194 lines
6.3 KiB
C++
194 lines
6.3 KiB
C++
#ifndef __CXXMPH_MPH_INDEX_H__
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#define __CXXMPH_MPH_INDEX_H__
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// Minimal perfect hash abstraction implementing the BDZ algorithm
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#include <stdint.h>
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#include <cassert>
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#include <cmath>
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#include <tr1/unordered_map> // for std::tr1::hash
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#include <vector>
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#include <iostream>
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using std::cerr;
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using std::endl;
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#include "seeded_hash.h"
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#include "trigraph.h"
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namespace cxxmph {
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class MPHIndex {
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public:
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MPHIndex(double c = 1.23, uint8_t b = 7) :
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c_(c), b_(b), m_(0), n_(0), k_(0), r_(0),
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g_(NULL), g_size_(0), ranktable_(NULL), ranktable_size_(0),
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deserialized_(false) { }
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~MPHIndex();
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template <class SeededHashFcn, class ForwardIterator>
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bool Reset(ForwardIterator begin, ForwardIterator end);
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template <class SeededHashFcn, class Key> // must agree with Reset
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uint32_t index(const Key& x) const;
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uint32_t size() const { return m_; }
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void clear();
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uint32_t perfect_hash_size() const { return n_; }
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template <class SeededHashFcn, class Key> // must agree with Reset
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uint32_t perfect_hash(const Key& x) const;
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template <class SeededHashFcn, class Key> // must agree with Reset
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uint32_t minimal_perfect_hash(const Key& x) const;
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// Serialization machinery for mmap usage.
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// Serialized tables are not guaranteed to work across versions or different
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// endianness (although they could easily be made to be).
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uint32_t serialize_bytes_needed() const;
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void serialize(char *memory) const;
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bool deserialize(const char* serialized_memory);
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private:
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template <class SeededHashFcn, class ForwardIterator>
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bool Mapping(ForwardIterator begin, ForwardIterator end,
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std::vector<TriGraph::Edge>* edges,
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std::vector<uint32_t>* queue);
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bool GenerateQueue(TriGraph* graph, std::vector<uint32_t>* queue);
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void Assigning(const std::vector<TriGraph::Edge>& edges,
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const std::vector<uint32_t>& queue);
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void Ranking();
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uint32_t Rank(uint32_t vertex) const;
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// Algorithm parameters
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double c_; // Number of bits per key (? is it right)
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uint8_t b_; // Number of bits of the kth index in the ranktable
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// Values used during generation
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uint32_t m_; // edges count
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uint32_t n_; // vertex count
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uint32_t k_; // kth index in ranktable, $k = log_2(n=3r)\varepsilon$
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// Values used during search
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// Partition vertex count, derived from c parameter.
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uint32_t r_;
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// The array containing the minimal perfect hash function graph. Do not use
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// c++ vector to make mmap based backing easier.
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const uint8_t* g_;
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uint32_t g_size_;
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// The table used for the rank step of the minimal perfect hash function
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const uint32_t* ranktable_;
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uint32_t ranktable_size_;
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// The selected hash seed triplet for finding the edges in the minimal
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// perfect hash function graph.
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uint32_t hash_seed_[3];
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bool deserialized_;
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static const uint8_t valuemask[];
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static void set_2bit_value(uint8_t *d, uint32_t i, uint8_t v) {
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d[(i >> 2)] &= ((v << ((i & 3) << 1)) | valuemask[i & 3]);
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}
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static uint32_t get_2bit_value(const uint8_t* d, uint32_t i) {
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return (d[(i >> 2)] >> (((i & 3) << 1)) & 3);
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}
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};
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// Template method needs to go in the header file.
