prometheus/tsdb/chunkenc/histogram.go

945 lines
27 KiB
Go

// Copyright 2021 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 chunkenc
import (
"encoding/binary"
"math"
"github.com/prometheus/prometheus/model/histogram"
"github.com/prometheus/prometheus/model/value"
)
// HistogramChunk holds encoded sample data for a sparse, high-resolution
// histogram.
//
// Each sample has multiple "fields", stored in the following way (raw = store
// number directly, delta = store delta to the previous number, dod = store
// delta of the delta to the previous number, xor = what we do for regular
// sample values):
//
// field → ts count zeroCount sum []posbuckets []negbuckets
// sample 1 raw raw raw raw []raw []raw
// sample 2 delta delta delta xor []delta []delta
// sample >2 dod dod dod xor []dod []dod
type HistogramChunk struct {
b bstream
}
// NewHistogramChunk returns a new chunk with histogram encoding of the given
// size.
func NewHistogramChunk() *HistogramChunk {
b := make([]byte, 3, 128)
return &HistogramChunk{b: bstream{stream: b, count: 0}}
}
// Encoding returns the encoding type.
func (c *HistogramChunk) Encoding() Encoding {
return EncHistogram
}
// Bytes returns the underlying byte slice of the chunk.
func (c *HistogramChunk) Bytes() []byte {
return c.b.bytes()
}
// NumSamples returns the number of samples in the chunk.
func (c *HistogramChunk) NumSamples() int {
return int(binary.BigEndian.Uint16(c.Bytes()))
}
// Layout returns the histogram layout. Only call this on chunks that have at
// least one sample.
func (c *HistogramChunk) Layout() (
schema int32, zeroThreshold float64,
negativeSpans, positiveSpans []histogram.Span,
err error,
) {
if c.NumSamples() == 0 {
panic("HistogramChunk.Layout() called on an empty chunk")
}
b := newBReader(c.Bytes()[2:])
return readHistogramChunkLayout(&b)
}
// CounterResetHeader defines the first 2 bits of the chunk header.
type CounterResetHeader byte
const (
// CounterReset means there was definitely a counter reset that resulted in this chunk.
CounterReset CounterResetHeader = 0b10000000
// NotCounterReset means there was definitely no counter reset when cutting this chunk.
NotCounterReset CounterResetHeader = 0b01000000
// GaugeType means this chunk contains a gauge histogram, where counter resets do not happen.
GaugeType CounterResetHeader = 0b11000000
// UnknownCounterReset means we cannot say if this chunk was created due to a counter reset or not.
// An explicit counter reset detection needs to happen during query time.
UnknownCounterReset CounterResetHeader = 0b00000000
)
// setCounterResetHeader sets the counter reset header of the chunk
// The third byte of the chunk is the counter reset header.
func setCounterResetHeader(h CounterResetHeader, bytes []byte) {
switch h {
case CounterReset, NotCounterReset, GaugeType, UnknownCounterReset:
bytes[2] = (bytes[2] & 0b00111111) | byte(h)
default:
panic("invalid CounterResetHeader type")
}
}
// SetCounterResetHeader sets the counter reset header.
func (c *HistogramChunk) SetCounterResetHeader(h CounterResetHeader) {
setCounterResetHeader(h, c.Bytes())
}
// GetCounterResetHeader returns the info about the first 2 bits of the chunk
// header.
func (c *HistogramChunk) GetCounterResetHeader() CounterResetHeader {
return CounterResetHeader(c.Bytes()[2] & 0b11000000)
}
// Compact implements the Chunk interface.
func (c *HistogramChunk) Compact() {
if l := len(c.b.stream); cap(c.b.stream) > l+chunkCompactCapacityThreshold {
buf := make([]byte, l)
copy(buf, c.b.stream)
c.b.stream = buf
}
}
// Appender implements the Chunk interface.
func (c *HistogramChunk) Appender() (Appender, error) {
it := c.iterator(nil)
// To get an appender, we must know the state it would have if we had
// appended all existing data from scratch. We iterate through the end
// and populate via the iterator's state.
