brotli/research/sieve.cc
Eugene Kliuchnikov 35e69fc7cf
New feature: "Large Window Brotli" (#640)
* New feature: "Large Window Brotli"

By setting special encoder/decoder flag it is now possible to extend
LZ-window up to 30 bits; though produced stream will not be RFC7932
compliant.

Added new dictionary generator - "DSH". It combines speed of "Sieve"
and quality of "DM". Plus utilities to prepare train corpora
(remove unique strings).

Improved compression ratio: now two sub-blocks could be stitched:
the last copy command could be extended to span the next sub-block.

Fixed compression ineffectiveness caused by floating numbers rounding and
wrong cost heuristic.

Other C changes:
 - combined / moved `context.h` to `common`
 - moved transforms to `common`
 - unified some aspects of code formatting
 - added an abstraction for encoder (static) dictionary
 - moved default allocator/deallocator functions to `common`

brotli CLI:
 - window size is auto-adjusted if not specified explicitly

Java:
 - added "eager" decoding both to JNI wrapper and pure decoder
 - huge speed-up of `DictionaryData` initialization

* Add dictionaryless compressed dictionary

* Fix `sources.lst`

* Fix `sources.lst` and add a note that `libtool` is also required.

* Update setup.py

* Fix `EagerStreamTest`

* Fix BUILD file

* Add missing `libdivsufsort` dependency

* Fix "unused parameter" warning.
2018-02-26 09:04:36 -05:00

260 lines
7.3 KiB
C++
Executable File

#include "./sieve.h"
/* Pointer to position in (combined corpus) text. */
typedef uint32_t TextIdx;
/* Index of sample / generation. */
typedef uint16_t SampleIdx;
typedef struct Slot {
TextIdx next;
TextIdx offset;
SampleIdx presence;
SampleIdx mark;
} Slot;
static const TextIdx kNowhere = static_cast<TextIdx>(-1);
static TextIdx dryRun(TextIdx sliceLen, Slot* map, TextIdx* shortcut,
TextIdx end, TextIdx middle, SampleIdx minPresence, SampleIdx iteration) {
TextIdx from = kNowhere;
TextIdx to = kNowhere;
TextIdx result = 0;
SampleIdx targetPresence = minPresence;
for (TextIdx i = 0; i < end; ++i) {
if (i == middle) {
targetPresence++;
}
Slot& item = map[shortcut[i]];
if (item.mark != iteration) {
item.mark = iteration;
if (item.presence >= targetPresence) {
if ((to == kNowhere) || (to < i)) {
if (from != kNowhere) {
result += to - from;
}
from = i;
}
to = i + sliceLen;
}
}
}
if (from != kNowhere) {
result += to - from;
}
return result;
}
static std::string createDictionary(const uint8_t* data, TextIdx sliceLen,
Slot* map, TextIdx* shortcut, TextIdx end, TextIdx middle,
SampleIdx minPresence, SampleIdx iteration) {
std::string output;
TextIdx from = kNowhere;
TextIdx to = kNowhere;
SampleIdx targetPresence = minPresence;
for (TextIdx i = 0; i < end; ++i) {
if (i == middle) {
targetPresence++;
}
Slot& item = map[shortcut[i]];
if (item.mark != iteration) {
item.mark = iteration;
if (item.presence >= targetPresence) {
if ((to == kNowhere) || (to < i)) {
if (from != kNowhere) {
output.insert(output.end(), &data[from], &data[to]);
}
from = i;
}
to = i + sliceLen;
}
}
}
if (from != kNowhere) {
output.insert(output.end(), &data[from], &data[to]);
}
return output;
}
std::string sieve_generate(size_t dictionary_size_limit, size_t slice_len,
const std::vector<size_t>& sample_sizes, const uint8_t* sample_data) {
/* Parameters aliasing */
TextIdx targetSize = static_cast<TextIdx>(dictionary_size_limit);
if (targetSize != dictionary_size_limit) {
fprintf(stderr, "dictionary_size_limit is too large\n");
return "";
}
TextIdx sliceLen = static_cast<TextIdx>(slice_len);
if (sliceLen != slice_len) {
fprintf(stderr, "slice_len is too large\n");
return "";
}
if (sliceLen < 1) {
fprintf(stderr, "slice_len is too small\n");
return "";
}
SampleIdx numSamples = static_cast<SampleIdx>(sample_sizes.size());
if ((numSamples != sample_sizes.size()) || (numSamples * 2 < numSamples)) {
fprintf(stderr, "too many samples\n");
return "";
}
const uint8_t* data = sample_data;
TextIdx total = 0;
