mirror of
https://github.com/prometheus/prometheus.git
synced 2024-12-28 15:09:39 -08:00
f4d3af73f0
Signed-off-by: Ganesh Vernekar <ganeshvern@gmail.com>
733 lines
21 KiB
Go
733 lines
21 KiB
Go
// Copyright 2020 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 storage
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import (
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"bytes"
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"container/heap"
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"math"
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"sort"
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"strings"
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"sync"
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"github.com/pkg/errors"
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"github.com/prometheus/prometheus/pkg/histogram"
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"github.com/prometheus/prometheus/pkg/labels"
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"github.com/prometheus/prometheus/tsdb/chunkenc"
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"github.com/prometheus/prometheus/tsdb/chunks"
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tsdb_errors "github.com/prometheus/prometheus/tsdb/errors"
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)
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type mergeGenericQuerier struct {
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queriers []genericQuerier
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// mergeFn is used when we see series from different queriers Selects with the same labels.
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mergeFn genericSeriesMergeFunc
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// TODO(bwplotka): Remove once remote queries are asynchronous. False by default.
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concurrentSelect bool
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}
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// NewMergeQuerier returns a new Querier that merges results of given primary and secondary queriers.
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// See NewFanout commentary to learn more about primary vs secondary differences.
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//
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// In case of overlaps between the data given by primaries' and secondaries' Selects, merge function will be used.
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func NewMergeQuerier(primaries []Querier, secondaries []Querier, mergeFn VerticalSeriesMergeFunc) Querier {
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queriers := make([]genericQuerier, 0, len(primaries)+len(secondaries))
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for _, q := range primaries {
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if _, ok := q.(noopQuerier); !ok && q != nil {
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queriers = append(queriers, newGenericQuerierFrom(q))
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}
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}
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for _, q := range secondaries {
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if _, ok := q.(noopQuerier); !ok && q != nil {
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queriers = append(queriers, newSecondaryQuerierFrom(q))
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}
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}
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concurrentSelect := false
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if len(secondaries) > 0 {
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concurrentSelect = true
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}
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return &querierAdapter{&mergeGenericQuerier{
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mergeFn: (&seriesMergerAdapter{VerticalSeriesMergeFunc: mergeFn}).Merge,
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queriers: queriers,
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concurrentSelect: concurrentSelect,
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}}
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}
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// NewMergeChunkQuerier returns a new Chunk Querier that merges results of given primary and secondary chunk queriers.
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// See NewFanout commentary to learn more about primary vs secondary differences.
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//
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// In case of overlaps between the data given by primaries' and secondaries' Selects, merge function will be used.
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// TODO(bwplotka): Currently merge will compact overlapping chunks with bigger chunk, without limit. Split it: https://github.com/prometheus/tsdb/issues/670
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func NewMergeChunkQuerier(primaries []ChunkQuerier, secondaries []ChunkQuerier, mergeFn VerticalChunkSeriesMergeFunc) ChunkQuerier {
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queriers := make([]genericQuerier, 0, len(primaries)+len(secondaries))
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for _, q := range primaries {
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if _, ok := q.(noopChunkQuerier); !ok && q != nil {
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queriers = append(queriers, newGenericQuerierFromChunk(q))
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}
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}
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for _, querier := range secondaries {
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if _, ok := querier.(noopChunkQuerier); !ok && querier != nil {
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queriers = append(queriers, newSecondaryQuerierFromChunk(querier))
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}
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}
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concurrentSelect := false
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if len(secondaries) > 0 {
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concurrentSelect = true
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}
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return &chunkQuerierAdapter{&mergeGenericQuerier{
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mergeFn: (&chunkSeriesMergerAdapter{VerticalChunkSeriesMergeFunc: mergeFn}).Merge,
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queriers: queriers,
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concurrentSelect: concurrentSelect,
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}}
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}
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// Select returns a set of series that matches the given label matchers.
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func (q *mergeGenericQuerier) Select(sortSeries bool, hints *SelectHints, matchers ...*labels.Matcher) genericSeriesSet {
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if len(q.queriers) == 0 {
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return noopGenericSeriesSet{}
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}
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if len(q.queriers) == 1 {
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return q.queriers[0].Select(sortSeries, hints, matchers...)
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}
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var seriesSets = make([]genericSeriesSet, 0, len(q.queriers))
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if !q.concurrentSelect {
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for _, querier := range q.queriers {
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// We need to sort for merge to work.
