github-mirrors/VictoriaMetrics
1
0
Fork 0
mirror of https://github.com/VictoriaMetrics/VictoriaMetrics.git synced 2024-11-21 14:44:00 +00:00
Code Issues Projects Releases Packages Wiki Activity

vendor: update github.com/klauspost/compress from v1.9.7 to v1.9.8

Browse source 
New version should have better gzip compression. See https://github.com/klauspost/compress#changelog
This commit is contained in:
Aliaksandr Valialkin 2020-01-22 16:49:35 +02:00
parent 0ef6f91410
commit f8954c7250
9 changed files with 474 additions and 89 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

2
go.mod
View file

@ -8,7 +8,7 @@ require (
github.com/aws/aws-sdk-go v1.28.3
github.com/cespare/xxhash/v2 v2.1.1
github.com/golang/snappy v0.0.1
github.com/klauspost/compress v1.9.7
github.com/klauspost/compress v1.9.8
github.com/valyala/fastjson v1.4.5
github.com/valyala/fastrand v1.0.0
github.com/valyala/gozstd v1.6.4

4
go.sum
View file

@ -85,8 +85,8 @@ github.com/jstemmer/go-junit-report v0.9.1/go.mod h1:Brl9GWCQeLvo8nXZwPNNblvFj/X
github.com/kisielk/gotool v1.0.0/go.mod h1:XhKaO+MFFWcvkIS/tQcRk01m1F5IRFswLeQ+oQHNcck=
github.com/klauspost/compress v1.4.0/go.mod h1:RyIbtBH6LamlWaDj8nUwkbUhJ87Yi3uG0guNDohfE1A=
github.com/klauspost/compress v1.4.1/go.mod h1:RyIbtBH6LamlWaDj8nUwkbUhJ87Yi3uG0guNDohfE1A=
github.com/klauspost/compress v1.9.7 h1:hYW1gP94JUmAhBtJ+LNz5My+gBobDxPR1iVuKug26aA=
github.com/klauspost/compress v1.9.7/go.mod h1:RyIbtBH6LamlWaDj8nUwkbUhJ87Yi3uG0guNDohfE1A=
github.com/klauspost/compress v1.9.8 h1:VMAMUUOh+gaxKTMk+zqbjsSjsIcUcL/LF4o63i82QyA=
github.com/klauspost/compress v1.9.8/go.mod h1:RyIbtBH6LamlWaDj8nUwkbUhJ87Yi3uG0guNDohfE1A=
github.com/klauspost/cpuid v0.0.0-20180405133222-e7e905edc00e/go.mod h1:Pj4uuM528wm8OyEC2QMXAi2YiTZ96dNQPGgoMS4s3ek=
github.com/klauspost/cpuid v1.2.0/go.mod h1:Pj4uuM528wm8OyEC2QMXAi2YiTZ96dNQPGgoMS4s3ek=
github.com/kr/pretty v0.1.0 h1:L/CwN0zerZDmRFUapSPitk6f+Q3+0za1rQkzVuMiMFI=

6
vendor/github.com/klauspost/compress/flate/deflate.go generated vendored
View file

@ -644,7 +644,7 @@ func (d *compressor) init(w io.Writer, level int) (err error) {
d.fill = (*compressor).fillBlock
d.step = (*compressor).store
case level == ConstantCompression:
d.w.logReusePenalty = uint(4)
d.w.logNewTablePenalty = 4
d.window = make([]byte, maxStoreBlockSize)
d.fill = (*compressor).fillBlock
d.step = (*compressor).storeHuff
@ -652,13 +652,13 @@ func (d *compressor) init(w io.Writer, level int) (err error) {
level = 5
fallthrough
case level >= 1 && level <= 6:
d.w.logReusePenalty = uint(level + 1)
d.w.logNewTablePenalty = 6
d.fast = newFastEnc(level)
d.window = make([]byte, maxStoreBlockSize)
d.fill = (*compressor).fillBlock
d.step = (*compressor).storeFast
case 7 <= level && level <= 9:
d.w.logReusePenalty = uint(level)
d.w.logNewTablePenalty = 10
d.state = &advancedState{}
d.compressionLevel = levels[level]
d.initDeflate()

