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727 lines
21 KiB
C++
727 lines
21 KiB
C++
#include "durchschlag.h"
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#include <algorithm>
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#include <exception> /* terminate */
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#include "third_party/libdivsufsort/include/divsufsort.h"
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/* Pointer to position in text. */
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typedef DurchschlagTextIdx TextIdx;
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/* (Sum of) value(s) of slice(s). */
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typedef uint32_t Score;
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typedef struct HashSlot {
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TextIdx next;
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TextIdx offset;
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} HashSlot;
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typedef struct MetaSlot {
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TextIdx mark;
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Score score;
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} MetaSlot;
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typedef struct Range {
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TextIdx start;
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TextIdx end;
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} Range;
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typedef struct Candidate {
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Score score;
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TextIdx position;
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} Candidate;
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struct greaterScore {
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bool operator()(const Candidate& a, const Candidate& b) const {
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return (a.score > b.score) ||
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((a.score == b.score) && (a.position < b.position));
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}
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};
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struct lessScore {
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bool operator()(const Candidate& a, const Candidate& b) const {
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return (a.score < b.score) ||
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((a.score == b.score) && (a.position > b.position));
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}
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};
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#define CANDIDATE_BUNDLE_SIZE (1 << 18)
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static void fatal(const char* error) {
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fprintf(stderr, "%s\n", error);
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std::terminate();
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}
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static TextIdx calculateDictionarySize(const std::vector<Range>& ranges) {
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TextIdx result = 0;
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for (size_t i = 0; i < ranges.size(); ++i) {
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const Range& r = ranges[i];
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result += r.end - r.start;
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}
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return result;
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}
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static std::string createDictionary(
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const uint8_t* data, const std::vector<Range>& ranges, size_t limit) {
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std::string output;
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output.reserve(calculateDictionarySize(ranges));
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for (size_t i = 0; i < ranges.size(); ++i) {
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const Range& r = ranges[i];
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output.insert(output.end(), &data[r.start], &data[r.end]);
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}
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if (output.size() > limit) {
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output.resize(limit);
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}
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return output;
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}
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/* precondition: span > 0
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precondition: end + span == len(shortcut) */
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static Score buildCandidatesList(std::vector<Candidate>* candidates,
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std::vector<MetaSlot>* map, TextIdx span, const TextIdx* shortcut,
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TextIdx end) {
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candidates->resize(0);
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size_t n = map->size();
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MetaSlot* slots = map->data();
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for (size_t j = 0; j < n; ++j) {
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slots[j].mark = 0;
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}
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Score score = 0;
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/* Consider the whole span, except one last item. The following loop will
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add the last item to the end of the "chain", evaluate it, and cut one
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"link" form the beginning. */
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for (size_t j = 0; j < span - 1; ++j) {
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MetaSlot& item = slots[shortcut[j]];
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if (item.mark == 0) {
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score += item.score;
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}
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item.mark++;
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}
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TextIdx i = 0;
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TextIdx limit = std::min<TextIdx>(end, CANDIDATE_BUNDLE_SIZE);
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Score maxScore = 0;
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for (; i < limit; ++i) {
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TextIdx slice = shortcut[i + span - 1];
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MetaSlot& pick = slots[slice];
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if (pick.mark == 0) {
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score += pick.score;
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}
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pick.mark++;
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if (score > maxScore) {
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maxScore = score;
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}
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candidates->push_back({score, i});
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MetaSlot& drop = slots[shortcut[i]];
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drop.mark--;
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if (drop.mark == 0) {
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score -= drop.score;
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}
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}
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std::make_heap(candidates->begin(), candidates->end(), greaterScore());
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Score minScore = candidates->at(0).score;
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for (; i < end; ++i) {
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TextIdx slice = shortcut[i + span - 1];
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MetaSlot& pick = slots[slice];
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if (pick.mark == 0) {
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score += pick.score;
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}
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pick.mark++;
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if (score > maxScore) {
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maxScore = score;
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}
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if (score >= minScore) {
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candidates->push_back({score, i});
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std::push_heap(candidates->begin(), candidates->end(), greaterScore());
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if (candidates->size() > CANDIDATE_BUNDLE_SIZE && maxScore != minScore) {
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while (candidates->at(0).score == minScore) {