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seriesSets = append(seriesSets, querier.Select(true, hints, matchers...))
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}
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return &lazyGenericSeriesSet{init: func() (genericSeriesSet, bool) {
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s := newGenericMergeSeriesSet(seriesSets, q.mergeFn)
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return s, s.Next()
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}}
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}
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var (
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wg sync.WaitGroup
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seriesSetChan = make(chan genericSeriesSet)
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)
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// Schedule all Selects for all queriers we know about.
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for _, querier := range q.queriers {
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wg.Add(1)
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go func(qr genericQuerier) {
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defer wg.Done()
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// We need to sort for NewMergeSeriesSet to work.
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seriesSetChan <- qr.Select(true, hints, matchers...)
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}(querier)
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}
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go func() {
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wg.Wait()
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close(seriesSetChan)
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}()
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for r := range seriesSetChan {
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seriesSets = append(seriesSets, r)
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}
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return &lazyGenericSeriesSet{init: func() (genericSeriesSet, bool) {
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s := newGenericMergeSeriesSet(seriesSets, q.mergeFn)
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return s, s.Next()
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}}
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}
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type labelGenericQueriers []genericQuerier
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func (l labelGenericQueriers) Len() int { return len(l) }
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func (l labelGenericQueriers) Get(i int) LabelQuerier { return l[i] }
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func (l labelGenericQueriers) SplitByHalf() (labelGenericQueriers, labelGenericQueriers) {
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i := len(l) / 2
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return l[:i], l[i:]
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}
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// LabelValues returns all potential values for a label name.
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// If matchers are specified the returned result set is reduced
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// to label values of metrics matching the matchers.
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func (q *mergeGenericQuerier) LabelValues(name string, matchers ...*labels.Matcher) ([]string, Warnings, error) {
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res, ws, err := q.lvals(q.queriers, name, matchers...)
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if err != nil {
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return nil, nil, errors.Wrapf(err, "LabelValues() from merge generic querier for label %s", name)
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}
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return res, ws, nil
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}
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// lvals performs merge sort for LabelValues from multiple queriers.
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func (q *mergeGenericQuerier) lvals(lq labelGenericQueriers, n string, matchers ...*labels.Matcher) ([]string, Warnings, error) {
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if lq.Len() == 0 {
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return nil, nil, nil
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}
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if lq.Len() == 1 {
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return lq.Get(0).LabelValues(n, matchers...)
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}
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a, b := lq.SplitByHalf()
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var ws Warnings
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s1, w, err := q.lvals(a, n, matchers...)
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ws = append(ws, w...)
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if err != nil {
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return nil, ws, err
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}
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s2, ws, err := q.lvals(b, n, matchers...)
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ws = append(ws, w...)
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if err != nil {
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return nil, ws, err
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}
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return mergeStrings(s1, s2), ws, nil
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}
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func mergeStrings(a, b []string) []string {
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maxl := len(a)
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if len(b) > len(a) {
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maxl = len(b)
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}
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res := make([]string, 0, maxl*10/9)
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for len(a) > 0 && len(b) > 0 {
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d := strings.Compare(a[0], b[0])
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if d == 0 {
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res = append(res, a[0])
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a, b = a[1:], b[1:]
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} else if d < 0 {
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res = append(res, a[0])
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a = a[1:]
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} else if d > 0 {
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res = append(res, b[0])
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b = b[1:]
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}
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}
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// Append all remaining elements.
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res = append(res, a...)
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res = append(res, b...)
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return res
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}
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// LabelNames returns all the unique label names present in all queriers in sorted order.
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func (q *mergeGenericQuerier) LabelNames() ([]string, Warnings, error) {
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var (
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labelNamesMap = make(map[string]struct{})
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warnings Warnings
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)
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for _, querier := range q.queriers {
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names, wrn, err := querier.LabelNames()
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if wrn != nil {
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// TODO(bwplotka): We could potentially wrap warnings.
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warnings = append(warnings, wrn...)
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}
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if err != nil {
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return nil, nil, errors.Wrap(err, "LabelNames() from merge generic querier")
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}
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for _, name := range names {
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labelNamesMap[name] = struct{}{}
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}
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}
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if len(labelNamesMap) == 0 {
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return nil, warnings, nil
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}
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labelNames := make([]string, 0, len(labelNamesMap))
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for name := range labelNamesMap {
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labelNames = append(labelNames, name)
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}
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sort.Strings(labelNames)
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return labelNames, warnings, nil
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}
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// Close releases the resources of the generic querier.
