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51689d965d
This adds timers around several query-relevant code blocks. For now, the query timer stats are only logged for queries initiated through the UI. In other cases (rule evaluations), the stats are simply thrown away. My hope is that this helps us understand where queries spend time, especially in cases where they sometimes hang for unusual amounts of time.
151 lines
5.3 KiB
Go
151 lines
5.3 KiB
Go
// Copyright 2013 Prometheus Team
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package ast
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import (
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"github.com/prometheus/prometheus/model"
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"github.com/prometheus/prometheus/stats"
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"github.com/prometheus/prometheus/storage/metric"
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"log"
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"time"
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)
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type FullRangeMap map[model.Fingerprint]time.Duration
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type IntervalRangeMap map[model.Fingerprint]bool
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type QueryAnalyzer struct {
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// Values collected by query analysis.
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//
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// Full ranges always implicitly span a time range of:
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// - start: query interval start - duration
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// - end: query interval end
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//
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// This is because full ranges can only result from matrix literals (like
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// "foo[5m]"), which have said time-spanning behavior during a ranged query.
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FullRanges FullRangeMap
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// Interval ranges always implicitly span the whole query interval.
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IntervalRanges IntervalRangeMap
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// The underlying storage to which the query will be applied. Needed for
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// extracting timeseries fingerprint information during query analysis.
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storage *metric.TieredStorage
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}
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func NewQueryAnalyzer(storage *metric.TieredStorage) *QueryAnalyzer {
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return &QueryAnalyzer{
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FullRanges: FullRangeMap{},
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IntervalRanges: IntervalRangeMap{},
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storage: storage,
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}
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}
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func (analyzer *QueryAnalyzer) Visit(node Node) {
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switch n := node.(type) {
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case *VectorLiteral:
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fingerprints, err := analyzer.storage.GetFingerprintsForLabelSet(n.labels)
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if err != nil {
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log.Printf("Error getting fingerprints for labelset %v: %v", n.labels, err)
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return
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}
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n.fingerprints = fingerprints
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for _, fingerprint := range fingerprints {
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if !analyzer.IntervalRanges[*fingerprint] {
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analyzer.IntervalRanges[*fingerprint] = true
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}
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}
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case *MatrixLiteral:
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fingerprints, err := analyzer.storage.GetFingerprintsForLabelSet(n.labels)
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if err != nil {
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log.Printf("Error getting fingerprints for labelset %v: %v", n.labels, err)
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return
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}
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n.fingerprints = fingerprints
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for _, fingerprint := range fingerprints {
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interval := n.interval
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// If an interval has already been recorded for this fingerprint, merge
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// it with the current interval.
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if oldInterval, ok := analyzer.FullRanges[*fingerprint]; ok {
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if oldInterval > interval {
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interval = oldInterval
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}
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}
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analyzer.FullRanges[*fingerprint] = interval
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}
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}
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}
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func (analyzer *QueryAnalyzer) AnalyzeQueries(node Node) {
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Walk(analyzer, node)
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// Find and dedupe overlaps between full and stepped ranges. Full ranges
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// always contain more points *and* span more time than stepped ranges, so
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// throw away stepped ranges for fingerprints which have full ranges.
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for fingerprint := range analyzer.FullRanges {
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if analyzer.IntervalRanges[fingerprint] {
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delete(analyzer.IntervalRanges, fingerprint)
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}
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}
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}
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func viewAdapterForInstantQuery(node Node, timestamp time.Time, storage *metric.TieredStorage, queryStats *stats.TimerGroup) (*viewAdapter, error) {
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analyzeTimer := queryStats.GetTimer(stats.QueryAnalysisTime).Start()
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analyzer := NewQueryAnalyzer(storage)
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analyzer.AnalyzeQueries(node)
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analyzeTimer.Stop()
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requestBuildTimer := queryStats.GetTimer(stats.ViewRequestBuildTime).Start()
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viewBuilder := metric.NewViewRequestBuilder()
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for fingerprint, rangeDuration := range analyzer.FullRanges {
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viewBuilder.GetMetricRange(fingerprint, timestamp.Add(-rangeDuration), timestamp)
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}
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for fingerprint := range analyzer.IntervalRanges {
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viewBuilder.GetMetricAtTime(fingerprint, timestamp)
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}
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requestBuildTimer.Stop()
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buildTimer := queryStats.GetTimer(stats.InnerViewBuildingTime).Start()
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view, err := analyzer.storage.MakeView(viewBuilder, time.Duration(60)*time.Second, queryStats)
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buildTimer.Stop()
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if err != nil {
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return nil, err
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}
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return NewViewAdapter(view, storage, queryStats), nil
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}
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func viewAdapterForRangeQuery(node Node, start time.Time, end time.Time, interval time.Duration, storage *metric.TieredStorage, queryStats *stats.TimerGroup) (*viewAdapter, error) {
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analyzeTimer := queryStats.GetTimer(stats.QueryAnalysisTime).Start()
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analyzer := NewQueryAnalyzer(storage)
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analyzer.AnalyzeQueries(node)
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analyzeTimer.Stop()
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requestBuildTimer := queryStats.GetTimer(stats.ViewRequestBuildTime).Start()
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viewBuilder := metric.NewViewRequestBuilder()
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for fingerprint, rangeDuration := range analyzer.FullRanges {
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// TODO: we should support GetMetricRangeAtInterval() or similar ops in the view builder.
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for t := start; t.Before(end); t = t.Add(interval) {
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viewBuilder.GetMetricRange(fingerprint, t.Add(-rangeDuration), t)
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}
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}
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for fingerprint := range analyzer.IntervalRanges {
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viewBuilder.GetMetricAtInterval(fingerprint, start, end, interval)
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}
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requestBuildTimer.Stop()
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buildTimer := queryStats.GetTimer(stats.InnerViewBuildingTime).Start()
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view, err := analyzer.storage.MakeView(viewBuilder, time.Duration(60)*time.Second, queryStats)
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buildTimer.Stop()
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if err != nil {
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return nil, err
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}
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return NewViewAdapter(view, storage, queryStats), nil
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}
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