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660 lines
21 KiB
660 lines
21 KiB
// Copyright 2014 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 local
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import (
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"sort"
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"sync"
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"time"
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"github.com/prometheus/common/model"
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"github.com/prometheus/prometheus/storage/metric"
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)
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const (
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// chunkDescEvictionFactor is a factor used for chunkDesc eviction (as opposed
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// to evictions of chunks, see method evictOlderThan. A chunk takes about 20x
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// more memory than a chunkDesc. With a chunkDescEvictionFactor of 10, not more
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// than a third of the total memory taken by a series will be used for
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// chunkDescs.
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chunkDescEvictionFactor = 10
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headChunkTimeout = time.Hour // Close head chunk if not touched for that long.
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)
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// fingerprintSeriesPair pairs a fingerprint with a memorySeries pointer.
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type fingerprintSeriesPair struct {
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fp model.Fingerprint
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series *memorySeries
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}
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// seriesMap maps fingerprints to memory series. All its methods are
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// goroutine-safe. A SeriesMap is effectively is a goroutine-safe version of
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// map[model.Fingerprint]*memorySeries.
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type seriesMap struct {
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mtx sync.RWMutex
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m map[model.Fingerprint]*memorySeries
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}
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// newSeriesMap returns a newly allocated empty seriesMap. To create a seriesMap
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// based on a prefilled map, use an explicit initializer.
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func newSeriesMap() *seriesMap {
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return &seriesMap{m: make(map[model.Fingerprint]*memorySeries)}
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}
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// length returns the number of mappings in the seriesMap.
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func (sm *seriesMap) length() int {
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sm.mtx.RLock()
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defer sm.mtx.RUnlock()
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return len(sm.m)
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}
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// get returns a memorySeries for a fingerprint. Return values have the same
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// semantics as the native Go map.
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func (sm *seriesMap) get(fp model.Fingerprint) (s *memorySeries, ok bool) {
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sm.mtx.RLock()
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defer sm.mtx.RUnlock()
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s, ok = sm.m[fp]
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return
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}
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// put adds a mapping to the seriesMap. It panics if s == nil.
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func (sm *seriesMap) put(fp model.Fingerprint, s *memorySeries) {
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sm.mtx.Lock()
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defer sm.mtx.Unlock()
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if s == nil {
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panic("tried to add nil pointer to seriesMap")
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}
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sm.m[fp] = s
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}
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// del removes a mapping from the series Map.
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func (sm *seriesMap) del(fp model.Fingerprint) {
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sm.mtx.Lock()
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defer sm.mtx.Unlock()
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delete(sm.m, fp)
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}
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// iter returns a channel that produces all mappings in the seriesMap. The
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// channel will be closed once all fingerprints have been received. Not
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// consuming all fingerprints from the channel will leak a goroutine. The
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// semantics of concurrent modification of seriesMap is the similar as the one
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// for iterating over a map with a 'range' clause. However, if the next element
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// in iteration order is removed after the current element has been received
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// from the channel, it will still be produced by the channel.
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func (sm *seriesMap) iter() <-chan fingerprintSeriesPair {
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ch := make(chan fingerprintSeriesPair)
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go func() {
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sm.mtx.RLock()
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for fp, s := range sm.m {
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sm.mtx.RUnlock()
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ch <- fingerprintSeriesPair{fp, s}
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sm.mtx.RLock()
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}
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sm.mtx.RUnlock()
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close(ch)
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}()
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return ch
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}
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// fpIter returns a channel that produces all fingerprints in the seriesMap. The
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// channel will be closed once all fingerprints have been received. Not
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// consuming all fingerprints from the channel will leak a goroutine. The
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// semantics of concurrent modification of seriesMap is the similar as the one
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// for iterating over a map with a 'range' clause. However, if the next element
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// in iteration order is removed after the current element has been received
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// from the channel, it will still be produced by the channel.
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func (sm *seriesMap) fpIter() <-chan model.Fingerprint {
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ch := make(chan model.Fingerprint)
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go func() {
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sm.mtx.RLock()
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for fp := range sm.m {
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sm.mtx.RUnlock()
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ch <- fp
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sm.mtx.RLock()
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}
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sm.mtx.RUnlock()
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close(ch)
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}()
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return ch
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}
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type memorySeries struct {
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metric model.Metric
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// Sorted by start time, overlapping chunk ranges are forbidden.