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std::pop_heap(candidates->begin(), candidates->end(), greaterScore());
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candidates->pop_back();
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}
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minScore = candidates->at(0).score;
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}
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}
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MetaSlot& drop = slots[shortcut[i]];
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drop.mark--;
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if (drop.mark == 0) {
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score -= drop.score;
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}
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}
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for (size_t j = 0; j < n; ++j) {
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slots[j].mark = 0;
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}
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std::make_heap(candidates->begin(), candidates->end(), lessScore());
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return minScore;
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}
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/* precondition: span > 0
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precondition: end + span == len(shortcut) */
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static Score rebuildCandidatesList(std::vector<TextIdx>* candidates,
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std::vector<MetaSlot>* map, TextIdx span, const TextIdx* shortcut,
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TextIdx end, TextIdx* next) {
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size_t n = candidates->size();
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TextIdx* data = candidates->data();
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for (size_t i = 0; i < n; ++i) {
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data[i] = 0;
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}
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n = map->size();
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MetaSlot* slots = map->data();
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for (size_t i = 0; i < n; ++i) {
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slots[i].mark = 0;
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}
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Score score = 0;
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/* Consider the whole span, except one last item. The following loop will
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add the last item to the end of the "chain", evaluate it, and cut one
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"link" form the beginning. */
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for (TextIdx i = 0; i < span - 1; ++i) {
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MetaSlot& item = slots[shortcut[i]];
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if (item.mark == 0) {
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score += item.score;
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}
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item.mark++;
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}
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Score maxScore = 0;
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for (TextIdx i = 0; i < end; ++i) {
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MetaSlot& pick = slots[shortcut[i + span - 1]];
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if (pick.mark == 0) {
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score += pick.score;
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}
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pick.mark++;
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if (candidates->size() <= score) {
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candidates->resize(score + 1);
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}
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if (score > maxScore) {
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maxScore = score;
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}
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next[i] = candidates->at(score);
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candidates->at(score) = i;
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MetaSlot& drop = slots[shortcut[i]];
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drop.mark--;
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if (drop.mark == 0) {
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score -= drop.score;
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}
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}
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for (size_t i = 0; i < n; ++i) {
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slots[i].mark = 0;
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}
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candidates->resize(maxScore + 1);
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return maxScore;
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}
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static void addRange(std::vector<Range>* ranges, TextIdx start, TextIdx end) {
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for (auto it = ranges->begin(); it != ranges->end();) {
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if (end < it->start) {
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ranges->insert(it, {start, end});
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return;
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}
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if (it->end < start) {
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it++;
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continue;
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}
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// Combine with existing.
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start = std::min(start, it->start);
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end = std::max(end, it->end);
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// Remove consumed vector and continue.
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it = ranges->erase(it);
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}
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ranges->push_back({start, end});
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}
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std::string durchschlag_generate(
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size_t dictionary_size_limit, size_t slice_len, size_t block_len,
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const std::vector<size_t>& sample_sizes, const uint8_t* sample_data) {
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DurchschlagContext ctx = durchschlag_prepare(
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slice_len, sample_sizes, sample_data);
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return durchschlag_generate(DURCHSCHLAG_COLLABORATIVE,
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dictionary_size_limit, block_len, ctx, sample_data);
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}
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DurchschlagContext durchschlag_prepare(size_t slice_len,
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const std::vector<size_t>& sample_sizes, const uint8_t* sample_data) {
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/* Parameters aliasing */
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TextIdx sliceLen = static_cast<TextIdx>(slice_len);
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if (sliceLen != slice_len) fatal("slice_len is too large");
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if (sliceLen < 1) fatal("slice_len is too small");
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const uint8_t* data = sample_data;
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TextIdx total = 0;
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std::vector<TextIdx> offsets;
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offsets.reserve(sample_sizes.size());
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for (size_t i = 0; i < sample_sizes.size(); ++i) {
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TextIdx delta = static_cast<TextIdx>(sample_sizes[i]);
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if (delta != sample_sizes[i]) fatal("sample is too large");
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if (delta == 0) fatal("0-length samples are prohibited");
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TextIdx next_total = total + delta;
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if (next_total <= total) fatal("corpus is too large");
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total = next_total;
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offsets.push_back(total);
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}
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if (total < sliceLen) fatal("slice_len is larger than corpus size");
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TextIdx end = total - static_cast<TextIdx>(sliceLen) + 1;
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TextIdx hashLen = 11;
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while (hashLen < 29 && ((1u << hashLen) < end)) {
