2016-04-13 07:08:22 -07:00
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// Copyright 2016 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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2024-04-29 05:14:18 -07:00
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package promql_test
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2015-03-30 10:13:36 -07:00
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import (
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2017-10-04 12:04:15 -07:00
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"context"
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2019-10-09 17:06:53 -07:00
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"errors"
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2021-11-02 08:01:32 -07:00
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"fmt"
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2020-01-17 03:21:44 -08:00
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"sort"
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2024-05-13 08:36:19 -07:00
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"strconv"
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2024-05-15 12:58:56 -07:00
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"sync"
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2015-03-30 10:13:36 -07:00
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"testing"
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"time"
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2020-10-29 02:43:23 -07:00
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"github.com/stretchr/testify/require"
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2020-10-22 02:00:08 -07:00
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2021-12-06 04:49:18 -08:00
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"github.com/prometheus/prometheus/model/histogram"
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2021-11-08 06:23:17 -08:00
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"github.com/prometheus/prometheus/model/labels"
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"github.com/prometheus/prometheus/model/timestamp"
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2024-04-29 05:14:18 -07:00
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"github.com/prometheus/prometheus/promql"
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2020-02-03 08:32:23 -08:00
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"github.com/prometheus/prometheus/promql/parser"
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2023-09-14 09:57:31 -07:00
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"github.com/prometheus/prometheus/promql/parser/posrange"
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2024-04-29 05:14:18 -07:00
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"github.com/prometheus/prometheus/promql/promqltest"
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2018-02-15 04:08:00 -08:00
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"github.com/prometheus/prometheus/storage"
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2023-09-14 09:57:31 -07:00
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"github.com/prometheus/prometheus/util/annotations"
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2023-02-10 03:39:33 -08:00
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"github.com/prometheus/prometheus/util/stats"
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2023-08-18 11:48:59 -07:00
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"github.com/prometheus/prometheus/util/teststorage"
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2023-04-16 05:13:31 -07:00
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"github.com/prometheus/prometheus/util/testutil"
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2015-03-30 10:13:36 -07:00
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)
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2024-04-29 05:14:18 -07:00
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const (
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env = "query execution"
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defaultLookbackDelta = 5 * time.Minute
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defaultEpsilon = 0.000001 // Relative error allowed for sample values.
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)
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2020-07-24 02:10:20 -07:00
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func TestMain(m *testing.M) {
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feat: add limitk() and limit_ratio() operators (#12503)
* rebase 2024-07-01, picks previous renaming to `limitk()` and `limit_ratio()`
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* gofumpt -d -extra
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* more lint fixes
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* more lint fixes+
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* put limitk() and limit_ratio() behind --enable-feature=promql-experimental-functions
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* EnableExperimentalFunctions for TestConcurrentRangeQueries() also
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* use testutil.RequireEqual to fix tests, WIP equivalent thingie for require.Contains
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* lint fix
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* moar linting
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* rebase 2024-06-19
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* re-add limit(2, metric) testing for N=2 common series subset
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* move `ratio = param` to default switch case, for better readability
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* gofumpt -d -extra util/testutil/cmp.go
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* early break when reaching k elems in limitk(), should have always been so (!)
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* small typo fix
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* no-change small break-loop rearrange for readability
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* remove IsNan(ratio) condition in switch-case, already handled as input validation
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* no-change adding some comments
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* no-change simplify fullMatrix() helper functions used for tests
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* add `limitk(-1, metric)` testcase, which is handled as any k < 1 case
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* engine_test.go: no-change create `requireCommonSeries() helper func (moving code into it) for readability
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* rebase 2024-06-21
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* engine_test.go: HAPPY NOW about its code -> reorg, create and use simpleRangeQuery() function, less lines and more readable ftW \o/
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* move limitk(), limit_ratio() testing to promql/promqltest/testdata/limit.test
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* remove stale leftover after moving tests from engine_test.go to testdata/
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* fix flaky `limit_ratio(0.5, ...)` test case
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* Update promql/engine.go
Co-authored-by: Julius Volz <julius.volz@gmail.com>
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* Update promql/engine.go
Co-authored-by: Julius Volz <julius.volz@gmail.com>
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* Update promql/engine.go
Co-authored-by: Julius Volz <julius.volz@gmail.com>
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* fix AddRatioSample() implementation to use a single conditional (instead of switch/case + fallback return)
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* docs/querying/operators.md: document r < 0
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* add negative limit_ratio() example to docs/querying/examples.md
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* move more extensive docu examples to docs/querying/operators.md
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* typo
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* small docu fix for poor-mans-normality-check, add it to limit.test ;)
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* limit.test: expand "Poor man's normality check" to whole eval range
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* restore mistakenly removed existing small comment
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* expand poors-man-normality-check case(s)
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* Revert "expand poors-man-normality-check case(s)"
This reverts commit f69e1603b2ebe69c0a100197cfbcf6f81644b564, indeed too
flaky 0:)
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* remove humor from docs/querying/operators.md
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* fix signoff
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* add web/ui missing changes
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* expand limit_ratio test cases, cross-fingering they'll not be flaky
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* remove flaky test
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* add missing warnings.Merge(ws) in instant-query return shortcut
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* add missing LimitK||LimitRatio case to codemirror-promql/src/parser/parser.ts
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* fix ui-lint
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
* actually fix returned warnings :]
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
---------
Signed-off-by: JuanJo Ciarlante <juanjosec@gmail.com>
Co-authored-by: Julius Volz <julius.volz@gmail.com>
2024-07-03 13:18:57 -07:00
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// Enable experimental functions testing
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parser.EnableExperimentalFunctions = true
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2024-07-30 08:25:19 -07:00
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testutil.TolerantVerifyLeak(m)
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2020-07-24 02:10:20 -07:00
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}
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2015-09-23 02:06:51 -07:00
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func TestQueryConcurrency(t *testing.T) {
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2020-01-27 14:29:44 -08:00
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maxConcurrency := 10
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2024-05-07 09:14:22 -07:00
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queryTracker := promql.NewActiveQueryTracker(t.TempDir(), maxConcurrency, nil)
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2024-04-29 05:14:18 -07:00
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opts := promql.EngineOpts{
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2020-01-27 14:29:44 -08:00
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Logger: nil,
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Reg: nil,
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MaxSamples: 10,
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Timeout: 100 * time.Second,
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ActiveQueryTracker: queryTracker,
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2018-10-02 04:59:19 -07:00
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}
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2024-07-14 04:28:59 -07:00
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engine := promqltest.NewTestEngineWithOpts(t, opts)
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2018-01-09 08:44:23 -08:00
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2016-09-15 15:58:06 -07:00
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ctx, cancelCtx := context.WithCancel(context.Background())
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2024-05-07 09:14:22 -07:00
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t.Cleanup(cancelCtx)
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2015-04-30 15:49:19 -07:00
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block := make(chan struct{})
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processing := make(chan struct{})
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2021-11-27 04:45:06 -08:00
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done := make(chan int)
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2024-05-07 09:14:22 -07:00
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t.Cleanup(func() {
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close(done)
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})
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2015-08-10 05:21:24 -07:00
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f := func(context.Context) error {
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2021-11-27 04:45:06 -08:00
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select {
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case processing <- struct{}{}:
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case <-done:
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}
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select {
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case <-block:
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case <-done:
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}
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return nil
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2015-08-10 05:21:24 -07:00
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}
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2015-04-30 15:49:19 -07:00
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2024-05-15 12:58:56 -07:00
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var wg sync.WaitGroup
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2020-01-28 12:38:49 -08:00
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for i := 0; i < maxConcurrency; i++ {
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2024-04-29 05:14:18 -07:00
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q := engine.NewTestQuery(f)
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2024-05-15 12:58:56 -07:00
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wg.Add(1)
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go func() {
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q.Exec(ctx)
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wg.Done()
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}()
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2015-04-30 15:49:19 -07:00
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select {
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case <-processing:
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// Expected.
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2015-09-23 02:06:51 -07:00
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case <-time.After(20 * time.Millisecond):
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2021-09-13 12:19:20 -07:00
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require.Fail(t, "Query within concurrency threshold not being executed")
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2015-04-30 15:49:19 -07:00
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}
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}
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2024-04-29 05:14:18 -07:00
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q := engine.NewTestQuery(f)
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2024-05-15 12:58:56 -07:00
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wg.Add(1)
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go func() {
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q.Exec(ctx)
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wg.Done()
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}()
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2015-04-30 15:49:19 -07:00
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select {
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case <-processing:
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2021-09-13 12:19:20 -07:00
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require.Fail(t, "Query above concurrency threshold being executed")
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2015-09-23 02:06:51 -07:00
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case <-time.After(20 * time.Millisecond):
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2015-04-30 15:49:19 -07:00
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// Expected.
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}
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// Terminate a running query.
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block <- struct{}{}
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select {
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case <-processing:
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// Expected.
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2015-09-23 02:06:51 -07:00
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case <-time.After(20 * time.Millisecond):
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2021-09-13 12:19:20 -07:00
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require.Fail(t, "Query within concurrency threshold not being executed")
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2015-04-30 15:49:19 -07:00
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}
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// Terminate remaining queries.
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2020-01-28 12:38:49 -08:00
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for i := 0; i < maxConcurrency; i++ {
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2015-04-30 15:49:19 -07:00
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block <- struct{}{}
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}
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2024-05-15 12:58:56 -07:00
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wg.Wait()
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2015-04-30 15:49:19 -07:00
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}
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2024-04-29 05:14:18 -07:00
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// contextDone returns an error if the context was canceled or timed out.
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func contextDone(ctx context.Context, env string) error {
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if err := ctx.Err(); err != nil {
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switch {
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case errors.Is(err, context.Canceled):
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return promql.ErrQueryCanceled(env)
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case errors.Is(err, context.DeadlineExceeded):
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return promql.ErrQueryTimeout(env)
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default:
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return err
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}
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}
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return nil
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}
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2015-03-30 10:13:36 -07:00
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func TestQueryTimeout(t *testing.T) {
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2024-04-29 05:14:18 -07:00
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opts := promql.EngineOpts{
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Logger: nil,
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Reg: nil,
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MaxSamples: 10,
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Timeout: 5 * time.Millisecond,
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2018-10-02 04:59:19 -07:00
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}
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2024-07-14 04:28:59 -07:00
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engine := promqltest.NewTestEngineWithOpts(t, opts)
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2016-09-15 15:58:06 -07:00
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ctx, cancelCtx := context.WithCancel(context.Background())
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defer cancelCtx()
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2015-03-30 10:13:36 -07:00
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2024-04-29 05:14:18 -07:00
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query := engine.NewTestQuery(func(ctx context.Context) error {
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2020-01-22 02:09:31 -08:00
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time.Sleep(100 * time.Millisecond)
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2015-08-10 05:21:24 -07:00
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return contextDone(ctx, "test statement execution")
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2015-03-30 10:13:36 -07:00
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})
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promql: Allow per-query contexts.
For Weaveworks' Frankenstein, we need to support multitenancy. In
Frankenstein, we initially solved this without modifying the promql
package at all: we constructed a new promql.Engine for every
query and injected a storage implementation into that engine which would
be primed to only collect data for a given user.
This is problematic to upstream, however. Prometheus assumes that there
is only one engine: the query concurrency gate is part of the engine,
and the engine contains one central cancellable context to shut down all
queries. Also, creating a new engine for every query seems like overkill.
Thus, we want to be able to pass per-query contexts into a single engine.
This change gets rid of the promql.Engine's built-in base context and
allows passing in a per-query context instead. Central cancellation of
all queries is still possible by deriving all passed-in contexts from
one central one, but this is now the responsibility of the caller. The
central query context is now created in main() and passed into the
relevant components (web handler / API, rule manager).
In a next step, the per-query context would have to be passed to the
storage implementation, so that the storage can implement multi-tenancy
or other features based on the contextual information.
2016-09-15 04:52:50 -07:00
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res := query.Exec(ctx)
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2020-10-29 02:43:23 -07:00
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require.Error(t, res.Err, "expected timeout error but got none")
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2019-10-09 17:06:53 -07:00
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2024-04-29 05:14:18 -07:00
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var e promql.ErrQueryTimeout
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2023-12-07 03:35:01 -08:00
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require.ErrorAs(t, res.Err, &e, "expected timeout error but got: %s", res.Err)
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2015-03-30 10:13:36 -07:00
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}
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2024-04-29 05:14:18 -07:00
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const errQueryCanceled = promql.ErrQueryCanceled("test statement execution")
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2019-10-09 17:06:53 -07:00
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2015-03-30 10:13:36 -07:00
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func TestQueryCancel(t *testing.T) {
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2024-04-29 05:14:18 -07:00
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opts := promql.EngineOpts{
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2020-01-28 12:38:49 -08:00
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Logger: nil,
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Reg: nil,
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MaxSamples: 10,
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Timeout: 10 * time.Second,
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2018-10-02 04:59:19 -07:00
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}
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2024-07-14 04:28:59 -07:00
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engine := promqltest.NewTestEngineWithOpts(t, opts)
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2016-09-15 15:58:06 -07:00
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ctx, cancelCtx := context.WithCancel(context.Background())
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defer cancelCtx()
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2015-03-30 10:13:36 -07:00
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2015-08-10 05:21:24 -07:00
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// Cancel a running query before it completes.
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block := make(chan struct{})
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processing := make(chan struct{})
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2015-03-30 10:13:36 -07:00
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2024-04-29 05:14:18 -07:00
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query1 := engine.NewTestQuery(func(ctx context.Context) error {
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2015-08-10 05:21:24 -07:00
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processing <- struct{}{}
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<-block
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return contextDone(ctx, "test statement execution")
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})
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2015-04-29 02:08:56 -07:00
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2024-04-29 05:14:18 -07:00
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var res *promql.Result
|
2015-03-30 10:13:36 -07:00
|
|
|
|
|
|
|
go func() {
|
promql: Allow per-query contexts.
For Weaveworks' Frankenstein, we need to support multitenancy. In
Frankenstein, we initially solved this without modifying the promql
package at all: we constructed a new promql.Engine for every
query and injected a storage implementation into that engine which would
be primed to only collect data for a given user.
This is problematic to upstream, however. Prometheus assumes that there
is only one engine: the query concurrency gate is part of the engine,
and the engine contains one central cancellable context to shut down all
queries. Also, creating a new engine for every query seems like overkill.
Thus, we want to be able to pass per-query contexts into a single engine.
This change gets rid of the promql.Engine's built-in base context and
allows passing in a per-query context instead. Central cancellation of
all queries is still possible by deriving all passed-in contexts from
one central one, but this is now the responsibility of the caller. The
central query context is now created in main() and passed into the
relevant components (web handler / API, rule manager).
In a next step, the per-query context would have to be passed to the
storage implementation, so that the storage can implement multi-tenancy
or other features based on the contextual information.
2016-09-15 04:52:50 -07:00
|
|
|
res = query1.Exec(ctx)
|
2015-08-10 05:21:24 -07:00
|
|
|
processing <- struct{}{}
|
2015-03-30 10:13:36 -07:00
|
|
|
}()
|
2015-08-10 05:21:24 -07:00
|
|
|
|
|
|
|
<-processing
|
2015-03-30 10:13:36 -07:00
|
|
|
query1.Cancel()
|
2015-08-10 05:21:24 -07:00
|
|
|
block <- struct{}{}
|
|
|
|
<-processing
|
2015-03-30 10:13:36 -07:00
|
|
|
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Error(t, res.Err, "expected cancellation error for query1 but got none")
|
|
|
|
require.Equal(t, errQueryCanceled, res.Err)
|
2015-03-30 10:13:36 -07:00
|
|
|
|
2015-08-10 05:21:24 -07:00
|
|
|
// Canceling a query before starting it must have no effect.
|
2024-04-29 05:14:18 -07:00
|
|
|
query2 := engine.NewTestQuery(func(ctx context.Context) error {
|
2015-08-10 05:21:24 -07:00
|
|
|
return contextDone(ctx, "test statement execution")
|
|
|
|
})
|
|
|
|
|
2015-03-30 10:13:36 -07:00
|
|
|
query2.Cancel()
|
promql: Allow per-query contexts.
For Weaveworks' Frankenstein, we need to support multitenancy. In
Frankenstein, we initially solved this without modifying the promql
package at all: we constructed a new promql.Engine for every
query and injected a storage implementation into that engine which would
be primed to only collect data for a given user.
This is problematic to upstream, however. Prometheus assumes that there
is only one engine: the query concurrency gate is part of the engine,
and the engine contains one central cancellable context to shut down all
queries. Also, creating a new engine for every query seems like overkill.
Thus, we want to be able to pass per-query contexts into a single engine.
This change gets rid of the promql.Engine's built-in base context and
allows passing in a per-query context instead. Central cancellation of
all queries is still possible by deriving all passed-in contexts from
one central one, but this is now the responsibility of the caller. The
central query context is now created in main() and passed into the
relevant components (web handler / API, rule manager).
In a next step, the per-query context would have to be passed to the
storage implementation, so that the storage can implement multi-tenancy
or other features based on the contextual information.
2016-09-15 04:52:50 -07:00
|
|
|
res = query2.Exec(ctx)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.NoError(t, res.Err)
|
2015-03-30 10:13:36 -07:00
|
|
|
}
|
|
|
|
|
2018-02-15 04:08:00 -08:00
|
|
|
// errQuerier implements storage.Querier which always returns error.
|
|
|
|
type errQuerier struct {
|
|
|
|
err error
|
|
|
|
}
|
|
|
|
|
2023-09-12 03:37:38 -07:00
|
|
|
func (q *errQuerier) Select(context.Context, bool, *storage.SelectHints, ...*labels.Matcher) storage.SeriesSet {
|
2020-06-09 09:57:31 -07:00
|
|
|
return errSeriesSet{err: q.err}
|
2018-02-15 04:08:00 -08:00
|
|
|
}
|
2021-10-22 01:06:44 -07:00
|
|
|
|
2024-05-15 11:39:54 -07:00
|
|
|
func (*errQuerier) LabelValues(context.Context, string, *storage.LabelHints, ...*labels.Matcher) ([]string, annotations.Annotations, error) {
|
2021-02-09 09:38:35 -08:00
|
|
|
return nil, nil, nil
|
|
|
|
}
|
2021-10-22 01:06:44 -07:00
|
|
|
|
2024-05-15 11:39:54 -07:00
|
|
|
func (*errQuerier) LabelNames(context.Context, *storage.LabelHints, ...*labels.Matcher) ([]string, annotations.Annotations, error) {
|
2021-07-20 05:38:08 -07:00
|
|
|
return nil, nil, nil
|
|
|
|
}
|
|
|
|
func (*errQuerier) Close() error { return nil }
|
2018-02-15 04:08:00 -08:00
|
|
|
|
|
|
|
// errSeriesSet implements storage.SeriesSet which always returns error.