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chunkDescs []*chunkDesc
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// The index (within chunkDescs above) of the first chunkDesc that
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// points to a non-persisted chunk. If all chunks are persisted, then
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// persistWatermark == len(chunkDescs).
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persistWatermark int
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// The modification time of the series file. The zero value of time.Time
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// is used to mark an unknown modification time.
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modTime time.Time
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// The chunkDescs in memory might not have all the chunkDescs for the
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// chunks that are persisted to disk. The missing chunkDescs are all
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// contiguous and at the tail end. chunkDescsOffset is the index of the
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// chunk on disk that corresponds to the first chunkDesc in memory. If
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// it is 0, the chunkDescs are all loaded. A value of -1 denotes a
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// special case: There are chunks on disk, but the offset to the
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// chunkDescs in memory is unknown. Also, in this special case, there is
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// no overlap between chunks on disk and chunks in memory (implying that
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// upon first persisting of a chunk in memory, the offset has to be
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// set).
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chunkDescsOffset int
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// The savedFirstTime field is used as a fallback when the
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// chunkDescsOffset is not 0. It can be used to save the firstTime of the
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// first chunk before its chunk desc is evicted. In doubt, this field is
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// just set to the oldest possible timestamp.
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savedFirstTime model.Time
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// The timestamp of the last sample in this series. Needed for fast access to
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// ensure timestamp monotonicity during ingestion.
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lastTime model.Time
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// Whether the current head chunk has already been finished. If true,
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// the current head chunk must not be modified anymore.
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headChunkClosed bool
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// Whether the current head chunk is used by an iterator. In that case,
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// a non-closed head chunk has to be cloned before more samples are
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// appended.
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headChunkUsedByIterator bool
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// Whether the series is inconsistent with the last checkpoint in a way
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// that would require a disk seek during crash recovery.
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dirty bool
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}
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// newMemorySeries returns a pointer to a newly allocated memorySeries for the
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// given metric. chunkDescs and modTime in the new series are set according to
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// the provided parameters. chunkDescs can be nil or empty if this is a
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// genuinely new time series (i.e. not one that is being unarchived). In that
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// case, headChunkClosed is set to false, and firstTime and lastTime are both
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// set to model.Earliest. The zero value for modTime can be used if the
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// modification time of the series file is unknown (e.g. if this is a genuinely
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// new series).
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func newMemorySeries(m model.Metric, chunkDescs []*chunkDesc, modTime time.Time) *memorySeries {
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firstTime := model.Earliest
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lastTime := model.Earliest
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if len(chunkDescs) > 0 {
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firstTime = chunkDescs[0].firstTime()
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lastTime = chunkDescs[len(chunkDescs)-1].lastTime()
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}
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return &memorySeries{
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metric: m,
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chunkDescs: chunkDescs,
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headChunkClosed: len(chunkDescs) > 0,
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savedFirstTime: firstTime,
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lastTime: lastTime,
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persistWatermark: len(chunkDescs),
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modTime: modTime,
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}
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}
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// add adds a sample pair to the series. It returns the number of newly
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// completed chunks (which are now eligible for persistence).
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//
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// The caller must have locked the fingerprint of the series.
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func (s *memorySeries) add(v *model.SamplePair) int {
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if len(s.chunkDescs) == 0 || s.headChunkClosed {
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newHead := newChunkDesc(newChunk(), v.Timestamp)
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s.chunkDescs = append(s.chunkDescs, newHead)
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s.headChunkClosed = false
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} else if s.headChunkUsedByIterator && s.head().refCount() > 1 {
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// We only need to clone the head chunk if the current head
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// chunk was used in an iterator at all and if the refCount is
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// still greater than the 1 we always have because the head
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// chunk is not yet persisted. The latter is just an
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// approximation. We will still clone unnecessarily if an older
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// iterator using a previous version of the head chunk is still
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// around and keep the head chunk pinned. We needed to track
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// pins by version of the head chunk, which is probably not
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// worth the effort.
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chunkOps.WithLabelValues(clone).Inc()
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// No locking needed here because a non-persisted head chunk can
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// not get evicted concurrently.