std::vector<TextIdx> offsets;
for (SampleIdx i = 0; i < numSamples; ++i) {
TextIdx delta = static_cast<TextIdx>(sample_sizes[i]);
if (delta != sample_sizes[i]) {
fprintf(stderr, "sample is too large\n");
return "";
}
if (delta == 0) {
fprintf(stderr, "empty samples are prohibited\n");
return "";
}
if (total + delta <= total) {
fprintf(stderr, "corpus is too large\n");
return "";
}
total += delta;
offsets.push_back(total);
}
if (total * 2 < total) {
fprintf(stderr, "corpus is too large\n");
return "";
}
if (total < sliceLen) {
fprintf(stderr, "slice_len is larger than corpus size\n");
return "";
}
/*****************************************************************************
* Build coverage map.
****************************************************************************/
std::vector<Slot> map;
std::vector<TextIdx> shortcut;
map.push_back({0, 0, 0, 0});
TextIdx end = total - sliceLen;
TextIdx hashLen = 11;
while (hashLen < 29 && ((1u << hashLen) < end)) {
hashLen += 3;
}
hashLen -= 3;
TextIdx hashMask = (1u << hashLen) - 1u;
std::vector<TextIdx> hashHead(1 << hashLen);
TextIdx hashSlot = 1;
SampleIdx piece = 0;
TextIdx hash = 0;
TextIdx lShift = 3;
TextIdx rShift = hashLen - lShift;
for (TextIdx i = 0; i < sliceLen - 1; ++i) {
TextIdx v = data[i];
hash = (((hash << lShift) | (hash >> rShift)) & hashMask) ^ v;
}
TextIdx lShiftX = (lShift * (sliceLen - 1)) % hashLen;
TextIdx rShiftX = hashLen - lShiftX;
for (TextIdx i = 0; i < end; ++i) {
TextIdx v = data[i + sliceLen - 1];
hash = (((hash << lShift) | (hash >> rShift)) & hashMask) ^ v;
if (offsets[piece] == i) {
piece++;
}
TextIdx slot = hashHead[hash];
while (slot != 0) {
Slot& item = map[slot];
TextIdx start = item.offset;
bool miss = false;
for (TextIdx j = 0; j < sliceLen; ++j) {
if (data[i + j] != data[start + j]) {
miss = true;
break;
}
}
if (!miss) {
if (item.mark != piece) {
item.mark = piece;
item.presence++;
}
shortcut.push_back(slot);
break;
}
slot = item.next;
}
if (slot == 0) {
map.push_back({hashHead[hash], i, 1, piece});
hashHead[hash] = hashSlot;
shortcut.push_back(hashSlot);
hashSlot++;
}
v = data[i];
hash ^= ((v << lShiftX) | (v >> rShiftX)) & hashMask;
}
/*****************************************************************************
* Build dictionary of specified size.
****************************************************************************/
SampleIdx a = 1;
TextIdx size = dryRun(
sliceLen, map.data(), shortcut.data(), end, end, a, ++piece);
/* Maximal output is smaller than target. */
if (size <= targetSize) {
return createDictionary(
data, sliceLen, map.data(), shortcut.data(), end, end, a, ++piece);
}
SampleIdx b = numSamples;
size = dryRun(sliceLen, map.data(), shortcut.data(), end, end, b, ++piece);
if (size == targetSize) {
return createDictionary(
data, sliceLen, map.data(), shortcut.data(), end, end, b, ++piece);
}
/* Run binary search. */
if (size < targetSize) {
/* size(a) > targetSize > size(b) && a < m < b */
while (a + 1 < b) {
SampleIdx m = static_cast<SampleIdx>((a + b) / 2);
size = dryRun(
sliceLen, map.data(), shortcut.data(), end, end, m, ++piece);
if (size < targetSize) {
b = m;
} else if (size > targetSize) {
a = m;
} else {
return createDictionary(
data, sliceLen, map.data(), shortcut.data(), end, end, b, ++piece);
}
}
} else {
a = b;
}
/* size(minPresence) > targetSize > size(minPresence + 1) */
SampleIdx minPresence = a;
TextIdx c = 0;
TextIdx d = end;
/* size(a) < targetSize < size(b) && a < m < b */
while (c + 1 < d) {
TextIdx m = (c + d) / 2;
size = dryRun(
sliceLen, map.data(), shortcut.data(), end, m, minPresence, ++piece);
if (size < targetSize) {
c = m;
} else if (size > targetSize) {
d = m;
} else {
return createDictionary(data, sliceLen, map.data(), shortcut.data(), end,
m, minPresence, ++piece);
}
}
bool unrestricted = false;
if (minPresence <= 2 && !unrestricted) {
minPresence = 2;
c = end;
}
return createDictionary(data, sliceLen, map.data(), shortcut.data(), end, c,
minPresence, ++piece);
}