mirror of
https://github.com/prometheus/prometheus.git
synced 2024-11-09 23:24:05 -08:00
7e42acd3b1
- Pick At... method via return value of Next/Seek. - Do not clobber returned buckets. - Add partial FloatHistogram suppert. Note that the promql package is now _only_ dealing with FloatHistograms, following the idea that PromQL only knows float values. As a byproduct, I have removed the histogramSeries metric. In my understanding, series can have both float and histogram samples, so that metric doesn't make sense anymore. As another byproduct, I have converged the sampleBuf and the histogramSampleBuf in memSeries into one. The sample type stored in the sampleBuf has been extended to also contain histograms even before this commit. Signed-off-by: beorn7 <beorn@grafana.com>
354 lines
9.4 KiB
Go
354 lines
9.4 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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"math"
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"sort"
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"github.com/prometheus/prometheus/model/histogram"
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"github.com/prometheus/prometheus/model/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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"github.com/prometheus/prometheus/tsdb/tsdbutil"
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)
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type SeriesEntry struct {
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Lset labels.Labels
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SampleIteratorFn func() chunkenc.Iterator
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}
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func (s *SeriesEntry) Labels() labels.Labels { return s.Lset }
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func (s *SeriesEntry) Iterator() chunkenc.Iterator { return s.SampleIteratorFn() }
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type ChunkSeriesEntry struct {
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Lset labels.Labels
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ChunkIteratorFn func() chunks.Iterator
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}
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func (s *ChunkSeriesEntry) Labels() labels.Labels { return s.Lset }
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func (s *ChunkSeriesEntry) Iterator() chunks.Iterator { return s.ChunkIteratorFn() }
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// NewListSeries returns series entry with iterator that allows to iterate over provided samples.
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func NewListSeries(lset labels.Labels, s []tsdbutil.Sample) *SeriesEntry {
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return &SeriesEntry{
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Lset: lset,
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SampleIteratorFn: func() chunkenc.Iterator {
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return NewListSeriesIterator(samples(s))
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},
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}
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}
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// NewListChunkSeriesFromSamples returns chunk series entry that allows to iterate over provided samples.
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// NOTE: It uses inefficient chunks encoding implementation, not caring about chunk size.
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func NewListChunkSeriesFromSamples(lset labels.Labels, samples ...[]tsdbutil.Sample) *ChunkSeriesEntry {
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return &ChunkSeriesEntry{
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Lset: lset,
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ChunkIteratorFn: func() chunks.Iterator {
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chks := make([]chunks.Meta, 0, len(samples))
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for _, s := range samples {
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chks = append(chks, tsdbutil.ChunkFromSamples(s))
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}
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return NewListChunkSeriesIterator(chks...)
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},
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}
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}
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type listSeriesIterator struct {
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samples Samples
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idx int
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}
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type samples []tsdbutil.Sample
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func (s samples) Get(i int) tsdbutil.Sample { return s[i] }
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func (s samples) Len() int { return len(s) }
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// Samples interface allows to work on arrays of types that are compatible with tsdbutil.Sample.
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type Samples interface {
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Get(i int) tsdbutil.Sample
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Len() int
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}
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// NewListSeriesIterator returns listSeriesIterator that allows to iterate over provided samples.
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func NewListSeriesIterator(samples Samples) chunkenc.Iterator {
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return &listSeriesIterator{samples: samples, idx: -1}
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}
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func (it *listSeriesIterator) At() (int64, float64) {
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s := it.samples.Get(it.idx)
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return s.T(), s.V()
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}
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func (it *listSeriesIterator) AtHistogram() (int64, *histogram.Histogram) {
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s := it.samples.Get(it.idx)
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return s.T(), s.H()
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}
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func (it *listSeriesIterator) AtFloatHistogram() (int64, *histogram.FloatHistogram) {
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s := it.samples.Get(it.idx)
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return s.T(), s.FH()
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}
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func (it *listSeriesIterator) AtT() int64 {
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s := it.samples.Get(it.idx)
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return s.T()
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}
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func (it *listSeriesIterator) Next() chunkenc.ValueType {
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it.idx++
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if it.idx >= it.samples.Len() {
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return chunkenc.ValNone
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}
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return it.samples.Get(it.idx).Type()
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}
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func (it *listSeriesIterator) Seek(t int64) chunkenc.ValueType {
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if it.idx == -1 {
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it.idx = 0
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}
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// No-op check.