for it.Next() == ValHistogram { // nolint:revive
}
if err := it.Err(); err != nil {
return nil, err
}
a := &HistogramAppender{
b: &c.b,
schema: it.schema,
zThreshold: it.zThreshold,
pSpans: it.pSpans,
nSpans: it.nSpans,
t: it.t,
cnt: it.cnt,
zCnt: it.zCnt,
tDelta: it.tDelta,
cntDelta: it.cntDelta,
zCntDelta: it.zCntDelta,
pBuckets: it.pBuckets,
nBuckets: it.nBuckets,
pBucketsDelta: it.pBucketsDelta,
nBucketsDelta: it.nBucketsDelta,
sum: it.sum,
leading: it.leading,
trailing: it.trailing,
}
if it.numTotal == 0 {
a.leading = 0xff
}
return a, nil
}
func countSpans(spans []histogram.Span) int {
var cnt int
for _, s := range spans {
cnt += int(s.Length)
}
return cnt
}
func newHistogramIterator(b []byte) *histogramIterator {
it := &histogramIterator{
br: newBReader(b),
numTotal: binary.BigEndian.Uint16(b),
t: math.MinInt64,
}
// The first 3 bytes contain chunk headers.
// We skip that for actual samples.
_, _ = it.br.readBits(24)
it.counterResetHeader = CounterResetHeader(b[2] & 0b11000000)
return it
}
func (c *HistogramChunk) iterator(it Iterator) *histogramIterator {
// This comment is copied from XORChunk.iterator:
// Should iterators guarantee to act on a copy of the data so it doesn't lock append?
// When using striped locks to guard access to chunks, probably yes.
// Could only copy data if the chunk is not completed yet.
if histogramIter, ok := it.(*histogramIterator); ok {
histogramIter.Reset(c.b.bytes())
return histogramIter
}
return newHistogramIterator(c.b.bytes())
}
// Iterator implements the Chunk interface.
func (c *HistogramChunk) Iterator(it Iterator) Iterator {
return c.iterator(it)
}
// HistogramAppender is an Appender implementation for sparse histograms.
type HistogramAppender struct {
b *bstream
// Layout:
schema int32
zThreshold float64
pSpans, nSpans []histogram.Span
// Although we intend to start new chunks on counter resets, we still
// have to handle negative deltas for gauge histograms. Therefore, even
// deltas are signed types here (even for tDelta to not treat that one
// specially).
t int64
cnt, zCnt uint64
tDelta, cntDelta, zCntDelta int64
pBuckets, nBuckets []int64
pBucketsDelta, nBucketsDelta []int64
// The sum is Gorilla xor encoded.
sum float64
leading uint8
trailing uint8
}
func (a *HistogramAppender) GetCounterResetHeader() CounterResetHeader {
return CounterResetHeader(a.b.bytes()[2] & 0b11000000)
}
func (a *HistogramAppender) NumSamples() int {
return int(binary.BigEndian.Uint16(a.b.bytes()))
}
// Append implements Appender. This implementation panics because normal float
// samples must never be appended to a histogram chunk.
func (a *HistogramAppender) Append(int64, float64) {
panic("appended a float sample to a histogram chunk")
}
// AppendFloatHistogram implements Appender. This implementation panics because float
// histogram samples must never be appended to a histogram chunk.
func (a *HistogramAppender) AppendFloatHistogram(int64, *histogram.FloatHistogram) {
panic("appended a float histogram to a histogram chunk")
}
// Appendable returns whether the chunk can be appended to, and if so whether
// any recoding needs to happen using the provided inserts (in case of any new
// buckets, positive or negative range, respectively). If the sample is a gauge
// histogram, AppendableGauge must be used instead.
//
// The chunk is not appendable in the following cases:
//
// - The schema has changed.
// - The threshold for the zero bucket has changed.
// - Any buckets have disappeared.
// - There was a counter reset in the count of observations or in any bucket,
// including the zero bucket.
// - The last sample in the chunk was stale while the current sample is not stale.