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func (q *mergeGenericQuerier) Close() error {
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errs := tsdb_errors.NewMulti()
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for _, querier := range q.queriers {
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if err := querier.Close(); err != nil {
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errs.Add(err)
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}
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}
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return errs.Err()
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}
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// VerticalSeriesMergeFunc returns merged series implementation that merges series with same labels together.
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// It has to handle time-overlapped series as well.
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type VerticalSeriesMergeFunc func(...Series) Series
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// NewMergeSeriesSet returns a new SeriesSet that merges many SeriesSets together.
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func NewMergeSeriesSet(sets []SeriesSet, mergeFunc VerticalSeriesMergeFunc) SeriesSet {
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genericSets := make([]genericSeriesSet, 0, len(sets))
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for _, s := range sets {
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genericSets = append(genericSets, &genericSeriesSetAdapter{s})
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}
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return &seriesSetAdapter{newGenericMergeSeriesSet(genericSets, (&seriesMergerAdapter{VerticalSeriesMergeFunc: mergeFunc}).Merge)}
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}
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// VerticalChunkSeriesMergeFunc returns merged chunk series implementation that merges potentially time-overlapping
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// chunk series with the same labels into single ChunkSeries.
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//
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// NOTE: It's up to implementation how series are vertically merged (if chunks are sorted, re-encoded etc).
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type VerticalChunkSeriesMergeFunc func(...ChunkSeries) ChunkSeries
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// NewMergeChunkSeriesSet returns a new ChunkSeriesSet that merges many SeriesSet together.
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func NewMergeChunkSeriesSet(sets []ChunkSeriesSet, mergeFunc VerticalChunkSeriesMergeFunc) ChunkSeriesSet {
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genericSets := make([]genericSeriesSet, 0, len(sets))
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for _, s := range sets {
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genericSets = append(genericSets, &genericChunkSeriesSetAdapter{s})
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}
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return &chunkSeriesSetAdapter{newGenericMergeSeriesSet(genericSets, (&chunkSeriesMergerAdapter{VerticalChunkSeriesMergeFunc: mergeFunc}).Merge)}
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}
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// genericMergeSeriesSet implements genericSeriesSet.
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type genericMergeSeriesSet struct {
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currentLabels labels.Labels
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mergeFunc genericSeriesMergeFunc
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heap genericSeriesSetHeap
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sets []genericSeriesSet
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currentSets []genericSeriesSet
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}
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// newGenericMergeSeriesSet returns a new genericSeriesSet that merges (and deduplicates)
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// series returned by the series sets when iterating.
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// Each series set must return its series in labels order, otherwise
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// merged series set will be incorrect.
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// Overlapped situations are merged using provided mergeFunc.
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func newGenericMergeSeriesSet(sets []genericSeriesSet, mergeFunc genericSeriesMergeFunc) genericSeriesSet {
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if len(sets) == 1 {
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return sets[0]
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}
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// We are pre-advancing sets, so we can introspect the label of the
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// series under the cursor.
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var h genericSeriesSetHeap
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for _, set := range sets {
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if set == nil {
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continue
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}
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if set.Next() {
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heap.Push(&h, set)
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}
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if err := set.Err(); err != nil {
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return errorOnlySeriesSet{err}
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}
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}
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return &genericMergeSeriesSet{
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mergeFunc: mergeFunc,
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sets: sets,
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heap: h,
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}
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}
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func (c *genericMergeSeriesSet) Next() bool {
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// Run in a loop because the "next" series sets may not be valid anymore.
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// If, for the current label set, all the next series sets come from
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// failed remote storage sources, we want to keep trying with the next label set.
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for {
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// Firstly advance all the current series sets. If any of them have run out,
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// we can drop them, otherwise they should be inserted back into the heap.
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for _, set := range c.currentSets {
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if set.Next() {
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heap.Push(&c.heap, set)
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}
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}
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if len(c.heap) == 0 {
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return false
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}
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// Now, pop items of the heap that have equal label sets.
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c.currentSets = nil
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c.currentLabels = c.heap[0].At().Labels()
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for len(c.heap) > 0 && labels.Equal(c.currentLabels, c.heap[0].At().Labels()) {
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set := heap.Pop(&c.heap).(genericSeriesSet)
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c.currentSets = append(c.currentSets, set)
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}
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// As long as the current set contains at least 1 set,
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// then it should return true.
