564 lines
18 KiB
Go
564 lines
18 KiB
Go
// 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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"math"
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"sort"
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"sync"
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"sync/atomic"
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clientmodel "github.com/prometheus/client_golang/model"
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"github.com/prometheus/prometheus/storage/metric"
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)
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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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const chunkDescEvictionFactor = 10
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// fingerprintSeriesPair pairs a fingerprint with a memorySeries pointer.
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type fingerprintSeriesPair struct {
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fp clientmodel.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[clientmodel.Fingerprint]*memorySeries.
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type seriesMap struct {
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mtx sync.RWMutex
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m map[clientmodel.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[clientmodel.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 clientmodel.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 clientmodel.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 clientmodel.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 clientmodel.Fingerprint {
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ch := make(chan clientmodel.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 clientmodel.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 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, there is no overlap between
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// chunks on disk and chunks in memory (implying that upon first
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// persisting of a chunk in memory, the offset has to be 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 clientmodel.Timestamp
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// Whether the current head chunk has already been scheduled to be
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// persisted. If true, the current head chunk must not be modified
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// anymore.
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headChunkPersisted bool
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// Whether the current head chunk is used by an iterator. In that case,
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// a non-persisted 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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}
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// newMemorySeries returns a pointer to a newly allocated memorySeries for the
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// given metric. reallyNew defines if the memorySeries is a genuinely new series
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// or (if false) a series for a metric being unarchived, i.e. a series that
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// existed before but has been evicted from memory. If reallyNew is false,
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// firstTime is ignored (and set to the lowest possible timestamp instead - it
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// will be set properly upon the first eviction of chunkDescs).
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func newMemorySeries(m clientmodel.Metric, reallyNew bool, firstTime clientmodel.Timestamp) *memorySeries {
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if reallyNew {
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firstTime = math.MinInt64
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}
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s := memorySeries{
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metric: m,
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headChunkPersisted: !reallyNew,
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savedFirstTime: firstTime,
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}
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if !reallyNew {
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s.chunkDescsOffset = -1
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}
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return &s
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}
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// add adds a sample pair to the series.
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// It returns chunkDescs that must be queued to be persisted.
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// The caller must have locked the fingerprint of the series.
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func (s *memorySeries) add(fp clientmodel.Fingerprint, v *metric.SamplePair) []*chunkDesc {
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if len(s.chunkDescs) == 0 || s.headChunkPersisted {
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newHead := newChunkDesc(newDeltaEncodedChunk(d1, d0, true))
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s.chunkDescs = append(s.chunkDescs, newHead)
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s.headChunkPersisted = false
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} else if s.headChunkUsedByIterator && s.head().getRefCount() > 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().chunk = s.head().chunk.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().chunk = chunks[0]
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var chunkDescsToPersist []*chunkDesc
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if len(chunks) > 1 {
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chunkDescsToPersist = append(chunkDescsToPersist, s.head())
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for i, c := range chunks[1:] {
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cd := newChunkDesc(c)
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s.chunkDescs = append(s.chunkDescs, cd)
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// The last chunk is still growing.
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if i < len(chunks[1:])-1 {
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chunkDescsToPersist = append(chunkDescsToPersist, cd)
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}
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}
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}
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return chunkDescsToPersist
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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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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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}
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}
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// purgeOlderThan removes chunkDescs older than t. It returns the number of
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// purged chunkDescs and true if all chunkDescs have been purged.
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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) purgeOlderThan(t clientmodel.Timestamp) (int, bool) {
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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(make([]*chunkDesc, 0, len(s.chunkDescs)-keepIdx), s.chunkDescs[keepIdx:]...)
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numMemChunkDescs.Sub(float64(keepIdx))
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}
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return keepIdx, len(s.chunkDescs) == 0
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}
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// preloadChunks is an internal helper method.
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func (s *memorySeries) preloadChunks(indexes []int, mss *memorySeriesStorage) ([]*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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fp := s.metric.Fingerprint()
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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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chunkOps.WithLabelValues(load).Add(float64(len(chunks)))
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atomic.AddInt64(&numMemChunks, int64(len(chunks)))
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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 clientmodel.Timestamp, 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 clientmodel.Timestamp, through clientmodel.Timestamp,
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fp clientmodel.Fingerprint, mss *memorySeriesStorage,
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) ([]*chunkDesc, error) {
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firstChunkDescTime := clientmodel.Timestamp(math.MaxInt64)
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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, firstChunkDescTime)
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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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}
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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, 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(lockFunc, unlockFunc func()) 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.getChunk(); chunk != nil {
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if i == len(s.chunkDescs)-1 && !s.headChunkPersisted {
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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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lock: lockFunc,
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unlock: unlockFunc,
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chunks: 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() clientmodel.Timestamp {
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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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// memorySeriesIterator implements SeriesIterator.
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type memorySeriesIterator struct {
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lock, unlock func()
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chunkIt chunkIterator
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chunks []chunk
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}
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// GetValueAtTime implements SeriesIterator.
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func (it *memorySeriesIterator) GetValueAtTime(t clientmodel.Timestamp) metric.Values {
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it.lock()
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defer it.unlock()
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// The most common case. We are iterating through a chunk.