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s.head().c = s.head().c.clone()
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s.headChunkUsedByIterator = false
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}
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chunks := s.head().add(v)
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s.head().c = chunks[0]
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for _, c := range chunks[1:] {
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s.chunkDescs = append(s.chunkDescs, newChunkDesc(c, c.firstTime()))
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}
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// Populate lastTime of now-closed chunks.
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for _, cd := range s.chunkDescs[len(s.chunkDescs)-len(chunks) : len(s.chunkDescs)-1] {
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cd.maybePopulateLastTime()
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}
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s.lastTime = v.Timestamp
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return len(chunks) - 1
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}
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// maybeCloseHeadChunk closes the head chunk if it has not been touched for the
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// duration of headChunkTimeout. It returns whether the head chunk was closed.
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// If the head chunk is already closed, the method is a no-op and returns false.
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//
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// The caller must have locked the fingerprint of the series.
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func (s *memorySeries) maybeCloseHeadChunk() bool {
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if s.headChunkClosed {
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return false
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}
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if time.Now().Sub(s.lastTime.Time()) > headChunkTimeout {
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s.headChunkClosed = true
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// Since we cannot modify the head chunk from now on, we
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// don't need to bother with cloning anymore.
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s.headChunkUsedByIterator = false
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s.head().maybePopulateLastTime()
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return true
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}
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return false
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}
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// evictChunkDescs evicts chunkDescs if there are chunkDescEvictionFactor times
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// more than non-evicted chunks. iOldestNotEvicted is the index within the
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// current chunkDescs of the oldest chunk that is not evicted.
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func (s *memorySeries) evictChunkDescs(iOldestNotEvicted int) {
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lenToKeep := chunkDescEvictionFactor * (len(s.chunkDescs) - iOldestNotEvicted)
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if lenToKeep < len(s.chunkDescs) {
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s.savedFirstTime = s.firstTime()
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lenEvicted := len(s.chunkDescs) - lenToKeep
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s.chunkDescsOffset += lenEvicted
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s.persistWatermark -= lenEvicted
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chunkDescOps.WithLabelValues(evict).Add(float64(lenEvicted))
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numMemChunkDescs.Sub(float64(lenEvicted))
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s.chunkDescs = append(
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make([]*chunkDesc, 0, lenToKeep),
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s.chunkDescs[lenEvicted:]...,
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)
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s.dirty = true
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}
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}
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// dropChunks removes chunkDescs older than t. The caller must have locked the
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// fingerprint of the series.
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func (s *memorySeries) dropChunks(t model.Time) {
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keepIdx := len(s.chunkDescs)
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for i, cd := range s.chunkDescs {
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if !cd.lastTime().Before(t) {
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keepIdx = i
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break
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}
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}
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if keepIdx > 0 {
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s.chunkDescs = append(
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make([]*chunkDesc, 0, len(s.chunkDescs)-keepIdx),
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s.chunkDescs[keepIdx:]...,
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)
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s.persistWatermark -= keepIdx
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if s.persistWatermark < 0 {
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panic("dropped unpersisted chunks from memory")
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}
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if s.chunkDescsOffset != -1 {
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s.chunkDescsOffset += keepIdx
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}
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numMemChunkDescs.Sub(float64(keepIdx))
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s.dirty = true
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}
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}
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// preloadChunks is an internal helper method.
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func (s *memorySeries) preloadChunks(
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indexes []int, fp model.Fingerprint, mss *memorySeriesStorage,
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) ([]*chunkDesc, error) {
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loadIndexes := []int{}
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pinnedChunkDescs := make([]*chunkDesc, 0, len(indexes))
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for _, idx := range indexes {
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cd := s.chunkDescs[idx]
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pinnedChunkDescs = append(pinnedChunkDescs, cd)
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cd.pin(mss.evictRequests) // Have to pin everything first to prevent immediate eviction on chunk loading.
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if cd.isEvicted() {
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loadIndexes = append(loadIndexes, idx)
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}
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}
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chunkOps.WithLabelValues(pin).Add(float64(len(pinnedChunkDescs)))
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if len(loadIndexes) > 0 {
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if s.chunkDescsOffset == -1 {
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panic("requested loading chunks from persistence in a situation where we must not have persisted data for chunk descriptors in memory")
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}
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chunks, err := mss.loadChunks(fp, loadIndexes, s.chunkDescsOffset)
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if err != nil {
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// Unpin the chunks since we won't return them as pinned chunks now.
