prometheus/storage/local/series.go

564 lines
18 KiB
Go

// Copyright 2014 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package local
import (
"math"
"sort"
"sync"
"sync/atomic"
clientmodel "github.com/prometheus/client_golang/model"
"github.com/prometheus/prometheus/storage/metric"
)
// chunkDescEvictionFactor is a factor used for chunkDesc eviction (as opposed
// to evictions of chunks, see method evictOlderThan. A chunk takes about 20x
// more memory than a chunkDesc. With a chunkDescEvictionFactor of 10, not more
// than a third of the total memory taken by a series will be used for
// chunkDescs.
const chunkDescEvictionFactor = 10
// fingerprintSeriesPair pairs a fingerprint with a memorySeries pointer.
type fingerprintSeriesPair struct {
fp clientmodel.Fingerprint
series *memorySeries
}
// seriesMap maps fingerprints to memory series. All its methods are
// goroutine-safe. A SeriesMap is effectively is a goroutine-safe version of
// map[clientmodel.Fingerprint]*memorySeries.
type seriesMap struct {
mtx sync.RWMutex
m map[clientmodel.Fingerprint]*memorySeries
}
// newSeriesMap returns a newly allocated empty seriesMap. To create a seriesMap
// based on a prefilled map, use an explicit initializer.
func newSeriesMap() *seriesMap {
return &seriesMap{m: make(map[clientmodel.Fingerprint]*memorySeries)}
}
// length returns the number of mappings in the seriesMap.
func (sm *seriesMap) length() int {
sm.mtx.RLock()
defer sm.mtx.RUnlock()
return len(sm.m)
}
// get returns a memorySeries for a fingerprint. Return values have the same
// semantics as the native Go map.
func (sm *seriesMap) get(fp clientmodel.Fingerprint) (s *memorySeries, ok bool) {
sm.mtx.RLock()
defer sm.mtx.RUnlock()
s, ok = sm.m[fp]
return
}
// put adds a mapping to the seriesMap. It panics if s == nil.
func (sm *seriesMap) put(fp clientmodel.Fingerprint, s *memorySeries) {
sm.mtx.Lock()
defer sm.mtx.Unlock()
if s == nil {
panic("tried to add nil pointer to seriesMap")
}
sm.m[fp] = s
}
// del removes a mapping from the series Map.
func (sm *seriesMap) del(fp clientmodel.Fingerprint) {
sm.mtx.Lock()
defer sm.mtx.Unlock()
delete(sm.m, fp)
}
// iter returns a channel that produces all mappings in the seriesMap. The
// channel will be closed once all fingerprints have been received. Not
// consuming all fingerprints from the channel will leak a goroutine. The
// semantics of concurrent modification of seriesMap is the similar as the one
// for iterating over a map with a 'range' clause. However, if the next element
// in iteration order is removed after the current element has been received
// from the channel, it will still be produced by the channel.
func (sm *seriesMap) iter() <-chan fingerprintSeriesPair {
ch := make(chan fingerprintSeriesPair)
go func() {
sm.mtx.RLock()
for fp, s := range sm.m {
sm.mtx.RUnlock()
ch <- fingerprintSeriesPair{fp, s}
sm.mtx.RLock()
}
sm.mtx.RUnlock()
close(ch)
}()
return ch
}
// fpIter returns a channel that produces all fingerprints in the seriesMap. The
// channel will be closed once all fingerprints have been received. Not
// consuming all fingerprints from the channel will leak a goroutine. The
// semantics of concurrent modification of seriesMap is the similar as the one
// for iterating over a map with a 'range' clause. However, if the next element
// in iteration order is removed after the current element has been received
// from the channel, it will still be produced by the channel.
func (sm *seriesMap) fpIter() <-chan clientmodel.Fingerprint {
ch := make(chan clientmodel.Fingerprint)
go func() {
sm.mtx.RLock()
for fp := range sm.m {
sm.mtx.RUnlock()
ch <- fp
sm.mtx.RLock()
}
sm.mtx.RUnlock()
close(ch)
}()
return ch
}
type memorySeries struct {
metric clientmodel.Metric
// Sorted by start time, overlapping chunk ranges are forbidden.