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if len(c.currentSets) != 0 {
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break
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}
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}
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return true
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}
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func (c *genericMergeSeriesSet) At() Labels {
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if len(c.currentSets) == 1 {
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return c.currentSets[0].At()
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}
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series := make([]Labels, 0, len(c.currentSets))
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for _, seriesSet := range c.currentSets {
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series = append(series, seriesSet.At())
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}
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return c.mergeFunc(series...)
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}
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func (c *genericMergeSeriesSet) Err() error {
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for _, set := range c.sets {
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if err := set.Err(); err != nil {
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return err
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}
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}
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return nil
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}
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func (c *genericMergeSeriesSet) Warnings() Warnings {
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var ws Warnings
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for _, set := range c.sets {
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ws = append(ws, set.Warnings()...)
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}
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return ws
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}
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type genericSeriesSetHeap []genericSeriesSet
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func (h genericSeriesSetHeap) Len() int { return len(h) }
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func (h genericSeriesSetHeap) Swap(i, j int) { h[i], h[j] = h[j], h[i] }
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func (h genericSeriesSetHeap) Less(i, j int) bool {
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a, b := h[i].At().Labels(), h[j].At().Labels()
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return labels.Compare(a, b) < 0
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}
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func (h *genericSeriesSetHeap) Push(x interface{}) {
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*h = append(*h, x.(genericSeriesSet))
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}
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func (h *genericSeriesSetHeap) Pop() interface{} {
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old := *h
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n := len(old)
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x := old[n-1]
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*h = old[0 : n-1]
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return x
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}
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// ChainedSeriesMerge returns single series from many same, potentially overlapping series by chaining samples together.
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// If one or more samples overlap, one sample from random overlapped ones is kept and all others with the same
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// timestamp are dropped.
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//
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// This works the best with replicated series, where data from two series are exactly the same. This does not work well
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// with "almost" the same data, e.g. from 2 Prometheus HA replicas. This is fine, since from the Prometheus perspective
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// this never happens.
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//
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// It's optimized for non-overlap cases as well.
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func ChainedSeriesMerge(series ...Series) Series {
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if len(series) == 0 {
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return nil
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}
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return &SeriesEntry{
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Lset: series[0].Labels(),
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SampleIteratorFn: func() chunkenc.Iterator {
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iterators := make([]chunkenc.Iterator, 0, len(series))
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for _, s := range series {
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iterators = append(iterators, s.Iterator())
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}
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return newChainSampleIterator(iterators)
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},
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}
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}
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// chainSampleIterator is responsible to iterate over samples from different iterators of the same time series in timestamps
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// order. If one or more samples overlap, one sample from random overlapped ones is kept and all others with the same
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// timestamp are dropped. It's optimized for non-overlap cases as well.
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type chainSampleIterator struct {
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iterators []chunkenc.Iterator
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h samplesIteratorHeap
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curr chunkenc.Iterator
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lastt int64
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}
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func newChainSampleIterator(iterators []chunkenc.Iterator) chunkenc.Iterator {
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return &chainSampleIterator{
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iterators: iterators,
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h: nil,
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lastt: math.MinInt64,
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}
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}
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func (c *chainSampleIterator) Seek(t int64) bool {
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c.h = samplesIteratorHeap{}
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for _, iter := range c.iterators {
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if iter.Seek(t) {
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heap.Push(&c.h, iter)
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}
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}
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if len(c.h) > 0 {
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c.curr = heap.Pop(&c.h).(chunkenc.Iterator)
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c.lastt, _ = c.curr.At()
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return true
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}
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c.curr = nil
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return false
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}
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|
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func (c *chainSampleIterator) At() (t int64, v float64) {
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if c.curr == nil {
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panic("chainSampleIterator.At() called before first .Next() or after .Next() returned false.")
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}
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return c.curr.At()
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}
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func (c *chainSampleIterator) AtHistogram() (int64, histogram.SparseHistogram) {
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if c.curr == nil {
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panic("chainSampleIterator.AtHistogram() called before first .Next() or after .Next() returned false.")
|
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}
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return c.curr.AtHistogram()
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}
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|
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func (c *chainSampleIterator) ChunkEncoding() chunkenc.Encoding {
|
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if c.curr == nil {
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panic("chainSampleIterator.ChunkEncoding() called before first .Next() or after .Next() returned false.")
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}
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return c.curr.ChunkEncoding()
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}
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|
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func (c *chainSampleIterator) Next() bool {
|
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if c.h == nil {
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c.h = samplesIteratorHeap{}
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// We call c.curr.Next() as the first thing below.