52
vendor/github.com/klauspost/compress/flate/huffman_bit_writer.go generated vendored
View file

@ -93,12 +93,12 @@ type huffmanBitWriter struct {
err error
lastHeader int
// Set between 0 (reused block can be up to 2x the size)
logReusePenalty uint
lastHuffMan bool
bytes [256]byte
literalFreq [lengthCodesStart + 32]uint16
offsetFreq [32]uint16
codegenFreq [codegenCodeCount]uint16
logNewTablePenalty uint
lastHuffMan bool
bytes [256]byte
literalFreq [lengthCodesStart + 32]uint16
offsetFreq [32]uint16
codegenFreq [codegenCodeCount]uint16
// codegen must have an extra space for the final symbol.
codegen [literalCount + offsetCodeCount + 1]uint8
@ -119,7 +119,7 @@ type huffmanBitWriter struct {
// If lastHuffMan is set, a table for outputting literals has been generated and offsets are invalid.
//
// An incoming block estimates the output size of a new table using a 'fresh' by calculating the
// optimal size and adding a penalty in 'logReusePenalty'.
// optimal size and adding a penalty in 'logNewTablePenalty'.
// A Huffman table is not optimal, which is why we add a penalty, and generating a new table
// is slower both for compression and decompression.
@ -349,6 +349,13 @@ func (w *huffmanBitWriter) headerSize() (size, numCodegens int) {
int(w.codegenFreq[18])*7, numCodegens
}
// dynamicSize returns the size of dynamically encoded data in bits.
func (w *huffmanBitWriter) dynamicReuseSize(litEnc, offEnc *huffmanEncoder) (size int) {
size = litEnc.bitLength(w.literalFreq[:]) +
offEnc.bitLength(w.offsetFreq[:])
return size
}
// dynamicSize returns the size of dynamically encoded data in bits.
func (w *huffmanBitWriter) dynamicSize(litEnc, offEnc *huffmanEncoder, extraBits int) (size, numCodegens int) {
header, numCodegens := w.headerSize()
@ -451,12 +458,12 @@ func (w *huffmanBitWriter) writeDynamicHeader(numLiterals int, numOffsets int, n
i := 0
for {
var codeWord int = int(w.codegen[i])
var codeWord = uint32(w.codegen[i])
i++
if codeWord == badCode {
break
}
w.writeCode(w.codegenEncoding.codes[uint32(codeWord)])
w.writeCode(w.codegenEncoding.codes[codeWord])
switch codeWord {
case 16:
@ -602,14 +609,14 @@ func (w *huffmanBitWriter) writeBlockDynamic(tokens *tokens, eof bool, input []b
var size int
// Check if we should reuse.
if w.lastHeader > 0 {
// Estimate size for using a new table
// Estimate size for using a new table.
// Use the previous header size as the best estimate.
newSize := w.lastHeader + tokens.EstimatedBits()
newSize += newSize >> w.logNewTablePenalty
// The estimated size is calculated as an optimal table.
// We add a penalty to make it more realistic and re-use a bit more.
newSize += newSize >> (w.logReusePenalty & 31)
extra := w.extraBitSize()
reuseSize, _ := w.dynamicSize(w.literalEncoding, w.offsetEncoding, extra)
reuseSize := w.dynamicReuseSize(w.literalEncoding, w.offsetEncoding) + w.extraBitSize()
// Check if a new table is better.
if newSize < reuseSize {
@ -801,21 +808,30 @@ func (w *huffmanBitWriter) writeBlockHuff(eof bool, input []byte, sync bool) {
}
// Add everything as literals
estBits := histogramSize(input, w.literalFreq[:], !eof && !sync) + 15
// We have to estimate the header size.
// Assume header is around 70 bytes:
// https://stackoverflow.com/a/25454430
const guessHeaderSizeBits = 70 * 8
estBits, estExtra := histogramSize(input, w.literalFreq[:], !eof && !sync)
estBits += w.lastHeader + 15
if w.lastHeader == 0 {
estBits += guessHeaderSizeBits
}
estBits += estBits >> w.logNewTablePenalty
// Store bytes, if we don't get a reasonable improvement.
ssize, storable := w.storedSize(input)
if storable && ssize < (estBits+estBits>>4) {
if storable && ssize < estBits {
w.writeStoredHeader(len(input), eof)
w.writeBytes(input)
return
}
if w.lastHeader > 0 {
size, _ := w.dynamicSize(w.literalEncoding, huffOffset, w.lastHeader)
estBits += estBits >> (w.logReusePenalty)
reuseSize := w.literalEncoding.bitLength(w.literalFreq[:256])
estBits += estExtra
if estBits < size {
if estBits < reuseSize {
// We owe an EOB
w.writeCode(w.literalEncoding.codes[endBlockMarker])
w.lastHeader = 0