|
|
|
|
type errSeriesSet struct {
|
|
|
|
err error
|
|
|
|
}
|
|
|
|
|
2023-09-14 09:57:31 -07:00
|
|
|
func (errSeriesSet) Next() bool { return false }
|
|
|
|
func (errSeriesSet) At() storage.Series { return nil }
|
|
|
|
func (e errSeriesSet) Err() error { return e.err }
|
|
|
|
func (e errSeriesSet) Warnings() annotations.Annotations { return nil }
|
2018-02-15 04:08:00 -08:00
|
|
|
|
|
|
|
func TestQueryError(t *testing.T) {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts := promql.EngineOpts{
|
2020-01-28 12:38:49 -08:00
|
|
|
Logger: nil,
|
|
|
|
Reg: nil,
|
|
|
|
MaxSamples: 10,
|
|
|
|
Timeout: 10 * time.Second,
|
2018-10-02 04:59:19 -07:00
|
|
|
}
|
2024-07-14 04:28:59 -07:00
|
|
|
engine := promqltest.NewTestEngineWithOpts(t, opts)
|
2024-04-29 05:14:18 -07:00
|
|
|
errStorage := promql.ErrStorage{errors.New("storage error")}
|
2023-09-12 03:37:38 -07:00
|
|
|
queryable := storage.QueryableFunc(func(mint, maxt int64) (storage.Querier, error) {
|
2018-02-15 04:08:00 -08:00
|
|
|
return &errQuerier{err: errStorage}, nil
|
|
|
|
})
|
|
|
|
ctx, cancelCtx := context.WithCancel(context.Background())
|
|
|
|
defer cancelCtx()
|
|
|
|
|
2023-04-17 21:32:38 -07:00
|
|
|
vectorQuery, err := engine.NewInstantQuery(ctx, queryable, nil, "foo", time.Unix(1, 0))
|
2020-10-29 02:43:23 -07:00
|
|
|
require.NoError(t, err)
|
2019-10-09 17:06:53 -07:00
|
|
|
|
2018-02-15 04:08:00 -08:00
|
|
|
res := vectorQuery.Exec(ctx)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Error(t, res.Err, "expected error on failed select but got none")
|
2023-12-07 03:35:01 -08:00
|
|
|
require.ErrorIs(t, res.Err, errStorage, "expected error doesn't match")
|
2018-02-15 04:08:00 -08:00
|
|
|
|
2023-04-17 21:32:38 -07:00
|
|
|
matrixQuery, err := engine.NewInstantQuery(ctx, queryable, nil, "foo[1m]", time.Unix(1, 0))
|
2020-10-29 02:43:23 -07:00
|
|
|
require.NoError(t, err)
|
2019-10-09 17:06:53 -07:00
|
|
|
|
2018-02-15 04:08:00 -08:00
|
|
|
res = matrixQuery.Exec(ctx)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Error(t, res.Err, "expected error on failed select but got none")
|
2023-12-07 03:35:01 -08:00
|
|
|
require.ErrorIs(t, res.Err, errStorage, "expected error doesn't match")
|
2018-02-15 04:08:00 -08:00
|
|
|
}
|
|
|
|
|
2020-07-23 15:05:43 -07:00
|
|
|
type noopHintRecordingQueryable struct {
|
|
|
|
hints []*storage.SelectHints
|
2019-04-17 05:52:41 -07:00
|
|
|
}
|
|
|
|
|
2023-09-12 03:37:38 -07:00
|
|
|
func (h *noopHintRecordingQueryable) Querier(int64, int64) (storage.Querier, error) {
|
2020-07-23 15:05:43 -07:00
|
|
|
return &hintRecordingQuerier{Querier: &errQuerier{}, h: h}, nil
|
|
|
|
}
|
|
|
|
|
|
|
|
type hintRecordingQuerier struct {
|
|
|
|
storage.Querier
|
2019-04-17 05:52:41 -07:00
|
|
|
|
2020-07-23 15:05:43 -07:00
|
|
|
h *noopHintRecordingQueryable
|
2019-04-17 05:52:41 -07:00
|
|
|
}
|
2020-07-23 15:05:43 -07:00
|
|
|
|
2023-09-12 03:37:38 -07:00
|
|
|
func (h *hintRecordingQuerier) Select(ctx context.Context, sortSeries bool, hints *storage.SelectHints, matchers ...*labels.Matcher) storage.SeriesSet {
|
2020-07-23 15:05:43 -07:00
|
|
|
h.h.hints = append(h.h.hints, hints)
|
2023-09-12 03:37:38 -07:00
|
|
|
return h.Querier.Select(ctx, sortSeries, hints, matchers...)
|
2019-06-17 00:31:17 -07:00
|
|
|
}
|
2019-04-17 05:52:41 -07:00
|
|
|
|
2020-07-23 15:05:43 -07:00
|
|
|
func TestSelectHintsSetCorrectly(t *testing.T) {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts := promql.EngineOpts{
|
2021-01-20 02:57:39 -08:00
|
|
|
Logger: nil,
|
|
|
|
Reg: nil,
|
|
|
|
MaxSamples: 10,
|
|
|
|
Timeout: 10 * time.Second,
|
|
|
|
LookbackDelta: 5 * time.Second,
|
|
|
|
EnableAtModifier: true,
|
2019-04-17 05:52:41 -07:00
|
|
|
}
|
|
|
|
|
2020-07-23 15:05:43 -07:00
|
|
|
for _, tc := range []struct {
|
2019-04-17 05:52:41 -07:00
|
|
|
query string
|
|
|
|
|
2020-07-23 15:05:43 -07:00
|
|
|
// All times are in milliseconds.
|
2019-04-17 05:52:41 -07:00
|
|
|
start int64
|
|
|
|
end int64
|
|
|
|
|
2020-07-23 15:05:43 -07:00
|
|
|
// TODO(bwplotka): Add support for better hints when subquerying.
|
|
|
|
expected []*storage.SelectHints
|
2021-10-22 01:06:44 -07:00
|
|
|
}{
|
|
|
|
{
|
|
|
|
query: "foo", start: 10000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 5000, End: 10000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo @ 15", start: 10000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 10000, End: 15000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo @ 1", start: 10000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: -4000, End: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo[2m]", start: 200000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 80000, End: 200000, Range: 120000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo[2m] @ 180", start: 200000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 60000, End: 180000, Range: 120000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo[2m] @ 300", start: 200000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 180000, End: 300000, Range: 120000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo[2m] @ 60", start: 200000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: -60000, End: 60000, Range: 120000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo[2m] offset 2m", start: 300000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 60000, End: 180000, Range: 120000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo[2m] @ 200 offset 2m", start: 300000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: -40000, End: 80000, Range: 120000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo[2m:1s]", start: 300000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 175000, End: 300000, Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time(foo[2m:1s])", start: 300000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 175000, End: 300000, Func: "count_over_time", Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time(foo[2m:1s] @ 300)", start: 200000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 175000, End: 300000, Func: "count_over_time", Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time(foo[2m:1s] @ 200)", start: 200000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 75000, End: 200000, Func: "count_over_time", Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time(foo[2m:1s] @ 100)", start: 200000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: -25000, End: 100000, Func: "count_over_time", Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time(foo[2m:1s] offset 10s)", start: 300000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 165000, End: 290000, Func: "count_over_time", Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time((foo offset 10s)[2m:1s] offset 10s)", start: 300000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 155000, End: 280000, Func: "count_over_time", Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
// When the @ is on the vector selector, the enclosing subquery parameters
|
|
|
|
// don't affect the hint ranges.
|
|
|
|
query: "count_over_time((foo @ 200 offset 10s)[2m:1s] offset 10s)", start: 300000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 185000, End: 190000, Func: "count_over_time", Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
// When the @ is on the vector selector, the enclosing subquery parameters
|
|
|
|
// don't affect the hint ranges.
|
|
|
|
query: "count_over_time((foo @ 200 offset 10s)[2m:1s] @ 100 offset 10s)", start: 300000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 185000, End: 190000, Func: "count_over_time", Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time((foo offset 10s)[2m:1s] @ 100 offset 10s)", start: 300000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: -45000, End: 80000, Func: "count_over_time", Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo", start: 10000, end: 20000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 5000, End: 20000, Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo @ 15", start: 10000, end: 20000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 10000, End: 15000, Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo @ 1", start: 10000, end: 20000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: -4000, End: 1000, Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "rate(foo[2m] @ 180)", start: 200000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 60000, End: 180000, Range: 120000, Func: "rate", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "rate(foo[2m] @ 300)", start: 200000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 180000, End: 300000, Range: 120000, Func: "rate", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "rate(foo[2m] @ 60)", start: 200000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: -60000, End: 60000, Range: 120000, Func: "rate", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "rate(foo[2m])", start: 200000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 80000, End: 500000, Range: 120000, Func: "rate", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "rate(foo[2m] offset 2m)", start: 300000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 60000, End: 380000, Range: 120000, Func: "rate", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "rate(foo[2m:1s])", start: 300000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 175000, End: 500000, Func: "rate", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time(foo[2m:1s])", start: 300000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 175000, End: 500000, Func: "count_over_time", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time(foo[2m:1s] offset 10s)", start: 300000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 165000, End: 490000, Func: "count_over_time", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time(foo[2m:1s] @ 300)", start: 200000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 175000, End: 300000, Func: "count_over_time", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time(foo[2m:1s] @ 200)", start: 200000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 75000, End: 200000, Func: "count_over_time", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time(foo[2m:1s] @ 100)", start: 200000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: -25000, End: 100000, Func: "count_over_time", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time((foo offset 10s)[2m:1s] offset 10s)", start: 300000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 155000, End: 480000, Func: "count_over_time", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
// When the @ is on the vector selector, the enclosing subquery parameters
|
|
|
|
// don't affect the hint ranges.
|
|
|
|
query: "count_over_time((foo @ 200 offset 10s)[2m:1s] offset 10s)", start: 300000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 185000, End: 190000, Func: "count_over_time", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
// When the @ is on the vector selector, the enclosing subquery parameters
|
|
|
|
// don't affect the hint ranges.
|
|
|
|
query: "count_over_time((foo @ 200 offset 10s)[2m:1s] @ 100 offset 10s)", start: 300000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 185000, End: 190000, Func: "count_over_time", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "count_over_time((foo offset 10s)[2m:1s] @ 100 offset 10s)", start: 300000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: -45000, End: 80000, Func: "count_over_time", Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "sum by (dim1) (foo)", start: 10000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 5000, End: 10000, Func: "sum", By: true, Grouping: []string{"dim1"}},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "sum without (dim1) (foo)", start: 10000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 5000, End: 10000, Func: "sum", Grouping: []string{"dim1"}},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "sum by (dim1) (avg_over_time(foo[1s]))", start: 10000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 9000, End: 10000, Func: "avg_over_time", Range: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "sum by (dim1) (max by (dim2) (foo))", start: 10000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 5000, End: 10000, Func: "max", By: true, Grouping: []string{"dim2"}},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "(max by (dim1) (foo))[5s:1s]", start: 10000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 0, End: 10000, Func: "max", By: true, Grouping: []string{"dim1"}, Step: 1000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "(sum(http_requests{group=~\"p.*\"})+max(http_requests{group=~\"c.*\"}))[20s:5s]", start: 120000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 95000, End: 120000, Func: "sum", By: true, Step: 5000},
|
|
|
|
{Start: 95000, End: 120000, Func: "max", By: true, Step: 5000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo @ 50 + bar @ 250 + baz @ 900", start: 100000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 45000, End: 50000, Step: 1000},
|
|
|
|
{Start: 245000, End: 250000, Step: 1000},
|
|
|
|
{Start: 895000, End: 900000, Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "foo @ 50 + bar + baz @ 900", start: 100000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 45000, End: 50000, Step: 1000},
|
|
|
|
{Start: 95000, End: 500000, Step: 1000},
|
|
|
|
{Start: 895000, End: 900000, Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "rate(foo[2s] @ 50) + bar @ 250 + baz @ 900", start: 100000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 48000, End: 50000, Step: 1000, Func: "rate", Range: 2000},
|
|
|
|
{Start: 245000, End: 250000, Step: 1000},
|
|
|
|
{Start: 895000, End: 900000, Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "rate(foo[2s:1s] @ 50) + bar + baz", start: 100000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 43000, End: 50000, Step: 1000, Func: "rate"},
|
|
|
|
{Start: 95000, End: 500000, Step: 1000},
|
|
|
|
{Start: 95000, End: 500000, Step: 1000},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "rate(foo[2s:1s] @ 50) + bar + rate(baz[2m:1s] @ 900 offset 2m) ", start: 100000, end: 500000,
|
|
|
|
expected: []*storage.SelectHints{
|
|
|
|
{Start: 43000, End: 50000, Step: 1000, Func: "rate"},
|
|
|
|
{Start: 95000, End: 500000, Step: 1000},
|
|
|
|
{Start: 655000, End: 780000, Step: 1000, Func: "rate"},
|
|
|
|
},
|
|
|
|
}, { // Hints are based on the inner most subquery timestamp.
|
|
|
|
query: `sum_over_time(sum_over_time(metric{job="1"}[100s])[100s:25s] @ 50)[3s:1s] @ 3000`, start: 100000,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: -150000, End: 50000, Range: 100000, Func: "sum_over_time", Step: 25000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
}, { // Hints are based on the inner most subquery timestamp.
|
|
|
|
query: `sum_over_time(sum_over_time(metric{job="1"}[100s])[100s:25s] @ 3000)[3s:1s] @ 50`,
|
|
|
|
expected: []*storage.SelectHints{
|
2022-09-30 07:43:38 -07:00
|
|
|
{Start: 2800000, End: 3000000, Range: 100000, Func: "sum_over_time", Step: 25000},
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
2021-01-20 02:57:39 -08:00
|
|
|
},
|
|
|
|
} {
|
2020-07-23 15:05:43 -07:00
|
|
|
t.Run(tc.query, func(t *testing.T) {
|
2024-07-14 04:28:59 -07:00
|
|
|
engine := promqltest.NewTestEngineWithOpts(t, opts)
|
2020-07-23 15:05:43 -07:00
|
|
|
hintsRecorder := &noopHintRecordingQueryable{}
|
|
|
|
|
|
|
|
var (
|
2024-04-29 05:14:18 -07:00
|
|
|
query promql.Query
|
2020-07-23 15:05:43 -07:00
|
|
|
err error
|
|
|
|
)
|
2023-04-17 21:32:38 -07:00
|
|
|
ctx := context.Background()
|
2023-08-18 11:48:59 -07:00
|
|
|
|
2020-07-23 15:05:43 -07:00
|
|
|
if tc.end == 0 {
|
2023-04-17 21:32:38 -07:00
|
|
|
query, err = engine.NewInstantQuery(ctx, hintsRecorder, nil, tc.query, timestamp.Time(tc.start))
|
2020-07-23 15:05:43 -07:00
|
|
|
} else {
|
2023-04-17 21:32:38 -07:00
|
|
|
query, err = engine.NewRangeQuery(ctx, hintsRecorder, nil, tc.query, timestamp.Time(tc.start), timestamp.Time(tc.end), time.Second)
|
2020-07-23 15:05:43 -07:00
|
|
|
}
|
2020-10-29 02:43:23 -07:00
|
|
|
require.NoError(t, err)
|
2019-04-17 05:52:41 -07:00
|
|
|
|
2023-08-18 11:48:59 -07:00
|
|
|
res := query.Exec(context.Background())
|
2020-10-29 02:43:23 -07:00
|
|
|
require.NoError(t, res.Err)
|
2020-07-23 15:05:43 -07:00
|
|
|
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Equal(t, tc.expected, hintsRecorder.hints)
|
2020-07-23 15:05:43 -07:00
|
|
|
})
|
2019-04-17 05:52:41 -07:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2015-03-30 10:13:36 -07:00
|
|
|
func TestEngineShutdown(t *testing.T) {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts := promql.EngineOpts{
|
2020-01-28 12:38:49 -08:00
|
|
|
Logger: nil,
|
|
|
|
Reg: nil,
|
|
|
|
MaxSamples: 10,
|
|
|
|
Timeout: 10 * time.Second,
|
2018-10-02 04:59:19 -07:00
|
|
|
}
|
2024-07-14 04:28:59 -07:00
|
|
|
engine := promqltest.NewTestEngineWithOpts(t, opts)
|
2016-09-15 15:58:06 -07:00
|
|
|
ctx, cancelCtx := context.WithCancel(context.Background())
|
2015-03-30 10:13:36 -07:00
|
|
|
|
2015-08-10 05:21:24 -07:00
|
|
|
block := make(chan struct{})
|
|
|
|
processing := make(chan struct{})
|
|
|
|
|
2015-03-30 10:13:36 -07:00
|
|
|
// Shutdown engine on first handler execution. Should handler execution ever become
|
|
|
|
// concurrent this test has to be adjusted accordingly.
|
2015-08-10 05:21:24 -07:00
|
|
|
f := func(ctx context.Context) error {
|
|
|
|
processing <- struct{}{}
|
|
|
|
<-block
|
|
|
|
return contextDone(ctx, "test statement execution")
|
|
|
|
}
|
2024-04-29 05:14:18 -07:00
|
|
|
query1 := engine.NewTestQuery(f)
|
2015-03-30 10:13:36 -07:00
|
|
|
|
2015-04-29 02:08:56 -07:00
|
|
|
// Stopping the engine must cancel the base context. While executing queries is
|
|
|
|
// still possible, their context is canceled from the beginning and execution should
|
2015-03-30 10:13:36 -07:00
|
|
|
// terminate immediately.
|
|
|
|
|
2024-04-29 05:14:18 -07:00
|
|
|
var res *promql.Result
|
2015-08-10 05:21:24 -07:00
|
|
|
go func() {
|
promql: Allow per-query contexts.
For Weaveworks' Frankenstein, we need to support multitenancy. In
Frankenstein, we initially solved this without modifying the promql
package at all: we constructed a new promql.Engine for every
query and injected a storage implementation into that engine which would
be primed to only collect data for a given user.
This is problematic to upstream, however. Prometheus assumes that there
is only one engine: the query concurrency gate is part of the engine,
and the engine contains one central cancellable context to shut down all
queries. Also, creating a new engine for every query seems like overkill.
Thus, we want to be able to pass per-query contexts into a single engine.
This change gets rid of the promql.Engine's built-in base context and
allows passing in a per-query context instead. Central cancellation of
all queries is still possible by deriving all passed-in contexts from
one central one, but this is now the responsibility of the caller. The
central query context is now created in main() and passed into the
relevant components (web handler / API, rule manager).
In a next step, the per-query context would have to be passed to the
storage implementation, so that the storage can implement multi-tenancy
or other features based on the contextual information.
2016-09-15 04:52:50 -07:00
|
|
|
res = query1.Exec(ctx)
|
2015-08-10 05:21:24 -07:00
|
|
|
processing <- struct{}{}
|
|
|
|
}()
|
|
|
|
|
|
|
|
<-processing
|
2016-09-15 15:58:06 -07:00
|
|
|
cancelCtx()
|
2015-08-10 05:21:24 -07:00
|
|
|
block <- struct{}{}
|
|
|
|
<-processing
|
|
|
|
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Error(t, res.Err, "expected error on shutdown during query but got none")
|
|
|
|
require.Equal(t, errQueryCanceled, res.Err)
|
2015-03-30 10:13:36 -07:00
|
|
|
|
2024-04-29 05:14:18 -07:00
|
|
|
query2 := engine.NewTestQuery(func(context.Context) error {
|
2021-09-13 12:19:20 -07:00
|
|
|
require.FailNow(t, "reached query execution unexpectedly")
|
2015-08-10 05:21:24 -07:00
|
|
|
return nil
|
|
|
|
})
|
|
|
|
|
|
|
|
// The second query is started after the engine shut down. It must
|
|
|
|
// be canceled immediately.
|
promql: Allow per-query contexts.
For Weaveworks' Frankenstein, we need to support multitenancy. In
Frankenstein, we initially solved this without modifying the promql
package at all: we constructed a new promql.Engine for every
query and injected a storage implementation into that engine which would
be primed to only collect data for a given user.
This is problematic to upstream, however. Prometheus assumes that there
is only one engine: the query concurrency gate is part of the engine,
and the engine contains one central cancellable context to shut down all
queries. Also, creating a new engine for every query seems like overkill.
Thus, we want to be able to pass per-query contexts into a single engine.
This change gets rid of the promql.Engine's built-in base context and
allows passing in a per-query context instead. Central cancellation of
all queries is still possible by deriving all passed-in contexts from
one central one, but this is now the responsibility of the caller. The
central query context is now created in main() and passed into the
relevant components (web handler / API, rule manager).
In a next step, the per-query context would have to be passed to the
storage implementation, so that the storage can implement multi-tenancy
or other features based on the contextual information.
2016-09-15 04:52:50 -07:00
|
|
|
res2 := query2.Exec(ctx)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Error(t, res2.Err, "expected error on querying with canceled context but got none")
|
2019-10-09 17:06:53 -07:00
|
|
|
|
2024-04-29 05:14:18 -07:00
|
|
|
var e promql.ErrQueryCanceled
|
2023-12-07 03:35:01 -08:00
|
|
|
require.ErrorAs(t, res2.Err, &e, "expected cancellation error but got: %s", res2.Err)
|
2015-03-30 10:13:36 -07:00
|
|
|
}
|
2015-08-19 06:28:53 -07:00
|
|
|
|
2017-04-18 06:51:10 -07:00
|
|
|
func TestEngineEvalStmtTimestamps(t *testing.T) {
|
2024-04-29 05:14:18 -07:00
|
|
|
storage := promqltest.LoadedStorage(t, `
|
2017-04-18 06:51:10 -07:00
|
|
|
load 10s
|
|
|
|
metric 1 2
|
|
|
|
`)
|
2023-08-18 11:48:59 -07:00
|
|
|
t.Cleanup(func() { storage.Close() })
|
2017-04-18 06:51:10 -07:00
|
|
|
|
|
|
|
cases := []struct {
|
2018-09-13 02:57:36 -07:00
|
|
|
Query string
|
2020-02-03 08:32:23 -08:00
|
|
|
Result parser.Value
|
2018-09-13 02:57:36 -07:00
|
|
|
Start time.Time
|
|
|
|
End time.Time
|
|
|
|
Interval time.Duration
|
|
|
|
ShouldError bool
|
2017-04-18 06:51:10 -07:00
|
|
|
}{
|
|
|
|
// Instant queries.
|
|
|
|
{
|
|
|
|
Query: "1",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Scalar{V: 1, T: 1000},
|
2017-04-18 06:51:10 -07:00
|
|
|
Start: time.Unix(1, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metric",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Vector{
|
|
|
|
promql.Sample{
|
promql: Separate `Point` into `FPoint` and `HPoint`
In other words: Instead of having a “polymorphous” `Point` that can
either contain a float value or a histogram value, use an `FPoint` for
floats and an `HPoint` for histograms.
This seemingly small change has a _lot_ of repercussions throughout
the codebase.
The idea here is to avoid the increase in size of `Point` arrays that
happened after native histograms had been added.
The higher-level data structures (`Sample`, `Series`, etc.) are still
“polymorphous”. The same idea could be applied to them, but at each
step the trade-offs needed to be evaluated.