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hashLen += 3;
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}
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hashLen -= 3;
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TextIdx hashMask = (1u << hashLen) - 1u;
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std::vector<TextIdx> hashHead(1 << hashLen);
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TextIdx hash = 0;
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TextIdx lShift = 3;
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TextIdx rShift = hashLen - lShift;
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for (TextIdx i = 0; i < sliceLen - 1; ++i) {
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TextIdx v = data[i];
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hash = (((hash << lShift) | (hash >> rShift)) & hashMask) ^ v;
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}
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TextIdx lShiftX = (lShift * (sliceLen - 1)) % hashLen;
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TextIdx rShiftX = hashLen - lShiftX;
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std::vector<HashSlot> map;
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map.push_back({0, 0});
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TextIdx hashSlot = 1;
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std::vector<TextIdx> sliceMap;
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sliceMap.reserve(end);
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for (TextIdx i = 0; i < end; ++i) {
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TextIdx v = data[i + sliceLen - 1];
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TextIdx bucket = (((hash << lShift) | (hash >> rShift)) & hashMask) ^ v;
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v = data[i];
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hash = bucket ^ (((v << lShiftX) | (v >> rShiftX)) & hashMask);
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TextIdx slot = hashHead[bucket];
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while (slot != 0) {
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HashSlot& item = map[slot];
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TextIdx start = item.offset;
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bool miss = false;
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for (TextIdx j = 0; j < sliceLen; ++j) {
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if (data[i + j] != data[start + j]) {
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miss = true;
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break;
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}
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}
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if (!miss) {
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sliceMap.push_back(slot);
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break;
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}
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slot = item.next;
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}
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if (slot == 0) {
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map.push_back({hashHead[bucket], i});
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hashHead[bucket] = hashSlot;
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sliceMap.push_back(hashSlot);
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hashSlot++;
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}
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}
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return {total, sliceLen, static_cast<TextIdx>(map.size()),
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std::move(offsets), std::move(sliceMap)};
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}
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DurchschlagContext durchschlag_prepare(size_t slice_len,
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const std::vector<size_t>& sample_sizes, const DurchschlagIndex& index) {
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/* Parameters aliasing */
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TextIdx sliceLen = static_cast<TextIdx>(slice_len);
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if (sliceLen != slice_len) fatal("slice_len is too large");
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if (sliceLen < 1) fatal("slice_len is too small");
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const TextIdx* lcp = index.lcp.data();
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const TextIdx* sa = index.sa.data();
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TextIdx total = 0;
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std::vector<TextIdx> offsets;
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offsets.reserve(sample_sizes.size());
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for (size_t i = 0; i < sample_sizes.size(); ++i) {
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TextIdx delta = static_cast<TextIdx>(sample_sizes[i]);
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if (delta != sample_sizes[i]) fatal("sample is too large");
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if (delta == 0) fatal("0-length samples are prohibited");
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TextIdx next_total = total + delta;
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if (next_total <= total) fatal("corpus is too large");
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total = next_total;
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offsets.push_back(total);
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}
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if (total < sliceLen) fatal("slice_len is larger than corpus size");
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TextIdx counter = 1;
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TextIdx end = total - sliceLen + 1;
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std::vector<TextIdx> sliceMap(total);
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TextIdx last = 0;
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TextIdx current = 1;
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while (current <= total) {
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if (lcp[current - 1] < sliceLen) {
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for (TextIdx i = last; i < current; ++i) {
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sliceMap[sa[i]] = counter;
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}
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counter++;
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last = current;
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}
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current++;
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}
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sliceMap.resize(end);
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// Reorder items for the better locality.
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std::vector<TextIdx> reorder(counter);
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counter = 1;
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for (TextIdx i = 0; i < end; ++i) {
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if (reorder[sliceMap[i]] == 0) {
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reorder[sliceMap[i]] = counter++;
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}
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}
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for (TextIdx i = 0; i < end; ++i) {
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sliceMap[i] = reorder[sliceMap[i]];
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}
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return {total, sliceLen, counter, std::move(offsets), std::move(sliceMap)};
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}
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DurchschlagIndex durchschlag_index(const std::vector<uint8_t>& data) {
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TextIdx total = static_cast<TextIdx>(data.size());
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if (total != data.size()) fatal("corpus is too large");
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saidx_t saTotal = static_cast<saidx_t>(total);
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if (saTotal < 0) fatal("corpus is too large");
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if (static_cast<TextIdx>(saTotal) != total) fatal("corpus is too large");
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std::vector<TextIdx> sa(total);
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/* Hopefully, non-negative int32_t values match TextIdx ones. */
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if (sizeof(TextIdx) != sizeof(int32_t)) fatal("type length mismatch");
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int32_t* saData = reinterpret_cast<int32_t*>(sa.data());
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divsufsort(data.data(), saData, saTotal);
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std::vector<TextIdx> isa(total);
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for (TextIdx i = 0; i < total; ++i) isa[sa[i]] = i;
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// TODO(eustas): borrowed -> unknown efficiency.