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if s := it.samples.Get(it.idx); s.T() >= t {
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return s.Type()
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}
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// Do binary search between current position and end.
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it.idx += sort.Search(it.samples.Len()-it.idx, func(i int) bool {
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s := it.samples.Get(i + it.idx)
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return s.T() >= t
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})
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if it.idx >= it.samples.Len() {
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return chunkenc.ValNone
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}
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return it.samples.Get(it.idx).Type()
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}
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func (it *listSeriesIterator) Err() error { return nil }
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type listChunkSeriesIterator struct {
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chks []chunks.Meta
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idx int
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}
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// NewListChunkSeriesIterator returns listChunkSeriesIterator that allows to iterate over provided chunks.
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func NewListChunkSeriesIterator(chks ...chunks.Meta) chunks.Iterator {
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return &listChunkSeriesIterator{chks: chks, idx: -1}
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}
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func (it *listChunkSeriesIterator) At() chunks.Meta {
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return it.chks[it.idx]
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}
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func (it *listChunkSeriesIterator) Next() bool {
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it.idx++
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return it.idx < len(it.chks)
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}
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func (it *listChunkSeriesIterator) Err() error { return nil }
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type chunkSetToSeriesSet struct {
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ChunkSeriesSet
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chkIterErr error
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sameSeriesChunks []Series
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}
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// NewSeriesSetFromChunkSeriesSet converts ChunkSeriesSet to SeriesSet by decoding chunks one by one.
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func NewSeriesSetFromChunkSeriesSet(chk ChunkSeriesSet) SeriesSet {
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return &chunkSetToSeriesSet{ChunkSeriesSet: chk}
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}
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func (c *chunkSetToSeriesSet) Next() bool {
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if c.Err() != nil || !c.ChunkSeriesSet.Next() {
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return false
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}
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iter := c.ChunkSeriesSet.At().Iterator()
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c.sameSeriesChunks = c.sameSeriesChunks[:0]
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for iter.Next() {
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c.sameSeriesChunks = append(
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c.sameSeriesChunks,
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newChunkToSeriesDecoder(c.ChunkSeriesSet.At().Labels(), iter.At()),
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)
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}
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if iter.Err() != nil {
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c.chkIterErr = iter.Err()
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return false
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}
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return true
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}
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func (c *chunkSetToSeriesSet) At() Series {
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// Series composed of same chunks for the same series.
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return ChainedSeriesMerge(c.sameSeriesChunks...)
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}
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func (c *chunkSetToSeriesSet) Err() error {
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if c.chkIterErr != nil {
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return c.chkIterErr
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}
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return c.ChunkSeriesSet.Err()
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}
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func newChunkToSeriesDecoder(labels labels.Labels, chk chunks.Meta) Series {
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return &SeriesEntry{
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Lset: labels,
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SampleIteratorFn: func() chunkenc.Iterator {
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// TODO(bwplotka): Can we provide any chunkenc buffer?
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return chk.Chunk.Iterator(nil)
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},
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}
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}
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type seriesSetToChunkSet struct {
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SeriesSet
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}
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// NewSeriesSetToChunkSet converts SeriesSet to ChunkSeriesSet by encoding chunks from samples.