The idea with this change is to do the minimum necessary to get back
to pre-histogram performance for functions that do not touch
histograms. Here are comparisons for the `changes` function. The test
data doesn't include histograms yet. Ideally, there would be no change
in the benchmark result at all.
First runtime v2.39 compared to directly prior to this commit:
```
name old time/op new time/op delta
RangeQuery/expr=changes(a_one[1d]),steps=1-16 391µs ± 2% 542µs ± 1% +38.58% (p=0.000 n=9+8)
RangeQuery/expr=changes(a_one[1d]),steps=10-16 452µs ± 2% 617µs ± 2% +36.48% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_one[1d]),steps=100-16 1.12ms ± 1% 1.36ms ± 2% +21.58% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_one[1d]),steps=1000-16 7.83ms ± 1% 8.94ms ± 1% +14.21% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_ten[1d]),steps=1-16 2.98ms ± 0% 3.30ms ± 1% +10.67% (p=0.000 n=9+10)
RangeQuery/expr=changes(a_ten[1d]),steps=10-16 3.66ms ± 1% 4.10ms ± 1% +11.82% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_ten[1d]),steps=100-16 10.5ms ± 0% 11.8ms ± 1% +12.50% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_ten[1d]),steps=1000-16 77.6ms ± 1% 87.4ms ± 1% +12.63% (p=0.000 n=9+9)
RangeQuery/expr=changes(a_hundred[1d]),steps=1-16 30.4ms ± 2% 32.8ms ± 1% +8.01% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=10-16 37.1ms ± 2% 40.6ms ± 2% +9.64% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=100-16 105ms ± 1% 117ms ± 1% +11.69% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=1000-16 783ms ± 3% 876ms ± 1% +11.83% (p=0.000 n=9+10)
```
And then runtime v2.39 compared to after this commit:
```
name old time/op new time/op delta
RangeQuery/expr=changes(a_one[1d]),steps=1-16 391µs ± 2% 547µs ± 1% +39.84% (p=0.000 n=9+8)
RangeQuery/expr=changes(a_one[1d]),steps=10-16 452µs ± 2% 616µs ± 2% +36.15% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_one[1d]),steps=100-16 1.12ms ± 1% 1.26ms ± 1% +12.20% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_one[1d]),steps=1000-16 7.83ms ± 1% 7.95ms ± 1% +1.59% (p=0.000 n=10+8)
RangeQuery/expr=changes(a_ten[1d]),steps=1-16 2.98ms ± 0% 3.38ms ± 2% +13.49% (p=0.000 n=9+10)
RangeQuery/expr=changes(a_ten[1d]),steps=10-16 3.66ms ± 1% 4.02ms ± 1% +9.80% (p=0.000 n=10+9)
RangeQuery/expr=changes(a_ten[1d]),steps=100-16 10.5ms ± 0% 10.8ms ± 1% +3.08% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_ten[1d]),steps=1000-16 77.6ms ± 1% 78.1ms ± 1% +0.58% (p=0.035 n=9+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=1-16 30.4ms ± 2% 33.5ms ± 4% +10.18% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=10-16 37.1ms ± 2% 40.0ms ± 1% +7.98% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=100-16 105ms ± 1% 107ms ± 1% +1.92% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=1000-16 783ms ± 3% 775ms ± 1% -1.02% (p=0.019 n=9+9)
```
In summary, the runtime doesn't really improve with this change for
queries with just a few steps. For queries with many steps, this
commit essentially reinstates the old performance. This is good
because the many-step queries are the one that matter most (longest
absolute runtime).
In terms of allocations, though, this commit doesn't make a dent at
all (numbers not shown). The reason is that most of the allocations
happen in the sampleRingIterator (in the storage package), which has
to be addressed in a separate commit.
Signed-off-by: beorn7 <beorn@grafana.com>
2022-10-28 07:58:40 -07:00
|
|
|
F: 1,
|
|
|
|
T: 1000,
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2017-04-18 06:51:10 -07:00
|
|
|
},
|
|
|
|
Start: time.Unix(1, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metric[20s]",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 1, T: 0}, {F: 2, T: 10000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2017-04-18 06:51:10 -07:00
|
|
|
},
|
|
|
|
Start: time.Unix(10, 0),
|
|
|
|
},
|
|
|
|
// Range queries.
|
|
|
|
{
|
|
|
|
Query: "1",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 1, T: 0}, {F: 1, T: 1000}, {F: 1, T: 2000}},
|
2022-03-09 14:16:54 -08:00
|
|
|
Metric: labels.EmptyLabels(),
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
2017-04-18 06:51:10 -07:00
|
|
|
},
|
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(2, 0),
|
|
|
|
Interval: time.Second,
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metric",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 1, T: 0}, {F: 1, T: 1000}, {F: 1, T: 2000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2017-04-18 06:51:10 -07:00
|
|
|
},
|
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(2, 0),
|
|
|
|
Interval: time.Second,
|
|
|
|
},
|
2017-06-12 22:22:27 -07:00
|
|
|
{
|
|
|
|
Query: "metric",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 1, T: 0}, {F: 1, T: 5000}, {F: 2, T: 10000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2017-06-12 22:22:27 -07:00
|
|
|
},
|
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(10, 0),
|
|
|
|
Interval: 5 * time.Second,
|
|
|
|
},
|
2018-09-13 02:57:36 -07:00
|
|
|
{
|
|
|
|
Query: `count_values("wrong label!", metric)`,
|
|
|
|
ShouldError: true,
|
|
|
|
},
|
2017-04-18 06:51:10 -07:00
|
|
|
}
|
|
|
|
|
2022-05-25 07:22:47 -07:00
|
|
|
for i, c := range cases {
|
|
|
|
t.Run(fmt.Sprintf("%d query=%s", i, c.Query), func(t *testing.T) {
|
|
|
|
var err error
|
2024-04-29 05:14:18 -07:00
|
|
|
var qry promql.Query
|
2024-05-07 09:14:22 -07:00
|
|
|
engine := newTestEngine(t)
|
2022-05-25 07:22:47 -07:00
|
|
|
if c.Interval == 0 {
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err = engine.NewInstantQuery(context.Background(), storage, nil, c.Query, c.Start)
|
2022-05-25 07:22:47 -07:00
|
|
|
} else {
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err = engine.NewRangeQuery(context.Background(), storage, nil, c.Query, c.Start, c.End, c.Interval)
|
2022-05-25 07:22:47 -07:00
|
|
|
}
|
|
|
|
require.NoError(t, err)
|
2019-10-09 17:06:53 -07:00
|
|
|
|
2023-08-18 11:48:59 -07:00
|
|
|
res := qry.Exec(context.Background())
|
2022-05-25 07:22:47 -07:00
|
|
|
if c.ShouldError {
|
|
|
|
require.Error(t, res.Err, "expected error for the query %q", c.Query)
|
|
|
|
return
|
|
|
|
}
|
2019-10-09 17:06:53 -07:00
|
|
|
|
2022-05-25 07:22:47 -07:00
|
|
|
require.NoError(t, res.Err)
|
|
|
|
require.Equal(t, c.Result, res.Value, "query %q failed", c.Query)
|
|
|
|
})
|
2017-04-18 06:51:10 -07:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2022-02-01 18:07:23 -08:00
|
|
|
func TestQueryStatistics(t *testing.T) {
|
2024-04-29 05:14:18 -07:00
|
|
|
storage := promqltest.LoadedStorage(t, `
|
2022-02-01 18:07:23 -08:00
|
|
|
load 10s
|
|
|
|
metricWith1SampleEvery10Seconds 1+1x100
|
|
|
|
metricWith3SampleEvery10Seconds{a="1",b="1"} 1+1x100
|
|
|
|
metricWith3SampleEvery10Seconds{a="2",b="2"} 1+1x100
|
|
|
|
metricWith3SampleEvery10Seconds{a="3",b="2"} 1+1x100
|
2024-02-28 09:10:46 -08:00
|
|
|
metricWith1HistogramEvery10Seconds {{schema:1 count:5 sum:20 buckets:[1 2 1 1]}}+{{schema:1 count:10 sum:5 buckets:[1 2 3 4]}}x100
|
2022-02-01 18:07:23 -08:00
|
|
|
`)
|
2023-08-18 11:48:59 -07:00
|
|
|
t.Cleanup(func() { storage.Close() })
|
2022-02-01 18:07:23 -08:00
|
|
|
|
|
|
|
cases := []struct {
|
|
|
|
Query string
|
2022-02-22 12:30:39 -08:00
|
|
|
SkipMaxCheck bool
|
2022-04-11 16:22:25 -07:00
|
|
|
TotalSamples int64
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamplesPerStep stats.TotalSamplesPerStep
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples int
|
2022-02-01 18:07:23 -08:00
|
|
|
Start time.Time
|
|
|
|
End time.Time
|
|
|
|
Interval time.Duration
|
|
|
|
}{
|
|
|
|
{
|
|
|
|
Query: `"literal string"`,
|
2022-02-22 12:30:39 -08:00
|
|
|
SkipMaxCheck: true, // This can't fail from a max samples limit.
|
2022-02-01 18:07:23 -08:00
|
|
|
Start: time.Unix(21, 0),
|
|
|
|
TotalSamples: 0,
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 0,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "1",
|
|
|
|
Start: time.Unix(21, 0),
|
|
|
|
TotalSamples: 0,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 1,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 0,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metricWith1SampleEvery10Seconds",
|
|
|
|
Start: time.Unix(21, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 1,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 1, // 1 sample / 10 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 1,
|
|
|
|
},
|
|
|
|
},
|
2024-02-28 07:13:15 -08:00
|
|
|
{
|
|
|
|
Query: "metricWith1HistogramEvery10Seconds",
|
|
|
|
Start: time.Unix(21, 0),
|
2024-03-27 10:19:14 -07:00
|
|
|
PeakSamples: 13,
|
|
|
|
TotalSamples: 13, // 1 histogram HPoint of size 13 / 10 seconds
|
2024-02-28 07:13:15 -08:00
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
2024-03-27 10:19:14 -07:00
|
|
|
21000: 13,
|
2024-02-28 07:13:15 -08:00
|
|
|
},
|
|
|
|
},
|
2022-02-01 18:07:23 -08:00
|
|
|
{
|
|
|
|
// timestamp function has a special handling.
|
|
|
|
Query: "timestamp(metricWith1SampleEvery10Seconds)",
|
|
|
|
Start: time.Unix(21, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 2,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 1, // 1 sample / 10 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 1,
|
|
|
|
},
|
|
|
|
},
|
2024-02-28 09:10:46 -08:00
|
|
|
{
|
|
|
|
Query: "timestamp(metricWith1HistogramEvery10Seconds)",
|
|
|
|
Start: time.Unix(21, 0),
|
2024-05-08 02:39:44 -07:00
|
|
|
PeakSamples: 2,
|
|
|
|
TotalSamples: 1, // 1 float sample (because of timestamp) / 10 seconds
|
2024-02-28 09:10:46 -08:00
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 1,
|
|
|
|
},
|
|
|
|
},
|
2022-02-01 18:07:23 -08:00
|
|
|
{
|
|
|
|
Query: "metricWith1SampleEvery10Seconds",
|
|
|
|
Start: time.Unix(22, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 1,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 1, // 1 sample / 10 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
22000: 1, // Aligned to the step time, not the sample time.
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metricWith1SampleEvery10Seconds offset 10s",
|
|
|
|
Start: time.Unix(21, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 1,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 1, // 1 sample / 10 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 1,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metricWith1SampleEvery10Seconds @ 15",
|
|
|
|
Start: time.Unix(21, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 1,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 1, // 1 sample / 10 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 1,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `metricWith3SampleEvery10Seconds{a="1"}`,
|
|
|
|
Start: time.Unix(21, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 1,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 1, // 1 sample / 10 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 1,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `metricWith3SampleEvery10Seconds{a="1"} @ 19`,
|
|
|
|
Start: time.Unix(21, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 1,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 1, // 1 sample / 10 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 1,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `metricWith3SampleEvery10Seconds{a="1"}[20s] @ 19`,
|
|
|
|
Start: time.Unix(21, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 2,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 2, // (1 sample / 10 seconds) * 20s
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 2,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metricWith3SampleEvery10Seconds",
|
|
|
|
Start: time.Unix(21, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 3,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 3, // 3 samples / 10 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
21000: 3,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metricWith1SampleEvery10Seconds[60s]",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 6,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 6,
|
|
|
|
},
|
|
|
|
},
|
2024-02-28 09:10:46 -08:00
|
|
|
{
|
|
|
|
Query: "metricWith1HistogramEvery10Seconds[60s]",
|
|
|
|
Start: time.Unix(201, 0),
|
2024-03-27 10:19:14 -07:00
|
|
|
PeakSamples: 78,
|
|
|
|
TotalSamples: 78, // 1 histogram (size 13 HPoint) / 10 seconds * 60 seconds
|
2024-02-28 09:10:46 -08:00
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
2024-03-27 10:19:14 -07:00
|
|
|
201000: 78,
|
2024-02-28 09:10:46 -08:00
|
|
|
},
|
|
|
|
},
|
2022-02-01 18:07:23 -08:00
|
|
|
{
|
|
|
|
Query: "max_over_time(metricWith1SampleEvery10Seconds[59s])[20s:5s]",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 10,
|
2024-02-28 09:10:46 -08:00
|
|
|
TotalSamples: 24, // (1 sample / 10 seconds * 60 seconds) * 20/5 (using 59s so we always return 6 samples
|
2022-02-01 18:07:23 -08:00
|
|
|
// as if we run a query on 00 looking back 60 seconds we will return 7 samples;
|
|
|
|
// see next test).
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 24,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "max_over_time(metricWith1SampleEvery10Seconds[60s])[20s:5s]",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 11,
|
2024-02-28 09:10:46 -08:00
|
|
|
TotalSamples: 26, // (1 sample / 10 seconds * 60 seconds) * 4 + 2 as
|
2022-02-01 18:07:23 -08:00
|
|
|
// max_over_time(metricWith1SampleEvery10Seconds[60s]) @ 190 and 200 will return 7 samples.
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 26,
|
|
|
|
},
|
|
|
|
},
|
2024-02-28 09:10:46 -08:00
|
|
|
{
|
|
|
|
Query: "max_over_time(metricWith1HistogramEvery10Seconds[60s])[20s:5s]",
|
|
|
|
Start: time.Unix(201, 0),
|
2024-03-27 10:19:14 -07:00
|
|
|
PeakSamples: 78,
|
|
|
|
TotalSamples: 338, // (1 histogram (size 13 HPoint) / 10 seconds * 60 seconds) * 4 + 2 * 13 as
|
2024-02-28 09:10:46 -08:00
|
|
|
// max_over_time(metricWith1SampleEvery10Seconds[60s]) @ 190 and 200 will return 7 samples.
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
2024-03-27 10:19:14 -07:00
|
|
|
201000: 338,
|
2024-02-28 09:10:46 -08:00
|
|
|
},
|
|
|
|
},
|
2022-02-01 18:07:23 -08:00
|
|
|
{
|
|
|
|
Query: "metricWith1SampleEvery10Seconds[60s] @ 30",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 4,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 4, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 1 series
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 4,
|
|
|
|
},
|
|
|
|
},
|
2024-02-28 09:10:46 -08:00
|
|
|
{
|
|
|
|
Query: "metricWith1HistogramEvery10Seconds[60s] @ 30",
|
|
|
|
Start: time.Unix(201, 0),
|
2024-03-27 10:19:14 -07:00
|
|
|
PeakSamples: 52,
|
|
|
|
TotalSamples: 52, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 1 series
|
2024-02-28 09:10:46 -08:00
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
2024-03-27 10:19:14 -07:00
|
|
|
201000: 52,
|
2024-02-28 09:10:46 -08:00
|
|
|
},
|
|
|
|
},
|
2022-02-01 18:07:23 -08:00
|
|
|
{
|
|
|
|
Query: "sum(max_over_time(metricWith3SampleEvery10Seconds[60s] @ 30))",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 7,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 12, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 3 series
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 12,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "sum by (b) (max_over_time(metricWith3SampleEvery10Seconds[60s] @ 30))",
|
|
|
|
Start: time.Unix(201, 0),
|
2024-02-29 15:21:46 -08:00
|
|
|
PeakSamples: 7,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 12, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 3 series
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 12,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metricWith1SampleEvery10Seconds[60s] offset 10s",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 6,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 6,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metricWith3SampleEvery10Seconds[60s]",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 18,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 18, // 3 sample / 10 seconds * 60 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 18,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "max_over_time(metricWith1SampleEvery10Seconds[60s])",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 7,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 6,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "absent_over_time(metricWith1SampleEvery10Seconds[60s])",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 7,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 6,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "max_over_time(metricWith3SampleEvery10Seconds[60s])",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 9,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 18, // 3 sample / 10 seconds * 60 seconds
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 18,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metricWith1SampleEvery10Seconds[60s:5s]",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 12,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 12, // 1 sample per query * 12 queries (60/5)
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 12,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metricWith1SampleEvery10Seconds[60s:5s] offset 10s",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 12,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 12, // 1 sample per query * 12 queries (60/5)
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 12,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "max_over_time(metricWith3SampleEvery10Seconds[60s:5s])",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 51,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 36, // 3 sample per query * 12 queries (60/5)
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 36,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s])) + sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s]))",
|
|
|
|
Start: time.Unix(201, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 52,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 72, // 2 * (3 sample per query * 12 queries (60/5))
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 72,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `metricWith3SampleEvery10Seconds{a="1"}`,
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 4,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 4, // 1 sample per query * 4 steps
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 1,
|
|
|
|
206000: 1,
|
|
|
|
211000: 1,
|
|
|
|
216000: 1,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `metricWith3SampleEvery10Seconds{a="1"}`,
|
|
|
|
Start: time.Unix(204, 0),
|
|
|
|
End: time.Unix(223, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 4,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 4, // 1 sample per query * 4 steps
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
204000: 1, // aligned to the step time, not the sample time
|
|
|
|
209000: 1,
|
|
|
|
214000: 1,
|
|
|
|
219000: 1,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
2024-02-28 09:10:46 -08:00
|
|
|
Query: `metricWith1HistogramEvery10Seconds`,
|
|
|
|
Start: time.Unix(204, 0),
|
|
|
|
End: time.Unix(223, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2024-03-27 10:19:14 -07:00
|
|
|
PeakSamples: 52,
|
|
|
|
TotalSamples: 52, // 1 histogram (size 13 HPoint) per query * 4 steps
|
2024-02-28 09:10:46 -08:00
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
2024-03-27 10:19:14 -07:00
|
|
|
204000: 13, // aligned to the step time, not the sample time
|
|
|
|
209000: 13,
|
|
|
|
214000: 13,
|
|
|
|
219000: 13,
|
2024-02-28 09:10:46 -08:00
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
// timestamp function has a special handling
|
2022-02-01 18:07:23 -08:00
|
|
|
Query: "timestamp(metricWith1SampleEvery10Seconds)",
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 5,
|
2024-02-28 07:13:15 -08:00
|
|
|
TotalSamples: 4, // 1 sample per query * 4 steps
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 1,
|
|
|
|
206000: 1,
|
|
|
|
211000: 1,
|
|
|
|
216000: 1,
|
|
|
|
},
|
|
|
|
},
|
2024-02-28 09:10:46 -08:00
|
|
|
{
|
|
|
|
// timestamp function has a special handling
|
|
|
|
Query: "timestamp(metricWith1HistogramEvery10Seconds)",
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2024-05-08 02:39:44 -07:00
|
|
|
PeakSamples: 5,
|
2024-02-28 09:10:46 -08:00
|
|
|
TotalSamples: 4, // 1 sample per query * 4 steps
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 1,
|
|
|
|
206000: 1,
|
|
|
|
211000: 1,
|
|
|
|
216000: 1,
|
|
|
|
},
|
|
|
|
},
|
2022-02-01 18:07:23 -08:00
|
|
|
{
|
|
|
|
Query: `max_over_time(metricWith3SampleEvery10Seconds{a="1"}[10s])`,
|
|
|
|
Start: time.Unix(991, 0),
|
|
|
|
End: time.Unix(1021, 0),
|
|
|
|
Interval: 10 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 2,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 2, // 1 sample per query * 2 steps with data
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
991000: 1,
|
|
|
|
1001000: 1,
|
|
|
|
1011000: 0,
|
|
|
|
1021000: 0,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `metricWith3SampleEvery10Seconds{a="1"} offset 10s`,
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 4,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 4, // 1 sample per query * 4 steps
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 1,
|
|
|
|
206000: 1,
|
|
|
|
211000: 1,
|
|
|
|
216000: 1,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "max_over_time(metricWith3SampleEvery10Seconds[60s] @ 30)",
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 12,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 48, // @ modifier force the evaluation timestamp at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 3 series * 4 steps
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 12,
|
|
|
|
206000: 12,
|
|
|
|
211000: 12,
|
|
|
|
216000: 12,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `metricWith3SampleEvery10Seconds`,
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 12,
|
2022-02-01 18:07:23 -08:00
|
|
|
Interval: 5 * time.Second,
|
|
|
|
TotalSamples: 12, // 3 sample per query * 4 steps
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 3,
|
|
|
|
206000: 3,
|
|
|
|
211000: 3,
|
|
|
|
216000: 3,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `max_over_time(metricWith3SampleEvery10Seconds[60s])`,
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 18,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 72, // (3 sample / 10 seconds * 60 seconds) * 4 steps = 72
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 18,
|
|
|
|
206000: 18,
|
|
|
|
211000: 18,
|
|
|
|
216000: 18,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "max_over_time(metricWith3SampleEvery10Seconds[60s:5s])",
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 72,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 144, // 3 sample per query * 12 queries (60/5) * 4 steps
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 36,
|
|
|
|
206000: 36,
|
|
|
|
211000: 36,
|
|
|
|
216000: 36,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "max_over_time(metricWith1SampleEvery10Seconds[60s:5s])",
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 32,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 48, // 1 sample per query * 12 queries (60/5) * 4 steps
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 12,
|
|
|
|
206000: 12,
|
|
|
|
211000: 12,
|
|
|
|
216000: 12,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "sum by (b) (max_over_time(metricWith1SampleEvery10Seconds[60s:5s]))",
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 32,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 48, // 1 sample per query * 12 queries (60/5) * 4 steps
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 12,
|
|
|
|
206000: 12,
|
|
|
|
211000: 12,
|
|
|
|
216000: 12,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s])) + sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s]))",
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 76,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 288, // 2 * (3 sample per query * 12 queries (60/5) * 4 steps)
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 72,
|
|
|
|
206000: 72,
|
|
|
|
211000: 72,
|
|
|
|
216000: 72,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s])) + sum(max_over_time(metricWith1SampleEvery10Seconds[60s:5s]))",
|
|
|
|
Start: time.Unix(201, 0),
|
|
|
|
End: time.Unix(220, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2022-02-22 12:30:39 -08:00
|
|
|
PeakSamples: 72,
|
2022-02-01 18:07:23 -08:00
|
|
|
TotalSamples: 192, // (1 sample per query * 12 queries (60/5) + 3 sample per query * 12 queries (60/5)) * 4 steps
|
|
|
|
TotalSamplesPerStep: stats.TotalSamplesPerStep{
|
|
|
|
201000: 48,
|
|
|
|
206000: 48,
|
|
|
|
211000: 48,
|
|
|
|
216000: 48,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}
|
|
|
|
|
|
|
|
for _, c := range cases {
|
|
|
|
t.Run(c.Query, func(t *testing.T) {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts := promql.NewPrometheusQueryOpts(true, 0)
|
2024-05-07 09:14:22 -07:00
|
|
|
engine := promqltest.NewTestEngine(t, true, 0, promqltest.DefaultMaxSamplesPerQuery)
|
2022-02-01 18:07:23 -08:00
|
|
|
|
2022-02-22 12:30:39 -08:00
|
|
|
runQuery := func(expErr error) *stats.Statistics {
|
|
|
|
var err error
|
2024-04-29 05:14:18 -07:00
|
|
|
var qry promql.Query
|
2022-02-22 12:30:39 -08:00
|
|
|
if c.Interval == 0 {
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err = engine.NewInstantQuery(context.Background(), storage, opts, c.Query, c.Start)
|
2022-02-22 12:30:39 -08:00
|
|
|
} else {
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err = engine.NewRangeQuery(context.Background(), storage, opts, c.Query, c.Start, c.End, c.Interval)
|
2022-02-22 12:30:39 -08:00
|
|
|
}
|
|
|
|
require.NoError(t, err)
|
|
|
|
|
2023-08-18 11:48:59 -07:00
|
|
|
res := qry.Exec(context.Background())
|
2022-02-22 12:30:39 -08:00
|
|
|
require.Equal(t, expErr, res.Err)
|
2022-02-01 18:07:23 -08:00
|
|
|
|
2022-02-22 12:30:39 -08:00
|
|
|
return qry.Stats()
|
|
|
|
}
|
2022-02-01 18:07:23 -08:00
|
|
|
|
2022-02-22 12:30:39 -08:00
|
|
|
stats := runQuery(nil)
|
2022-02-01 18:07:23 -08:00
|
|
|
require.Equal(t, c.TotalSamples, stats.Samples.TotalSamples, "Total samples mismatch")
|
|
|
|
require.Equal(t, &c.TotalSamplesPerStep, stats.Samples.TotalSamplesPerStepMap(), "Total samples per time mismatch")
|
2022-02-22 12:30:39 -08:00
|
|
|
require.Equal(t, c.PeakSamples, stats.Samples.PeakSamples, "Peak samples mismatch")
|
|
|
|
|
|
|
|
// Check that the peak is correct by setting the max to one less.