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std::vector<TextIdx> lcp(total);
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TextIdx k = 0;
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lcp[total - 1] = 0;
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for (TextIdx i = 0; i < total; ++i) {
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TextIdx current = isa[i];
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if (current == total - 1) {
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k = 0;
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continue;
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}
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TextIdx j = sa[current + 1]; // Suffix which follow i-th suffix.
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while ((i + k < total) && (j + k < total) && (data[i + k] == data[j + k])) {
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++k;
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}
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lcp[current] = k;
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if (k > 0) --k;
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}
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return {std::move(lcp), std::move(sa)};
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}
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static void ScoreSlices(const std::vector<TextIdx>& offsets,
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std::vector<MetaSlot>& map, const TextIdx* shortcut, TextIdx end) {
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TextIdx piece = 0;
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/* Fresh map contains all zeroes -> initial mark should be different. */
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TextIdx mark = 1;
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for (TextIdx i = 0; i < end; ++i) {
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if (offsets[piece] == i) {
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piece++;
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mark++;
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}
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MetaSlot& item = map[shortcut[i]];
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if (item.mark != mark) {
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item.mark = mark;
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item.score++;
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}
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}
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}
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static std::string durchschlagGenerateExclusive(
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size_t dictionary_size_limit, size_t block_len,
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const DurchschlagContext& context, const uint8_t* sample_data) {
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/* Parameters aliasing */
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TextIdx targetSize = static_cast<TextIdx>(dictionary_size_limit);
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if (targetSize != dictionary_size_limit) {
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fprintf(stderr, "dictionary_size_limit is too large\n");
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return "";
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}
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TextIdx sliceLen = context.sliceLen;
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TextIdx total = context.dataSize;
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TextIdx blockLen = static_cast<TextIdx>(block_len);
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if (blockLen != block_len) {
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fprintf(stderr, "block_len is too large\n");
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return "";
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}
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const uint8_t* data = sample_data;
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const std::vector<TextIdx>& offsets = context.offsets;
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std::vector<MetaSlot> map(context.numUniqueSlices);
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const TextIdx* shortcut = context.sliceMap.data();
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/* Initialization */
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if (blockLen < sliceLen) {
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fprintf(stderr, "sliceLen is larger than block_len\n");
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return "";
