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// Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#pragma once
#include "wand_parts.h"
#include <vespa/vespalib/util/priority_queue.h>
#include <atomic>
#include <mutex>
namespace search::queryeval {
/**
* An interface used to insert scores into an underlying heap (or similar data structure)
* that can be shared between multiple search iterators.
* An implementation of this interface must keep the best N scores and
* provide the threshold score (lowest score among the best N).
*/
class WeakAndHeap {
public:
using score_t = wand::score_t;
WeakAndHeap(uint32_t scoresToTrack) :
_minScore((scoresToTrack == 0)
? std::numeric_limits<score_t>::max()
: 0),
_scoresToTrack(scoresToTrack)
{ }
virtual ~WeakAndHeap() {}
/**
* Consider the given scores for insertion into the underlying structure.
* The implementation may change the given score array to speed up execution.
*/
virtual void adjust(score_t *begin, score_t *end) = 0;
/**
* The number of scores this heap is tracking.
**/
uint32_t getScoresToTrack() const { return _scoresToTrack; }
score_t getMinScore() const { return _minScore.load(std::memory_order_relaxed); }
protected:
void setMinScore(score_t minScore) { _minScore.store(minScore, std::memory_order_relaxed); }
private:
std::atomic<score_t> _minScore;
const uint32_t _scoresToTrack;
};
/**
* An implementation using an underlying priority queue to keep track of the N
* best hits that can be shared among multiple search iterators.
*/
class SharedWeakAndPriorityQueue : public WeakAndHeap
{
private:
using Scores = vespalib::PriorityQueue<score_t>;
Scores _bestScores;
std::mutex _lock;
bool is_full() const { return (_bestScores.size() >= getScoresToTrack()); }
public:
SharedWeakAndPriorityQueue(uint32_t scoresToTrack);
~SharedWeakAndPriorityQueue();
Scores &getScores() { return _bestScores; }
void adjust(score_t *begin, score_t *end) override;
};
}
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