|
|
|
|
if c.SkipMaxCheck {
|
|
|
|
return
|
|
|
|
}
|
2024-05-07 09:14:22 -07:00
|
|
|
engine = promqltest.NewTestEngine(t, true, 0, stats.Samples.PeakSamples-1)
|
2024-04-29 05:14:18 -07:00
|
|
|
runQuery(promql.ErrTooManySamples(env))
|
2022-02-01 18:07:23 -08:00
|
|
|
})
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2018-10-02 04:59:19 -07:00
|
|
|
func TestMaxQuerySamples(t *testing.T) {
|
2024-04-29 05:14:18 -07:00
|
|
|
storage := promqltest.LoadedStorage(t, `
|
2018-10-02 04:59:19 -07:00
|
|
|
load 10s
|
2021-01-20 02:57:39 -08:00
|
|
|
metric 1+1x100
|
|
|
|
bigmetric{a="1"} 1+1x100
|
|
|
|
bigmetric{a="2"} 1+1x100
|
2018-10-02 04:59:19 -07:00
|
|
|
`)
|
2023-08-18 11:48:59 -07:00
|
|
|
t.Cleanup(func() { storage.Close() })
|
2018-10-02 04:59:19 -07:00
|
|
|
|
2021-01-04 01:03:36 -08:00
|
|
|
// These test cases should be touching the limit exactly (hence no exceeding).
|
|
|
|
// Exceeding the limit will be tested by doing -1 to the MaxSamples.
|
2018-10-02 04:59:19 -07:00
|
|
|
cases := []struct {
|
|
|
|
Query string
|
|
|
|
MaxSamples int
|
|
|
|
Start time.Time
|
|
|
|
End time.Time
|
|
|
|
Interval time.Duration
|
|
|
|
}{
|
|
|
|
// Instant queries.
|
|
|
|
{
|
|
|
|
Query: "1",
|
|
|
|
MaxSamples: 1,
|
2021-01-04 01:03:36 -08:00
|
|
|
Start: time.Unix(1, 0),
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2018-10-02 04:59:19 -07:00
|
|
|
Query: "metric",
|
|
|
|
MaxSamples: 1,
|
2021-01-04 01:03:36 -08:00
|
|
|
Start: time.Unix(1, 0),
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2018-10-02 04:59:19 -07:00
|
|
|
Query: "metric[20s]",
|
|
|
|
MaxSamples: 2,
|
2021-01-04 01:03:36 -08:00
|
|
|
Start: time.Unix(10, 0),
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2018-12-22 05:47:13 -08:00
|
|
|
Query: "rate(metric[20s])",
|
|
|
|
MaxSamples: 3,
|
2021-01-04 01:03:36 -08:00
|
|
|
Start: time.Unix(10, 0),
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2018-12-22 05:47:13 -08:00
|
|
|
Query: "metric[20s:5s]",
|
|
|
|
MaxSamples: 3,
|
2021-01-04 01:03:36 -08:00
|
|
|
Start: time.Unix(10, 0),
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
Query: "metric[20s] @ 10",
|
|
|
|
MaxSamples: 2,
|
|
|
|
Start: time.Unix(0, 0),
|
2018-10-02 04:59:19 -07:00
|
|
|
},
|
|
|
|
// Range queries.
|
|
|
|
{
|
|
|
|
Query: "1",
|
|
|
|
MaxSamples: 3,
|
2021-01-04 01:03:36 -08:00
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(2, 0),
|
|
|
|
Interval: time.Second,
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2018-10-02 04:59:19 -07:00
|
|
|
Query: "1",
|
|
|
|
MaxSamples: 3,
|
2021-01-04 01:03:36 -08:00
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(2, 0),
|
|
|
|
Interval: time.Second,
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2018-10-02 04:59:19 -07:00
|
|
|
Query: "metric",
|
|
|
|
MaxSamples: 3,
|
2021-01-04 01:03:36 -08:00
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(2, 0),
|
|
|
|
Interval: time.Second,
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2018-10-02 04:59:19 -07:00
|
|
|
Query: "metric",
|
2021-01-04 01:03:36 -08:00
|
|
|
MaxSamples: 3,
|
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(10, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2020-05-28 05:36:30 -07:00
|
|
|
Query: "rate(bigmetric[1s])",
|
|
|
|
MaxSamples: 1,
|
2021-01-04 01:03:36 -08:00
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(10, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
// Result is duplicated, so @ also produces 3 samples.
|
|
|
|
Query: "metric @ 10",
|
|
|
|
MaxSamples: 3,
|
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(10, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
// The peak samples in memory is during the first evaluation:
|
|
|
|
// - Subquery takes 22 samples, 11 for each bigmetric,
|
|
|
|
// - Result is calculated per series where the series samples is buffered, hence 11 more here.
|
|
|
|
// - The result of two series is added before the last series buffer is discarded, so 2 more here.
|
|
|
|
// Hence at peak it is 22 (subquery) + 11 (buffer of a series) + 2 (result from 2 series).
|
|
|
|
// The subquery samples and the buffer is discarded before duplicating.
|
|
|
|
Query: `rate(bigmetric[10s:1s] @ 10)`,
|
|
|
|
MaxSamples: 35,
|
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(10, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
// Here the reasoning is same as above. But LHS and RHS are done one after another.
|
|
|
|
// So while one of them takes 35 samples at peak, we need to hold the 2 sample
|
|
|
|
// result of the other till then.
|
|
|
|
Query: `rate(bigmetric[10s:1s] @ 10) + rate(bigmetric[10s:1s] @ 30)`,
|
|
|
|
MaxSamples: 37,
|
|
|
|
Start: time.Unix(0, 0),
|
|
|
|
End: time.Unix(10, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2024-04-29 05:14:18 -07:00
|
|
|
// promql.Sample as above but with only 1 part as step invariant.
|
2021-01-20 02:57:39 -08:00
|
|
|
// Here the peak is caused by the non-step invariant part as it touches more time range.
|
|
|
|
// Hence at peak it is 2*21 (subquery from 0s to 20s)
|
|
|
|
// + 11 (buffer of a series per evaluation)
|
|
|
|
// + 6 (result from 2 series at 3 eval times).
|
|
|
|
Query: `rate(bigmetric[10s:1s]) + rate(bigmetric[10s:1s] @ 30)`,
|
|
|
|
MaxSamples: 59,
|
|
|
|
Start: time.Unix(10, 0),
|
|
|
|
End: time.Unix(20, 0),
|
|
|
|
Interval: 5 * time.Second,
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
// Nested subquery.
|
|
|
|
// We saw that innermost rate takes 35 samples which is still the peak
|
|
|
|
// since the other two subqueries just duplicate the result.
|
|
|
|
Query: `rate(rate(bigmetric[10s:1s] @ 10)[100s:25s] @ 1000)[100s:20s] @ 2000`,
|
|
|
|
MaxSamples: 35,
|
|
|
|
Start: time.Unix(10, 0),
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
// Nested subquery.
|
|
|
|
// Now the outmost subquery produces more samples than inner most rate.
|
|
|
|
Query: `rate(rate(bigmetric[10s:1s] @ 10)[100s:25s] @ 1000)[17s:1s] @ 2000`,
|
|
|
|
MaxSamples: 36,
|
|
|
|
Start: time.Unix(10, 0),
|
2020-05-28 05:36:30 -07:00
|
|
|
},
|
2018-10-02 04:59:19 -07:00
|
|
|
}
|
|
|
|
|
|
|
|
for _, c := range cases {
|
2021-01-04 01:03:36 -08:00
|
|
|
t.Run(c.Query, func(t *testing.T) {
|
2024-05-07 09:14:22 -07:00
|
|
|
engine := newTestEngine(t)
|
2021-01-20 02:57:39 -08:00
|
|
|
testFunc := func(expError error) {
|
|
|
|
var err error
|
2024-04-29 05:14:18 -07:00
|
|
|
var qry promql.Query
|
2021-01-20 02:57:39 -08:00
|
|
|
if c.Interval == 0 {
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err = engine.NewInstantQuery(context.Background(), storage, nil, c.Query, c.Start)
|
2021-01-20 02:57:39 -08:00
|
|
|
} else {
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err = engine.NewRangeQuery(context.Background(), storage, nil, c.Query, c.Start, c.End, c.Interval)
|
2021-01-20 02:57:39 -08:00
|
|
|
}
|
|
|
|
require.NoError(t, err)
|
|
|
|
|
2023-08-18 11:48:59 -07:00
|
|
|
res := qry.Exec(context.Background())
|
2022-02-01 18:07:23 -08:00
|
|
|
stats := qry.Stats()
|
2021-01-20 02:57:39 -08:00
|
|
|
require.Equal(t, expError, res.Err)
|
2022-02-01 18:07:23 -08:00
|
|
|
require.NotNil(t, stats)
|
2022-02-22 12:30:39 -08:00
|
|
|
if expError == nil {
|
|
|
|
require.Equal(t, c.MaxSamples, stats.Samples.PeakSamples, "peak samples mismatch for query %q", c.Query)
|
|
|
|
}
|
2021-01-20 02:57:39 -08:00
|
|
|
}
|
2018-10-02 04:59:19 -07:00
|
|
|
|
2021-01-20 02:57:39 -08:00
|
|
|
// Within limit.
|
2024-05-07 09:14:22 -07:00
|
|
|
engine = promqltest.NewTestEngine(t, false, 0, c.MaxSamples)
|
2021-01-20 02:57:39 -08:00
|
|
|
testFunc(nil)
|
|
|
|
|
|
|
|
// Exceeding limit.
|
2024-05-07 09:14:22 -07:00
|
|
|
engine = promqltest.NewTestEngine(t, false, 0, c.MaxSamples-1)
|
2024-04-29 05:14:18 -07:00
|
|
|
testFunc(promql.ErrTooManySamples(env))
|
2021-01-20 02:57:39 -08:00
|
|
|
})
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
func TestAtModifier(t *testing.T) {
|
2024-05-07 09:14:22 -07:00
|
|
|
engine := newTestEngine(t)
|
2024-04-29 05:14:18 -07:00
|
|
|
storage := promqltest.LoadedStorage(t, `
|
2021-01-20 02:57:39 -08:00
|
|
|
load 10s
|
|
|
|
metric{job="1"} 0+1x1000
|
|
|
|
metric{job="2"} 0+2x1000
|
|
|
|
metric_topk{instance="1"} 0+1x1000
|
|
|
|
metric_topk{instance="2"} 0+2x1000
|
|
|
|
metric_topk{instance="3"} 1000-1x1000
|
|
|
|
|
|
|
|
load 1ms
|
|
|
|
metric_ms 0+1x10000
|
|
|
|
`)
|
2023-08-18 11:48:59 -07:00
|
|
|
t.Cleanup(func() { storage.Close() })
|
2021-01-20 02:57:39 -08:00
|
|
|
|
|
|
|
lbls1 := labels.FromStrings("__name__", "metric", "job", "1")
|
|
|
|
lbls2 := labels.FromStrings("__name__", "metric", "job", "2")
|
|
|
|
lblstopk2 := labels.FromStrings("__name__", "metric_topk", "instance", "2")
|
|
|
|
lblstopk3 := labels.FromStrings("__name__", "metric_topk", "instance", "3")
|
|
|
|
lblsms := labels.FromStrings("__name__", "metric_ms")
|
|
|
|
lblsneg := labels.FromStrings("__name__", "metric_neg")
|
|
|
|
|
|
|
|
// Add some samples with negative timestamp.
|
2023-08-18 11:48:59 -07:00
|
|
|
db := storage.DB
|
2021-01-20 02:57:39 -08:00
|
|
|
app := db.Appender(context.Background())
|
2021-02-18 04:07:00 -08:00
|
|
|
ref, err := app.Append(0, lblsneg, -1000000, 1000)
|
2021-01-20 02:57:39 -08:00
|
|
|
require.NoError(t, err)
|
|
|
|
for ts := int64(-1000000 + 1000); ts <= 0; ts += 1000 {
|
2022-07-21 09:23:30 -07:00
|
|
|
_, err := app.Append(ref, labels.EmptyLabels(), ts, -float64(ts/1000)+1)
|
2021-02-18 04:07:00 -08:00
|
|
|
require.NoError(t, err)
|
2021-01-20 02:57:39 -08:00
|
|
|
}
|
2021-02-03 05:43:12 -08:00
|
|
|
|
|
|
|
// To test the fix for https://github.com/prometheus/prometheus/issues/8433.
|
2021-02-18 04:07:00 -08:00
|
|
|
_, err = app.Append(0, labels.FromStrings("__name__", "metric_timestamp"), 3600*1000, 1000)
|
2021-02-03 05:43:12 -08:00
|
|
|
require.NoError(t, err)
|
|
|
|
|
2021-01-20 02:57:39 -08:00
|
|
|
require.NoError(t, app.Commit())
|
2018-10-02 04:59:19 -07:00
|
|
|
|
2021-01-20 02:57:39 -08:00
|
|
|
cases := []struct {
|
|
|
|
query string
|
|
|
|
start, end, interval int64 // Time in seconds.
|
|
|
|
result parser.Value
|
|
|
|
}{
|
|
|
|
{ // Time of the result is the evaluation time.
|
|
|
|
query: `metric_neg @ 0`,
|
|
|
|
start: 100,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Vector{
|
|
|
|
promql.Sample{F: 1, T: 100000, Metric: lblsneg},
|
2021-01-20 02:57:39 -08:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: `metric_neg @ -200`,
|
|
|
|
start: 100,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Vector{
|
|
|
|
promql.Sample{F: 201, T: 100000, Metric: lblsneg},
|
2021-01-20 02:57:39 -08:00
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: `metric{job="2"} @ 50`,
|
|
|
|
start: -2, end: 2, interval: 1,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 10, T: -2000}, {F: 10, T: -1000}, {F: 10, T: 0}, {F: 10, T: 1000}, {F: 10, T: 2000}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lbls2,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, { // Timestamps for matrix selector does not depend on the evaluation time.
|
|
|
|
query: "metric[20s] @ 300",
|
|
|
|
start: 10,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 28, T: 280000}, {F: 29, T: 290000}, {F: 30, T: 300000}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lbls1,
|
|
|
|
},
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 56, T: 280000}, {F: 58, T: 290000}, {F: 60, T: 300000}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lbls2,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: `metric_neg[2s] @ 0`,
|
|
|
|
start: 100,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 3, T: -2000}, {F: 2, T: -1000}, {F: 1, T: 0}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lblsneg,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: `metric_neg[3s] @ -500`,
|
|
|
|
start: 100,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 504, T: -503000}, {F: 503, T: -502000}, {F: 502, T: -501000}, {F: 501, T: -500000}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lblsneg,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: `metric_ms[3ms] @ 2.345`,
|
|
|
|
start: 100,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 2342, T: 2342}, {F: 2343, T: 2343}, {F: 2344, T: 2344}, {F: 2345, T: 2345}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lblsms,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "metric[100s:25s] @ 300",
|
|
|
|
start: 100,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 20, T: 200000}, {F: 22, T: 225000}, {F: 25, T: 250000}, {F: 27, T: 275000}, {F: 30, T: 300000}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lbls1,
|
|
|
|
},
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 40, T: 200000}, {F: 44, T: 225000}, {F: 50, T: 250000}, {F: 54, T: 275000}, {F: 60, T: 300000}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lbls2,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "metric_neg[50s:25s] @ 0",
|
|
|
|
start: 100,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 51, T: -50000}, {F: 26, T: -25000}, {F: 1, T: 0}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lblsneg,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: "metric_neg[50s:25s] @ -100",
|
|
|
|
start: 100,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 151, T: -150000}, {F: 126, T: -125000}, {F: 101, T: -100000}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lblsneg,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: `metric_ms[100ms:25ms] @ 2.345`,
|
|
|
|
start: 100,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 2250, T: 2250}, {F: 2275, T: 2275}, {F: 2300, T: 2300}, {F: 2325, T: 2325}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lblsms,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: `metric_topk and topk(1, sum_over_time(metric_topk[50s] @ 100))`,
|
|
|
|
start: 50, end: 80, interval: 10,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 995, T: 50000}, {F: 994, T: 60000}, {F: 993, T: 70000}, {F: 992, T: 80000}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lblstopk3,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: `metric_topk and topk(1, sum_over_time(metric_topk[50s] @ 5000))`,
|
|
|
|
start: 50, end: 80, interval: 10,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 10, T: 50000}, {F: 12, T: 60000}, {F: 14, T: 70000}, {F: 16, T: 80000}},
|
2021-01-20 02:57:39 -08:00
|
|
|
Metric: lblstopk2,
|
|
|
|
},
|
|
|
|
},
|
2021-02-09 08:03:16 -08:00
|
|
|
}, {
|
|
|
|
query: `metric_topk and topk(1, sum_over_time(metric_topk[50s] @ end()))`,
|
|
|
|
start: 70, end: 100, interval: 10,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 993, T: 70000}, {F: 992, T: 80000}, {F: 991, T: 90000}, {F: 990, T: 100000}},
|
2021-02-09 08:03:16 -08:00
|
|
|
Metric: lblstopk3,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}, {
|
|
|
|
query: `metric_topk and topk(1, sum_over_time(metric_topk[50s] @ start()))`,
|
|
|
|
start: 100, end: 130, interval: 10,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 990, T: 100000}, {F: 989, T: 110000}, {F: 988, T: 120000}, {F: 987, T: 130000}},
|
2021-02-09 08:03:16 -08:00
|
|
|
Metric: lblstopk3,
|
|
|
|
},
|
|
|
|
},
|
2021-02-03 05:43:12 -08:00
|
|
|
}, {
|
|
|
|
// Tests for https://github.com/prometheus/prometheus/issues/8433.
|
|
|
|
// The trick here is that the query range should be > lookback delta.
|
|
|
|
query: `timestamp(metric_timestamp @ 3600)`,
|
|
|
|
start: 0, end: 7 * 60, interval: 60,
|
2024-04-29 05:14:18 -07:00
|
|
|
result: promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{
|
promql: Separate `Point` into `FPoint` and `HPoint`
In other words: Instead of having a “polymorphous” `Point` that can
either contain a float value or a histogram value, use an `FPoint` for
floats and an `HPoint` for histograms.