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}
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if (targetSize < blockLen || total < blockLen) {
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fprintf(stderr, "block_len is too large\n");
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return "";
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}
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TextIdx end = total - sliceLen + 1;
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ScoreSlices(offsets, map, shortcut, end);
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TextIdx span = blockLen - sliceLen + 1;
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end = static_cast<TextIdx>(context.sliceMap.size()) - span;
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std::vector<TextIdx> candidates;
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std::vector<TextIdx> next(end);
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Score maxScore = rebuildCandidatesList(
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&candidates, &map, span, shortcut, end, next.data());
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/* Block selection */
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const size_t triesLimit = (600 * 1000000) / span;
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const size_t candidatesLimit = (150 * 1000000) / span;
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std::vector<Range> ranges;
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TextIdx mark = 0;
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size_t numTries = 0;
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while (true) {
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TextIdx dictSize = calculateDictionarySize(ranges);
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size_t numCandidates = 0;
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if (dictSize > targetSize - blockLen) {
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break;
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}
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if (maxScore == 0) {
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break;
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}
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while (true) {
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TextIdx candidate = 0;
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while (maxScore > 0) {
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if (candidates[maxScore] != 0) {
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candidate = candidates[maxScore];
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candidates[maxScore] = next[candidate];
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break;
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|
}
|
|
maxScore--;
|
|
}
|
|
if (maxScore == 0) {
|
|
break;
|
|
}
|
|
mark++;
|
|
numTries++;
|
|
numCandidates++;
|
|
Score score = 0;
|
|
for (size_t j = candidate; j < candidate + span; ++j) {
|
|
MetaSlot& item = map[shortcut[j]];
|
|
if (item.mark != mark) {
|
|
score += item.score;
|
|
item.mark = mark;
|
|
}
|
|
}
|
|
if (score < maxScore) {
|
|
if (numTries < triesLimit && numCandidates < candidatesLimit) {
|
|
next[candidate] = candidates[score];
|
|
candidates[score] = candidate;
|
|
} else {
|
|
maxScore = rebuildCandidatesList(
|
|
&candidates, &map, span, shortcut, end, next.data());
|
|
mark = 0;
|
|
numTries = 0;
|
|
numCandidates = 0;
|
|
}
|
|
continue;
|
|
} else if (score > maxScore) {
|
|
fprintf(stderr, "Broken invariant\n");
|
|
return "";
|
|
}
|
|
for (TextIdx j = candidate; j < candidate + span; ++j) {
|
|
MetaSlot& item = map[shortcut[j]];
|
|
item.score = 0;
|
|
}
|
|
addRange(&ranges, candidate, candidate + blockLen);
|
|
break;
|
|
}
|
|
}
|
|
|
|
return createDictionary(data, ranges, targetSize);
|
|
}
|
|
|
|
static std::string durchschlagGenerateCollaborative(
|
|
size_t dictionary_size_limit, size_t block_len,
|
|
const DurchschlagContext& context, 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 = context.sliceLen;
|
|
TextIdx total = context.dataSize;
|
|
TextIdx blockLen = static_cast<TextIdx>(block_len);
|
|
if (blockLen != block_len) {
|
|
fprintf(stderr, "block_len is too large\n");
|
|
return "";
|
|
}
|
|
const uint8_t* data = sample_data;
|
|
const std::vector<TextIdx>& offsets = context.offsets;
|
|
std::vector<MetaSlot> map(context.numUniqueSlices);
|
|
const TextIdx* shortcut = context.sliceMap.data();
|
|
|
|
/* Initialization */
|
|
if (blockLen < sliceLen) {
|
|
fprintf(stderr, "sliceLen is larger than block_len\n");
|
|
return "";
|
|
}
|
|
if (targetSize < blockLen || total < blockLen) {
|
|
fprintf(stderr, "block_len is too large\n");
|
|