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for _, cd := range pinnedChunkDescs {
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cd.unpin(mss.evictRequests)
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}
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chunkOps.WithLabelValues(unpin).Add(float64(len(pinnedChunkDescs)))
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return nil, err
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}
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for i, c := range chunks {
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s.chunkDescs[loadIndexes[i]].setChunk(c)
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}
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}
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return pinnedChunkDescs, nil
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}
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/*
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func (s *memorySeries) preloadChunksAtTime(t model.Time, p *persistence) (chunkDescs, error) {
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s.mtx.Lock()
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defer s.mtx.Unlock()
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if len(s.chunkDescs) == 0 {
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return nil, nil
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}
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var pinIndexes []int
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// Find first chunk where lastTime() is after or equal to t.
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i := sort.Search(len(s.chunkDescs), func(i int) bool {
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return !s.chunkDescs[i].lastTime().Before(t)
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})
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switch i {
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case 0:
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pinIndexes = []int{0}
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case len(s.chunkDescs):
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pinIndexes = []int{i - 1}
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default:
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if s.chunkDescs[i].contains(t) {
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pinIndexes = []int{i}
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} else {
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pinIndexes = []int{i - 1, i}
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}
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}
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return s.preloadChunks(pinIndexes, p)
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}
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*/
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// preloadChunksForRange loads chunks for the given range from the persistence.
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// The caller must have locked the fingerprint of the series.
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func (s *memorySeries) preloadChunksForRange(
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from model.Time, through model.Time,
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fp model.Fingerprint, mss *memorySeriesStorage,
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) ([]*chunkDesc, error) {
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firstChunkDescTime := model.Latest
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if len(s.chunkDescs) > 0 {
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firstChunkDescTime = s.chunkDescs[0].firstTime()
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}
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if s.chunkDescsOffset != 0 && from.Before(firstChunkDescTime) {
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cds, err := mss.loadChunkDescs(fp, s.persistWatermark)
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if err != nil {
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return nil, err
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}
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s.chunkDescs = append(cds, s.chunkDescs...)
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s.chunkDescsOffset = 0
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s.persistWatermark += len(cds)
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}
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if len(s.chunkDescs) == 0 {
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return nil, nil
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}
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// Find first chunk with start time after "from".
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fromIdx := sort.Search(len(s.chunkDescs), func(i int) bool {
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return s.chunkDescs[i].firstTime().After(from)
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})
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// Find first chunk with start time after "through".
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throughIdx := sort.Search(len(s.chunkDescs), func(i int) bool {
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return s.chunkDescs[i].firstTime().After(through)
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})
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if fromIdx > 0 {
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fromIdx--
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}
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if throughIdx == len(s.chunkDescs) {
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throughIdx--
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}
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pinIndexes := make([]int, 0, throughIdx-fromIdx+1)
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for i := fromIdx; i <= throughIdx; i++ {
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pinIndexes = append(pinIndexes, i)
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}
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return s.preloadChunks(pinIndexes, fp, mss)
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}
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// newIterator returns a new SeriesIterator. The caller must have locked the
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// fingerprint of the memorySeries.
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func (s *memorySeries) newIterator() SeriesIterator {
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chunks := make([]chunk, 0, len(s.chunkDescs))
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for i, cd := range s.chunkDescs {
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if chunk := cd.chunk(); chunk != nil {
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if i == len(s.chunkDescs)-1 && !s.headChunkClosed {
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s.headChunkUsedByIterator = true
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}
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chunks = append(chunks, chunk)
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}
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}
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return &memorySeriesIterator{
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chunks: chunks,
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chunkIts: make([]chunkIterator, len(chunks)),
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}
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}
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// head returns a pointer to the head chunk descriptor. The caller must have
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// locked the fingerprint of the memorySeries. This method will panic if this
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// series has no chunk descriptors.
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func (s *memorySeries) head() *chunkDesc {
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return s.chunkDescs[len(s.chunkDescs)-1]
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}
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// firstTime returns the timestamp of the first sample in the series. The caller
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// must have locked the fingerprint of the memorySeries.