This seemingly small change has a _lot_ of repercussions throughout
the codebase.
The idea here is to avoid the increase in size of `Point` arrays that
happened after native histograms had been added.
The higher-level data structures (`Sample`, `Series`, etc.) are still
“polymorphous”. The same idea could be applied to them, but at each
step the trade-offs needed to be evaluated.
The idea with this change is to do the minimum necessary to get back
to pre-histogram performance for functions that do not touch
histograms. Here are comparisons for the `changes` function. The test
data doesn't include histograms yet. Ideally, there would be no change
in the benchmark result at all.
First runtime v2.39 compared to directly prior to this commit:
```
name old time/op new time/op delta
RangeQuery/expr=changes(a_one[1d]),steps=1-16 391µs ± 2% 542µs ± 1% +38.58% (p=0.000 n=9+8)
RangeQuery/expr=changes(a_one[1d]),steps=10-16 452µs ± 2% 617µs ± 2% +36.48% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_one[1d]),steps=100-16 1.12ms ± 1% 1.36ms ± 2% +21.58% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_one[1d]),steps=1000-16 7.83ms ± 1% 8.94ms ± 1% +14.21% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_ten[1d]),steps=1-16 2.98ms ± 0% 3.30ms ± 1% +10.67% (p=0.000 n=9+10)
RangeQuery/expr=changes(a_ten[1d]),steps=10-16 3.66ms ± 1% 4.10ms ± 1% +11.82% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_ten[1d]),steps=100-16 10.5ms ± 0% 11.8ms ± 1% +12.50% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_ten[1d]),steps=1000-16 77.6ms ± 1% 87.4ms ± 1% +12.63% (p=0.000 n=9+9)
RangeQuery/expr=changes(a_hundred[1d]),steps=1-16 30.4ms ± 2% 32.8ms ± 1% +8.01% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=10-16 37.1ms ± 2% 40.6ms ± 2% +9.64% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=100-16 105ms ± 1% 117ms ± 1% +11.69% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=1000-16 783ms ± 3% 876ms ± 1% +11.83% (p=0.000 n=9+10)
```
And then runtime v2.39 compared to after this commit:
```
name old time/op new time/op delta
RangeQuery/expr=changes(a_one[1d]),steps=1-16 391µs ± 2% 547µs ± 1% +39.84% (p=0.000 n=9+8)
RangeQuery/expr=changes(a_one[1d]),steps=10-16 452µs ± 2% 616µs ± 2% +36.15% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_one[1d]),steps=100-16 1.12ms ± 1% 1.26ms ± 1% +12.20% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_one[1d]),steps=1000-16 7.83ms ± 1% 7.95ms ± 1% +1.59% (p=0.000 n=10+8)
RangeQuery/expr=changes(a_ten[1d]),steps=1-16 2.98ms ± 0% 3.38ms ± 2% +13.49% (p=0.000 n=9+10)
RangeQuery/expr=changes(a_ten[1d]),steps=10-16 3.66ms ± 1% 4.02ms ± 1% +9.80% (p=0.000 n=10+9)
RangeQuery/expr=changes(a_ten[1d]),steps=100-16 10.5ms ± 0% 10.8ms ± 1% +3.08% (p=0.000 n=8+10)
RangeQuery/expr=changes(a_ten[1d]),steps=1000-16 77.6ms ± 1% 78.1ms ± 1% +0.58% (p=0.035 n=9+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=1-16 30.4ms ± 2% 33.5ms ± 4% +10.18% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=10-16 37.1ms ± 2% 40.0ms ± 1% +7.98% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=100-16 105ms ± 1% 107ms ± 1% +1.92% (p=0.000 n=10+10)
RangeQuery/expr=changes(a_hundred[1d]),steps=1000-16 783ms ± 3% 775ms ± 1% -1.02% (p=0.019 n=9+9)
```
In summary, the runtime doesn't really improve with this change for
queries with just a few steps. For queries with many steps, this
commit essentially reinstates the old performance. This is good
because the many-step queries are the one that matter most (longest
absolute runtime).
In terms of allocations, though, this commit doesn't make a dent at
all (numbers not shown). The reason is that most of the allocations
happen in the sampleRingIterator (in the storage package), which has
to be addressed in a separate commit.
Signed-off-by: beorn7 <beorn@grafana.com>
2022-10-28 07:58:40 -07:00
|
|
|
{F: 3600, T: 0},
|
|
|
|
{F: 3600, T: 60 * 1000},
|
|
|
|
{F: 3600, T: 2 * 60 * 1000},
|
|
|
|
{F: 3600, T: 3 * 60 * 1000},
|
|
|
|
{F: 3600, T: 4 * 60 * 1000},
|
|
|
|
{F: 3600, T: 5 * 60 * 1000},
|
|
|
|
{F: 3600, T: 6 * 60 * 1000},
|
|
|
|
{F: 3600, T: 7 * 60 * 1000},
|
2021-02-03 05:43:12 -08:00
|
|
|
},
|
PromQL engine: Delay deletion of __name__ label to the end of the query evaluation (#14477)
PromQL engine: Delay deletion of __name__ label to the end of the query evaluation
- This change allows optionally preserving the `__name__` label via the `label_replace` and `label_join` functions, and helps prevent the dreaded "vector cannot contain metrics with the same labelset" error.
- The implementation extends the `Series` and `Sample` structs with a boolean flag indicating whether the `__name__` label should be deleted at the end of the query evaluation.
- The `label_replace` and `label_join` functions can still access the value of the `__name__` label, even if it has been previously marked for deletion. If `__name__` is used as target label, it won't be dropped at the end of the query evaluation.
- Fixes https://github.com/prometheus/prometheus/issues/11397
- See https://github.com/jcreixell/prometheus/pull/2 for previous discussion, including the decision to create this PR and benchmark it before considering other alternatives (like refactoring `labels.Labels`).
- See https://github.com/jcreixell/prometheus/pull/1 for an alternative implementation using a special label instead of boolean flags.
- Note: a feature flag `promql-delayed-name-removal` has been added as it changes the behavior of some "weird" queries (see https://github.com/prometheus/prometheus/issues/11397#issuecomment-1451998792)
Example (this always fails, as `__name__` is being dropped by `count_over_time`):
```
count_over_time({__name__!=""}[1m])
=> Error executing query: vector cannot contain metrics with the same labelset
```
Before:
```
label_replace(count_over_time({__name__!=""}[1m]), "__name__", "count_$1", "__name__", "(.+)")
=> Error executing query: vector cannot contain metrics with the same labelset
```
After:
```
label_replace(count_over_time({__name__!=""}[1m]), "__name__", "count_$1", "__name__", "(.+)")
=>
count_go_gc_cycles_automatic_gc_cycles_total{instance="localhost:9090", job="prometheus"} 1
count_go_gc_cycles_forced_gc_cycles_total{instance="localhost:9090", job="prometheus"} 1
...
```
Signed-off-by: Jorge Creixell <jcreixell@gmail.com>
---------
Signed-off-by: Jorge Creixell <jcreixell@gmail.com>
Signed-off-by: Björn Rabenstein <github@rabenste.in>
2024-08-29 06:50:39 -07:00
|
|
|
Metric: labels.EmptyLabels(),
|
|
|
|
DropName: true,
|
2021-02-03 05:43:12 -08:00
|
|
|
},
|
|
|
|
},
|
2021-01-20 02:57:39 -08:00
|
|
|
},
|
|
|
|
}
|
|
|
|
|
|
|
|
for _, c := range cases {
|
|
|
|
t.Run(c.query, func(t *testing.T) {
|
|
|
|
if c.interval == 0 {
|
|
|
|
c.interval = 1
|
|
|
|
}
|
|
|
|
start, end, interval := time.Unix(c.start, 0), time.Unix(c.end, 0), time.Duration(c.interval)*time.Second
|
|
|
|
var err error
|
2024-04-29 05:14:18 -07:00
|
|
|
var qry promql.Query
|
2021-01-20 02:57:39 -08:00
|
|
|
if c.end == 0 {
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err = engine.NewInstantQuery(context.Background(), storage, nil, c.query, start)
|
2021-01-04 01:03:36 -08:00
|
|
|
} else {
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err = engine.NewRangeQuery(context.Background(), storage, nil, c.query, start, end, interval)
|
2021-01-04 01:03:36 -08:00
|
|
|
}
|
|
|
|
require.NoError(t, err)
|
2019-10-09 17:06:53 -07:00
|
|
|
|
2023-08-18 11:48:59 -07:00
|
|
|
res := qry.Exec(context.Background())
|
2021-01-04 01:03:36 -08:00
|
|
|
require.NoError(t, res.Err)
|
2024-04-29 05:14:18 -07:00
|
|
|
if expMat, ok := c.result.(promql.Matrix); ok {
|
2021-01-24 06:53:30 -08:00
|
|
|
sort.Sort(expMat)
|
2024-04-29 05:14:18 -07:00
|
|
|
sort.Sort(res.Value.(promql.Matrix))
|
2021-01-24 06:53:30 -08:00
|
|
|
}
|
2023-04-16 05:13:31 -07:00
|
|
|
testutil.RequireEqual(t, c.result, res.Value, "query %q failed", c.query)
|
2021-01-04 01:03:36 -08:00
|
|
|
})
|
2018-10-02 04:59:19 -07:00
|
|
|
}
|
|
|
|
}
|
2021-02-03 05:43:12 -08:00
|
|
|
|
2018-12-22 05:47:13 -08:00
|
|
|
func TestSubquerySelector(t *testing.T) {
|
2020-07-23 15:05:43 -07:00
|
|
|
type caseType struct {
|
|
|
|
Query string
|
2024-04-29 05:14:18 -07:00
|
|
|
Result promql.Result
|
2020-07-23 15:05:43 -07:00
|
|
|
Start time.Time
|
|
|
|
}
|
|
|
|
|
|
|
|
for _, tst := range []struct {
|
2018-12-22 05:47:13 -08:00
|
|
|
loadString string
|
2020-07-23 15:05:43 -07:00
|
|
|
cases []caseType
|
2018-12-22 05:47:13 -08:00
|
|
|
}{
|
|
|
|
{
|
|
|
|
loadString: `load 10s
|
|
|
|
metric 1 2`,
|
2020-07-23 15:05:43 -07:00
|
|
|
cases: []caseType{
|
2018-12-22 05:47:13 -08:00
|
|
|
{
|
|
|
|
Query: "metric[20s:10s]",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 1, T: 0}, {F: 2, T: 10000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(10, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metric[20s:5s]",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 1, T: 0}, {F: 1, T: 5000}, {F: 2, T: 10000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(10, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metric[20s:5s] offset 2s",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 1, T: 0}, {F: 1, T: 5000}, {F: 2, T: 10000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(12, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metric[20s:5s] offset 6s",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 1, T: 0}, {F: 1, T: 5000}, {F: 2, T: 10000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(20, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metric[20s:5s] offset 4s",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 2, T: 15000}, {F: 2, T: 20000}, {F: 2, T: 25000}, {F: 2, T: 30000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(35, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metric[20s:5s] offset 5s",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 2, T: 10000}, {F: 2, T: 15000}, {F: 2, T: 20000}, {F: 2, T: 25000}, {F: 2, T: 30000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(35, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metric[20s:5s] offset 6s",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 2, T: 10000}, {F: 2, T: 15000}, {F: 2, T: 20000}, {F: 2, T: 25000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(35, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: "metric[20s:5s] offset 7s",
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 2, T: 10000}, {F: 2, T: 15000}, {F: 2, T: 20000}, {F: 2, T: 25000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "metric"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(35, 0),
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
loadString: `load 10s
|
|
|
|
http_requests{job="api-server", instance="0", group="production"} 0+10x1000 100+30x1000
|
|
|
|
http_requests{job="api-server", instance="1", group="production"} 0+20x1000 200+30x1000
|
|
|
|
http_requests{job="api-server", instance="0", group="canary"} 0+30x1000 300+80x1000
|
|
|
|
http_requests{job="api-server", instance="1", group="canary"} 0+40x2000`,
|
2020-07-23 15:05:43 -07:00
|
|
|
cases: []caseType{
|
2018-12-22 05:47:13 -08:00
|
|
|
{ // Normal selector.
|
|
|
|
Query: `http_requests{group=~"pro.*",instance="0"}[30s:10s]`,
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 9990, T: 9990000}, {F: 10000, T: 10000000}, {F: 100, T: 10010000}, {F: 130, T: 10020000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "http_requests", "job", "api-server", "instance", "0", "group", "production"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(10020, 0),
|
|
|
|
},
|
|
|
|
{ // Default step.
|
|
|
|
Query: `http_requests{group=~"pro.*",instance="0"}[5m:]`,
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 9840, T: 9840000}, {F: 9900, T: 9900000}, {F: 9960, T: 9960000}, {F: 130, T: 10020000}, {F: 310, T: 10080000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "http_requests", "job", "api-server", "instance", "0", "group", "production"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(10100, 0),
|
|
|
|
},
|
|
|
|
{ // Checking if high offset (>LookbackDelta) is being taken care of.
|
|
|
|
Query: `http_requests{group=~"pro.*",instance="0"}[5m:] offset 20m`,
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 8640, T: 8640000}, {F: 8700, T: 8700000}, {F: 8760, T: 8760000}, {F: 8820, T: 8820000}, {F: 8880, T: 8880000}},
|
2021-10-22 01:06:44 -07:00
|
|
|
Metric: labels.FromStrings("__name__", "http_requests", "job", "api-server", "instance", "0", "group", "production"),
|
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(10100, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `rate(http_requests[1m])[15s:5s]`,
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
PromQL engine: Delay deletion of __name__ label to the end of the query evaluation (#14477)
PromQL engine: Delay deletion of __name__ label to the end of the query evaluation
- This change allows optionally preserving the `__name__` label via the `label_replace` and `label_join` functions, and helps prevent the dreaded "vector cannot contain metrics with the same labelset" error.
- The implementation extends the `Series` and `Sample` structs with a boolean flag indicating whether the `__name__` label should be deleted at the end of the query evaluation.
- The `label_replace` and `label_join` functions can still access the value of the `__name__` label, even if it has been previously marked for deletion. If `__name__` is used as target label, it won't be dropped at the end of the query evaluation.
- Fixes https://github.com/prometheus/prometheus/issues/11397
- See https://github.com/jcreixell/prometheus/pull/2 for previous discussion, including the decision to create this PR and benchmark it before considering other alternatives (like refactoring `labels.Labels`).
- See https://github.com/jcreixell/prometheus/pull/1 for an alternative implementation using a special label instead of boolean flags.
- Note: a feature flag `promql-delayed-name-removal` has been added as it changes the behavior of some "weird" queries (see https://github.com/prometheus/prometheus/issues/11397#issuecomment-1451998792)
Example (this always fails, as `__name__` is being dropped by `count_over_time`):
```
count_over_time({__name__!=""}[1m])
=> Error executing query: vector cannot contain metrics with the same labelset
```
Before:
```
label_replace(count_over_time({__name__!=""}[1m]), "__name__", "count_$1", "__name__", "(.+)")
=> Error executing query: vector cannot contain metrics with the same labelset
```
After:
```
label_replace(count_over_time({__name__!=""}[1m]), "__name__", "count_$1", "__name__", "(.+)")
=>
count_go_gc_cycles_automatic_gc_cycles_total{instance="localhost:9090", job="prometheus"} 1
count_go_gc_cycles_forced_gc_cycles_total{instance="localhost:9090", job="prometheus"} 1
...
```
Signed-off-by: Jorge Creixell <jcreixell@gmail.com>
---------
Signed-off-by: Jorge Creixell <jcreixell@gmail.com>
Signed-off-by: Björn Rabenstein <github@rabenste.in>
2024-08-29 06:50:39 -07:00
|
|
|
Floats: []promql.FPoint{{F: 3, T: 7985000}, {F: 3, T: 7990000}, {F: 3, T: 7995000}, {F: 3, T: 8000000}},
|
|
|
|
Metric: labels.FromStrings("job", "api-server", "instance", "0", "group", "canary"),
|
|
|
|
DropName: true,
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Series{
|
PromQL engine: Delay deletion of __name__ label to the end of the query evaluation (#14477)
PromQL engine: Delay deletion of __name__ label to the end of the query evaluation
- This change allows optionally preserving the `__name__` label via the `label_replace` and `label_join` functions, and helps prevent the dreaded "vector cannot contain metrics with the same labelset" error.
- The implementation extends the `Series` and `Sample` structs with a boolean flag indicating whether the `__name__` label should be deleted at the end of the query evaluation.
- The `label_replace` and `label_join` functions can still access the value of the `__name__` label, even if it has been previously marked for deletion. If `__name__` is used as target label, it won't be dropped at the end of the query evaluation.
- Fixes https://github.com/prometheus/prometheus/issues/11397
- See https://github.com/jcreixell/prometheus/pull/2 for previous discussion, including the decision to create this PR and benchmark it before considering other alternatives (like refactoring `labels.Labels`).
- See https://github.com/jcreixell/prometheus/pull/1 for an alternative implementation using a special label instead of boolean flags.
- Note: a feature flag `promql-delayed-name-removal` has been added as it changes the behavior of some "weird" queries (see https://github.com/prometheus/prometheus/issues/11397#issuecomment-1451998792)
Example (this always fails, as `__name__` is being dropped by `count_over_time`):
```
count_over_time({__name__!=""}[1m])
=> Error executing query: vector cannot contain metrics with the same labelset
```
Before:
```
label_replace(count_over_time({__name__!=""}[1m]), "__name__", "count_$1", "__name__", "(.+)")
=> Error executing query: vector cannot contain metrics with the same labelset
```
After:
```
label_replace(count_over_time({__name__!=""}[1m]), "__name__", "count_$1", "__name__", "(.+)")
=>
count_go_gc_cycles_automatic_gc_cycles_total{instance="localhost:9090", job="prometheus"} 1
count_go_gc_cycles_forced_gc_cycles_total{instance="localhost:9090", job="prometheus"} 1
...
```
Signed-off-by: Jorge Creixell <jcreixell@gmail.com>
---------
Signed-off-by: Jorge Creixell <jcreixell@gmail.com>
Signed-off-by: Björn Rabenstein <github@rabenste.in>
2024-08-29 06:50:39 -07:00
|
|
|
Floats: []promql.FPoint{{F: 4, T: 7985000}, {F: 4, T: 7990000}, {F: 4, T: 7995000}, {F: 4, T: 8000000}},
|
|
|
|
Metric: labels.FromStrings("job", "api-server", "instance", "1", "group", "canary"),
|
|
|
|
DropName: true,
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Series{
|
PromQL engine: Delay deletion of __name__ label to the end of the query evaluation (#14477)
PromQL engine: Delay deletion of __name__ label to the end of the query evaluation
- This change allows optionally preserving the `__name__` label via the `label_replace` and `label_join` functions, and helps prevent the dreaded "vector cannot contain metrics with the same labelset" error.
- The implementation extends the `Series` and `Sample` structs with a boolean flag indicating whether the `__name__` label should be deleted at the end of the query evaluation.
- The `label_replace` and `label_join` functions can still access the value of the `__name__` label, even if it has been previously marked for deletion. If `__name__` is used as target label, it won't be dropped at the end of the query evaluation.