return "";
|
|
}
|
|
TextIdx end = total - sliceLen + 1;
|
|
ScoreSlices(offsets, map, shortcut, end);
|
|
TextIdx span = blockLen - sliceLen + 1;
|
|
end = static_cast<TextIdx>(context.sliceMap.size()) - span;
|
|
std::vector<Candidate> candidates;
|
|
candidates.reserve(CANDIDATE_BUNDLE_SIZE + 1024);
|
|
Score minScore = buildCandidatesList(&candidates, &map, span, shortcut, end);
|
|
|
|
/* Block selection */
|
|
std::vector<Range> ranges;
|
|
TextIdx mark = 0;
|
|
while (true) {
|
|
TextIdx dictSize = calculateDictionarySize(ranges);
|
|
if (dictSize > targetSize - blockLen) {
|
|
break;
|
|
}
|
|
if (minScore == 0 && candidates.empty()) {
|
|
break;
|
|
}
|
|
while (true) {
|
|
if (candidates.empty()) {
|
|
minScore = buildCandidatesList(&candidates, &map, span, shortcut, end);
|
|
mark = 0;
|
|
}
|
|
TextIdx candidate = candidates[0].position;
|
|
Score expectedScore = candidates[0].score;
|
|
if (expectedScore == 0) {
|
|
candidates.resize(0);
|
|
break;
|
|
}
|
|
std::pop_heap(candidates.begin(), candidates.end(), lessScore());
|
|
candidates.pop_back();
|
|
mark++;
|
|
Score score = 0;
|
|
for (TextIdx j = candidate; j < candidate + span; ++j) {
|
|
MetaSlot& item = map[shortcut[j]];
|
|
if (item.mark != mark) {
|
|
score += item.score;
|
|
item.mark = mark;
|
|
}
|
|
}
|
|
if (score < expectedScore) {
|
|
if (score >= minScore) {
|
|
candidates.push_back({score, candidate});
|
|
std::push_heap(candidates.begin(), candidates.end(), lessScore());
|
|
}
|
|
continue;
|
|
} else if (score > expectedScore) {
|
|
fatal("Broken invariant");
|
|
}
|
|
for (TextIdx j = candidate; j < candidate + span; ++j) {
|
|
MetaSlot& item = map[shortcut[j]];
|
|
item.score = 0;
|
|
}
|
|
addRange(&ranges, candidate, candidate + blockLen);
|
|
break;
|
|
}
|
|
}
|
|
|
|
return createDictionary(data, ranges, targetSize);
|
|
}
|
|
|
|
std::string durchschlag_generate(DurchschalgResourceStrategy strategy,
|
|
size_t dictionary_size_limit, size_t block_len,
|
|
const DurchschlagContext& context, const uint8_t* sample_data) {
|
|
if (strategy == DURCHSCHLAG_COLLABORATIVE) {
|
|
return durchschlagGenerateCollaborative(
|
|
dictionary_size_limit, block_len, context, sample_data);
|
|
} else {
|
|
return durchschlagGenerateExclusive(
|
|
dictionary_size_limit, block_len, context, sample_data);
|
|
}
|
|
}
|
|
|
|
void durchschlag_distill(size_t slice_len, size_t minimum_population,
|
|
std::vector<size_t>* sample_sizes, uint8_t* sample_data) {
|
|
/* Parameters aliasing */
|
|
uint8_t* data = sample_data;
|
|
|
|
/* Build slice map. */
|
|
DurchschlagContext context = durchschlag_prepare(
|
|
slice_len, *sample_sizes, data);
|
|
|
|
/* Calculate slice population. */
|
|
const std::vector<TextIdx>& offsets = context.offsets;
|
|
std::vector<MetaSlot> map(context.numUniqueSlices);
|
|
const TextIdx* shortcut = context.sliceMap.data();
|
|
TextIdx sliceLen = context.sliceLen;
|
|
TextIdx total = context.dataSize;
|
|
TextIdx end = total - sliceLen + 1;
|
|
ScoreSlices(offsets, map, shortcut, end);
|
|
|
|
/* Condense samples, omitting unique slices. */
|
|
TextIdx readPos = 0;
|
|
TextIdx writePos = 0;
|
|
TextIdx lastNonUniquePos = 0;
|
|
for (TextIdx i = 0; i < sample_sizes->size(); ++i) {
|
|
TextIdx sampleStart = writePos;
|
|
TextIdx oldSampleEnd =
|
|
readPos + static_cast<TextIdx>(sample_sizes->at(i));
|
|
while (readPos < oldSampleEnd) {
|
|
if (readPos < end) {
|
|
MetaSlot& item = map[shortcut[readPos]];
|
|
if (item.score >= minimum_population) {
|
|
lastNonUniquePos = readPos + sliceLen;
|
|
}
|
|
}
|
|
if (readPos < lastNonUniquePos) {
|
|
data[writePos++] = data[readPos];
|
|
}
|
|
readPos++;
|
|
}
|
|
sample_sizes->at(i) = writePos - sampleStart;
|
|
}
|
|
}
|
|
|
|
void durchschlag_purify(size_t slice_len, size_t minimum_population,
|
|
const std::vector<size_t>& sample_sizes, uint8_t* sample_data) {
|
|
/* Parameters aliasing */
|
|
uint8_t* data = sample_data;
|
|
|
|
/* Build slice map. */
|
|
DurchschlagContext context = durchschlag_prepare(
|
|
slice_len, sample_sizes, data);
|
|
|
|
/* Calculate slice population. */
|
|
const std::vector<TextIdx>& offsets = context.offsets;
|
|
std::vector<MetaSlot> map(context.numUniqueSlices);
|
|
const TextIdx* shortcut = context.sliceMap.data();
|
|
TextIdx sliceLen = context.sliceLen;
|
|
TextIdx total = context.dataSize;
|
|
TextIdx end = total - sliceLen + 1;
|
|
ScoreSlices(offsets, map, shortcut, end);
|
|
|
|
/* Rewrite samples, zeroing out unique slices. */
|
|
TextIdx lastNonUniquePos = 0;
|
|
for (TextIdx readPos = 0; readPos < total; ++readPos) {
|
|
if (readPos < end) {
|
|
MetaSlot& item = map[shortcut[readPos]];
|
|
if (item.score >= minimum_population) {
|
|
lastNonUniquePos = readPos + sliceLen;
|
|
}
|
|
}
|
|
if (readPos >= lastNonUniquePos) {
|
|
data[readPos] = 0;
|
|
}
|
|
}
|
|
}
|