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// Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include "weak_and_search.h"
#include "wand_parts.h"
#include <vespa/searchlib/queryeval/orsearch.h>
#include <vespa/vespalib/util/left_right_heap.h>
#include <vespa/vespalib/util/priority_queue.h>
#include <vespa/vespalib/objects/visit.hpp>
namespace search::queryeval {
namespace wand {
template <typename FutureHeap, typename PastHeap, bool IS_STRICT>
class WeakAndSearchLR final : public WeakAndSearch
{
private:
using Scores = vespalib::PriorityQueue<score_t>;
VectorizedIteratorTerms _terms;
DualHeap<FutureHeap, PastHeap> _heaps;
Algorithm _algo;
score_t _threshold; // current score threshold
Scores _scores; // best n scores
const uint32_t _n;
void seek_strict(uint32_t docid) {
_algo.set_candidate(_terms, _heaps, docid);
if (_algo.solve_wand_constraint(_terms, _heaps, GreaterThanEqual(_threshold))) {
setDocId(_algo.get_candidate());
} else {
setAtEnd();
}
}
void seek_unstrict(uint32_t docid) {
if (docid > _algo.get_candidate()) {
_algo.set_candidate(_terms, _heaps, docid);
if (_algo.check_wand_constraint(_terms, _heaps, GreaterThanEqual(_threshold))) {
setDocId(_algo.get_candidate());
}
}
}
public:
WeakAndSearchLR(const Terms &terms, uint32_t n)
: _terms(terms, TermFrequencyScorer(), 0, {}),
_heaps(DocIdOrder(_terms.docId()), _terms.size()),
_algo(),
_threshold(1),
_scores(),
_n(n)
{
}
size_t get_num_terms() const override { return _terms.size(); }
int32_t get_term_weight(size_t idx) const override { return _terms.weight(idx); }
score_t get_max_score(size_t idx) const override { return _terms.maxScore(idx); }
const Terms &getTerms() const override { return _terms.input_terms(); }
uint32_t getN() const override { return _n; }
void doSeek(uint32_t docid) override {
if (IS_STRICT) {
seek_strict(docid);
} else {
seek_unstrict(docid);
}
}
void doUnpack(uint32_t docid) override {
_algo.find_matching_terms(_terms, _heaps);
_scores.push(_algo.get_upper_bound());
if (_scores.size() > _n) {
_scores.pop_front();
}
if (_scores.size() == _n) {
_threshold = _scores.front();
}
ref_t *end = _heaps.present_end();
for (ref_t *ref = _heaps.present_begin(); ref != end; ++ref) {
_terms.unpack(*ref, docid);
}
}
void initRange(uint32_t begin, uint32_t end) override {
WeakAndSearch::initRange(begin, end);
_algo.init_range(_terms, _heaps, begin, end);
if (_n == 0) {
setAtEnd();
}
}
Trinary is_strict() const override { return IS_STRICT ? Trinary::True : Trinary::False; }
};
//-----------------------------------------------------------------------------
} // namespace search::queryeval::wand
//-----------------------------------------------------------------------------
void
WeakAndSearch::visitMembers(vespalib::ObjectVisitor &visitor) const
{
visit(visitor, "n", getN());
visit(visitor, "terms", getTerms());
}
//-----------------------------------------------------------------------------
SearchIterator::UP
WeakAndSearch::createArrayWand(const Terms &terms, uint32_t n, bool strict)
{
if (strict) {
return std::make_unique<wand::WeakAndSearchLR<vespalib::LeftArrayHeap, vespalib::RightArrayHeap, true>>(terms, n);
} else {
return std::make_unique<wand::WeakAndSearchLR<vespalib::LeftArrayHeap, vespalib::RightArrayHeap, false>>(terms, n);
}
}
SearchIterator::UP
WeakAndSearch::createHeapWand(const Terms &terms, uint32_t n, bool strict)
{
if (strict) {
return std::make_unique<wand::WeakAndSearchLR<vespalib::LeftHeap, vespalib::RightHeap, true>>(terms, n);
} else {
return std::make_unique<wand::WeakAndSearchLR<vespalib::LeftHeap, vespalib::RightHeap, false>>(terms, n);
}
}
SearchIterator::UP
WeakAndSearch::create(const Terms &terms, uint32_t n, bool strict)
{
if (terms.size() < 128) {
return createArrayWand(terms, n, strict);
} else {
return createHeapWand(terms, n, strict);
}
}
//-----------------------------------------------------------------------------
}
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