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func (s *memorySeries) firstTime() model.Time {
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if s.chunkDescsOffset == 0 && len(s.chunkDescs) > 0 {
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return s.chunkDescs[0].firstTime()
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}
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return s.savedFirstTime
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}
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// chunksToPersist returns a slice of chunkDescs eligible for persistence. It's
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// the caller's responsibility to actually persist the returned chunks
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// afterwards. The method sets the persistWatermark and the dirty flag
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// accordingly.
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//
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// The caller must have locked the fingerprint of the series.
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func (s *memorySeries) chunksToPersist() []*chunkDesc {
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newWatermark := len(s.chunkDescs)
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if !s.headChunkClosed {
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newWatermark--
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}
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if newWatermark == s.persistWatermark {
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return nil
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}
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cds := s.chunkDescs[s.persistWatermark:newWatermark]
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s.dirty = true
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s.persistWatermark = newWatermark
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return cds
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}
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// memorySeriesIterator implements SeriesIterator.
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type memorySeriesIterator struct {
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|
chunkIt chunkIterator // Last chunkIterator used by ValueAtTime.
|
|
chunkIts []chunkIterator // Caches chunkIterators.
|
|
chunks []chunk
|
|
}
|
|
|
|
// ValueAtTime implements SeriesIterator.
|
|
func (it *memorySeriesIterator) ValueAtTime(t model.Time) []model.SamplePair {
|
|
// The most common case. We are iterating through a chunk.
|
|
if it.chunkIt != nil && it.chunkIt.contains(t) {
|
|
return it.chunkIt.valueAtTime(t)
|
|
}
|
|
|
|
if len(it.chunks) == 0 {
|
|
return nil
|
|
}
|
|
|
|
// Before or exactly on the first sample of the series.
|
|
it.chunkIt = it.chunkIterator(0)
|
|
ts := it.chunkIt.timestampAtIndex(0)
|
|
if !t.After(ts) {
|
|
// return first value of first chunk
|
|
return []model.SamplePair{{
|
|
Timestamp: ts,
|
|
Value: it.chunkIt.sampleValueAtIndex(0),
|
|
}}
|
|
}
|
|
|
|
// After or exactly on the last sample of the series.
|
|
it.chunkIt = it.chunkIterator(len(it.chunks) - 1)
|
|
ts = it.chunkIt.lastTimestamp()
|
|
if !t.Before(ts) {
|
|
// return last value of last chunk
|
|
return []model.SamplePair{{
|
|
Timestamp: ts,
|
|
Value: it.chunkIt.sampleValueAtIndex(it.chunkIt.length() - 1),
|
|
}}
|
|
}
|
|
|
|
// Find last chunk where firstTime() is before or equal to t.
|
|
l := len(it.chunks) - 1
|
|
i := sort.Search(len(it.chunks), func(i int) bool {
|
|
return !it.chunks[l-i].firstTime().After(t)
|
|
})
|
|
if i == len(it.chunks) {
|
|
panic("out of bounds")
|
|
}
|
|
it.chunkIt = it.chunkIterator(l - i)
|
|
ts = it.chunkIt.lastTimestamp()
|
|
if t.After(ts) {
|
|
// We ended up between two chunks.
|
|
sp1 := model.SamplePair{
|
|
Timestamp: ts,
|
|
Value: it.chunkIt.sampleValueAtIndex(it.chunkIt.length() - 1),
|
|
}
|
|
it.chunkIt = it.chunkIterator(l - i + 1)
|
|
return []model.SamplePair{
|
|
sp1,
|
|
{
|
|
Timestamp: it.chunkIt.timestampAtIndex(0),
|
|
Value: it.chunkIt.sampleValueAtIndex(0),
|
|
},
|
|
}
|
|
}
|
|
return it.chunkIt.valueAtTime(t)
|
|
}
|
|
|
|
// BoundaryValues implements SeriesIterator.
|
|
func (it *memorySeriesIterator) BoundaryValues(in metric.Interval) []model.SamplePair {
|
|
// Find the first chunk for which the first sample is within the interval.
|
|
i := sort.Search(len(it.chunks), func(i int) bool {
|
|
return !it.chunks[i].firstTime().Before(in.OldestInclusive)
|
|
})
|
|
// Only now check the last timestamp of the previous chunk (which is
|
|
// fairly expensive).