//
// The method returns an additional boolean set to true if it is not appendable
// because of a counter reset. If the given sample is stale, it is always ok to
// append. If counterReset is true, okToAppend is always false.
func (a *HistogramAppender) Appendable(h *histogram.Histogram) (
positiveInserts, negativeInserts []Insert,
okToAppend, counterReset bool,
) {
if a.NumSamples() > 0 && a.GetCounterResetHeader() == GaugeType {
return
}
if value.IsStaleNaN(h.Sum) {
// This is a stale sample whose buckets and spans don't matter.
okToAppend = true
return
}
if value.IsStaleNaN(a.sum) {
// If the last sample was stale, then we can only accept stale
// samples in this chunk.
return
}
if h.Count < a.cnt {
// There has been a counter reset.
counterReset = true
return
}
if h.Schema != a.schema || h.ZeroThreshold != a.zThreshold {
return
}
if h.ZeroCount < a.zCnt {
// There has been a counter reset since ZeroThreshold didn't change.
counterReset = true
return
}
var ok bool
positiveInserts, ok = expandSpansForward(a.pSpans, h.PositiveSpans)
if !ok {
counterReset = true
return
}
negativeInserts, ok = expandSpansForward(a.nSpans, h.NegativeSpans)
if !ok {
counterReset = true
return
}
if counterResetInAnyBucket(a.pBuckets, h.PositiveBuckets, a.pSpans, h.PositiveSpans) ||
counterResetInAnyBucket(a.nBuckets, h.NegativeBuckets, a.nSpans, h.NegativeSpans) {
counterReset, positiveInserts, negativeInserts = true, nil, nil
return
}
okToAppend = true
return
}
// AppendableGauge returns whether the chunk can be appended to, and if so
// whether:
// 1. Any recoding needs to happen to the chunk using the provided inserts
// (in case of any new buckets, positive or negative range, respectively).
// 2. Any recoding needs to happen for the histogram being appended, using the
// backward inserts (in case of any missing buckets, positive or negative
// range, respectively).
//
// This method must be only used for gauge histograms.
//
// The chunk is not appendable in the following cases:
// - The schema has changed.
// - The threshold for the zero bucket has changed.
// - The last sample in the chunk was stale while the current sample is not stale.
func (a *HistogramAppender) AppendableGauge(h *histogram.Histogram) (
positiveInserts, negativeInserts []Insert,
backwardPositiveInserts, backwardNegativeInserts []Insert,
positiveSpans, negativeSpans []histogram.Span,
okToAppend bool,
) {
if a.NumSamples() > 0 && a.GetCounterResetHeader() != GaugeType {
return
}
if value.IsStaleNaN(h.Sum) {
// This is a stale sample whose buckets and spans don't matter.
okToAppend = true
return
}
if value.IsStaleNaN(a.sum) {
// If the last sample was stale, then we can only accept stale
// samples in this chunk.
return
}
if h.Schema != a.schema || h.ZeroThreshold != a.zThreshold {
return
}
positiveInserts, backwardPositiveInserts, positiveSpans = expandSpansBothWays(a.pSpans, h.PositiveSpans)
negativeInserts, backwardNegativeInserts, negativeSpans = expandSpansBothWays(a.nSpans, h.NegativeSpans)
okToAppend = true
return
}
// counterResetInAnyBucket returns true if there was a counter reset for any
// bucket. This should be called only when the bucket layout is the same or new
// buckets were added. It does not handle the case of buckets missing.
func counterResetInAnyBucket(oldBuckets, newBuckets []int64, oldSpans, newSpans []histogram.Span) bool {
if len(oldSpans) == 0 || len(oldBuckets) == 0 {
return false
}
oldSpanSliceIdx, newSpanSliceIdx := 0, 0 // Index for the span slices.
oldInsideSpanIdx, newInsideSpanIdx := uint32(0), uint32(0) // Index inside a span.
oldIdx, newIdx := oldSpans[0].Offset, newSpans[0].Offset
oldBucketSliceIdx, newBucketSliceIdx := 0, 0 // Index inside bucket slice.
oldVal, newVal := oldBuckets[0], newBuckets[0]
// Since we assume that new spans won't have missing buckets, there will never be a case
// where the old index will not find a matching new index.
for {
if oldIdx == newIdx {
if newVal < oldVal {
return true
}
}
if oldIdx <= newIdx {
// Moving ahead old bucket and span by 1 index.
if oldInsideSpanIdx+1 >= oldSpans[oldSpanSliceIdx].Length {
// Current span is over.
oldSpanSliceIdx = nextNonEmptySpanSliceIdx(oldSpanSliceIdx, oldSpans)
oldInsideSpanIdx = 0
if oldSpanSliceIdx >= len(oldSpans) {
// All old spans are over.
