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591 lines
16 KiB
591 lines
16 KiB
// 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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"fmt"
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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) 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(it chunkenc.Iterator) chunkenc.Iterator { return s.SampleIteratorFn(it) }
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type ChunkSeriesEntry struct {
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Lset labels.Labels
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ChunkIteratorFn func(chunks.Iterator) 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(it chunks.Iterator) chunks.Iterator { return s.ChunkIteratorFn(it) }
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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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samplesS := Samples(samples(s))
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return &SeriesEntry{
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Lset: lset,
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SampleIteratorFn: func(it chunkenc.Iterator) chunkenc.Iterator {
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if lsi, ok := it.(*listSeriesIterator); ok {
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lsi.Reset(samplesS)
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return lsi
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}
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return NewListSeriesIterator(samplesS)
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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(it chunks.Iterator) chunks.Iterator {
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lcsi, existing := it.(*listChunkSeriesIterator)
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var chks []chunks.Meta
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if existing {
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chks = lcsi.chks[:0]
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} else {
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chks = make([]chunks.Meta, 0, len(samples))
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}
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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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if existing {
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lcsi.Reset(chks...)
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return lcsi
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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) Reset(samples Samples) {
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it.samples = samples
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it.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.F()
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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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if it.idx >= it.samples.Len() {
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return chunkenc.ValNone
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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) Reset(chks ...chunks.Meta) {
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it.chks = chks
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it.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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iter chunks.Iterator
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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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c.iter = c.ChunkSeriesSet.At().Iterator(c.iter)
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c.sameSeriesChunks = nil
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for c.iter.Next() {
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c.sameSeriesChunks = append(
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c.sameSeriesChunks,
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newChunkToSeriesDecoder(c.ChunkSeriesSet.At().Labels(), c.iter.At()),
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)
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}
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if c.iter.Err() != nil {
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c.chkIterErr = c.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(it chunkenc.Iterator) chunkenc.Iterator {
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// TODO(bwplotka): Can we provide any chunkenc buffer?
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return chk.Chunk.Iterator(it)
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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(it chunks.Iterator) chunks.Iterator {
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var (
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chk chunkenc.Chunk
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app *RecodingAppender
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err error
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)
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mint := int64(math.MaxInt64)
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maxt := int64(math.MinInt64)
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var chks []chunks.Meta
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lcsi, existing := it.(*listChunkSeriesIterator)
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if existing {
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chks = lcsi.chks[:0]
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}
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i := 0
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seriesIter := s.Series.Iterator(nil)
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lastType := chunkenc.ValNone
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for typ := seriesIter.Next(); typ != chunkenc.ValNone; typ = seriesIter.Next() {
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chunkCreated := false
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if typ != lastType || i >= seriesToChunkEncoderSplit {
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// Create a new chunk if the sample type changed or too many samples in the current one.
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chks = appendChunk(chks, mint, maxt, chk)
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chunkCreated = true
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chk, err = chunkenc.NewEmptyChunk(typ.ChunkEncoding())
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if err != nil {
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return errChunksIterator{err: err}
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}
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chkAppender, 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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app = NewRecodingAppender(&chk, chkAppender)
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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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lastType = typ
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var (
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t int64
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v float64
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h *histogram.Histogram
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fh *histogram.FloatHistogram
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)
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switch typ {
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case chunkenc.ValFloat:
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t, v = seriesIter.At()
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app.Append(t, v)
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case chunkenc.ValHistogram:
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t, h = seriesIter.AtHistogram()
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if ok, counterReset := app.AppendHistogram(t, h); !ok {
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chks = appendChunk(chks, mint, maxt, chk)
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histChunk := chunkenc.NewHistogramChunk()
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chunkCreated = true
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if counterReset {
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histChunk.SetCounterResetHeader(chunkenc.CounterReset)
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}
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chk = histChunk
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chkAppender, 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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i = 0
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app = NewRecodingAppender(&chk, chkAppender)
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if ok, _ := app.AppendHistogram(t, h); !ok {
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panic("unexpected error while appending histogram")
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}
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}
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if chunkCreated && h.CounterResetHint == histogram.GaugeType {
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chk.(*chunkenc.HistogramChunk).SetCounterResetHeader(chunkenc.GaugeType)
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}
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case chunkenc.ValFloatHistogram:
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t, fh = seriesIter.AtFloatHistogram()
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if ok, counterReset := app.AppendFloatHistogram(t, fh); !ok {
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chks = appendChunk(chks, mint, maxt, chk)
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floatHistChunk := chunkenc.NewFloatHistogramChunk()
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chunkCreated = true
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if counterReset {
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floatHistChunk.SetCounterResetHeader(chunkenc.CounterReset)
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}
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chk = floatHistChunk
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chkAppender, 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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i = 0
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app = NewRecodingAppender(&chk, chkAppender)
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if ok, _ := app.AppendFloatHistogram(t, fh); !ok {
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panic("unexpected error while float appending histogram")
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}
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}
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if chunkCreated && fh.CounterResetHint == histogram.GaugeType {
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chk.(*chunkenc.FloatHistogramChunk).SetCounterResetHeader(chunkenc.GaugeType)
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}
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default:
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return errChunksIterator{err: fmt.Errorf("unknown sample type %s", typ.String())}
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}
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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 = appendChunk(chks, mint, maxt, chk)
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if existing {
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lcsi.Reset(chks...)
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return lcsi
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}
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return NewListChunkSeriesIterator(chks...)