|
|
if i > 0 && !it.chunkIterator(i-1).lastTimestamp().Before(in.OldestInclusive) {
|
|
i--
|
|
}
|
|
|
|
values := make([]model.SamplePair, 0, 2)
|
|
for j, c := range it.chunks[i:] {
|
|
if c.firstTime().After(in.NewestInclusive) {
|
|
if len(values) == 1 {
|
|
// We found the first value before but are now
|
|
// already past the last value. The value we
|
|
// want must be the last value of the previous
|
|
// chunk. So backtrack...
|
|
chunkIt := it.chunkIterator(i + j - 1)
|
|
values = append(values, model.SamplePair{
|
|
Timestamp: chunkIt.lastTimestamp(),
|
|
Value: chunkIt.lastSampleValue(),
|
|
})
|
|
}
|
|
break
|
|
}
|
|
chunkIt := it.chunkIterator(i + j)
|
|
if len(values) == 0 {
|
|
firstValues := chunkIt.valueAtTime(in.OldestInclusive)
|
|
switch len(firstValues) {
|
|
case 2:
|
|
values = append(values, firstValues[1])
|
|
case 1:
|
|
values = firstValues
|
|
default:
|
|
panic("unexpected return from valueAtTime")
|
|
}
|
|
}
|
|
if chunkIt.lastTimestamp().After(in.NewestInclusive) {
|
|
values = append(values, chunkIt.valueAtTime(in.NewestInclusive)[0])
|
|
break
|
|
}
|
|
}
|
|
if len(values) == 1 {
|
|
// We found exactly one value. In that case, add the most recent we know.
|
|
chunkIt := it.chunkIterator(len(it.chunks) - 1)
|
|
values = append(values, model.SamplePair{
|
|
Timestamp: chunkIt.lastTimestamp(),
|
|
Value: chunkIt.lastSampleValue(),
|
|
})
|
|
}
|
|
if len(values) == 2 && values[0].Equal(&values[1]) {
|
|
return values[:1]
|
|
}
|
|
return values
|
|
}
|
|
|
|
// RangeValues implements SeriesIterator.
|
|
func (it *memorySeriesIterator) RangeValues(in metric.Interval) []model.SamplePair {
|
|
// Find the first chunk for which the first sample is within the interval.
|
|
i := sort.Search(len(it.chunks), func(i int) bool {
|
|
return !it.chunks[i].firstTime().Before(in.OldestInclusive)
|
|
})
|
|
// Only now check the last timestamp of the previous chunk (which is
|
|
// fairly expensive).
|
|
if i > 0 && !it.chunkIterator(i-1).lastTimestamp().Before(in.OldestInclusive) {
|
|
i--
|
|
}
|
|
|
|
values := []model.SamplePair{}
|
|
for j, c := range it.chunks[i:] {
|
|
if c.firstTime().After(in.NewestInclusive) {
|
|
break
|
|
}
|
|
values = append(values, it.chunkIterator(i+j).rangeValues(in)...)
|
|
}
|
|
return values
|
|
}
|
|
|
|
// chunkIterator returns the chunkIterator for the chunk at position i (and
|
|
// creates it if needed).
|
|
func (it *memorySeriesIterator) chunkIterator(i int) chunkIterator {
|
|
chunkIt := it.chunkIts[i]
|
|
if chunkIt == nil {
|
|
chunkIt = it.chunks[i].newIterator()
|
|
it.chunkIts[i] = chunkIt
|
|
}
|
|
return chunkIt
|
|
}
|
|
|
|
// nopSeriesIterator implements Series Iterator. It never returns any values.
|
|
type nopSeriesIterator struct{}
|
|
|
|
// ValueAtTime implements SeriesIterator.
|
|
func (i nopSeriesIterator) ValueAtTime(t model.Time) []model.SamplePair {
|
|
return []model.SamplePair{}
|
|
}
|
|
|
|
// BoundaryValues implements SeriesIterator.
|
|
func (i nopSeriesIterator) BoundaryValues(in metric.Interval) []model.SamplePair {
|
|
return []model.SamplePair{}
|
|
}
|
|
|
|
// RangeValues implements SeriesIterator.
|
|
func (i nopSeriesIterator) RangeValues(in metric.Interval) []model.SamplePair {
|
|
return []model.SamplePair{}
|
|
}
|