break
}
oldIdx += 1 + oldSpans[oldSpanSliceIdx].Offset
} else {
oldInsideSpanIdx++
oldIdx++
}
oldBucketSliceIdx++
oldVal += oldBuckets[oldBucketSliceIdx]
}
if oldIdx > newIdx {
// Moving ahead new bucket and span by 1 index.
if newInsideSpanIdx+1 >= newSpans[newSpanSliceIdx].Length {
// Current span is over.
newSpanSliceIdx = nextNonEmptySpanSliceIdx(newSpanSliceIdx, newSpans)
newInsideSpanIdx = 0
if newSpanSliceIdx >= len(newSpans) {
// All new spans are over.
// This should not happen, old spans above should catch this first.
panic("new spans over before old spans in counterReset")
}
newIdx += 1 + newSpans[newSpanSliceIdx].Offset
} else {
newInsideSpanIdx++
newIdx++
}
newBucketSliceIdx++
newVal += newBuckets[newBucketSliceIdx]
}
}
return false
}
// AppendHistogram appends a histogram to the chunk. The caller must ensure that
// the histogram is properly structured, e.g. the number of buckets used
// corresponds to the number conveyed by the span structures. First call
// Appendable() and act accordingly!
func (a *HistogramAppender) AppendHistogram(t int64, h *histogram.Histogram) {
var tDelta, cntDelta, zCntDelta int64
num := binary.BigEndian.Uint16(a.b.bytes())
if value.IsStaleNaN(h.Sum) {
// Emptying out other fields to write no buckets, and an empty
// layout in case of first histogram in the chunk.
h = &histogram.Histogram{Sum: h.Sum}
}
if num == 0 {
// The first append gets the privilege to dictate the layout
// but it's also responsible for encoding it into the chunk!
writeHistogramChunkLayout(a.b, h.Schema, h.ZeroThreshold, h.PositiveSpans, h.NegativeSpans)
a.schema = h.Schema
a.zThreshold = h.ZeroThreshold
if len(h.PositiveSpans) > 0 {
a.pSpans = make([]histogram.Span, len(h.PositiveSpans))
copy(a.pSpans, h.PositiveSpans)
} else {
a.pSpans = nil
}
if len(h.NegativeSpans) > 0 {
a.nSpans = make([]histogram.Span, len(h.NegativeSpans))
copy(a.nSpans, h.NegativeSpans)
} else {
a.nSpans = nil
}
numPBuckets, numNBuckets := countSpans(h.PositiveSpans), countSpans(h.NegativeSpans)
if numPBuckets > 0 {
a.pBuckets = make([]int64, numPBuckets)
a.pBucketsDelta = make([]int64, numPBuckets)
} else {
a.pBuckets = nil
a.pBucketsDelta = nil
}
if numNBuckets > 0 {
a.nBuckets = make([]int64, numNBuckets)
a.nBucketsDelta = make([]int64, numNBuckets)
} else {
a.nBuckets = nil
a.nBucketsDelta = nil
}
// Now store the actual data.
putVarbitInt(a.b, t)
putVarbitUint(a.b, h.Count)
putVarbitUint(a.b, h.ZeroCount)
a.b.writeBits(math.Float64bits(h.Sum), 64)
for _, b := range h.PositiveBuckets {
putVarbitInt(a.b, b)
}
for _, b := range h.NegativeBuckets {
putVarbitInt(a.b, b)
}
} else {
// The case for the 2nd sample with single deltas is implicitly
// handled correctly with the double delta code, so we don't
// need a separate single delta logic for the 2nd sample.