76
vendor/github.com/klauspost/compress/flate/huffman_code.go generated vendored
View file

@ -7,7 +7,6 @@ package flate
import (
"math"
"math/bits"
"sort"
)
const (
@ -25,8 +24,6 @@ type huffmanEncoder struct {
codes []hcode
freqcache []literalNode
bitCount [17]int32
lns byLiteral // stored to avoid repeated allocation in generate
lfs byFreq // stored to avoid repeated allocation in generate
}
type literalNode struct {
@ -270,7 +267,7 @@ func (h *huffmanEncoder) assignEncodingAndSize(bitCount []int32, list []literalN
// assigned in literal order (not frequency order).
chunk := list[len(list)-int(bits):]
h.lns.sort(chunk)
sortByLiteral(chunk)
for _, node := range chunk {
h.codes[node.literal] = hcode{code: reverseBits(code, uint8(n)), len: uint16(n)}
code++
@ -315,7 +312,7 @@ func (h *huffmanEncoder) generate(freq []uint16, maxBits int32) {
}
return
}
h.lfs.sort(list)
sortByFreq(list)
// Get the number of literals for each bit count
bitCount := h.bitCounts(list, maxBits)
@ -323,59 +320,44 @@ func (h *huffmanEncoder) generate(freq []uint16, maxBits int32) {
h.assignEncodingAndSize(bitCount, list)
}
type byLiteral []literalNode
func (s *byLiteral) sort(a []literalNode) {
*s = byLiteral(a)
sort.Sort(s)
}
func (s byLiteral) Len() int { return len(s) }
func (s byLiteral) Less(i, j int) bool {
return s[i].literal < s[j].literal
}
func (s byLiteral) Swap(i, j int) { s[i], s[j] = s[j], s[i] }
type byFreq []literalNode
func (s *byFreq) sort(a []literalNode) {
*s = byFreq(a)
sort.Sort(s)
}
func (s byFreq) Len() int { return len(s) }
func (s byFreq) Less(i, j int) bool {
if s[i].freq == s[j].freq {
return s[i].literal < s[j].literal
func atLeastOne(v float32) float32 {
if v < 1 {
return 1
}
return s[i].freq < s[j].freq
return v
}
func (s byFreq) Swap(i, j int) { s[i], s[j] = s[j], s[i] }
// histogramSize accumulates a histogram of b in h.
// An estimated size in bits is returned.
// Unassigned values are assigned '1' in the histogram.
// len(h) must be >= 256, and h's elements must be all zeroes.
func histogramSize(b []byte, h []uint16, fill bool) int {
func histogramSize(b []byte, h []uint16, fill bool) (int, int) {
h = h[:256]
for _, t := range b {
h[t]++
}
invTotal := 1.0 / float64(len(b))
shannon := 0.0
single := math.Ceil(-math.Log2(invTotal))
for i, v := range h[:] {
if v > 0 {
n := float64(v)
shannon += math.Ceil(-math.Log2(n*invTotal) * n)
} else if fill {
shannon += single
h[i] = 1
invTotal := 1.0 / float32(len(b))
shannon := float32(0.0)
var extra float32
if fill {
oneBits := atLeastOne(-mFastLog2(invTotal))
for i, v := range h[:] {
if v > 0 {
n := float32(v)
shannon += atLeastOne(-mFastLog2(n*invTotal)) * n
} else {
h[i] = 1
extra += oneBits
}
}
} else {
for _, v := range h[:] {
if v > 0 {
n := float32(v)
shannon += atLeastOne(-mFastLog2(n*invTotal)) * n
}
}
}
return int(shannon + 0.99)
return int(shannon + 0.99), int(extra + 0.99)
}

