistogramCustomBucketsSeries(app, 3000); err != nil {
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b.Fatal(err)
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}
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if err := app.Commit(); err != nil {
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b.Fatal(err)
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}
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start := time.Unix(0, 0)
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end := start.Add(2 * time.Hour)
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step := time.Second * 30
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cases := []struct {
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name string
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query string
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}{
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{
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name: "sum",
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query: "sum(native_histogram_custom_bucket_series)",
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},
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{
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name: "sum rate with short rate interval",
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query: "sum(rate(native_histogram_custom_bucket_series[2m]))",
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},
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{
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name: "sum rate with long rate interval",
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query: "sum(rate(native_histogram_custom_bucket_series[20m]))",
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},
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{
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name: "histogram_count with short rate interval",
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query: "histogram_count(sum(rate(native_histogram_custom_bucket_series[2m])))",
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},
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{
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name: "histogram_count with long rate interval",
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query: "histogram_count(sum(rate(native_histogram_custom_bucket_series[20m])))",
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},
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}
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opts := promql.EngineOpts{
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Logger: nil,
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Reg: nil,
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MaxSamples: 50000000,
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Timeout: 100 * time.Second,
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EnableAtModifier: true,
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EnableNegativeOffset: true,
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}
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b.ResetTimer()
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b.ReportAllocs()
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for _, tc := range cases {
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b.Run(tc.name, func(b *testing.B) {
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ng := promqltest.NewTestEngineWithOpts(b, opts)
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for i := 0; i < b.N; i++ {
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qry, err := ng.NewRangeQuery(context.Background(), testStorage, nil, tc.query, start, end, step)
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if err != nil {
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b.Fatal(err)
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}
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if result := qry.Exec(context.Background()); result.Err != nil {
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b.Fatal(result.Err)
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}
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}
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})
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}
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}
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func BenchmarkInfoFunction(b *testing.B) {
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// Initialize test storage and generate test series data.
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testStorage := teststorage.New(b)
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defer testStorage.Close()
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start := time.Unix(0, 0)
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end := start.Add(2 * time.Hour)
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step := 30 * time.Second
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// Generate time series data for the benchmark.
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generateInfoFunctionTestSeries(b, testStorage, 100, 2000, 3600)
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// Define test cases with queries to benchmark.
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cases := []struct {
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name string
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query string
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}{
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{
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name: "Joining info metrics with other metrics with group_left example 1",
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query: "rate(http_server_request_duration_seconds_count[2m]) * on (job, instance) group_left (k8s_cluster_name) target_info{k8s_cluster_name=\"us-east\"}",
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},
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{
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name: "Joining info metrics with other metrics with info() example 1",
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query: `info(rate(http_server_request_duration_seconds_count[2m]), {k8s_cluster_name="us-east"})`,
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},
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{
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name: "Joining info metrics with other metrics with group_left example 2",
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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)",
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},
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{
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name: "Joining info metrics with other metrics with info() example 2",
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query: `sum by (k8s_cluster_name, http_status_code) (info(rate(http_server_request_duration_seconds_count[2m]), {k8s_cluster_name=~".+"}))`,
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},
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}
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// Benchmark each query type.
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for _, tc := range cases {
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// Initialize the PromQL engine once for all benchmarks.
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opts := promql.EngineOpts{
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Logger: nil,
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Reg: nil,
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MaxSamples: 50000000,
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Timeout: 100 * time.Second,
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EnableAtModifier: true,
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EnableNegativeOffset: true,
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}
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engine := promql.NewEngine(opts)
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b.Run(tc.name, func(b *testing.B) {
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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b.StopTimer() // Stop the timer to exclude setup time.
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qry, err := engine.NewRangeQuery(context.Background(), testStorage, nil, tc.query, start, end, step)
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require.NoError(b, err)
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b.StartTimer()
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|
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.ForceHeadMMap() // Ensure we have at most one head chunk for every series.
|
|
stor.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 generateNativeHistogramCustomBucketsSeries(app storage.Appender, numSeries int) error {
|
|
commonLabels := []string{labels.MetricName, "native_histogram_custom_bucket_series", "foo", "bar"}
|
|
series := make([][]*histogram.Histogram, numSeries)
|
|
for i := range series {
|
|
series[i] = tsdbutil.GenerateTestCustomBucketsHistograms(2000)
|
|
}
|
|
|
|
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 _, 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)
|
|
}
|
|
})
|
|
}
|
|
}
|