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if it.chunkIt != nil && it.chunkIt.contains(t) {
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return it.chunkIt.getValueAtTime(t)
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}
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it.chunkIt = nil
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if len(it.chunks) == 0 {
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return nil
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}
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// Before or exactly on the first sample of the series.
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if !t.After(it.chunks[0].firstTime()) {
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// return first value of first chunk
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return it.chunks[0].newIterator().getValueAtTime(t)
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}
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// After or exactly on the last sample of the series.
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if !t.Before(it.chunks[len(it.chunks)-1].lastTime()) {
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// return last value of last chunk
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return it.chunks[len(it.chunks)-1].newIterator().getValueAtTime(t)
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}
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// Find first chunk where lastTime() is after or equal to t.
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i := sort.Search(len(it.chunks), func(i int) bool {
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return !it.chunks[i].lastTime().Before(t)
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})
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if i == len(it.chunks) {
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panic("out of bounds")
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}
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if t.Before(it.chunks[i].firstTime()) {
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// We ended up between two chunks.
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return metric.Values{
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it.chunks[i-1].newIterator().getValueAtTime(t)[0],
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it.chunks[i].newIterator().getValueAtTime(t)[0],
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}
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}
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// We ended up in the middle of a chunk. We might stay there for a while,
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// so save it as the current chunk iterator.
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it.chunkIt = it.chunks[i].newIterator()
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return it.chunkIt.getValueAtTime(t)
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}
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// GetBoundaryValues implements SeriesIterator.
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func (it *memorySeriesIterator) GetBoundaryValues(in metric.Interval) metric.Values {
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it.lock()
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defer it.unlock()
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// Find the first relevant chunk.
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i := sort.Search(len(it.chunks), func(i int) bool {
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return !it.chunks[i].lastTime().Before(in.OldestInclusive)
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})
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values := make(metric.Values, 0, 2)
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for i, c := range it.chunks[i:] {
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var chunkIt chunkIterator
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if c.firstTime().After(in.NewestInclusive) {
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if len(values) == 1 {
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// 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.chunks[i-1].newIterator()
|
|
values = append(values, chunkIt.getValueAtTime(in.NewestInclusive)[0])
|
|
}
|
|
break
|
|
}
|
|
if len(values) == 0 {
|
|
chunkIt = c.newIterator()
|
|
firstValues := chunkIt.getValueAtTime(in.OldestInclusive)
|
|
switch len(firstValues) {
|
|
case 2:
|
|
values = append(values, firstValues[1])
|
|
case 1:
|
|
values = firstValues
|
|
default:
|
|
panic("unexpected return from getValueAtTime")
|
|
}
|
|
}
|
|
if c.lastTime().After(in.NewestInclusive) {
|
|
if chunkIt == nil {
|
|
chunkIt = c.newIterator()
|
|
}
|
|
values = append(values, chunkIt.getValueAtTime(in.NewestInclusive)[0])
|
|
break
|
|
}
|
|
}
|
|
if len(values) == 1 {
|
|
// We found exactly one value. In that case, add the most recent we know.
|
|
values = append(
|
|
values,
|
|
it.chunks[len(it.chunks)-1].newIterator().getValueAtTime(in.NewestInclusive)[0],
|
|
)
|
|
}
|
|
if len(values) == 2 && values[0].Equal(&values[1]) {
|
|
return values[:1]
|
|
}
|
|
return values
|
|
}
|
|
|
|
// GetRangeValues implements SeriesIterator.
|
|
func (it *memorySeriesIterator) GetRangeValues(in metric.Interval) metric.Values {
|
|
it.lock()
|
|
defer it.unlock()
|
|
|
|
// Find the first relevant chunk.
|
|
i := sort.Search(len(it.chunks), func(i int) bool {
|
|
return !it.chunks[i].lastTime().Before(in.OldestInclusive)
|
|
})
|
|
values := metric.Values{}
|
|
for _, c := range it.chunks[i:] {
|
|
if c.firstTime().After(in.NewestInclusive) {
|
|
break
|
|
}
|
|
// TODO: actually reuse an iterator between calls if we get multiple ranges
|
|
// from the same chunk.
|
|
values = append(values, c.newIterator().getRangeValues(in)...)
|
|
}
|
|
return values
|
|
}
|
|
|
|
// nopSeriesIterator implements Series Iterator. It never returns any values.
|
|
type nopSeriesIterator struct{}
|
|
|
|
// GetValueAtTime implements SeriesIterator.
|
|
func (_ nopSeriesIterator) GetValueAtTime(t clientmodel.Timestamp) metric.Values {
|
|
return metric.Values{}
|
|
}
|
|
|
|
// GetBoundaryValues implements SeriesIterator.
|
|
func (_ nopSeriesIterator) GetBoundaryValues(in metric.Interval) metric.Values {
|
|
return metric.Values{}
|
|
}
|
|
|
|
// GetRangeValues implements SeriesIterator.
|
|
func (_ nopSeriesIterator) GetRangeValues(in metric.Interval) metric.Values {
|
|
return metric.Values{}
|
|
}
|