178
vendor/github.com/klauspost/compress/flate/huffman_sortByFreq.go generated vendored Normal file
View file

@ -0,0 +1,178 @@
// Copyright 2009 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package flate
// Sort sorts data.
// It makes one call to data.Len to determine n, and O(n*log(n)) calls to
// data.Less and data.Swap. The sort is not guaranteed to be stable.
func sortByFreq(data []literalNode) {
n := len(data)
quickSortByFreq(data, 0, n, maxDepth(n))
}
func quickSortByFreq(data []literalNode, a, b, maxDepth int) {
for b-a > 12 { // Use ShellSort for slices <= 12 elements
if maxDepth == 0 {
heapSort(data, a, b)
return
}
maxDepth--
mlo, mhi := doPivotByFreq(data, a, b)
// Avoiding recursion on the larger subproblem guarantees
// a stack depth of at most lg(b-a).
if mlo-a < b-mhi {
quickSortByFreq(data, a, mlo, maxDepth)
a = mhi // i.e., quickSortByFreq(data, mhi, b)
} else {
quickSortByFreq(data, mhi, b, maxDepth)
b = mlo // i.e., quickSortByFreq(data, a, mlo)
}
}
if b-a > 1 {
// Do ShellSort pass with gap 6
// It could be written in this simplified form cause b-a <= 12
for i := a + 6; i < b; i++ {
if data[i].freq == data[i-6].freq && data[i].literal < data[i-6].literal || data[i].freq < data[i-6].freq {
data[i], data[i-6] = data[i-6], data[i]
}
}
insertionSortByFreq(data, a, b)
}
}
// siftDownByFreq implements the heap property on data[lo, hi).
// first is an offset into the array where the root of the heap lies.
func siftDownByFreq(data []literalNode, lo, hi, first int) {
root := lo
for {
child := 2*root + 1
if child >= hi {
break
}
if child+1 < hi && (data[first+child].freq == data[first+child+1].freq && data[first+child].literal < data[first+child+1].literal || data[first+child].freq < data[first+child+1].freq) {
child++
}
if data[first+root].freq == data[first+child].freq && data[first+root].literal > data[first+child].literal || data[first+root].freq > data[first+child].freq {
return
}
data[first+root], data[first+child] = data[first+child], data[first+root]
root = child
}
}
func doPivotByFreq(data []literalNode, lo, hi int) (midlo, midhi int) {
m := int(uint(lo+hi) >> 1) // Written like this to avoid integer overflow.
if hi-lo > 40 {
// Tukey's ``Ninther,'' median of three medians of three.
s := (hi - lo) / 8
medianOfThreeSortByFreq(data, lo, lo+s, lo+2*s)
medianOfThreeSortByFreq(data, m, m-s, m+s)
medianOfThreeSortByFreq(data, hi-1, hi-1-s, hi-1-2*s)
}
medianOfThreeSortByFreq(data, lo, m, hi-1)
// Invariants are:
// data[lo] = pivot (set up by ChoosePivot)
// data[lo < i < a] < pivot
// data[a <= i < b] <= pivot
// data[b <= i < c] unexamined
// data[c <= i < hi-1] > pivot
// data[hi-1] >= pivot
pivot := lo
a, c := lo+1, hi-1
for ; a < c && (data[a].freq == data[pivot].freq && data[a].literal < data[pivot].literal || data[a].freq < data[pivot].freq); a++ {
}
b := a
for {
for ; b < c && (data[pivot].freq == data[b].freq && data[pivot].literal > data[b].literal || data[pivot].freq > data[b].freq); b++ { // data[b] <= pivot
}