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template <class SeededHashFcn, class ForwardIterator>
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bool MPHIndex::Reset(ForwardIterator begin, ForwardIterator end) {
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if (end == begin) {
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clear();
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return true;
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}
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m_ = end - begin;
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r_ = static_cast<uint32_t>(ceil((c_*m_)/3));
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if ((r_ % 2) == 0) r_ += 1;
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n_ = 3*r_;
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k_ = 1U << b_;
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// cerr << "m " << m_ << " n " << n_ << " r " << r_ << endl;
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int iterations = 10;
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std::vector<TriGraph::Edge> edges;
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std::vector<uint32_t> queue;
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while (1) {
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// cerr << "Iterations missing: " << iterations << endl;
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for (int i = 0; i < 3; ++i) hash_seed_[i] = random() % m_;
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// for (int i = 0; i < 3; ++i) hash_seed_[i] = random() + i;
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if (Mapping<SeededHashFcn>(begin, end, &edges, &queue)) break;
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else --iterations;
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if (iterations == 0) break;
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}
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if (iterations == 0) return false;
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Assigning(edges, queue);
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std::vector<TriGraph::Edge>().swap(edges);
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Ranking();
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deserialized_ = false;
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return true;
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}
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template <class SeededHashFcn, class ForwardIterator>
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bool MPHIndex::Mapping(
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ForwardIterator begin, ForwardIterator end,
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std::vector<TriGraph::Edge>* edges, std::vector<uint32_t>* queue) {
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TriGraph graph(n_, m_);
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for (ForwardIterator it = begin; it != end; ++it) {
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uint32_t h[3];
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for (int i = 0; i < 3; ++i) h[i] = SeededHashFcn()(*it, hash_seed_[i]);
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uint32_t v0 = h[0] % r_;
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uint32_t v1 = h[1] % r_ + r_;
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uint32_t v2 = h[2] % r_ + (r_ << 1);
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// cerr << "Key: " << *it << " edge " << it - begin << " (" << v0 << "," << v1 << "," << v2 << ")" << endl;
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graph.AddEdge(TriGraph::Edge(v0, v1, v2));
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}
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if (GenerateQueue(&graph, queue)) {
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graph.ExtractEdgesAndClear(edges);
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return true;
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}
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return false;
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}
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template <class SeededHashFcn, class Key>
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uint32_t MPHIndex::perfect_hash(const Key& key) const {
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uint32_t h[3];
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for (int i = 0; i < 3; ++i) h[i] = SeededHashFcn()(key, hash_seed_[i]);
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assert(r_);
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h[0] = h[0] % r_;
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h[1] = h[1] % r_ + r_;
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h[2] = h[2] % r_ + (r_ << 1);
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assert(g_size_);
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// cerr << "g_.size() " << g_size_ << " h0 >> 2 " << (h[0] >> 2) << endl;
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assert((h[0] >> 2) <g_size_);
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assert((h[1] >> 2) <g_size_);
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assert((h[2] >> 2) <g_size_);
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uint32_t vertex = h[(get_2bit_value(g_, h[0]) + get_2bit_value(g_, h[1]) + get_2bit_value(g_, h[2])) % 3];
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return vertex;
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}
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template <class SeededHashFcn, class Key>
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uint32_t MPHIndex::minimal_perfect_hash(const Key& key) const {
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return Rank(perfect_hash<SeededHashFcn, Key>(key));
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}
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template <class SeededHashFcn, class Key>
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uint32_t MPHIndex::index(const Key& key) const {
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return minimal_perfect_hash<SeededHashFcn, Key>(key);
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}
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template <class Key, class HashFcn = typename seeded_hash<std::tr1::hash<Key> >::hash_function>
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class SimpleMPHIndex : public MPHIndex {
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public:
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template <class ForwardIterator>
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bool Reset(ForwardIterator begin, ForwardIterator end) {
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return MPHIndex::Reset<HashFcn>(begin, end);
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}
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uint32_t index(const Key& key) const { return MPHIndex::index<HashFcn>(key); }
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uint32_t perfect_hash(const Key& key) const { return MPHIndex::perfect_hash<HashFcn>(key); }
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uint32_t minimal_perfect_hash(const Key& key) const { return MPHIndex::minimal_perfect_hash<HashFcn>(key); }
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};
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} // namespace cxxmph
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#endif // __CXXMPH_MPH_INDEX_H__
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