chunkDescs []*chunkDesc
// The chunkDescs in memory might not have all the chunkDescs for the
// chunks that are persisted to disk. The missing chunkDescs are all
// contiguous and at the tail end. chunkDescsOffset is the index of the
// chunk on disk that corresponds to the first chunkDesc in memory. If
// it is 0, the chunkDescs are all loaded. A value of -1 denotes a
// special case: There are chunks on disk, but the offset to the
// chunkDescs in memory is unknown. Also, there is no overlap between
// chunks on disk and chunks in memory (implying that upon first
// persisting of a chunk in memory, the offset has to be set).
chunkDescsOffset int
// The savedFirstTime field is used as a fallback when the
// chunkDescsOffset is not 0. It can be used to save the firstTime of the
// first chunk before its chunk desc is evicted. In doubt, this field is
// just set to the oldest possible timestamp.
savedFirstTime clientmodel.Timestamp
// Whether the current head chunk has already been scheduled to be
// persisted. If true, the current head chunk must not be modified
// anymore.
headChunkPersisted bool
// Whether the current head chunk is used by an iterator. In that case,
// a non-persisted head chunk has to be cloned before more samples are
// appended.
headChunkUsedByIterator bool
}
// newMemorySeries returns a pointer to a newly allocated memorySeries for the
// given metric. reallyNew defines if the memorySeries is a genuinely new series
// or (if false) a series for a metric being unarchived, i.e. a series that
// existed before but has been evicted from memory. If reallyNew is false,
// firstTime is ignored (and set to the lowest possible timestamp instead - it
// will be set properly upon the first eviction of chunkDescs).
func newMemorySeries(m clientmodel.Metric, reallyNew bool, firstTime clientmodel.Timestamp) *memorySeries {
if reallyNew {
firstTime = math.MinInt64
}
s := memorySeries{
metric: m,
headChunkPersisted: !reallyNew,
savedFirstTime: firstTime,
}
if !reallyNew {
s.chunkDescsOffset = -1
}
return &s
}
// add adds a sample pair to the series.
// It returns chunkDescs that must be queued to be persisted.
// The caller must have locked the fingerprint of the series.
func (s *memorySeries) add(fp clientmodel.Fingerprint, v *metric.SamplePair) []*chunkDesc {
if len(s.chunkDescs) == 0 || s.headChunkPersisted {
newHead := newChunkDesc(newDeltaEncodedChunk(d1, d0, true))
s.chunkDescs = append(s.chunkDescs, newHead)
s.headChunkPersisted = false
} else if s.headChunkUsedByIterator && s.head().getRefCount() > 1 {
// We only need to clone the head chunk if the current head
// chunk was used in an iterator at all and if the refCount is
// still greater than the 1 we always have because the head
// chunk is not yet persisted. The latter is just an
// approximation. We will still clone unnecessarily if an older
// iterator using a previous version of the head chunk is still
// around and keep the head chunk pinned. We needed to track
// pins by version of the head chunk, which is probably not
// worth the effort.
chunkOps.WithLabelValues(clone).Inc()
// No locking needed here because a non-persisted head chunk can
// not get evicted concurrently.
s.head().chunk = s.head().chunk.clone()
s.headChunkUsedByIterator = false
}
chunks := s.head().add(v)
s.head().chunk = chunks[0]
var chunkDescsToPersist []*chunkDesc
if len(chunks) > 1 {
chunkDescsToPersist = append(chunkDescsToPersist, s.head())
for i, c := range chunks[1:] {
cd := newChunkDesc(c)
s.chunkDescs = append(s.chunkDescs, cd)
// The last chunk is still growing.
if i < len(chunks[1:])-1 {
chunkDescsToPersist = append(chunkDescsToPersist, cd)
}
}
}
return chunkDescsToPersist
}
// evictChunkDescs evicts chunkDescs if there are chunkDescEvictionFactor times
// more than non-evicted chunks. iOldestNotEvicted is the index within the
// current chunkDescs of the oldest chunk that is not evicted.
func (s *memorySeries) evictChunkDescs(iOldestNotEvicted int) {
lenToKeep := chunkDescEvictionFactor * (len(s.chunkDescs) - iOldestNotEvicted)
if lenToKeep < len(s.chunkDescs) {
s.savedFirstTime = s.firstTime()
lenEvicted := len(s.chunkDescs) - lenToKeep
s.chunkDescsOffset += lenEvicted
chunkDescOps.WithLabelValues(evict).Add(float64(lenEvicted))
numMemChunkDescs.Sub(float64(lenEvicted))
s.chunkDescs = append(
make([]*chunkDesc, 0, lenToKeep),
s.chunkDescs[lenEvicted:]...,
)
}
}
// purgeOlderThan removes chunkDescs older than t. It returns the number of
// purged chunkDescs and true if all chunkDescs have been purged.