- Fixes https://github.com/prometheus/prometheus/issues/11397
- See https://github.com/jcreixell/prometheus/pull/2 for previous discussion, including the decision to create this PR and benchmark it before considering other alternatives (like refactoring `labels.Labels`).
- See https://github.com/jcreixell/prometheus/pull/1 for an alternative implementation using a special label instead of boolean flags.
- Note: a feature flag `promql-delayed-name-removal` has been added as it changes the behavior of some "weird" queries (see https://github.com/prometheus/prometheus/issues/11397#issuecomment-1451998792)
Example (this always fails, as `__name__` is being dropped by `count_over_time`):
```
count_over_time({__name__!=""}[1m])
=> Error executing query: vector cannot contain metrics with the same labelset
```
Before:
```
label_replace(count_over_time({__name__!=""}[1m]), "__name__", "count_$1", "__name__", "(.+)")
=> Error executing query: vector cannot contain metrics with the same labelset
```
After:
```
label_replace(count_over_time({__name__!=""}[1m]), "__name__", "count_$1", "__name__", "(.+)")
=>
count_go_gc_cycles_automatic_gc_cycles_total{instance="localhost:9090", job="prometheus"} 1
count_go_gc_cycles_forced_gc_cycles_total{instance="localhost:9090", job="prometheus"} 1
...
```
Signed-off-by: Jorge Creixell <jcreixell@gmail.com>
---------
Signed-off-by: Jorge Creixell <jcreixell@gmail.com>
Signed-off-by: Björn Rabenstein <github@rabenste.in>
2024-08-29 06:50:39 -07:00
|
|
|
Floats: []promql.FPoint{{F: 1, T: 7985000}, {F: 1, T: 7990000}, {F: 1, T: 7995000}, {F: 1, T: 8000000}},
|
|
|
|
Metric: labels.FromStrings("job", "api-server", "instance", "0", "group", "production"),
|
|
|
|
DropName: true,
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Series{
|
PromQL engine: Delay deletion of __name__ label to the end of the query evaluation (#14477)
PromQL engine: Delay deletion of __name__ label to the end of the query evaluation
- This change allows optionally preserving the `__name__` label via the `label_replace` and `label_join` functions, and helps prevent the dreaded "vector cannot contain metrics with the same labelset" error.
- The implementation extends the `Series` and `Sample` structs with a boolean flag indicating whether the `__name__` label should be deleted at the end of the query evaluation.
- The `label_replace` and `label_join` functions can still access the value of the `__name__` label, even if it has been previously marked for deletion. If `__name__` is used as target label, it won't be dropped at the end of the query evaluation.
- Fixes https://github.com/prometheus/prometheus/issues/11397
- See https://github.com/jcreixell/prometheus/pull/2 for previous discussion, including the decision to create this PR and benchmark it before considering other alternatives (like refactoring `labels.Labels`).
- See https://github.com/jcreixell/prometheus/pull/1 for an alternative implementation using a special label instead of boolean flags.
- Note: a feature flag `promql-delayed-name-removal` has been added as it changes the behavior of some "weird" queries (see https://github.com/prometheus/prometheus/issues/11397#issuecomment-1451998792)
Example (this always fails, as `__name__` is being dropped by `count_over_time`):
```
count_over_time({__name__!=""}[1m])
=> Error executing query: vector cannot contain metrics with the same labelset
```
Before:
```
label_replace(count_over_time({__name__!=""}[1m]), "__name__", "count_$1", "__name__", "(.+)")
=> Error executing query: vector cannot contain metrics with the same labelset
```
After:
```
label_replace(count_over_time({__name__!=""}[1m]), "__name__", "count_$1", "__name__", "(.+)")
=>
count_go_gc_cycles_automatic_gc_cycles_total{instance="localhost:9090", job="prometheus"} 1
count_go_gc_cycles_forced_gc_cycles_total{instance="localhost:9090", job="prometheus"} 1
...
```
Signed-off-by: Jorge Creixell <jcreixell@gmail.com>
---------
Signed-off-by: Jorge Creixell <jcreixell@gmail.com>
Signed-off-by: Björn Rabenstein <github@rabenste.in>
2024-08-29 06:50:39 -07:00
|
|
|
Floats: []promql.FPoint{{F: 2, T: 7985000}, {F: 2, T: 7990000}, {F: 2, T: 7995000}, {F: 2, T: 8000000}},
|
|
|
|
Metric: labels.FromStrings("job", "api-server", "instance", "1", "group", "production"),
|
|
|
|
DropName: true,
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(8000, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `sum(http_requests{group=~"pro.*"})[30s:10s]`,
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 270, T: 90000}, {F: 300, T: 100000}, {F: 330, T: 110000}, {F: 360, T: 120000}},
|
2022-07-21 09:23:30 -07:00
|
|
|
Metric: labels.EmptyLabels(),
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(120, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `sum(http_requests)[40s:10s]`,
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 800, T: 80000}, {F: 900, T: 90000}, {F: 1000, T: 100000}, {F: 1100, T: 110000}, {F: 1200, T: 120000}},
|
2022-07-21 09:23:30 -07:00
|
|
|
Metric: labels.EmptyLabels(),
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(120, 0),
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Query: `(sum(http_requests{group=~"p.*"})+sum(http_requests{group=~"c.*"}))[20s:5s]`,
|
2024-04-29 05:14:18 -07:00
|
|
|
Result: promql.Result{
|
2018-12-22 05:47:13 -08:00
|
|
|
nil,
|
2024-04-29 05:14:18 -07:00
|
|
|
promql.Matrix{
|
|
|
|
promql.Series{
|
|
|
|
Floats: []promql.FPoint{{F: 1000, T: 100000}, {F: 1000, T: 105000}, {F: 1100, T: 110000}, {F: 1100, T: 115000}, {F: 1200, T: 120000}},
|
2022-07-21 09:23:30 -07:00
|
|
|
Metric: labels.EmptyLabels(),
|
2021-10-22 01:06:44 -07:00
|
|
|
},
|
2018-12-22 05:47:13 -08:00
|
|
|
},
|
|
|
|
nil,
|
|
|
|
},
|
|
|
|
Start: time.Unix(120, 0),
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2020-07-23 15:05:43 -07:00
|
|
|
} {
|
2020-07-22 06:39:51 -07:00
|
|
|
t.Run("", func(t *testing.T) {
|
2024-05-07 09:14:22 -07:00
|
|
|
engine := newTestEngine(t)
|
2024-04-29 05:14:18 -07:00
|
|
|
storage := promqltest.LoadedStorage(t, tst.loadString)
|
2023-08-18 11:48:59 -07:00
|
|
|
t.Cleanup(func() { storage.Close() })
|
2020-07-22 06:39:51 -07:00
|
|
|
|
|
|
|
for _, c := range tst.cases {
|
|
|
|
t.Run(c.Query, func(t *testing.T) {
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, c.Query, c.Start)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.NoError(t, err)
|
2020-07-22 06:39:51 -07:00
|
|
|
|
2023-08-18 11:48:59 -07:00
|
|
|
res := qry.Exec(context.Background())
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Equal(t, c.Result.Err, res.Err)
|
2024-04-29 05:14:18 -07:00
|
|
|
mat := res.Value.(promql.Matrix)
|
2020-07-22 06:39:51 -07:00
|
|
|
sort.Sort(mat)
|
2023-04-16 05:13:31 -07:00
|
|
|
testutil.RequireEqual(t, c.Result.Value, mat)
|
2020-07-22 06:39:51 -07:00
|
|
|
})
|
|
|
|
}
|
|
|
|
})
|
2018-12-22 05:47:13 -08:00
|
|
|
}
|
|
|
|
}
|
2020-01-08 05:28:43 -08:00
|
|
|
|
|
|
|
type FakeQueryLogger struct {
|
|
|
|
closed bool
|
|
|
|
logs []interface{}
|
|
|
|
}
|
|
|
|
|
|
|
|
func NewFakeQueryLogger() *FakeQueryLogger {
|
|
|
|
return &FakeQueryLogger{
|
|
|
|
closed: false,
|
|
|
|
logs: make([]interface{}, 0),
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
func (f *FakeQueryLogger) Close() error {
|
|
|
|
f.closed = true
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
|
|
|
|
func (f *FakeQueryLogger) Log(l ...interface{}) error {
|
|
|
|
f.logs = append(f.logs, l...)
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
|
|
|
|
func TestQueryLogger_basic(t *testing.T) {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts := promql.EngineOpts{
|
2020-01-28 12:38:49 -08:00
|
|
|
Logger: nil,
|
|
|
|
Reg: nil,
|
|
|
|
MaxSamples: 10,
|
|
|
|
Timeout: 10 * time.Second,
|
2020-01-08 05:28:43 -08:00
|
|
|
}
|
2024-07-14 04:28:59 -07:00
|
|
|
engine := promqltest.NewTestEngineWithOpts(t, opts)
|
2020-01-08 05:28:43 -08:00
|
|
|
|
|
|
|
queryExec := func() {
|
|
|
|
ctx, cancelCtx := context.WithCancel(context.Background())
|
|
|
|
defer cancelCtx()
|
2024-04-29 05:14:18 -07:00
|
|
|
query := engine.NewTestQuery(func(ctx context.Context) error {
|
2020-01-08 05:28:43 -08:00
|
|
|
return contextDone(ctx, "test statement execution")
|
|
|
|
})
|
|
|
|
res := query.Exec(ctx)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.NoError(t, res.Err)
|
2020-01-08 05:28:43 -08:00
|
|
|
}
|
|
|
|
|
2024-04-29 05:14:18 -07:00
|
|
|
// promql.Query works without query log initialized.
|
2020-01-08 05:28:43 -08:00
|
|
|
queryExec()
|
|
|
|
|
|
|
|
f1 := NewFakeQueryLogger()
|
|
|
|
engine.SetQueryLogger(f1)
|
|
|
|
queryExec()
|
2020-01-27 01:53:10 -08:00
|
|
|
for i, field := range []interface{}{"params", map[string]interface{}{"query": "test statement"}} {
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Equal(t, field, f1.logs[i])
|
2020-01-08 05:28:43 -08:00
|
|
|
}
|
|
|
|
|
|
|
|
l := len(f1.logs)
|
|
|
|
queryExec()
|
2023-12-07 03:35:01 -08:00
|
|
|
require.Len(t, f1.logs, 2*l)
|
2020-01-08 05:28:43 -08:00
|
|
|
|
|
|
|
// Test that we close the query logger when unsetting it.
|
2020-10-29 02:43:23 -07:00
|
|
|
require.False(t, f1.closed, "expected f1 to be open, got closed")
|
2020-01-08 05:28:43 -08:00
|
|
|
engine.SetQueryLogger(nil)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.True(t, f1.closed, "expected f1 to be closed, got open")
|
2020-01-08 05:28:43 -08:00
|
|
|
queryExec()
|
|
|
|
|
|
|
|
// Test that we close the query logger when swapping.
|
|
|
|
f2 := NewFakeQueryLogger()
|
|
|
|
f3 := NewFakeQueryLogger()
|
|
|
|
engine.SetQueryLogger(f2)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.False(t, f2.closed, "expected f2 to be open, got closed")
|
2020-01-08 05:28:43 -08:00
|
|
|
queryExec()
|
|
|
|
engine.SetQueryLogger(f3)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.True(t, f2.closed, "expected f2 to be closed, got open")
|
|
|
|
require.False(t, f3.closed, "expected f3 to be open, got closed")
|
2020-01-08 05:28:43 -08:00
|
|
|
queryExec()
|
|
|
|
}
|
|
|
|
|
|
|
|
func TestQueryLogger_fields(t *testing.T) {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts := promql.EngineOpts{
|
2020-01-28 12:38:49 -08:00
|
|
|
Logger: nil,
|
|
|
|
Reg: nil,
|
|
|
|
MaxSamples: 10,
|
|
|
|
Timeout: 10 * time.Second,
|
2020-01-08 05:28:43 -08:00
|
|
|
}
|
2024-07-14 04:28:59 -07:00
|
|
|
engine := promqltest.NewTestEngineWithOpts(t, opts)
|
2020-01-08 05:28:43 -08:00
|
|
|
|
|
|
|
f1 := NewFakeQueryLogger()
|
|
|
|
engine.SetQueryLogger(f1)
|
|
|
|
|
|
|
|
ctx, cancelCtx := context.WithCancel(context.Background())
|
2024-04-29 05:14:18 -07:00
|
|
|
ctx = promql.NewOriginContext(ctx, map[string]interface{}{"foo": "bar"})
|
2020-01-08 05:28:43 -08:00
|
|
|
defer cancelCtx()
|
2024-04-29 05:14:18 -07:00
|
|
|
query := engine.NewTestQuery(func(ctx context.Context) error {
|
2020-01-08 05:28:43 -08:00
|
|
|
return contextDone(ctx, "test statement execution")
|
|
|
|
})
|
|
|
|
|
|
|
|
res := query.Exec(ctx)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.NoError(t, res.Err)
|
2020-01-08 05:28:43 -08:00
|
|
|
|
|
|
|
expected := []string{"foo", "bar"}
|
|
|
|
for i, field := range expected {
|
|
|
|
v := f1.logs[len(f1.logs)-len(expected)+i].(string)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Equal(t, field, v)
|
2020-01-08 05:28:43 -08:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
func TestQueryLogger_error(t *testing.T) {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts := promql.EngineOpts{
|
2020-01-28 12:38:49 -08:00
|
|
|
Logger: nil,
|
|
|
|
Reg: nil,
|
|
|
|
MaxSamples: 10,
|
|
|
|
Timeout: 10 * time.Second,
|
2020-01-08 05:28:43 -08:00
|
|
|
}
|
2024-07-14 04:28:59 -07:00
|
|
|
engine := promqltest.NewTestEngineWithOpts(t, opts)
|
2020-01-08 05:28:43 -08:00
|
|
|
|
|
|
|
f1 := NewFakeQueryLogger()
|
|
|
|
engine.SetQueryLogger(f1)
|
|
|
|
|
|
|
|
ctx, cancelCtx := context.WithCancel(context.Background())
|
2024-04-29 05:14:18 -07:00
|
|
|
ctx = promql.NewOriginContext(ctx, map[string]interface{}{"foo": "bar"})
|
2020-01-08 05:28:43 -08:00
|
|
|
defer cancelCtx()
|
|
|
|
testErr := errors.New("failure")
|
2024-04-29 05:14:18 -07:00
|
|
|
query := engine.NewTestQuery(func(ctx context.Context) error {
|
2020-01-08 05:28:43 -08:00
|
|
|
return testErr
|
|
|
|
})
|
|
|
|
|
|
|
|
res := query.Exec(ctx)
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Error(t, res.Err, "query should have failed")
|
2020-01-08 05:28:43 -08:00
|
|
|
|
2020-01-27 01:53:10 -08:00
|
|
|
for i, field := range []interface{}{"params", map[string]interface{}{"query": "test statement"}, "error", testErr} {
|
2020-10-29 02:43:23 -07:00
|
|
|
require.Equal(t, f1.logs[i], field)
|
2020-01-08 05:28:43 -08:00
|
|
|
}
|
|
|
|
}
|
2021-01-20 02:57:39 -08:00
|
|
|
|
2021-02-09 08:03:16 -08:00
|
|
|
func TestPreprocessAndWrapWithStepInvariantExpr(t *testing.T) {
|
|
|
|
startTime := time.Unix(1000, 0)
|
|
|
|
endTime := time.Unix(9999, 0)
|
2021-10-22 01:06:44 -07:00
|
|
|
testCases := []struct {
|
2021-11-10 06:46:24 -08:00
|
|
|
input string // The input to be parsed.
|
|
|
|
expected parser.Expr // The expected expression AST.
|
|
|
|
outputTest bool
|
2021-01-20 02:57:39 -08:00
|
|
|
}{
|
|
|
|
{
|
|
|
|
input: "123.4567",
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.NumberLiteral{
|
|
|
|
Val: 123.4567,
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{Start: 0, End: 8},
|
2021-01-20 02:57:39 -08:00
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: `"foo"`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.StringLiteral{
|
|
|
|
Val: "foo",
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{Start: 0, End: 5},
|
2021-01-20 02:57:39 -08:00
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "foo * bar",
|
|
|
|
expected: &parser.BinaryExpr{
|
|
|
|
Op: parser.MUL,
|
|
|
|
LHS: &parser.VectorSelector{
|
|
|
|
Name: "foo",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 3,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
RHS: &parser.VectorSelector{
|
|
|
|
Name: "bar",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "bar"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 6,
|
|
|
|
End: 9,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
VectorMatching: &parser.VectorMatching{Card: parser.CardOneToOne},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "foo * bar @ 10",
|
|
|
|
expected: &parser.BinaryExpr{
|
|
|
|
Op: parser.MUL,
|
|
|
|
LHS: &parser.VectorSelector{
|
|
|
|
Name: "foo",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 3,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
RHS: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "bar",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "bar"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 6,
|
|
|
|
End: 14,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(10000),
|
|
|
|
},
|
|
|
|
},
|
|
|
|
VectorMatching: &parser.VectorMatching{Card: parser.CardOneToOne},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "foo @ 20 * bar @ 10",
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.BinaryExpr{
|
|
|
|
Op: parser.MUL,
|
|
|
|
LHS: &parser.VectorSelector{
|
|
|
|
Name: "foo",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 8,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(20000),
|
|
|
|
},
|
|
|
|
RHS: &parser.VectorSelector{
|
|
|
|
Name: "bar",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "bar"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 11,
|
|
|
|
End: 19,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(10000),
|
|
|
|
},
|
|
|
|
VectorMatching: &parser.VectorMatching{Card: parser.CardOneToOne},
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "test[5s]",
|
|
|
|
expected: &parser.MatrixSelector{
|
|
|
|
VectorSelector: &parser.VectorSelector{
|
|
|
|
Name: "test",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "test"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 4,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 5 * time.Second,
|
|
|
|
EndPos: 8,
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: `test{a="b"}[5y] @ 1603774699`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.MatrixSelector{
|
|
|
|
VectorSelector: &parser.VectorSelector{
|
|
|
|
Name: "test",
|
|
|
|
Timestamp: makeInt64Pointer(1603774699000),
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "a", "b"),
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "test"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 11,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 5 * 365 * 24 * time.Hour,
|
|
|
|
EndPos: 28,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "sum by (foo)(some_metric)",
|
|
|
|
expected: &parser.AggregateExpr{
|
|
|
|
Op: parser.SUM,
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "some_metric",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 13,
|
|
|
|
End: 24,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Grouping: []string{"foo"},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 25,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "sum by (foo)(some_metric @ 10)",
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.AggregateExpr{
|
|
|
|
Op: parser.SUM,
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "some_metric",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 13,
|
|
|
|
End: 29,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(10000),
|
|
|
|
},
|
|
|
|
Grouping: []string{"foo"},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 30,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "sum(some_metric1 @ 10) + sum(some_metric2 @ 20)",
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.BinaryExpr{
|
|
|
|
Op: parser.ADD,
|
|
|
|
VectorMatching: &parser.VectorMatching{},
|
|
|
|
LHS: &parser.AggregateExpr{
|
|
|
|
Op: parser.SUM,
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "some_metric1",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric1"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 4,
|
|
|
|
End: 21,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(10000),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 22,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
RHS: &parser.AggregateExpr{
|
|
|
|
Op: parser.SUM,
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "some_metric2",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric2"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 29,
|
|
|
|
End: 46,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(20000),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 25,
|
|
|
|
End: 47,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "some_metric and topk(5, rate(some_metric[1m] @ 20))",
|
|
|
|
expected: &parser.BinaryExpr{
|
|
|
|
Op: parser.LAND,
|
|
|
|
VectorMatching: &parser.VectorMatching{
|
|
|
|
Card: parser.CardManyToMany,
|
|
|
|
},
|
|
|
|
LHS: &parser.VectorSelector{
|
|
|
|
Name: "some_metric",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 11,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
RHS: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.AggregateExpr{
|
|
|
|
Op: parser.TOPK,
|
|
|
|
Expr: &parser.Call{
|
|
|
|
Func: parser.MustGetFunction("rate"),
|
|
|
|
Args: parser.Expressions{
|
|
|
|
&parser.MatrixSelector{
|
|
|
|
VectorSelector: &parser.VectorSelector{
|
|
|
|
Name: "some_metric",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 29,
|
|
|
|
End: 40,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(20000),
|
|
|
|
},
|
|
|
|
Range: 1 * time.Minute,
|
|
|
|
EndPos: 49,
|
|
|
|
},
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 24,
|
|
|
|
End: 50,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Param: &parser.NumberLiteral{
|
|
|
|
Val: 5,
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 21,
|
|
|
|
End: 22,
|
|
|
|
},
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 16,
|
|
|
|
End: 51,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "time()",
|
|
|
|
expected: &parser.Call{
|
|
|
|
Func: parser.MustGetFunction("time"),
|
|
|
|
Args: parser.Expressions{},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 6,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: `foo{bar="baz"}[10m:6s]`,
|
|
|
|
expected: &parser.SubqueryExpr{
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "foo",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "bar", "baz"),
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 14,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 10 * time.Minute,
|
|
|
|
Step: 6 * time.Second,
|
|
|
|
EndPos: 22,
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: `foo{bar="baz"}[10m:6s] @ 10`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.SubqueryExpr{
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "foo",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "bar", "baz"),
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 14,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 10 * time.Minute,
|
|
|
|
Step: 6 * time.Second,
|
|
|
|
Timestamp: makeInt64Pointer(10000),
|
|
|
|
EndPos: 27,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{ // Even though the subquery is step invariant, the inside is also wrapped separately.
