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prometheus/rules/ast/query_analyzer.go

161 lines
6.0 KiB

// Copyright 2013 Prometheus Team
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package ast
import (
"time"
"github.com/golang/glog"
clientmodel "github.com/prometheus/client_golang/model"
"github.com/prometheus/prometheus/stats"
"github.com/prometheus/prometheus/storage/metric"
)
// FullRangeMap maps the fingerprint of a full range to the duration
// of the matrix literal it resulted from.
type FullRangeMap map[clientmodel.Fingerprint]time.Duration
// IntervalRangeMap is a set of fingerprints of interval ranges.
type IntervalRangeMap map[clientmodel.Fingerprint]bool
// A QueryAnalyzer recursively traverses the AST to look for any nodes
// which will need data from the datastore. Instantiate with
// NewQueryAnalyzer.
type QueryAnalyzer struct {
// Values collected by query analysis.
//
// Full ranges always implicitly span a time range of:
// - start: query interval start - duration
// - end: query interval end
//
// This is because full ranges can only result from matrix literals (like
// "foo[5m]"), which have said time-spanning behavior during a ranged query.
FullRanges FullRangeMap
// Interval ranges always implicitly span the whole query range.
IntervalRanges IntervalRangeMap
// The underlying storage to which the query will be applied. Needed for
// extracting timeseries fingerprint information during query analysis.
storage *metric.TieredStorage
}
// NewQueryAnalyzer returns a pointer to a newly instantiated
// QueryAnalyzer. The storage is needed to extract timeseries
// fingerprint information during query analysis.
func NewQueryAnalyzer(storage *metric.TieredStorage) *QueryAnalyzer {
return &QueryAnalyzer{
FullRanges: FullRangeMap{},
IntervalRanges: IntervalRangeMap{},
storage: storage,
}
}
// Visit implements the Visitor interface.
func (analyzer *QueryAnalyzer) Visit(node Node) {
switch n := node.(type) {
case *VectorLiteral:
fingerprints, err := analyzer.storage.GetFingerprintsForLabelSet(n.labels)
if err != nil {
glog.Errorf("Error getting fingerprints for labelset %v: %v", n.labels, err)
return
}
n.fingerprints = fingerprints
for _, fingerprint := range fingerprints {
// Only add the fingerprint to IntervalRanges if not yet present in FullRanges.
// Full ranges always contain more points and span more time than interval ranges.
if _, alreadyInFullRanges := analyzer.FullRanges[*fingerprint]; !alreadyInFullRanges {
analyzer.IntervalRanges[*fingerprint] = true
}
}
case *MatrixLiteral:
fingerprints, err := analyzer.storage.GetFingerprintsForLabelSet(n.labels)
if err != nil {
glog.Errorf("Error getting fingerprints for labelset %v: %v", n.labels, err)
return
}
n.fingerprints = fingerprints
for _, fingerprint := range fingerprints {
if analyzer.FullRanges[*fingerprint] < n.interval {
analyzer.FullRanges[*fingerprint] = n.interval
// Delete the fingerprint from IntervalRanges. Full ranges always contain
// more points and span more time than interval ranges, so we don't need
// an interval range for the same fingerprint, should we have one.
delete(analyzer.IntervalRanges, *fingerprint)
}
}
}
}
// AnalyzeQueries walks the AST, starting at node, calling Visit on
// each node to collect fingerprints.
func (analyzer *QueryAnalyzer) AnalyzeQueries(node Node) {
Walk(analyzer, node)
}
func viewAdapterForInstantQuery(node Node, timestamp clientmodel.Timestamp, storage *metric.TieredStorage, queryStats *stats.TimerGroup) (*viewAdapter, error) {
analyzeTimer := queryStats.GetTimer(stats.QueryAnalysisTime).Start()
analyzer := NewQueryAnalyzer(storage)
analyzer.AnalyzeQueries(node)
analyzeTimer.Stop()
requestBuildTimer := queryStats.GetTimer(stats.ViewRequestBuildTime).Start()
viewBuilder := metric.NewViewRequestBuilder()
for fingerprint, rangeDuration := range analyzer.FullRanges {
viewBuilder.GetMetricRange(&fingerprint, timestamp.Add(-rangeDuration), timestamp)
}
for fingerprint := range analyzer.IntervalRanges {
viewBuilder.GetMetricAtTime(&fingerprint, timestamp)
}
requestBuildTimer.Stop()
buildTimer := queryStats.GetTimer(stats.InnerViewBuildingTime).Start()
// BUG(julius): Clear Law of Demeter violation.
view, err := analyzer.storage.MakeView(viewBuilder, 60*time.Second, queryStats)
buildTimer.Stop()
if err != nil {
return nil, err
}
return NewViewAdapter(view, storage, queryStats), nil
}
func viewAdapterForRangeQuery(node Node, start clientmodel.Timestamp, end clientmodel.Timestamp, interval time.Duration, storage *metric.TieredStorage, queryStats *stats.TimerGroup) (*viewAdapter, error) {
analyzeTimer := queryStats.GetTimer(stats.QueryAnalysisTime).Start()
analyzer := NewQueryAnalyzer(storage)
analyzer.AnalyzeQueries(node)
analyzeTimer.Stop()
requestBuildTimer := queryStats.GetTimer(stats.ViewRequestBuildTime).Start()
viewBuilder := metric.NewViewRequestBuilder()
for fingerprint, rangeDuration := range analyzer.FullRanges {
if interval < rangeDuration {
viewBuilder.GetMetricRange(&fingerprint, start.Add(-rangeDuration), end)
} else {
viewBuilder.GetMetricRangeAtInterval(&fingerprint, start.Add(-rangeDuration), end, interval, rangeDuration)
}
}
for fingerprint := range analyzer.IntervalRanges {
viewBuilder.GetMetricAtInterval(&fingerprint, start, end, interval)
}
requestBuildTimer.Stop()
buildTimer := queryStats.GetTimer(stats.InnerViewBuildingTime).Start()
view, err := analyzer.storage.MakeView(viewBuilder, time.Duration(60)*time.Second, queryStats)
buildTimer.Stop()
if err != nil {
return nil, err
}
return NewViewAdapter(view, storage, queryStats), nil
}