//
// The caller must have locked the fingerprint of the series.
func (s *memorySeries) purgeOlderThan(t clientmodel.Timestamp) (int, bool) {
keepIdx := len(s.chunkDescs)
for i, cd := range s.chunkDescs {
if !cd.lastTime().Before(t) {
keepIdx = i
break
}
}
if keepIdx > 0 {
s.chunkDescs = append(make([]*chunkDesc, 0, len(s.chunkDescs)-keepIdx), s.chunkDescs[keepIdx:]...)
numMemChunkDescs.Sub(float64(keepIdx))
}
return keepIdx, len(s.chunkDescs) == 0
}
// preloadChunks is an internal helper method.
func (s *memorySeries) preloadChunks(indexes []int, mss *memorySeriesStorage) ([]*chunkDesc, error) {
loadIndexes := []int{}
pinnedChunkDescs := make([]*chunkDesc, 0, len(indexes))
for _, idx := range indexes {
cd := s.chunkDescs[idx]
pinnedChunkDescs = append(pinnedChunkDescs, cd)
cd.pin(mss.evictRequests) // Have to pin everything first to prevent immediate eviction on chunk loading.
if cd.isEvicted() {
loadIndexes = append(loadIndexes, idx)
}
}
chunkOps.WithLabelValues(pin).Add(float64(len(pinnedChunkDescs)))
if len(loadIndexes) > 0 {
if s.chunkDescsOffset == -1 {
panic("requested loading chunks from persistence in a situation where we must not have persisted data for chunk descriptors in memory")
}
fp := s.metric.Fingerprint()
chunks, err := mss.loadChunks(fp, loadIndexes, s.chunkDescsOffset)
if err != nil {
// Unpin the chunks since we won't return them as pinned chunks now.
for _, cd := range pinnedChunkDescs {
cd.unpin(mss.evictRequests)
}
chunkOps.WithLabelValues(unpin).Add(float64(len(pinnedChunkDescs)))
return nil, err
}
for i, c := range chunks {
s.chunkDescs[loadIndexes[i]].setChunk(c)
}
chunkOps.WithLabelValues(load).Add(float64(len(chunks)))
atomic.AddInt64(&numMemChunks, int64(len(chunks)))
}
return pinnedChunkDescs, nil
}
/*
func (s *memorySeries) preloadChunksAtTime(t clientmodel.Timestamp, p *persistence) (chunkDescs, error) {
s.mtx.Lock()
defer s.mtx.Unlock()
if len(s.chunkDescs) == 0 {
return nil, nil
}
var pinIndexes []int
// Find first chunk where lastTime() is after or equal to t.
i := sort.Search(len(s.chunkDescs), func(i int) bool {
return !s.chunkDescs[i].lastTime().Before(t)
})
switch i {
case 0:
pinIndexes = []int{0}
case len(s.chunkDescs):
pinIndexes = []int{i - 1}
default:
if s.chunkDescs[i].contains(t) {
pinIndexes = []int{i}
} else {
pinIndexes = []int{i - 1, i}
}
}
return s.preloadChunks(pinIndexes, p)
}
*/
// preloadChunksForRange loads chunks for the given range from the persistence.
