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So far we've been using Go's native time.Time for anything related to sample timestamps. Since the range of time.Time is much bigger than what we need, this has created two problems: - there could be time.Time values which were out of the range/precision of the time type that we persist to disk, therefore causing incorrectly ordered keys. One bug caused by this was: https://github.com/prometheus/prometheus/issues/367 It would be good to use a timestamp type that's more closely aligned with what the underlying storage supports. - sizeof(time.Time) is 192, while Prometheus should be ok with a single 64-bit Unix timestamp (possibly even a 32-bit one). Since we store samples in large numbers, this seriously affects memory usage. Furthermore, copying/working with the data will be faster if it's smaller. *MEMORY USAGE RESULTS* Initial memory usage comparisons for a running Prometheus with 1 timeseries and 100,000 samples show roughly a 13% decrease in total (VIRT) memory usage. In my tests, this advantage for some reason decreased a bit the more samples the timeseries had (to 5-7% for millions of samples). This I can't fully explain, but perhaps garbage collection issues were involved. *WHEN TO USE THE NEW TIMESTAMP TYPE* The new clientmodel.Timestamp type should be used whenever time calculations are either directly or indirectly related to sample timestamps. For example: - the timestamp of a sample itself - all kinds of watermarks - anything that may become or is compared to a sample timestamp (like the timestamp passed into Target.Scrape()). When to still use time.Time: - for measuring durations/times not related to sample timestamps, like duration telemetry exporting, timers that indicate how frequently to execute some action, etc. *NOTE ON OPERATOR OPTIMIZATION TESTS* We don't use operator optimization code anymore, but it still lives in the code as dead code. It still has tests, but I couldn't get all of them to pass with the new timestamp format. I commented out the failing cases for now, but we should probably remove the dead code soon. I just didn't want to do that in the same change as this. Change-Id: I821787414b0debe85c9fffaeb57abd453727af0f
156 lines
5.5 KiB
Go
156 lines
5.5 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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"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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type FullRangeMap map[clientmodel.Fingerprint]time.Duration
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type IntervalRangeMap map[clientmodel.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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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.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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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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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 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, 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 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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