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}
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func appendChunk(chks []chunks.Meta, mint, maxt int64, chk chunkenc.Chunk) []chunks.Meta {
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if chk != nil {
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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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}
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return 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, f 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, f float64, h *histogram.Histogram, fh *histogram.FloatHistogram) tsdbutil.Sample {
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switch {
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case h != nil:
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return hSample{t, h}
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case fh != nil:
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return fhSample{t, fh}
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default:
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return fSample{t, f}
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}
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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, f := iter.At()
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// NaNs can't be compared normally, so substitute for another value.
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if math.IsNaN(f) {
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f = -42
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}
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result = append(result, newSampleFn(t, f, 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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|
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// RecodingAppender is a tsdb.Appender that recodes histogram samples if needed during appends.
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// It takes an existing appender and a chunk to which samples are appended.
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type RecodingAppender struct {
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chk *chunkenc.Chunk
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app chunkenc.Appender
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}
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func NewRecodingAppender(chk *chunkenc.Chunk, app chunkenc.Appender) *RecodingAppender {
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return &RecodingAppender{
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chk: chk,
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app: app,
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}
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}
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// Append appends a float sample to the appender.
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func (a *RecodingAppender) Append(t int64, v float64) {
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a.app.Append(t, v)
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}
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// AppendHistogram appends a histogram sample to the underlying chunk.
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// The method returns false if the sample cannot be appended and a boolean value set to true
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// when it is not appendable because of a counter reset.
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// If counterReset is true, okToAppend is always false.
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func (a *RecodingAppender) AppendHistogram(t int64, h *histogram.Histogram) (okToAppend, counterReset bool) {
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app, ok := a.app.(*chunkenc.HistogramAppender)
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if !ok {
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return false, false
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}
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if app.NumSamples() == 0 {
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a.app.AppendHistogram(t, h)
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return true, false
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}
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var (
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pForwardInserts, nForwardInserts []chunkenc.Insert
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pBackwardInserts, nBackwardInserts []chunkenc.Insert
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pMergedSpans, nMergedSpans []histogram.Span
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)
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switch h.CounterResetHint {
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case histogram.GaugeType:
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pForwardInserts, nForwardInserts,
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pBackwardInserts, nBackwardInserts,
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pMergedSpans, nMergedSpans,
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okToAppend = app.AppendableGauge(h)
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default:
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pForwardInserts, nForwardInserts, okToAppend, counterReset = app.Appendable(h)
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}
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if !okToAppend || counterReset {
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return false, counterReset
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}
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if len(pBackwardInserts)+len(nBackwardInserts) > 0 {
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h.PositiveSpans = pMergedSpans
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|
h.NegativeSpans = nMergedSpans
|
|
app.RecodeHistogram(h, pBackwardInserts, nBackwardInserts)
|
|
}
|
|
if len(pForwardInserts) > 0 || len(nForwardInserts) > 0 {
|
|
chk, app := app.Recode(
|
|
pForwardInserts, nForwardInserts,
|
|
h.PositiveSpans, h.NegativeSpans,
|
|
)
|
|
*a.chk = chk
|
|
a.app = app
|
|
}
|
|
|
|
a.app.AppendHistogram(t, h)
|
|
return true, counterReset
|
|
}
|
|
|
|
// AppendFloatHistogram appends a float histogram sample to the underlying chunk.
|
|
// The method returns false if the sample cannot be appended and a boolean value set to true
|
|
// when it is not appendable because of a counter reset.
|
|
// If counterReset is true, okToAppend is always false.
|
|
func (a *RecodingAppender) AppendFloatHistogram(t int64, fh *histogram.FloatHistogram) (okToAppend, counterReset bool) {
|
|
app, ok := a.app.(*chunkenc.FloatHistogramAppender)
|
|
if !ok {
|
|
return false, false
|
|
}
|
|
|
|
if app.NumSamples() == 0 {
|
|
a.app.AppendFloatHistogram(t, fh)
|
|
return true, false
|
|
}
|
|
|
|
var (
|
|
pForwardInserts, nForwardInserts []chunkenc.Insert
|
|
pBackwardInserts, nBackwardInserts []chunkenc.Insert
|
|
pMergedSpans, nMergedSpans []histogram.Span
|
|
)
|
|
switch fh.CounterResetHint {
|
|
case histogram.GaugeType:
|
|
pForwardInserts, nForwardInserts,
|
|
pBackwardInserts, nBackwardInserts,
|
|
pMergedSpans, nMergedSpans,
|
|
okToAppend = app.AppendableGauge(fh)
|
|
default:
|
|
pForwardInserts, nForwardInserts, okToAppend, counterReset = app.Appendable(fh)
|
|
}
|
|
|
|
if !okToAppend || counterReset {
|
|
return false, counterReset
|
|
}
|
|
|
|
if len(pBackwardInserts)+len(nBackwardInserts) > 0 {
|
|
fh.PositiveSpans = pMergedSpans
|
|
fh.NegativeSpans = nMergedSpans
|
|
app.RecodeHistogramm(fh, pBackwardInserts, nBackwardInserts)
|
|
}
|
|
|
|
if len(pForwardInserts) > 0 || len(nForwardInserts) > 0 {
|
|
chunk, app := app.Recode(
|
|
pForwardInserts, nForwardInserts,
|
|
fh.PositiveSpans, fh.NegativeSpans,
|
|
)
|
|
*a.chk = chunk
|
|
a.app = app
|
|
}
|
|
|
|
a.app.AppendFloatHistogram(t, fh)
|
|
return true, counterReset
|
|
}
|