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|
// So, we don't call Next() on it here.
|
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c.curr = c.iterators[0]
|
|
for _, iter := range c.iterators[1:] {
|
|
if iter.Next() {
|
|
heap.Push(&c.h, iter)
|
|
}
|
|
}
|
|
}
|
|
|
|
if c.curr == nil {
|
|
return false
|
|
}
|
|
|
|
var currt int64
|
|
for {
|
|
if c.curr.Next() {
|
|
currt, _ = c.curr.At()
|
|
if currt == c.lastt {
|
|
// Ignoring sample for the same timestamp.
|
|
continue
|
|
}
|
|
if len(c.h) == 0 {
|
|
// curr is the only iterator remaining,
|
|
// no need to check with the heap.
|
|
break
|
|
}
|
|
|
|
// Check current iterator with the top of the heap.
|
|
if nextt, _ := c.h[0].At(); currt < nextt {
|
|
// Current iterator has smaller timestamp than the heap.
|
|
break
|
|
}
|
|
// Current iterator does not hold the smallest timestamp.
|
|
heap.Push(&c.h, c.curr)
|
|
} else if len(c.h) == 0 {
|
|
// No iterator left to iterate.
|
|
c.curr = nil
|
|
return false
|
|
}
|
|
|
|
c.curr = heap.Pop(&c.h).(chunkenc.Iterator)
|
|
currt, _ = c.curr.At()
|
|
if currt != c.lastt {
|
|
break
|
|
}
|
|
}
|
|
|
|
c.lastt = currt
|
|
return true
|
|
}
|
|
|
|
func (c *chainSampleIterator) Err() error {
|
|
errs := tsdb_errors.NewMulti()
|
|
for _, iter := range c.iterators {
|
|
errs.Add(iter.Err())
|
|
}
|
|
return errs.Err()
|
|
}
|
|
|
|
type samplesIteratorHeap []chunkenc.Iterator
|
|
|
|
func (h samplesIteratorHeap) Len() int { return len(h) }
|
|
func (h samplesIteratorHeap) Swap(i, j int) { h[i], h[j] = h[j], h[i] }
|
|
|
|
func (h samplesIteratorHeap) Less(i, j int) bool {
|
|
at, _ := h[i].At()
|
|
bt, _ := h[j].At()
|
|
return at < bt
|
|
}
|
|
|
|
func (h *samplesIteratorHeap) Push(x interface{}) {
|
|
*h = append(*h, x.(chunkenc.Iterator))
|
|
}
|
|
|
|
func (h *samplesIteratorHeap) Pop() interface{} {
|
|
old := *h
|
|
n := len(old)
|
|
x := old[n-1]
|
|
*h = old[0 : n-1]
|
|
return x
|
|
}
|
|
|
|
// NewCompactingChunkSeriesMerger returns VerticalChunkSeriesMergeFunc that merges the same chunk series into single chunk series.
|
|
// In case of the chunk overlaps, it compacts those into one or more time-ordered non-overlapping chunks with merged data.
|
|
// Samples from overlapped chunks are merged using series vertical merge func.
|
|
// It expects the same labels for each given series.
|
|
//
|
|
// NOTE: Use the returned merge function only when you see potentially overlapping series, as this introduces small a overhead
|
|
// to handle overlaps between series.
|
|
func NewCompactingChunkSeriesMerger(mergeFunc VerticalSeriesMergeFunc) VerticalChunkSeriesMergeFunc {
|
|
return func(series ...ChunkSeries) ChunkSeries {
|
|
if len(series) == 0 {
|
|
return nil
|
|
}
|
|
return &ChunkSeriesEntry{
|
|
Lset: series[0].Labels(),
|
|
ChunkIteratorFn: func() chunks.Iterator {
|
|
iterators := make([]chunks.Iterator, 0, len(series))
|
|
for _, s := range series {
|
|
iterators = append(iterators, s.Iterator())
|
|
}
|
|
return &compactChunkIterator{
|
|
mergeFunc: mergeFunc,
|
|
iterators: iterators,
|
|
}
|
|
},
|
|
}
|
|
}
|
|
}
|
|
|
|
// compactChunkIterator is responsible to compact chunks from different iterators of the same time series into single chainSeries.
|
|
// If time-overlapping chunks are found, they are encoded and passed to series merge and encoded again into one bigger chunk.
