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171 lines
5.6 KiB
171 lines
5.6 KiB
10 years ago
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// Copyright 2013 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package promql
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import (
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"errors"
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"time"
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"golang.org/x/net/context"
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clientmodel "github.com/prometheus/client_golang/model"
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"github.com/prometheus/prometheus/storage/local"
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)
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// An Analyzer traverses an expression and determines which data has to be requested
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// from the storage. It is bound to a context that allows cancellation and timing out.
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type Analyzer struct {
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// The storage from which to query data.
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Storage local.Storage
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// The expression being analyzed.
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Expr Expr
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// The time range for evaluation of Expr.
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Start, End clientmodel.Timestamp
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// The preload times for different query time offsets.
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offsetPreloadTimes map[time.Duration]preloadTimes
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}
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// preloadTimes tracks which instants or ranges to preload for a set of
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// fingerprints. One of these structs is collected for each offset by the query
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// analyzer.
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type preloadTimes struct {
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// Instants require single samples to be loaded along the entire query
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// range, with intervals between the samples corresponding to the query
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// resolution.
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instants map[clientmodel.Fingerprint]struct{}
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// Ranges require loading a range of samples at each resolution step,
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// stretching backwards from the current evaluation timestamp. The length of
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// the range into the past is given by the duration, as in "foo[5m]".
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ranges map[clientmodel.Fingerprint]time.Duration
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}
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// Analyze the provided expression and attach metrics and fingerprints to data-selecting
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// AST nodes that are later used to preload the data from the storage.
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func (a *Analyzer) Analyze(ctx context.Context) error {
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a.offsetPreloadTimes = map[time.Duration]preloadTimes{}
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getPreloadTimes := func(offset time.Duration) preloadTimes {
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if _, ok := a.offsetPreloadTimes[offset]; !ok {
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a.offsetPreloadTimes[offset] = preloadTimes{
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instants: map[clientmodel.Fingerprint]struct{}{},
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ranges: map[clientmodel.Fingerprint]time.Duration{},
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}
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}
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return a.offsetPreloadTimes[offset]
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}
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// Retrieve fingerprints and metrics for the required time range for
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// each metric or matrix selector node.
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Inspect(a.Expr, func(node Node) bool {
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switch n := node.(type) {
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case *VectorSelector:
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pt := getPreloadTimes(n.Offset)
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fpts := a.Storage.GetFingerprintsForLabelMatchers(n.LabelMatchers)
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n.fingerprints = fpts
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n.metrics = map[clientmodel.Fingerprint]clientmodel.COWMetric{}
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n.iterators = map[clientmodel.Fingerprint]local.SeriesIterator{}
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for _, fp := range fpts {
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// Only add the fingerprint to the instants if not yet present in the
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// ranges. Ranges always contain more points and span more time than
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// instants for the same offset.
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if _, alreadyInRanges := pt.ranges[fp]; !alreadyInRanges {
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pt.instants[fp] = struct{}{}
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}
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n.metrics[fp] = a.Storage.GetMetricForFingerprint(fp)
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}
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case *MatrixSelector:
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pt := getPreloadTimes(n.Offset)
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fpts := a.Storage.GetFingerprintsForLabelMatchers(n.LabelMatchers)
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n.fingerprints = fpts
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n.metrics = map[clientmodel.Fingerprint]clientmodel.COWMetric{}
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n.iterators = map[clientmodel.Fingerprint]local.SeriesIterator{}
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for _, fp := range fpts {
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if pt.ranges[fp] < n.Range {
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pt.ranges[fp] = n.Range
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// Delete the fingerprint from the instants. Ranges always contain more
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// points and span more time than instants, so we don't need to track
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// an instant for the same fingerprint, should we have one.
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delete(pt.instants, fp)
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}
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n.metrics[fp] = a.Storage.GetMetricForFingerprint(fp)
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}
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}
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return true
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})
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// Currently we do not return an error but we might place a context check in here
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// or extend the stage in some other way.
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return nil
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}
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// Prepare the expression evaluation by preloading all required chunks from the storage
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// and setting the respective storage iterators in the AST nodes.
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func (a *Analyzer) Prepare(ctx context.Context) (local.Preloader, error) {
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const env = "query preparation"
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if a.offsetPreloadTimes == nil {
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return nil, errors.New("analysis must be performed before preparing query")
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}
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var err error
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// The preloader must not be closed unless an error ocurred as closing
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// unpins the preloaded chunks.
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p := a.Storage.NewPreloader()
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defer func() {
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if err != nil {
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p.Close()
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}
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}()
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// Preload all analyzed ranges.
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for offset, pt := range a.offsetPreloadTimes {
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if err = contextDone(ctx, env); err != nil {
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return nil, err
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}
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start := a.Start.Add(-offset)
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end := a.End.Add(-offset)
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for fp, rangeDuration := range pt.ranges {
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err = p.PreloadRange(fp, start.Add(-rangeDuration), end, *stalenessDelta)
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if err != nil {
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return nil, err
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}
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}
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for fp := range pt.instants {
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err = p.PreloadRange(fp, start, end, *stalenessDelta)
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if err != nil {
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return nil, err
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}
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}
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}
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// Attach storage iterators to AST nodes.
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Inspect(a.Expr, func(node Node) bool {
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switch n := node.(type) {
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case *VectorSelector:
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for _, fp := range n.fingerprints {
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n.iterators[fp] = a.Storage.NewIterator(fp)
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}
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case *MatrixSelector:
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for _, fp := range n.fingerprints {
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n.iterators[fp] = a.Storage.NewIterator(fp)
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}
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}
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return true
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})
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return p, nil
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}
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