for ; b < c && (data[pivot].freq == data[c-1].freq && data[pivot].literal < data[c-1].literal || data[pivot].freq < data[c-1].freq); c-- { // data[c-1] > pivot
}
if b >= c {
break
}
// data[b] > pivot; data[c-1] <= pivot
data[b], data[c-1] = data[c-1], data[b]
b++
c--
}
// If hi-c<3 then there are duplicates (by property of median of nine).
// Let's be a bit more conservative, and set border to 5.
protect := hi-c < 5
if !protect && hi-c < (hi-lo)/4 {
// Lets test some points for equality to pivot
dups := 0
if data[pivot].freq == data[hi-1].freq && data[pivot].literal > data[hi-1].literal || data[pivot].freq > data[hi-1].freq { // data[hi-1] = pivot
data[c], data[hi-1] = data[hi-1], data[c]
c++
dups++
}
if data[b-1].freq == data[pivot].freq && data[b-1].literal > data[pivot].literal || data[b-1].freq > data[pivot].freq { // data[b-1] = pivot
b--
dups++
}
// m-lo = (hi-lo)/2 > 6
// b-lo > (hi-lo)*3/4-1 > 8
// ==> m < b ==> data[m] <= pivot
if data[m].freq == data[pivot].freq && data[m].literal > data[pivot].literal || data[m].freq > data[pivot].freq { // data[m] = pivot
data[m], data[b-1] = data[b-1], data[m]
b--
dups++
}
// if at least 2 points are equal to pivot, assume skewed distribution
protect = dups > 1
}
if protect {
// Protect against a lot of duplicates
// Add invariant:
// data[a <= i < b] unexamined
// data[b <= i < c] = pivot
for {
for ; a < b && (data[b-1].freq == data[pivot].freq && data[b-1].literal > data[pivot].literal || data[b-1].freq > data[pivot].freq); b-- { // data[b] == pivot
}
for ; a < b && (data[a].freq == data[pivot].freq && data[a].literal < data[pivot].literal || data[a].freq < data[pivot].freq); a++ { // data[a] < pivot
}
if a >= b {
break
}
// data[a] == pivot; data[b-1] < pivot
data[a], data[b-1] = data[b-1], data[a]
a++
b--
}
}
// Swap pivot into middle
data[pivot], data[b-1] = data[b-1], data[pivot]
return b - 1, c
}
// Insertion sort
func insertionSortByFreq(data []literalNode, a, b int) {
for i := a + 1; i < b; i++ {
for j := i; j > a && (data[j].freq == data[j-1].freq && data[j].literal < data[j-1].literal || data[j].freq < data[j-1].freq); j-- {
data[j], data[j-1] = data[j-1], data[j]
}
}
}
// quickSortByFreq, loosely following Bentley and McIlroy,
// ``Engineering a Sort Function,'' SP&E November 1993.
// medianOfThreeSortByFreq moves the median of the three values data[m0], data[m1], data[m2] into data[m1].
func medianOfThreeSortByFreq(data []literalNode, m1, m0, m2 int) {
// sort 3 elements
if data[m1].freq == data[m0].freq && data[m1].literal < data[m0].literal || data[m1].freq < data[m0].freq {
data[m1], data[m0] = data[m0], data[m1]
}
// data[m0] <= data[m1]
if data[m2].freq == data[m1].freq && data[m2].literal < data[m1].literal || data[m2].freq < data[m1].freq {
data[m2], data[m1] = data[m1], data[m2]
// data[m0] <= data[m2] && data[m1] < data[m2]
if data[m1].freq == data[m0].freq && data[m1].literal < data[m0].literal || data[m1].freq < data[m0].freq {
data[m1], data[m0] = data[m0], data[m1]
}
}
// now data[m0] <= data[m1] <= data[m2]
}