// The caller must have locked the fingerprint of the series.
func (s *memorySeries) preloadChunksForRange(
from clientmodel.Timestamp, through clientmodel.Timestamp,
fp clientmodel.Fingerprint, mss *memorySeriesStorage,
) ([]*chunkDesc, error) {
firstChunkDescTime := clientmodel.Timestamp(math.MaxInt64)
if len(s.chunkDescs) > 0 {
firstChunkDescTime = s.chunkDescs[0].firstTime()
}
if s.chunkDescsOffset != 0 && from.Before(firstChunkDescTime) {
cds, err := mss.loadChunkDescs(fp, firstChunkDescTime)
if err != nil {
return nil, err
}
s.chunkDescs = append(cds, s.chunkDescs...)
s.chunkDescsOffset = 0
}
if len(s.chunkDescs) == 0 {
return nil, nil
}
// Find first chunk with start time after "from".
fromIdx := sort.Search(len(s.chunkDescs), func(i int) bool {
return s.chunkDescs[i].firstTime().After(from)
})
// Find first chunk with start time after "through".
throughIdx := sort.Search(len(s.chunkDescs), func(i int) bool {
return s.chunkDescs[i].firstTime().After(through)
})
if fromIdx > 0 {
fromIdx--
}
if throughIdx == len(s.chunkDescs) {
throughIdx--
}
pinIndexes := make([]int, 0, throughIdx-fromIdx+1)
for i := fromIdx; i <= throughIdx; i++ {
pinIndexes = append(pinIndexes, i)
}
return s.preloadChunks(pinIndexes, mss)
}
// newIterator returns a new SeriesIterator. The caller must have locked the
// fingerprint of the memorySeries.
func (s *memorySeries) newIterator(lockFunc, unlockFunc func()) SeriesIterator {
chunks := make([]chunk, 0, len(s.chunkDescs))
for i, cd := range s.chunkDescs {
if chunk := cd.getChunk(); chunk != nil {
if i == len(s.chunkDescs)-1 && !s.headChunkPersisted {
s.headChunkUsedByIterator = true
}
chunks = append(chunks, chunk)
}
}
return &memorySeriesIterator{
lock: lockFunc,
unlock: unlockFunc,
chunks: chunks,
}
}
// head returns a pointer to the head chunk descriptor. The caller must have
// locked the fingerprint of the memorySeries. This method will panic if this
// series has no chunk descriptors.
func (s *memorySeries) head() *chunkDesc {
return s.chunkDescs[len(s.chunkDescs)-1]
}
// firstTime returns the timestamp of the first sample in the series. The caller
// must have locked the fingerprint of the memorySeries.
func (s *memorySeries) firstTime() clientmodel.Timestamp {
if s.chunkDescsOffset == 0 && len(s.chunkDescs) > 0 {
return s.chunkDescs[0].firstTime()
}
return s.savedFirstTime
}
// memorySeriesIterator implements SeriesIterator.
type memorySeriesIterator struct {
lock, unlock func()
chunkIt chunkIterator
chunks []chunk
}
// GetValueAtTime implements SeriesIterator.
func (it *memorySeriesIterator) GetValueAtTime(t clientmodel.Timestamp) metric.Values {
it.lock()
defer it.unlock()
// The most common case. We are iterating through a chunk.
if it.chunkIt != nil && it.chunkIt.contains(t) {
return it.chunkIt.getValueAtTime(t)
}
it.chunkIt = nil
if len(it.chunks) == 0 {
return nil
}
// Before or exactly on the first sample of the series.
if !t.After(it.chunks[0].firstTime()) {
// return first value of first chunk
return it.chunks[0].newIterator().getValueAtTime(t)
}
// After or exactly on the last sample of the series.
if !t.Before(it.chunks[len(it.chunks)-1].lastTime()) {
// return last value of last chunk
return it.chunks[len(it.chunks)-1].newIterator().getValueAtTime(t)
}
// Find first chunk where lastTime() is after or equal to t.
i := sort.Search(len(it.chunks), func(i int) bool {
return !it.chunks[i].lastTime().Before(t)
})
if i == len(it.chunks) {
panic("out of bounds")
}
if t.Before(it.chunks[i].firstTime()) {
// We ended up between two chunks.
return metric.Values{
it.chunks[i-1].newIterator().getValueAtTime(t)[0],
it.chunks[i].newIterator().getValueAtTime(t)[0],
}
}
// We ended up in the middle of a chunk. We might stay there for a while,
// so save it as the current chunk iterator.
it.chunkIt = it.chunks[i].newIterator()
return it.chunkIt.getValueAtTime(t)
}
// GetBoundaryValues implements SeriesIterator.
func (it *memorySeriesIterator) GetBoundaryValues(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 := make(metric.Values, 0, 2)
for i, c := range it.chunks[i:] {
var chunkIt chunkIterator
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.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{}
}