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161 lines
6.0 KiB
161 lines
6.0 KiB
// 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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"time"
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"github.com/golang/glog"
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clientmodel "github.com/prometheus/client_golang/model"
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"github.com/prometheus/prometheus/stats"
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"github.com/prometheus/prometheus/storage/metric"
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)
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// FullRangeMap maps the fingerprint of a full range to the duration
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// of the matrix literal it resulted from.
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type FullRangeMap map[clientmodel.Fingerprint]time.Duration
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// IntervalRangeMap is a set of fingerprints of interval ranges.
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type IntervalRangeMap map[clientmodel.Fingerprint]bool
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// A QueryAnalyzer recursively traverses the AST to look for any nodes
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// which will need data from the datastore. Instantiate with
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// NewQueryAnalyzer.
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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 range.
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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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// NewQueryAnalyzer returns a pointer to a newly instantiated
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// QueryAnalyzer. The storage is needed to extract timeseries
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// fingerprint information during query analysis.
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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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// Visit implements the Visitor interface.
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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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glog.Errorf("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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// Only add the fingerprint to IntervalRanges if not yet present in FullRanges.
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// Full ranges always contain more points and span more time than interval ranges.
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if _, alreadyInFullRanges := analyzer.FullRanges[*fingerprint]; !alreadyInFullRanges {
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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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glog.Errorf("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.FullRanges[*fingerprint] < n.interval {
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analyzer.FullRanges[*fingerprint] = n.interval
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// Delete the fingerprint from IntervalRanges. Full ranges always contain
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// more points and span more time than interval ranges, so we don't need
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// an interval range for the same fingerprint, should we have one.
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delete(analyzer.IntervalRanges, *fingerprint)
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}
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}
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}
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}
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// AnalyzeQueries walks the AST, starting at node, calling Visit on
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// each node to collect fingerprints.
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func (analyzer *QueryAnalyzer) AnalyzeQueries(node Node) {
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Walk(analyzer, node)
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}
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func viewAdapterForInstantQuery(node Node, timestamp clientmodel.Timestamp, 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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// BUG(julius): Clear Law of Demeter violation.
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view, err := analyzer.storage.MakeView(viewBuilder, 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 clientmodel.Timestamp, end clientmodel.Timestamp, 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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if interval < rangeDuration {
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viewBuilder.GetMetricRange(&fingerprint, start.Add(-rangeDuration), end)
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} else {
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viewBuilder.GetMetricRangeAtInterval(&fingerprint, start.Add(-rangeDuration), end, interval, rangeDuration)
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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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