|
2021-01-20 02:57:39 -08:00
|
|
|
input: `sum(foo{bar="baz"} @ 20)[10m:6s] @ 10`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.SubqueryExpr{
|
|
|
|
Expr: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.AggregateExpr{
|
|
|
|
Op: parser.SUM,
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "foo",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "bar", "baz"),
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 4,
|
|
|
|
End: 23,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(20000),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 24,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 10 * time.Minute,
|
|
|
|
Step: 6 * time.Second,
|
|
|
|
Timestamp: makeInt64Pointer(10000),
|
|
|
|
EndPos: 37,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: `min_over_time(rate(foo{bar="baz"}[2s])[5m:] @ 1603775091)[4m:3s]`,
|
|
|
|
expected: &parser.SubqueryExpr{
|
|
|
|
Expr: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.Call{
|
|
|
|
Func: parser.MustGetFunction("min_over_time"),
|
|
|
|
Args: parser.Expressions{
|
|
|
|
&parser.SubqueryExpr{
|
|
|
|
Expr: &parser.Call{
|
|
|
|
Func: parser.MustGetFunction("rate"),
|
|
|
|
Args: parser.Expressions{
|
|
|
|
&parser.MatrixSelector{
|
|
|
|
VectorSelector: &parser.VectorSelector{
|
|
|
|
Name: "foo",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "bar", "baz"),
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 19,
|
|
|
|
End: 33,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 2 * time.Second,
|
|
|
|
EndPos: 37,
|
|
|
|
},
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 14,
|
|
|
|
End: 38,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 5 * time.Minute,
|
|
|
|
Timestamp: makeInt64Pointer(1603775091000),
|
|
|
|
EndPos: 56,
|
|
|
|
},
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 57,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 4 * time.Minute,
|
|
|
|
Step: 3 * time.Second,
|
|
|
|
EndPos: 64,
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: `some_metric @ 123 offset 1m [10m:5s]`,
|
|
|
|
expected: &parser.SubqueryExpr{
|
|
|
|
Expr: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "some_metric",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 27,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(123000),
|
|
|
|
OriginalOffset: 1 * time.Minute,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 10 * time.Minute,
|
|
|
|
Step: 5 * time.Second,
|
|
|
|
EndPos: 36,
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: `some_metric[10m:5s] offset 1m @ 123`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.SubqueryExpr{
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "some_metric",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 11,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(123000),
|
|
|
|
OriginalOffset: 1 * time.Minute,
|
|
|
|
Range: 10 * time.Minute,
|
|
|
|
Step: 5 * time.Second,
|
|
|
|
EndPos: 35,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: `(foo + bar{nm="val"} @ 1234)[5m:] @ 1603775019`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.SubqueryExpr{
|
|
|
|
Expr: &parser.ParenExpr{
|
|
|
|
Expr: &parser.BinaryExpr{
|
|
|
|
Op: parser.ADD,
|
|
|
|
VectorMatching: &parser.VectorMatching{
|
|
|
|
Card: parser.CardOneToOne,
|
|
|
|
},
|
|
|
|
LHS: &parser.VectorSelector{
|
|
|
|
Name: "foo",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 1,
|
|
|
|
End: 4,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
RHS: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "bar",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "nm", "val"),
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "bar"),
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(1234000),
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 7,
|
|
|
|
End: 27,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 28,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 5 * time.Minute,
|
|
|
|
Timestamp: makeInt64Pointer(1603775019000),
|
|
|
|
EndPos: 46,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "abs(abs(metric @ 10))",
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.Call{
|
|
|
|
Func: &parser.Function{
|
|
|
|
Name: "abs",
|
|
|
|
ArgTypes: []parser.ValueType{parser.ValueTypeVector},
|
|
|
|
ReturnType: parser.ValueTypeVector,
|
|
|
|
},
|
|
|
|
Args: parser.Expressions{&parser.Call{
|
|
|
|
Func: &parser.Function{
|
|
|
|
Name: "abs",
|
|
|
|
ArgTypes: []parser.ValueType{parser.ValueTypeVector},
|
|
|
|
ReturnType: parser.ValueTypeVector,
|
|
|
|
},
|
|
|
|
Args: parser.Expressions{&parser.VectorSelector{
|
|
|
|
Name: "metric",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "metric"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 8,
|
|
|
|
End: 19,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(10000),
|
|
|
|
}},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 4,
|
|
|
|
End: 20,
|
|
|
|
},
|
|
|
|
}},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 21,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-01-20 02:57:39 -08:00
|
|
|
input: "sum(sum(some_metric1 @ 10) + sum(some_metric2 @ 20))",
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.AggregateExpr{
|
|
|
|
Op: parser.SUM,
|
|
|
|
Expr: &parser.BinaryExpr{
|
|
|
|
Op: parser.ADD,
|
|
|
|
VectorMatching: &parser.VectorMatching{},
|
|
|
|
LHS: &parser.AggregateExpr{
|
|
|
|
Op: parser.SUM,
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "some_metric1",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric1"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 8,
|
|
|
|
End: 25,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(10000),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 4,
|
|
|
|
End: 26,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
RHS: &parser.AggregateExpr{
|
|
|
|
Op: parser.SUM,
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "some_metric2",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric2"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 33,
|
|
|
|
End: 50,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(20000),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 29,
|
|
|
|
End: 52,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-01-20 02:57:39 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 52,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-02-09 08:03:16 -08:00
|
|
|
input: `foo @ start()`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "foo",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-02-09 08:03:16 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 13,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(timestamp.FromTime(startTime)),
|
|
|
|
StartOrEnd: parser.START,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-02-09 08:03:16 -08:00
|
|
|
input: `foo @ end()`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "foo",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-02-09 08:03:16 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 11,
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(timestamp.FromTime(endTime)),
|
|
|
|
StartOrEnd: parser.END,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-02-09 08:03:16 -08:00
|
|
|
input: `test[5y] @ start()`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.MatrixSelector{
|
|
|
|
VectorSelector: &parser.VectorSelector{
|
|
|
|
Name: "test",
|
|
|
|
Timestamp: makeInt64Pointer(timestamp.FromTime(startTime)),
|
|
|
|
StartOrEnd: parser.START,
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "test"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-02-09 08:03:16 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 4,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 5 * 365 * 24 * time.Hour,
|
|
|
|
EndPos: 18,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-02-09 08:03:16 -08:00
|
|
|
input: `test[5y] @ end()`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.MatrixSelector{
|
|
|
|
VectorSelector: &parser.VectorSelector{
|
|
|
|
Name: "test",
|
|
|
|
Timestamp: makeInt64Pointer(timestamp.FromTime(endTime)),
|
|
|
|
StartOrEnd: parser.END,
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "test"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-02-09 08:03:16 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 4,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Range: 5 * 365 * 24 * time.Hour,
|
|
|
|
EndPos: 16,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-02-09 08:03:16 -08:00
|
|
|
input: `some_metric[10m:5s] @ start()`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.SubqueryExpr{
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "some_metric",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-02-09 08:03:16 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 11,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(timestamp.FromTime(startTime)),
|
|
|
|
StartOrEnd: parser.START,
|
|
|
|
Range: 10 * time.Minute,
|
|
|
|
Step: 5 * time.Second,
|
|
|
|
EndPos: 29,
|
|
|
|
},
|
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
},
|
|
|
|
{
|
2021-02-09 08:03:16 -08:00
|
|
|
input: `some_metric[10m:5s] @ end()`,
|
|
|
|
expected: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.SubqueryExpr{
|
|
|
|
Expr: &parser.VectorSelector{
|
|
|
|
Name: "some_metric",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-02-09 08:03:16 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 11,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
Timestamp: makeInt64Pointer(timestamp.FromTime(endTime)),
|
|
|
|
StartOrEnd: parser.END,
|
|
|
|
Range: 10 * time.Minute,
|
|
|
|
Step: 5 * time.Second,
|
|
|
|
EndPos: 27,
|
|
|
|
},
|
|
|
|
},
|
2021-01-20 02:57:39 -08:00
|
|
|
},
|
2021-11-10 06:46:24 -08:00
|
|
|
{
|
|
|
|
input: `floor(some_metric / (3 * 1024))`,
|
|
|
|
outputTest: true,
|
|
|
|
expected: &parser.Call{
|
|
|
|
Func: &parser.Function{
|
|
|
|
Name: "floor",
|
|
|
|
ArgTypes: []parser.ValueType{parser.ValueTypeVector},
|
|
|
|
ReturnType: parser.ValueTypeVector,
|
|
|
|
},
|
|
|
|
Args: parser.Expressions{
|
|
|
|
&parser.BinaryExpr{
|
|
|
|
Op: parser.DIV,
|
|
|
|
LHS: &parser.VectorSelector{
|
|
|
|
Name: "some_metric",
|
|
|
|
LabelMatchers: []*labels.Matcher{
|
|
|
|
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-11-10 06:46:24 -08:00
|
|
|
Start: 6,
|
|
|
|
End: 17,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
RHS: &parser.StepInvariantExpr{
|
|
|
|
Expr: &parser.ParenExpr{
|
|
|
|
Expr: &parser.BinaryExpr{
|
|
|
|
Op: parser.MUL,
|
|
|
|
LHS: &parser.NumberLiteral{
|
|
|
|
Val: 3,
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-11-10 06:46:24 -08:00
|
|
|
Start: 21,
|
|
|
|
End: 22,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
RHS: &parser.NumberLiteral{
|
|
|
|
Val: 1024,
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-11-10 06:46:24 -08:00
|
|
|
Start: 25,
|
|
|
|
End: 29,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-11-10 06:46:24 -08:00
|
|
|
Start: 20,
|
|
|
|
End: 30,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2023-09-14 09:57:31 -07:00
|
|
|
PosRange: posrange.PositionRange{
|
2021-11-10 06:46:24 -08:00
|
|
|
Start: 0,
|
|
|
|
End: 31,
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
2021-01-20 02:57:39 -08:00
|
|
|
}
|
|
|
|
|
|
|
|
for _, test := range testCases {
|
|
|
|
t.Run(test.input, func(t *testing.T) {
|
|
|
|
expr, err := parser.ParseExpr(test.input)
|
|
|
|
require.NoError(t, err)
|
2024-04-29 05:14:18 -07:00
|
|
|
expr = promql.PreprocessExpr(expr, startTime, endTime)
|
2021-11-10 06:46:24 -08:00
|
|
|
if test.outputTest {
|
|
|
|
require.Equal(t, test.input, expr.String(), "error on input '%s'", test.input)
|
|
|
|
}
|
2021-01-20 02:57:39 -08:00
|
|
|
require.Equal(t, test.expected, expr, "error on input '%s'", test.input)
|
|
|
|
})
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
func TestEngineOptsValidation(t *testing.T) {
|
|
|
|
cases := []struct {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts promql.EngineOpts
|
2021-01-20 02:57:39 -08:00
|
|
|
query string
|
|
|
|
fail bool
|
2021-02-09 08:03:16 -08:00
|
|
|
expError error
|
2021-01-20 02:57:39 -08:00
|
|
|
}{
|
|
|
|
{
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: false},
|
|
|
|
query: "metric @ 100", fail: true, expError: promql.ErrValidationAtModifierDisabled,
|
2021-02-09 08:03:16 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: false},
|
|
|
|
query: "rate(metric[1m] @ 100)", fail: true, expError: promql.ErrValidationAtModifierDisabled,
|
2021-02-09 08:03:16 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: false},
|
|
|
|
query: "rate(metric[1h:1m] @ 100)", fail: true, expError: promql.ErrValidationAtModifierDisabled,
|
2021-02-09 08:03:16 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: false},
|
|
|
|
query: "metric @ start()", fail: true, expError: promql.ErrValidationAtModifierDisabled,
|
2021-02-09 08:03:16 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: false},
|
|
|
|
query: "rate(metric[1m] @ start())", fail: true, expError: promql.ErrValidationAtModifierDisabled,
|
2021-02-09 08:03:16 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: false},
|
|
|
|
query: "rate(metric[1h:1m] @ start())", fail: true, expError: promql.ErrValidationAtModifierDisabled,
|
2021-02-09 08:03:16 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: false},
|
|
|
|
query: "metric @ end()", fail: true, expError: promql.ErrValidationAtModifierDisabled,
|
2021-02-09 08:03:16 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: false},
|
|
|
|
query: "rate(metric[1m] @ end())", fail: true, expError: promql.ErrValidationAtModifierDisabled,
|
2021-02-09 08:03:16 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: false},
|
|
|
|
query: "rate(metric[1h:1m] @ end())", fail: true, expError: promql.ErrValidationAtModifierDisabled,
|
2021-01-20 02:57:39 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: true},
|
2021-01-20 02:57:39 -08:00
|
|
|
query: "metric @ 100",
|
2021-02-09 08:03:16 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: true},
|
2021-02-09 08:03:16 -08:00
|
|
|
query: "rate(metric[1m] @ start())",
|
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: true},
|
2021-02-09 08:03:16 -08:00
|
|
|
query: "rate(metric[1h:1m] @ end())",
|
2021-02-21 10:03:58 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableNegativeOffset: false},
|
|
|
|
query: "metric offset -1s", fail: true, expError: promql.ErrValidationNegativeOffsetDisabled,
|
2021-02-21 10:03:58 -08:00
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableNegativeOffset: true},
|
2021-02-21 10:03:58 -08:00
|
|
|
query: "metric offset -1s",
|
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: true, EnableNegativeOffset: true},
|
2021-02-21 10:03:58 -08:00
|
|
|
query: "metric @ 100 offset -2m",
|
|
|
|
}, {
|
2024-04-29 05:14:18 -07:00
|
|
|
opts: promql.EngineOpts{EnableAtModifier: true, EnableNegativeOffset: true},
|
2021-02-21 10:03:58 -08:00
|
|
|
query: "metric offset -2m @ 100",
|
2021-01-20 02:57:39 -08:00
|
|
|
},
|
|
|
|
}
|
|
|
|
|
|
|
|
for _, c := range cases {
|
2024-07-14 04:28:59 -07:00
|
|
|
eng := promqltest.NewTestEngineWithOpts(t, c.opts)
|
2023-08-18 11:48:59 -07:00
|
|
|
_, err1 := eng.NewInstantQuery(context.Background(), nil, nil, c.query, time.Unix(10, 0))
|
|
|
|
_, err2 := eng.NewRangeQuery(context.Background(), nil, nil, c.query, time.Unix(0, 0), time.Unix(10, 0), time.Second)
|
2021-01-20 02:57:39 -08:00
|
|
|
if c.fail {
|
2021-02-09 08:03:16 -08:00
|
|
|
require.Equal(t, c.expError, err1)
|
|
|
|
require.Equal(t, c.expError, err2)
|
2021-01-20 02:57:39 -08:00
|
|
|
} else {
|
2023-12-07 03:35:01 -08:00
|
|
|
require.NoError(t, err1)
|
|
|
|
require.NoError(t, err2)
|
2021-01-20 02:57:39 -08:00
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
2021-04-26 15:43:22 -07:00
|
|
|
|
2024-05-12 17:43:06 -07:00
|
|
|
func TestInstantQueryWithRangeVectorSelector(t *testing.T) {
|
2024-06-05 01:50:41 -07:00
|
|
|
engine := newTestEngine(t)
|
2024-05-12 17:43:06 -07:00
|
|
|
|
|
|
|
baseT := timestamp.Time(0)
|
|
|
|
storage := promqltest.LoadedStorage(t, `
|
|
|
|
load 1m
|
|
|
|
some_metric{env="1"} 0+1x4
|
|
|
|
some_metric{env="2"} 0+2x4
|
|
|
|
some_metric_with_stale_marker 0 1 stale 3
|
|
|
|
`)
|
|
|
|
t.Cleanup(func() { require.NoError(t, storage.Close()) })
|
|
|
|
|
|
|
|
testCases := map[string]struct {
|
|
|
|
expr string
|
|
|
|
expected promql.Matrix
|
|
|
|
ts time.Time
|
|
|
|
}{
|
|
|
|
"matches series with points in range": {
|
|
|
|
expr: "some_metric[1m]",
|
|
|
|
ts: baseT.Add(2 * time.Minute),
|
|
|
|
expected: promql.Matrix{
|
|
|
|
{
|
|
|
|
Metric: labels.FromStrings("__name__", "some_metric", "env", "1"),
|
|
|
|
Floats: []promql.FPoint{
|
|
|
|
{T: timestamp.FromTime(baseT.Add(time.Minute)), F: 1},
|
|
|
|
{T: timestamp.FromTime(baseT.Add(2 * time.Minute)), F: 2},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Metric: labels.FromStrings("__name__", "some_metric", "env", "2"),
|
|
|
|
Floats: []promql.FPoint{
|
|
|
|
{T: timestamp.FromTime(baseT.Add(time.Minute)), F: 2},
|
|
|
|
{T: timestamp.FromTime(baseT.Add(2 * time.Minute)), F: 4},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
"matches no series": {
|
|
|
|
expr: "some_nonexistent_metric[1m]",
|
|
|
|
ts: baseT,
|
|
|
|
expected: promql.Matrix{},
|
|
|
|
},
|
|
|
|
"no samples in range": {
|
|
|
|
expr: "some_metric[1m]",
|
|
|
|
ts: baseT.Add(20 * time.Minute),
|
|
|
|
expected: promql.Matrix{},
|
|
|
|
},
|
|
|
|
"metric with stale marker": {
|
|
|
|
expr: "some_metric_with_stale_marker[3m]",
|
|
|
|
ts: baseT.Add(3 * time.Minute),
|
|
|
|
expected: promql.Matrix{
|
|
|
|
{
|
|
|
|
Metric: labels.FromStrings("__name__", "some_metric_with_stale_marker"),
|
|
|
|
Floats: []promql.FPoint{
|
|
|
|
{T: timestamp.FromTime(baseT), F: 0},
|
|
|
|
{T: timestamp.FromTime(baseT.Add(time.Minute)), F: 1},
|
|
|
|
{T: timestamp.FromTime(baseT.Add(3 * time.Minute)), F: 3},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
}
|
|
|
|
|
|
|
|
for name, testCase := range testCases {
|
|
|
|
t.Run(name, func(t *testing.T) {
|
|
|
|
q, err := engine.NewInstantQuery(context.Background(), storage, nil, testCase.expr, testCase.ts)
|
|
|
|
require.NoError(t, err)
|
|
|
|
defer q.Close()
|
|
|
|
|
|
|
|
res := q.Exec(context.Background())
|
|
|
|
require.NoError(t, res.Err)
|
|
|
|
testutil.RequireEqual(t, testCase.expected, res.Value)
|
|
|
|
})
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2023-05-16 12:15:20 -07:00
|
|
|
func TestNativeHistogram_SubOperator(t *testing.T) {
|
2021-12-06 08:08:10 -08:00
|
|
|
// TODO(codesome): Integrate histograms into the PromQL testing framework
|
|
|
|
// and write more tests there.