tDelta = t - a.t
cntDelta = int64(h.Count) - int64(a.cnt)
zCntDelta = int64(h.ZeroCount) - int64(a.zCnt)
tDod := tDelta - a.tDelta
cntDod := cntDelta - a.cntDelta
zCntDod := zCntDelta - a.zCntDelta
if value.IsStaleNaN(h.Sum) {
cntDod, zCntDod = 0, 0
}
putVarbitInt(a.b, tDod)
putVarbitInt(a.b, cntDod)
putVarbitInt(a.b, zCntDod)
a.writeSumDelta(h.Sum)
for i, b := range h.PositiveBuckets {
delta := b - a.pBuckets[i]
dod := delta - a.pBucketsDelta[i]
putVarbitInt(a.b, dod)
a.pBucketsDelta[i] = delta
}
for i, b := range h.NegativeBuckets {
delta := b - a.nBuckets[i]
dod := delta - a.nBucketsDelta[i]
putVarbitInt(a.b, dod)
a.nBucketsDelta[i] = delta
}
}
binary.BigEndian.PutUint16(a.b.bytes(), num+1)
a.t = t
a.cnt = h.Count
a.zCnt = h.ZeroCount
a.tDelta = tDelta
a.cntDelta = cntDelta
a.zCntDelta = zCntDelta
copy(a.pBuckets, h.PositiveBuckets)
copy(a.nBuckets, h.NegativeBuckets)
// Note that the bucket deltas were already updated above.
a.sum = h.Sum
}
// Recode converts the current chunk to accommodate an expansion of the set of
// (positive and/or negative) buckets used, according to the provided inserts,
// resulting in the honoring of the provided new positive and negative spans. To
// continue appending, use the returned Appender rather than the receiver of
// this method.
func (a *HistogramAppender) Recode(
positiveInserts, negativeInserts []Insert,
positiveSpans, negativeSpans []histogram.Span,
) (Chunk, Appender) {
// TODO(beorn7): This currently just decodes everything and then encodes
// it again with the new span layout. This can probably be done in-place
// by editing the chunk. But let's first see how expensive it is in the
// big picture. Also, in-place editing might create concurrency issues.
byts := a.b.bytes()
it := newHistogramIterator(byts)
hc := NewHistogramChunk()
app, err := hc.Appender()
if err != nil {
panic(err)
}
numPositiveBuckets, numNegativeBuckets := countSpans(positiveSpans), countSpans(negativeSpans)
for it.Next() == ValHistogram {
tOld, hOld := it.AtHistogram()
// We have to newly allocate slices for the modified buckets
// here because they are kept by the appender until the next
// append.
// TODO(beorn7): We might be able to optimize this.
var positiveBuckets, negativeBuckets []int64
if numPositiveBuckets > 0 {
positiveBuckets = make([]int64, numPositiveBuckets)
}
if numNegativeBuckets > 0 {
negativeBuckets = make([]int64, numNegativeBuckets)
}
// Save the modified histogram to the new chunk.
hOld.PositiveSpans, hOld.NegativeSpans = positiveSpans, negativeSpans
if len(positiveInserts) > 0 {
hOld.PositiveBuckets = insert(hOld.PositiveBuckets, positiveBuckets, positiveInserts, true)
}
if len(negativeInserts) > 0 {
hOld.NegativeBuckets = insert(hOld.NegativeBuckets, negativeBuckets, negativeInserts, true)
}
app.AppendHistogram(tOld, hOld)
}
hc.SetCounterResetHeader(CounterResetHeader(byts[2] & 0b11000000))
return hc, app
}
// RecodeHistogram converts the current histogram (in-place) to accommodate an
// expansion of the set of (positive and/or negative) buckets used.
func (a *HistogramAppender) RecodeHistogram(
h *histogram.Histogram,
pBackwardInserts, nBackwardInserts []Insert,
) {
if len(pBackwardInserts) > 0 {
numPositiveBuckets := countSpans(h.PositiveSpans)
h.PositiveBuckets = insert(h.PositiveBuckets, make([]int64, numPositiveBuckets), pBackwardInserts, true)
}
if len(nBackwardInserts) > 0 {
numNegativeBuckets := countSpans(h.NegativeSpans)
h.NegativeBuckets = insert(h.NegativeBuckets, make([]int64, numNegativeBuckets), nBackwardInserts, true)
}
}
func (a *HistogramAppender) writeSumDelta(v float64) {
xorWrite(a.b, v, a.sum, &a.leading, &a.trailing)
}
type histogramIterator struct {
br bstreamReader
numTotal uint16
numRead uint16
counterResetHeader CounterResetHeader
// Layout:
schema int32
zThreshold float64
pSpans, nSpans []histogram.Span
// For the fields that are tracked as deltas and ultimately dod's.