201
vendor/github.com/klauspost/compress/flate/huffman_sortByLiteral.go generated vendored Normal file
View file

@ -0,0 +1,201 @@
// Copyright 2009 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package flate
// Sort sorts data.
// It makes one call to data.Len to determine n, and O(n*log(n)) calls to
// data.Less and data.Swap. The sort is not guaranteed to be stable.
func sortByLiteral(data []literalNode) {
n := len(data)
quickSort(data, 0, n, maxDepth(n))
}
func quickSort(data []literalNode, a, b, maxDepth int) {
for b-a > 12 { // Use ShellSort for slices <= 12 elements
if maxDepth == 0 {
heapSort(data, a, b)
return
}
maxDepth--
mlo, mhi := doPivot(data, a, b)
// Avoiding recursion on the larger subproblem guarantees
// a stack depth of at most lg(b-a).
if mlo-a < b-mhi {
quickSort(data, a, mlo, maxDepth)
a = mhi // i.e., quickSort(data, mhi, b)
} else {
quickSort(data, mhi, b, maxDepth)
b = mlo // i.e., quickSort(data, a, mlo)
}
}
if b-a > 1 {
// Do ShellSort pass with gap 6
// It could be written in this simplified form cause b-a <= 12
for i := a + 6; i < b; i++ {
if data[i].literal < data[i-6].literal {
data[i], data[i-6] = data[i-6], data[i]
}
}
insertionSort(data, a, b)
}
}
func heapSort(data []literalNode, a, b int) {
first := a
lo := 0
hi := b - a
// Build heap with greatest element at top.
for i := (hi - 1) / 2; i >= 0; i-- {
siftDown(data, i, hi, first)
}
// Pop elements, largest first, into end of data.
for i := hi - 1; i >= 0; i-- {
data[first], data[first+i] = data[first+i], data[first]
siftDown(data, lo, i, first)
}
}
// siftDown implements the heap property on data[lo, hi).
// first is an offset into the array where the root of the heap lies.
func siftDown(data []literalNode, lo, hi, first int) {
root := lo
for {
child := 2*root + 1
if child >= hi {
break
}
if child+1 < hi && data[first+child].literal < data[first+child+1].literal {
child++
}
if data[first+root].literal > data[first+child].literal {
return
}
data[first+root], data[first+child] = data[first+child], data[first+root]
root = child
}
}
func doPivot(data []literalNode, lo, hi int) (midlo, midhi int) {
m := int(uint(lo+hi) >> 1) // Written like this to avoid integer overflow.
if hi-lo > 40 {
// Tukey's ``Ninther,'' median of three medians of three.
s := (hi - lo) / 8
medianOfThree(data, lo, lo+s, lo+2*s)
medianOfThree(data, m, m-s, m+s)
medianOfThree(data, hi-1, hi-1-s, hi-1-2*s)
}
medianOfThree(data, lo, m, hi-1)
// Invariants are:
// data[lo] = pivot (set up by ChoosePivot)
// data[lo < i < a] < pivot
// data[a <= i < b] <= pivot
// data[b <= i < c] unexamined
// data[c <= i < hi-1] > pivot
// data[hi-1] >= pivot
pivot := lo
a, c := lo+1, hi-1
for ; a < c && data[a].literal < data[pivot].literal; a++ {
}
b := a
for {
for ; b < c && data[pivot].literal > data[b].literal; b++ { // data[b] <= pivot
}
for ; b < c && data[pivot].literal < data[c-1].literal; c-- { // data[c-1] > pivot
}
if b >= c {
break
}
// data[b] > pivot; data[c-1] <= pivot
data[b], data[c-1] = data[c-1], data[b]
b++
c--
}
// If hi-c<3 then there are duplicates (by property of median of nine).
// Let's be a bit more conservative, and set border to 5.
protect := hi-c < 5
if !protect && hi-c < (hi-lo)/4 {
// Lets test some points for equality to pivot
dups := 0
if data[pivot].literal > data[hi-1].literal { // data[hi-1] = pivot
data[c], data[hi-1] = data[hi-1], data[c]
c++
dups++
}
if data[b-1].literal > data[pivot].literal { // data[b-1] = pivot
b--
dups++
}
// m-lo = (hi-lo)/2 > 6
// b-lo > (hi-lo)*3/4-1 > 8
// ==> m < b ==> data[m] <= pivot
if data[m].literal > data[pivot].literal { // data[m] = pivot
data[m], data[b-1] = data[b-1], data[m]
b--
dups++
}
// if at least 2 points are equal to pivot, assume skewed distribution
protect = dups > 1
}
if protect {
// Protect against a lot of duplicates
// Add invariant:
// data[a <= i < b] unexamined
// data[b <= i < c] = pivot
for {
for ; a < b && data[b-1].literal > data[pivot].literal; b-- { // data[b] == pivot
}
for ; a < b && data[a].literal < data[pivot].literal; a++ { // data[a] < pivot
}
if a >= b {
break
}
// data[a] == pivot; data[b-1] < pivot
data[a], data[b-1] = data[b-1], data[a]
a++
b--
}
}
// Swap pivot into middle
data[pivot], data[b-1] = data[b-1], data[pivot]
return b - 1, c
}
// Insertion sort
func insertionSort(data []literalNode, a, b int) {
for i := a + 1; i < b; i++ {
for j := i; j > a && data[j].literal < data[j-1].literal; j-- {
data[j], data[j-1] = data[j-1], data[j]
}
}
}
// maxDepth returns a threshold at which quicksort should switch
// to heapsort. It returns 2*ceil(lg(n+1)).
func maxDepth(n int) int {
var depth int
for i := n; i > 0; i >>= 1 {
depth++
}
return depth * 2
}
// medianOfThree moves the median of the three values data[m0], data[m1], data[m2] into data[m1].
func medianOfThree(data []literalNode, m1, m0, m2 int) {
// sort 3 elements
if data[m1].literal < data[m0].literal {
data[m1], data[m0] = data[m0], data[m1]
}
// data[m0] <= data[m1]
if data[m2].literal < data[m1].literal {
data[m2], data[m1] = data[m1], data[m2]
// data[m0] <= data[m2] && data[m1] < data[m2]
if data[m1].literal < data[m0].literal {
data[m1], data[m0] = data[m0], data[m1]
}
}
// now data[m0] <= data[m1] <= data[m2]
}