|
|
// TODO(bwplotka): Currently merge will compact overlapping chunks with bigger chunk, without limit. Split it: https://github.com/prometheus/tsdb/issues/670
|
|
type compactChunkIterator struct {
|
|
mergeFunc VerticalSeriesMergeFunc
|
|
iterators []chunks.Iterator
|
|
|
|
h chunkIteratorHeap
|
|
|
|
err error
|
|
curr chunks.Meta
|
|
}
|
|
|
|
func (c *compactChunkIterator) At() chunks.Meta {
|
|
return c.curr
|
|
}
|
|
|
|
func (c *compactChunkIterator) Next() bool {
|
|
if c.h == nil {
|
|
for _, iter := range c.iterators {
|
|
if iter.Next() {
|
|
heap.Push(&c.h, iter)
|
|
}
|
|
}
|
|
}
|
|
if len(c.h) == 0 {
|
|
return false
|
|
}
|
|
|
|
iter := heap.Pop(&c.h).(chunks.Iterator)
|
|
c.curr = iter.At()
|
|
if iter.Next() {
|
|
heap.Push(&c.h, iter)
|
|
}
|
|
|
|
var (
|
|
overlapping []Series
|
|
oMaxTime = c.curr.MaxTime
|
|
prev = c.curr
|
|
)
|
|
// Detect overlaps to compact. Be smart about it and deduplicate on the fly if chunks are identical.
|
|
for len(c.h) > 0 {
|
|
// Get the next oldest chunk by min, then max time.
|
|
next := c.h[0].At()
|
|
if next.MinTime > oMaxTime {
|
|
// No overlap with current one.
|
|
break
|
|
}
|
|
|
|
if next.MinTime == prev.MinTime &&
|
|
next.MaxTime == prev.MaxTime &&
|
|
bytes.Equal(next.Chunk.Bytes(), prev.Chunk.Bytes()) {
|
|
// 1:1 duplicates, skip it.
|
|
} else {
|
|
// We operate on same series, so labels does not matter here.
|
|
overlapping = append(overlapping, newChunkToSeriesDecoder(nil, next))
|
|
if next.MaxTime > oMaxTime {
|
|
oMaxTime = next.MaxTime
|
|
}
|
|
prev = next
|
|
}
|
|
|
|
iter := heap.Pop(&c.h).(chunks.Iterator)
|
|
if iter.Next() {
|
|
heap.Push(&c.h, iter)
|
|
}
|
|
}
|
|
if len(overlapping) == 0 {
|
|
return true
|
|
}
|
|
|
|
// Add last as it's not yet included in overlap. We operate on same series, so labels does not matter here.
|
|
iter = NewSeriesToChunkEncoder(c.mergeFunc(append(overlapping, newChunkToSeriesDecoder(nil, c.curr))...)).Iterator()
|
|
if !iter.Next() {
|
|
if c.err = iter.Err(); c.err != nil {
|
|
return false
|
|
}
|
|
panic("unexpected seriesToChunkEncoder lack of iterations")
|
|
}
|
|
c.curr = iter.At()
|
|
if iter.Next() {
|
|
heap.Push(&c.h, iter)
|
|
}
|
|
return true
|
|
}
|
|
|
|
func (c *compactChunkIterator) Err() error {
|
|
errs := tsdb_errors.NewMulti()
|
|
for _, iter := range c.iterators {
|
|
errs.Add(iter.Err())
|
|
}
|
|
errs.Add(c.err)
|
|
return errs.Err()
|
|
}
|
|
|
|
type chunkIteratorHeap []chunks.Iterator
|
|
|
|
func (h chunkIteratorHeap) Len() int { return len(h) }
|
|
func (h chunkIteratorHeap) Swap(i, j int) { h[i], h[j] = h[j], h[i] }
|
|
|
|
func (h chunkIteratorHeap) Less(i, j int) bool {
|
|
at := h[i].At()
|
|
bt := h[j].At()
|
|
if at.MinTime == bt.MinTime {
|
|
return at.MaxTime < bt.MaxTime
|
|
}
|
|
return at.MinTime < bt.MinTime
|
|
}
|
|
|
|
func (h *chunkIteratorHeap) Push(x interface{}) {
|
|
*h = append(*h, x.(chunks.Iterator))
|
|
}
|
|
|
|
func (h *chunkIteratorHeap) Pop() interface{} {
|
|
old := *h
|
|
n := len(old)
|
|
x := old[n-1]
|
|
*h = old[0 : n-1]
|
|
return x
|
|
}
|