t int64
cnt, zCnt uint64
tDelta, cntDelta, zCntDelta int64
pBuckets, nBuckets []int64 // Delta between buckets.
pFloatBuckets, nFloatBuckets []float64 // Absolute counts.
pBucketsDelta, nBucketsDelta []int64
// The sum is Gorilla xor encoded.
sum float64
leading uint8
trailing uint8
// Track calls to retrieve methods. Once they have been called, we
// cannot recycle the bucket slices anymore because we have returned
// them in the histogram.
atHistogramCalled, atFloatHistogramCalled bool
err error
}
func (it *histogramIterator) Seek(t int64) ValueType {
if it.err != nil {
return ValNone
}
for t > it.t || it.numRead == 0 {
if it.Next() == ValNone {
return ValNone
}
}
return ValHistogram
}
func (it *histogramIterator) At() (int64, float64) {
panic("cannot call histogramIterator.At")
}
func (it *histogramIterator) AtHistogram() (int64, *histogram.Histogram) {
if value.IsStaleNaN(it.sum) {
return it.t, &histogram.Histogram{Sum: it.sum}
}
it.atHistogramCalled = true
return it.t, &histogram.Histogram{
CounterResetHint: counterResetHint(it.counterResetHeader, it.numRead),
Count: it.cnt,
ZeroCount: it.zCnt,
Sum: it.sum,
ZeroThreshold: it.zThreshold,
Schema: it.schema,
PositiveSpans: it.pSpans,
NegativeSpans: it.nSpans,
PositiveBuckets: it.pBuckets,
NegativeBuckets: it.nBuckets,
}
}
func (it *histogramIterator) AtFloatHistogram() (int64, *histogram.FloatHistogram) {
if value.IsStaleNaN(it.sum) {
return it.t, &histogram.FloatHistogram{Sum: it.sum}
}
it.atFloatHistogramCalled = true
return it.t, &histogram.FloatHistogram{
CounterResetHint: counterResetHint(it.counterResetHeader, it.numRead),
Count: float64(it.cnt),
ZeroCount: float64(it.zCnt),
Sum: it.sum,
ZeroThreshold: it.zThreshold,
Schema: it.schema,
PositiveSpans: it.pSpans,
NegativeSpans: it.nSpans,
PositiveBuckets: it.pFloatBuckets,
NegativeBuckets: it.nFloatBuckets,
}
}
func (it *histogramIterator) AtT() int64 {
return it.t
}
func (it *histogramIterator) Err() error {
return it.err
}
func (it *histogramIterator) Reset(b []byte) {
// The first 3 bytes contain chunk headers.
// We skip that for actual samples.
it.br = newBReader(b[3:])
it.numTotal = binary.BigEndian.Uint16(b)
it.numRead = 0
it.counterResetHeader = CounterResetHeader(b[2] & 0b11000000)
it.t, it.cnt, it.zCnt = 0, 0, 0
it.tDelta, it.cntDelta, it.zCntDelta = 0, 0, 0
// Recycle slices that have not been returned yet. Otherwise, start from
// scratch.
if it.atHistogramCalled {
it.atHistogramCalled = false
it.pBuckets, it.nBuckets = nil, nil
} else {
it.pBuckets = it.pBuckets[:0]
it.nBuckets = it.nBuckets[:0]
}
if it.atFloatHistogramCalled {
it.atFloatHistogramCalled = false
it.pFloatBuckets, it.nFloatBuckets = nil, nil
} else {
it.pFloatBuckets = it.pFloatBuckets[:0]
it.nFloatBuckets = it.nFloatBuckets[:0]
}
it.pBucketsDelta = it.pBucketsDelta[:0]
it.nBucketsDelta = it.nBucketsDelta[:0]
it.sum = 0
it.leading = 0
it.trailing = 0
it.err = nil
}
func (it *histogramIterator) Next() ValueType {
if it.err != nil || it.numRead == it.numTotal {
return ValNone
}
if it.numRead == 0 {
// The first read is responsible for reading the chunk layout
// and for initializing fields that depend on it. We give
// counter reset info at chunk level, hence we discard it here.
schema, zeroThreshold, posSpans, negSpans, err := readHistogramChunkLayout(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.schema = schema
it.zThreshold = zeroThreshold
it.pSpans, it.nSpans = posSpans, negSpans
numPBuckets, numNBuckets := countSpans(posSpans), countSpans(negSpans)
// The code below recycles existing slices in case this iterator
// was reset and already has slices of a sufficient capacity.
if numPBuckets > 0 {
it.pBuckets = append(it.pBuckets, make([]int64, numPBuckets)...)
it.pBucketsDelta = append(it.pBucketsDelta, make([]int64, numPBuckets)...)
it.pFloatBuckets = append(it.pFloatBuckets, make([]float64, numPBuckets)...)