42
vendor/github.com/klauspost/compress/flate/token.go generated vendored
View file

@ -184,9 +184,7 @@ func (t *tokens) indexTokens(in []token) {
t.Reset()
for _, tok := range in {
if tok < matchType {
t.tokens[t.n] = tok
t.litHist[tok]++
t.n++
t.AddLiteral(tok.literal())
continue
}
t.AddMatch(uint32(tok.length()), tok.offset())
@ -211,43 +209,53 @@ func (t *tokens) AddLiteral(lit byte) {
t.nLits++
}
// from https://stackoverflow.com/a/28730362
func mFastLog2(val float32) float32 {
ux := int32(math.Float32bits(val))
log2 := (float32)(((ux >> 23) & 255) - 128)
ux &= -0x7f800001
ux += 127 << 23
uval := math.Float32frombits(uint32(ux))
log2 += ((-0.34484843)*uval+2.02466578)*uval - 0.67487759
return log2
}
// EstimatedBits will return an minimum size estimated by an *optimal*
// compression of the block.
// The size of the block
func (t *tokens) EstimatedBits() int {
shannon := float64(0)
shannon := float32(0)
bits := int(0)
nMatches := 0
if t.nLits > 0 {
invTotal := 1.0 / float64(t.nLits)
invTotal := 1.0 / float32(t.nLits)
for _, v := range t.litHist[:] {
if v > 0 {
n := float64(v)
shannon += math.Ceil(-math.Log2(n*invTotal) * n)
n := float32(v)
shannon += -mFastLog2(n*invTotal) * n
}
}
// Just add 15 for EOB
shannon += 15
for _, v := range t.extraHist[1 : literalCount-256] {
for i, v := range t.extraHist[1 : literalCount-256] {
if v > 0 {
n := float64(v)
shannon += math.Ceil(-math.Log2(n*invTotal) * n)
bits += int(lengthExtraBits[v&31]) * int(v)
n := float32(v)
shannon += -mFastLog2(n*invTotal) * n
bits += int(lengthExtraBits[i&31]) * int(v)
nMatches += int(v)
}
}
}
if nMatches > 0 {
invTotal := 1.0 / float64(nMatches)
for _, v := range t.offHist[:offsetCodeCount] {
invTotal := 1.0 / float32(nMatches)
for i, v := range t.offHist[:offsetCodeCount] {
if v > 0 {
n := float64(v)
shannon += math.Ceil(-math.Log2(n*invTotal) * n)
bits += int(offsetExtraBits[v&31]) * int(n)
n := float32(v)
shannon += -mFastLog2(n*invTotal) * n
bits += int(offsetExtraBits[i&31]) * int(v)
}
}
}
return int(shannon) + bits
}

2
vendor/modules.txt vendored
View file

@ -83,7 +83,7 @@ github.com/jmespath/go-jmespath
github.com/jstemmer/go-junit-report
github.com/jstemmer/go-junit-report/formatter
github.com/jstemmer/go-junit-report/parser
# github.com/klauspost/compress v1.9.7
# github.com/klauspost/compress v1.9.8
github.com/klauspost/compress/flate
github.com/klauspost/compress/fse
github.com/klauspost/compress/gzip