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func NewSeriesSetToChunkSet(chk SeriesSet) ChunkSeriesSet {
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return &seriesSetToChunkSet{SeriesSet: chk}
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}
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func (c *seriesSetToChunkSet) Next() bool {
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if c.Err() != nil || !c.SeriesSet.Next() {
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return false
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}
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return true
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}
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func (c *seriesSetToChunkSet) At() ChunkSeries {
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return NewSeriesToChunkEncoder(c.SeriesSet.At())
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}
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func (c *seriesSetToChunkSet) Err() error {
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return c.SeriesSet.Err()
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}
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type seriesToChunkEncoder struct {
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Series
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}
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const seriesToChunkEncoderSplit = 120
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// NewSeriesToChunkEncoder encodes samples to chunks with 120 samples limit.
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func NewSeriesToChunkEncoder(series Series) ChunkSeries {
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return &seriesToChunkEncoder{series}
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}
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func (s *seriesToChunkEncoder) Iterator() chunks.Iterator {
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// TODO(beorn7): Add Histogram support.
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chk := chunkenc.NewXORChunk()
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app, err := chk.Appender()
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if err != nil {
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return errChunksIterator{err: err}
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}
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mint := int64(math.MaxInt64)
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maxt := int64(math.MinInt64)
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chks := []chunks.Meta{}
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i := 0
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seriesIter := s.Series.Iterator()
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for seriesIter.Next() == chunkenc.ValFloat {
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// Create a new chunk if too many samples in the current one.
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if i >= seriesToChunkEncoderSplit {
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chks = append(chks, chunks.Meta{
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MinTime: mint,
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MaxTime: maxt,
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Chunk: chk,
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})
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chk = chunkenc.NewXORChunk()
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app, err = chk.Appender()
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if err != nil {
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return errChunksIterator{err: err}
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}
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mint = int64(math.MaxInt64)
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// maxt is immediately overwritten below which is why setting it here won't make a difference.
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i = 0
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}
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t, v := seriesIter.At()
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app.Append(t, v)
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maxt = t
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if mint == math.MaxInt64 {
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mint = t
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}
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i++
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}
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if err := seriesIter.Err(); err != nil {
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return errChunksIterator{err: err}
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}
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chks = append(chks, chunks.Meta{
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MinTime: mint,
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MaxTime: maxt,
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Chunk: chk,
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})
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return NewListChunkSeriesIterator(chks...)
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}
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type errChunksIterator struct {
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err error
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}
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func (e errChunksIterator) At() chunks.Meta { return chunks.Meta{} }
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func (e errChunksIterator) Next() bool { return false }
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func (e errChunksIterator) Err() error { return e.err }
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// ExpandSamples iterates over all samples in the iterator, buffering all in slice.
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// Optionally it takes samples constructor, useful when you want to compare sample slices with different
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// sample implementations. if nil, sample type from this package will be used.
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func ExpandSamples(iter chunkenc.Iterator, newSampleFn func(t int64, v float64, h *histogram.Histogram, fh *histogram.FloatHistogram) tsdbutil.Sample) ([]tsdbutil.Sample, error) {
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if newSampleFn == nil {
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newSampleFn = func(t int64, v float64, h *histogram.Histogram, fh *histogram.FloatHistogram) tsdbutil.Sample {
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return sample{t, v, h, fh}
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}
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}
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var result []tsdbutil.Sample
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for {
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switch iter.Next() {
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case chunkenc.ValNone:
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return result, iter.Err()
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case chunkenc.ValFloat:
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t, v := iter.At()
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// NaNs can't be compared normally, so substitute for another value.
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if math.IsNaN(v) {
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v = -42
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}
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result = append(result, newSampleFn(t, v, nil, nil))
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case chunkenc.ValHistogram:
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t, h := iter.AtHistogram()
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result = append(result, newSampleFn(t, 0, h, nil))
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case chunkenc.ValFloatHistogram:
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t, fh := iter.AtFloatHistogram()
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result = append(result, newSampleFn(t, 0, nil, fh))
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}
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}
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}
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// ExpandChunks iterates over all chunks in the iterator, buffering all in slice.
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func ExpandChunks(iter chunks.Iterator) ([]chunks.Meta, error) {
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var result []chunks.Meta
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for iter.Next() {
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result = append(result, iter.At())
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}
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return result, iter.Err()
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}
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