|
|
|
|
cases := []struct {
|
|
|
|
histograms []histogram.Histogram
|
|
|
|
expected histogram.FloatHistogram
|
|
|
|
}{
|
|
|
|
{
|
|
|
|
histograms: []histogram.Histogram{
|
|
|
|
{
|
|
|
|
Schema: 0,
|
2023-08-22 12:51:56 -07:00
|
|
|
Count: 41,
|
2023-05-16 12:15:20 -07:00
|
|
|
Sum: 2345.6,
|
|
|
|
ZeroThreshold: 0.001,
|
|
|
|
ZeroCount: 5,
|
|
|
|
PositiveSpans: []histogram.Span{
|
|
|
|
{Offset: 0, Length: 4},
|
|
|
|
{Offset: 0, Length: 0},
|
|
|
|
{Offset: 0, Length: 3},
|
|
|
|
},
|
|
|
|
PositiveBuckets: []int64{1, 2, -2, 1, -1, 0, 0},
|
|
|
|
NegativeSpans: []histogram.Span{
|
|
|
|
{Offset: 1, Length: 4},
|
|
|
|
{Offset: 2, Length: 0},
|
|
|
|
{Offset: 2, Length: 3},
|
|
|
|
},
|
|
|
|
NegativeBuckets: []int64{1, 3, -2, 5, -2, 0, -3},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Schema: 0,
|
|
|
|
Count: 11,
|
2021-12-06 08:08:10 -08:00
|
|
|
Sum: 1234.5,
|
|
|
|
ZeroThreshold: 0.001,
|
2023-05-16 12:15:20 -07:00
|
|
|
ZeroCount: 3,
|
2021-12-06 08:08:10 -08:00
|
|
|
PositiveSpans: []histogram.Span{
|
|
|
|
{Offset: 1, Length: 2},
|
|
|
|
},
|
2023-05-16 12:15:20 -07:00
|
|
|
PositiveBuckets: []int64{2, -1},
|
2021-12-06 08:08:10 -08:00
|
|
|
NegativeSpans: []histogram.Span{
|
|
|
|
{Offset: 2, Length: 2},
|
|
|
|
},
|
2023-05-16 12:15:20 -07:00
|
|
|
NegativeBuckets: []int64{3, -1},
|
2021-12-06 08:08:10 -08:00
|
|
|
},
|
2023-05-16 12:15:20 -07:00
|
|
|
},
|
|
|
|
expected: histogram.FloatHistogram{
|
|
|
|
Schema: 0,
|
2023-08-22 12:51:56 -07:00
|
|
|
Count: 30,
|
2023-05-16 12:15:20 -07:00
|
|
|
Sum: 1111.1,
|
|
|
|
ZeroThreshold: 0.001,
|
|
|
|
ZeroCount: 2,
|
|
|
|
PositiveSpans: []histogram.Span{
|
|
|
|
{Offset: 0, Length: 2},
|
|
|
|
{Offset: 1, Length: 4},
|
|
|
|
},
|
|
|
|
PositiveBuckets: []float64{1, 1, 2, 1, 1, 1},
|
|
|
|
NegativeSpans: []histogram.Span{
|
|
|
|
{Offset: 1, Length: 2},
|
|
|
|
{Offset: 1, Length: 1},
|
|
|
|
{Offset: 4, Length: 3},
|
|
|
|
},
|
|
|
|
NegativeBuckets: []float64{1, 1, 7, 5, 5, 2},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
histograms: []histogram.Histogram{
|
2021-12-06 08:08:10 -08:00
|
|
|
{
|
|
|
|
Schema: 0,
|
2023-08-22 12:51:56 -07:00
|
|
|
Count: 41,
|
2021-12-06 08:08:10 -08:00
|
|
|
Sum: 2345.6,
|
|
|
|
ZeroThreshold: 0.001,
|
|
|
|
ZeroCount: 5,
|
|
|
|
PositiveSpans: []histogram.Span{
|
|
|
|
{Offset: 0, Length: 4},
|
|
|
|
{Offset: 0, Length: 0},
|
|
|
|
{Offset: 0, Length: 3},
|
|
|
|
},
|
|
|
|
PositiveBuckets: []int64{1, 2, -2, 1, -1, 0, 0},
|
|
|
|
NegativeSpans: []histogram.Span{
|
|
|
|
{Offset: 1, Length: 4},
|
|
|
|
{Offset: 2, Length: 0},
|
|
|
|
{Offset: 2, Length: 3},
|
|
|
|
},
|
|
|
|
NegativeBuckets: []int64{1, 3, -2, 5, -2, 0, -3},
|
|
|
|
},
|
2023-05-16 12:15:20 -07:00
|
|
|
{
|
|
|
|
Schema: 1,
|
|
|
|
Count: 11,
|
|
|
|
Sum: 1234.5,
|
|
|
|
ZeroThreshold: 0.001,
|
|
|
|
ZeroCount: 3,
|
|
|
|
PositiveSpans: []histogram.Span{
|
|
|
|
{Offset: 1, Length: 2},
|
|
|
|
},
|
|
|
|
PositiveBuckets: []int64{2, -1},
|
|
|
|
NegativeSpans: []histogram.Span{
|
|
|
|
{Offset: 2, Length: 2},
|
|
|
|
},
|
|
|
|
NegativeBuckets: []int64{3, -1},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
expected: histogram.FloatHistogram{
|
|
|
|
Schema: 0,
|
2023-08-22 12:51:56 -07:00
|
|
|
Count: 30,
|
2023-05-16 12:15:20 -07:00
|
|
|
Sum: 1111.1,
|
|
|
|
ZeroThreshold: 0.001,
|
|
|
|
ZeroCount: 2,
|
|
|
|
PositiveSpans: []histogram.Span{
|
|
|
|
{Offset: 0, Length: 1},
|
|
|
|
{Offset: 1, Length: 5},
|
|
|
|
},
|
|
|
|
PositiveBuckets: []float64{1, 1, 2, 1, 1, 1},
|
|
|
|
NegativeSpans: []histogram.Span{
|
|
|
|
{Offset: 1, Length: 4},
|
|
|
|
{Offset: 4, Length: 3},
|
|
|
|
},
|
|
|
|
NegativeBuckets: []float64{-2, 2, 2, 7, 5, 5, 2},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
histograms: []histogram.Histogram{
|
|
|
|
{
|
|
|
|
Schema: 1,
|
|
|
|
Count: 11,
|
|
|
|
Sum: 1234.5,
|
|
|
|
ZeroThreshold: 0.001,
|
|
|
|
ZeroCount: 3,
|
|
|
|
PositiveSpans: []histogram.Span{
|
|
|
|
{Offset: 1, Length: 2},
|
|
|
|
},
|
|
|
|
PositiveBuckets: []int64{2, -1},
|
|
|
|
NegativeSpans: []histogram.Span{
|
|
|
|
{Offset: 2, Length: 2},
|
|
|
|
},
|
|
|
|
NegativeBuckets: []int64{3, -1},
|
|
|
|
},
|
2021-12-06 08:08:10 -08:00
|
|
|
{
|
|
|
|
Schema: 0,
|
2023-08-22 12:51:56 -07:00
|
|
|
Count: 41,
|
2023-05-16 12:15:20 -07:00
|
|
|
Sum: 2345.6,
|
2021-12-06 08:08:10 -08:00
|
|
|
ZeroThreshold: 0.001,
|
|
|
|
ZeroCount: 5,
|
|
|
|
PositiveSpans: []histogram.Span{
|
|
|
|
{Offset: 0, Length: 4},
|
|
|
|
{Offset: 0, Length: 0},
|
|
|
|
{Offset: 0, Length: 3},
|
|
|
|
},
|
|
|
|
PositiveBuckets: []int64{1, 2, -2, 1, -1, 0, 0},
|
|
|
|
NegativeSpans: []histogram.Span{
|
|
|
|
{Offset: 1, Length: 4},
|
|
|
|
{Offset: 2, Length: 0},
|
|
|
|
{Offset: 2, Length: 3},
|
|
|
|
},
|
|
|
|
NegativeBuckets: []int64{1, 3, -2, 5, -2, 0, -3},
|
|
|
|
},
|
|
|
|
},
|
|
|
|
expected: histogram.FloatHistogram{
|
|
|
|
Schema: 0,
|
2023-08-22 12:51:56 -07:00
|
|
|
Count: -30,
|
2023-05-16 12:15:20 -07:00
|
|
|
Sum: -1111.1,
|
2021-12-06 08:08:10 -08:00
|
|
|
ZeroThreshold: 0.001,
|
2023-05-16 12:15:20 -07:00
|
|
|
ZeroCount: -2,
|
2021-12-06 08:08:10 -08:00
|
|
|
PositiveSpans: []histogram.Span{
|
2023-05-16 12:15:20 -07:00
|
|
|
{Offset: 0, Length: 1},
|
|
|
|
{Offset: 1, Length: 5},
|
2021-12-06 08:08:10 -08:00
|
|
|
},
|
2023-05-16 12:15:20 -07:00
|
|
|
PositiveBuckets: []float64{-1, -1, -2, -1, -1, -1},
|
2021-12-06 08:08:10 -08:00
|
|
|
NegativeSpans: []histogram.Span{
|
2023-05-16 12:15:20 -07:00
|
|
|
{Offset: 1, Length: 4},
|
|
|
|
{Offset: 4, Length: 3},
|
2021-12-06 08:08:10 -08:00
|
|
|
},
|
2023-05-16 12:15:20 -07:00
|
|
|
NegativeBuckets: []float64{2, -2, -2, -7, -5, -5, -2},
|
2021-12-06 08:08:10 -08:00
|
|
|
},
|
|
|
|
},
|
|
|
|
}
|
|
|
|
|
2022-12-28 05:45:47 -08:00
|
|
|
idx0 := int64(0)
|
|
|
|
for _, c := range cases {
|
|
|
|
for _, floatHisto := range []bool{true, false} {
|
|
|
|
t.Run(fmt.Sprintf("floatHistogram=%t %d", floatHisto, idx0), func(t *testing.T) {
|
2024-05-07 09:14:22 -07:00
|
|
|
engine := newTestEngine(t)
|
2023-08-18 11:48:59 -07:00
|
|
|
storage := teststorage.New(t)
|
|
|
|
t.Cleanup(func() { storage.Close() })
|
2021-12-06 08:08:10 -08:00
|
|
|
|
2022-12-28 05:45:47 -08:00
|
|
|
seriesName := "sparse_histogram_series"
|
2021-12-06 08:08:10 -08:00
|
|
|
|
2022-12-28 05:45:47 -08:00
|
|
|
ts := idx0 * int64(10*time.Minute/time.Millisecond)
|
2023-08-18 11:48:59 -07:00
|
|
|
app := storage.Appender(context.Background())
|
2022-12-28 05:45:47 -08:00
|
|
|
for idx1, h := range c.histograms {
|
2024-05-13 08:36:19 -07:00
|
|
|
lbls := labels.FromStrings("__name__", seriesName, "idx", strconv.Itoa(idx1))
|
2022-12-28 05:45:47 -08:00
|
|
|
// Since we mutate h later, we need to create a copy here.
|
2023-08-18 11:48:59 -07:00
|
|
|
var err error
|
2022-12-28 05:45:47 -08:00
|
|
|
if floatHisto {
|
2023-11-29 06:15:57 -08:00
|
|
|
_, err = app.AppendHistogram(0, lbls, ts, nil, h.Copy().ToFloat(nil))
|
2022-12-28 05:45:47 -08:00
|
|
|
} else {
|
|
|
|
_, err = app.AppendHistogram(0, lbls, ts, h.Copy(), nil)
|
|
|
|
}
|
|
|
|
require.NoError(t, err)
|
|
|
|
}
|
|
|
|
require.NoError(t, app.Commit())
|
2021-12-06 08:08:10 -08:00
|
|
|
|
2024-04-29 05:14:18 -07:00
|
|
|
queryAndCheck := func(queryString string, exp promql.Vector) {
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(ts))
|
2022-12-28 05:45:47 -08:00
|
|
|
require.NoError(t, err)
|
2021-12-06 08:08:10 -08:00
|
|
|
|
2023-08-18 11:48:59 -07:00
|
|
|
res := qry.Exec(context.Background())
|
2022-12-28 05:45:47 -08:00
|
|
|
require.NoError(t, res.Err)
|
2021-12-06 08:08:10 -08:00
|
|
|
|
2022-12-28 05:45:47 -08:00
|
|
|
vector, err := res.Vector()
|
|
|
|
require.NoError(t, err)
|
2021-12-06 09:36:58 -08:00
|
|
|
|
2023-08-25 14:35:42 -07:00
|
|
|
if len(vector) == len(exp) {
|
|
|
|
for i, e := range exp {
|
|
|
|
got := vector[i].H
|
|
|
|
if got != e.H {
|
|
|
|
// Error messages are better if we compare structs, not pointers.
|
|
|
|
require.Equal(t, *e.H, *got)
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2023-04-16 05:13:31 -07:00
|
|
|
testutil.RequireEqual(t, exp, vector)
|
2022-12-28 05:45:47 -08:00
|
|
|
}
|
2021-12-06 08:08:10 -08:00
|
|
|
|
2023-05-16 12:15:20 -07:00
|
|
|
// - operator.
|
|
|
|
queryString := fmt.Sprintf(`%s{idx="0"}`, seriesName)
|
2022-12-28 05:45:47 -08:00
|
|
|
for idx := 1; idx < len(c.histograms); idx++ {
|
2023-05-16 12:15:20 -07:00
|
|
|
queryString += fmt.Sprintf(` - ignoring(idx) %s{idx="%d"}`, seriesName, idx)
|
2022-12-28 05:45:47 -08:00
|
|
|
}
|
2024-04-29 05:14:18 -07:00
|
|
|
queryAndCheck(queryString, []promql.Sample{{T: ts, H: &c.expected, Metric: labels.EmptyLabels()}})
|
2023-05-16 12:15:20 -07:00
|
|
|
})
|
|
|
|
}
|
2023-08-25 14:35:42 -07:00
|
|
|
idx0++
|
2023-05-16 12:15:20 -07:00
|
|
|
}
|
|
|
|
}
|
2022-08-29 07:27:29 -07:00
|
|
|
|
2022-08-02 02:15:39 -07:00
|
|
|
func TestQueryLookbackDelta(t *testing.T) {
|
|
|
|
var (
|
|
|
|
load = `load 5m
|
|
|
|
metric 0 1 2
|
|
|
|
`
|
|
|
|
query = "metric"
|
|
|
|
lastDatapointTs = time.Unix(600, 0)
|
|
|
|
)
|
|
|
|
|
|
|
|
cases := []struct {
|
|
|
|
name string
|
|
|
|
ts time.Time
|
|
|
|
engineLookback, queryLookback time.Duration
|
|
|
|
expectSamples bool
|
|
|
|
}{
|
|
|
|
{
|
|
|
|
name: "default lookback delta",
|
|
|
|
ts: lastDatapointTs.Add(defaultLookbackDelta),
|
|
|
|
expectSamples: true,
|
|
|
|
},
|
|
|
|
{
|
|
|
|
name: "outside default lookback delta",
|
|
|
|
ts: lastDatapointTs.Add(defaultLookbackDelta + time.Millisecond),
|
|
|
|
expectSamples: false,
|
|
|
|
},
|
|
|
|
{
|
|
|
|
name: "custom engine lookback delta",
|
|
|
|
ts: lastDatapointTs.Add(10 * time.Minute),
|
|
|
|
engineLookback: 10 * time.Minute,
|
|
|
|
expectSamples: true,
|
|
|
|
},
|
|
|
|
{
|
|
|
|
name: "outside custom engine lookback delta",
|
|
|
|
ts: lastDatapointTs.Add(10*time.Minute + time.Millisecond),
|
|
|
|
engineLookback: 10 * time.Minute,
|
|
|
|
expectSamples: false,
|
|
|
|
},
|
|
|
|
{
|
|
|
|
name: "custom query lookback delta",
|
|
|
|
ts: lastDatapointTs.Add(20 * time.Minute),
|
|
|
|
engineLookback: 10 * time.Minute,
|
|
|
|
queryLookback: 20 * time.Minute,
|
|
|
|
expectSamples: true,
|
|
|
|
},
|
|
|
|
{
|
|
|
|
name: "outside custom query lookback delta",
|
|
|
|
ts: lastDatapointTs.Add(20*time.Minute + time.Millisecond),
|
|
|
|
engineLookback: 10 * time.Minute,
|
|
|
|
queryLookback: 20 * time.Minute,
|
|
|
|
expectSamples: false,
|
|
|
|
},
|
|
|
|
{
|
|
|
|
name: "negative custom query lookback delta",
|
|
|
|
ts: lastDatapointTs.Add(20 * time.Minute),
|
|
|
|
engineLookback: -10 * time.Minute,
|
|
|
|
queryLookback: 20 * time.Minute,
|
|
|
|
expectSamples: true,
|
|
|
|
},
|
|
|
|
}
|
|
|
|
|
|
|
|
for _, c := range cases {
|
|
|
|
c := c
|
|
|
|
t.Run(c.name, func(t *testing.T) {
|
2024-05-07 09:14:22 -07:00
|
|
|
engine := promqltest.NewTestEngine(t, false, c.engineLookback, promqltest.DefaultMaxSamplesPerQuery)
|
2024-04-29 05:14:18 -07:00
|
|
|
storage := promqltest.LoadedStorage(t, load)
|
2023-08-18 11:48:59 -07:00
|
|
|
t.Cleanup(func() { storage.Close() })
|
2022-08-02 02:15:39 -07:00
|
|
|
|
2024-04-29 05:13:23 -07:00
|
|
|
opts := promql.NewPrometheusQueryOpts(false, c.queryLookback)
|
2023-08-18 11:48:59 -07:00
|
|
|
qry, err := engine.NewInstantQuery(context.Background(), storage, opts, query, c.ts)
|
2022-08-02 02:15:39 -07:00
|
|
|
require.NoError(t, err)
|
|
|
|
|
2023-08-18 11:48:59 -07:00
|
|
|
res := qry.Exec(context.Background())
|
2022-08-02 02:15:39 -07:00
|
|
|
require.NoError(t, res.Err)
|
2024-04-29 05:14:18 -07:00
|
|
|
vec, ok := res.Value.(promql.Vector)
|
2022-08-02 02:15:39 -07:00
|
|
|
require.True(t, ok)
|
|
|
|
if c.expectSamples {
|
|
|
|
require.NotEmpty(t, vec)
|
|
|
|
} else {
|
|
|
|
require.Empty(t, vec)
|
|
|
|
}
|
|
|
|
})
|
|
|
|
}
|
|
|
|
}
|
2024-04-29 05:14:18 -07:00
|
|
|
|
|
|
|
func makeInt64Pointer(val int64) *int64 {
|
|
|
|
valp := new(int64)
|
|
|
|
*valp = val
|
|
|
|
return valp
|
|
|
|
}
|
2024-08-06 11:48:16 -07:00
|
|
|
|
|
|
|
func TestHistogramCopyFromIteratorRegression(t *testing.T) {
|
|
|
|
// Loading the following histograms creates two chunks because there's a
|
|
|
|
// counter reset. Not only the counter is lower in the last histogram
|
|
|
|
// but also there's missing buckets.
|
|
|
|
// This in turns means that chunk iterators will have different spans.
|
|
|
|
load := `load 1m
|
|
|
|
histogram {{sum:4 count:4 buckets:[2 2]}} {{sum:6 count:6 buckets:[3 3]}} {{sum:1 count:1 buckets:[1]}}
|
|
|
|
`
|
|
|
|
storage := promqltest.LoadedStorage(t, load)
|
|
|
|
t.Cleanup(func() { storage.Close() })
|
2024-08-26 02:54:55 -07:00
|
|
|
engine := promqltest.NewTestEngine(t, false, 0, promqltest.DefaultMaxSamplesPerQuery)
|
2024-08-06 11:48:16 -07:00
|
|
|
|
|
|
|
verify := func(t *testing.T, qry promql.Query, expected []histogram.FloatHistogram) {
|
|
|
|
res := qry.Exec(context.Background())
|
|
|
|
require.NoError(t, res.Err)
|
|
|
|
|
|
|
|
m, ok := res.Value.(promql.Matrix)
|
|
|
|
require.True(t, ok)
|
|
|
|
|
|
|
|
require.Len(t, m, 1)
|
|
|
|
series := m[0]
|
|
|
|
|
|
|
|
require.Empty(t, series.Floats)
|
|
|
|
require.Len(t, series.Histograms, len(expected))
|
|
|
|
for i, e := range expected {
|
|
|
|
series.Histograms[i].H.CounterResetHint = histogram.UnknownCounterReset // Don't care.
|
|
|
|
require.Equal(t, &e, series.Histograms[i].H)
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
qry, err := engine.NewRangeQuery(context.Background(), storage, nil, "increase(histogram[60s])", time.Unix(0, 0), time.Unix(0, 0).Add(1*time.Minute), time.Minute)
|
|
|
|
require.NoError(t, err)
|
|
|
|
verify(t, qry, []histogram.FloatHistogram{
|
|
|
|
{
|
|
|
|
Count: 2,
|
|
|
|
Sum: 2, // Increase from 4 to 6 is 2.
|
|
|
|
PositiveSpans: []histogram.Span{{Offset: 0, Length: 2}}, // Two buckets changed between the first and second histogram.
|
|
|
|
PositiveBuckets: []float64{1, 1}, // Increase from 2 to 3 is 1 in both buckets.
|
|
|
|
},
|
|
|
|
})
|
|
|
|
|
|
|
|
qry, err = engine.NewInstantQuery(context.Background(), storage, nil, "histogram[60s]", time.Unix(0, 0).Add(2*time.Minute))
|
|
|
|
require.NoError(t, err)
|
|
|
|
verify(t, qry, []histogram.FloatHistogram{
|
|
|
|
{
|
|
|
|
Count: 6,
|
|
|
|
Sum: 6,
|
|
|
|
PositiveSpans: []histogram.Span{{Offset: 0, Length: 2}},
|
|
|
|
PositiveBuckets: []float64{3, 3},
|
|
|
|
},
|
|
|
|
{
|
|
|
|
Count: 1,
|
|
|
|
Sum: 1,
|
|
|
|
PositiveSpans: []histogram.Span{{Offset: 0, Length: 1}},
|
|
|
|
PositiveBuckets: []float64{1},
|
|
|
|
},
|
|
|
|
})
|
|
|
|
}
|