}
if numNBuckets > 0 {
it.nBuckets = append(it.nBuckets, make([]int64, numNBuckets)...)
it.nBucketsDelta = append(it.nBucketsDelta, make([]int64, numNBuckets)...)
it.nFloatBuckets = append(it.nFloatBuckets, make([]float64, numNBuckets)...)
}
// Now read the actual data.
t, err := readVarbitInt(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.t = t
cnt, err := readVarbitUint(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.cnt = cnt
zcnt, err := readVarbitUint(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.zCnt = zcnt
sum, err := it.br.readBits(64)
if err != nil {
it.err = err
return ValNone
}
it.sum = math.Float64frombits(sum)
var current int64
for i := range it.pBuckets {
v, err := readVarbitInt(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.pBuckets[i] = v
current += it.pBuckets[i]
it.pFloatBuckets[i] = float64(current)
}
current = 0
for i := range it.nBuckets {
v, err := readVarbitInt(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.nBuckets[i] = v
current += it.nBuckets[i]
it.nFloatBuckets[i] = float64(current)
}
it.numRead++
return ValHistogram
}
// The case for the 2nd sample with single deltas is implicitly handled correctly with the double delta code,
// so we don't need a separate single delta logic for the 2nd sample.
// Recycle bucket slices that have not been returned yet. Otherwise,
// copy them.
if it.atHistogramCalled {
it.atHistogramCalled = false
if len(it.pBuckets) > 0 {
newBuckets := make([]int64, len(it.pBuckets))
copy(newBuckets, it.pBuckets)
it.pBuckets = newBuckets
} else {
it.pBuckets = nil
}
if len(it.nBuckets) > 0 {
newBuckets := make([]int64, len(it.nBuckets))
copy(newBuckets, it.nBuckets)
it.nBuckets = newBuckets
} else {
it.nBuckets = nil
}
}
// FloatBuckets are set from scratch, so simply create empty ones.
if it.atFloatHistogramCalled {
it.atFloatHistogramCalled = false
if len(it.pFloatBuckets) > 0 {
it.pFloatBuckets = make([]float64, len(it.pFloatBuckets))
} else {
it.pFloatBuckets = nil
}
if len(it.nFloatBuckets) > 0 {
it.nFloatBuckets = make([]float64, len(it.nFloatBuckets))
} else {
it.nFloatBuckets = nil
}
}
tDod, err := readVarbitInt(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.tDelta += tDod
it.t += it.tDelta
cntDod, err := readVarbitInt(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.cntDelta += cntDod
it.cnt = uint64(int64(it.cnt) + it.cntDelta)
zcntDod, err := readVarbitInt(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.zCntDelta += zcntDod
it.zCnt = uint64(int64(it.zCnt) + it.zCntDelta)
ok := it.readSum()
if !ok {
return ValNone
}
if value.IsStaleNaN(it.sum) {
it.numRead++
return ValHistogram
}
var current int64
for i := range it.pBuckets {
dod, err := readVarbitInt(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.pBucketsDelta[i] += dod
it.pBuckets[i] += it.pBucketsDelta[i]
current += it.pBuckets[i]
it.pFloatBuckets[i] = float64(current)
}
current = 0
for i := range it.nBuckets {
dod, err := readVarbitInt(&it.br)
if err != nil {
it.err = err
return ValNone
}
it.nBucketsDelta[i] += dod
it.nBuckets[i] += it.nBucketsDelta[i]
current += it.nBuckets[i]
it.nFloatBuckets[i] = float64(current)
}
it.numRead++
return ValHistogram
}
func (it *histogramIterator) readSum() bool {
err := xorRead(&it.br, &it.sum, &it.leading, &it.trailing)
if err != nil {
it.err = err
return false
}
return true
}