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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 "bitvector_search_cache.h"
#include "posting_list_merger.h"
#include <vespa/searchcommon/attribute/search_context_params.h>
#include <vespa/searchcommon/attribute/i_search_context.h>
#include <vespa/vespalib/datastore/atomic_value_wrapper.h>
#include <vespa/vespalib/util/arrayref.h>
namespace search::fef { class TermFieldMatchData; }
namespace search { class QueryTermSimple; }
namespace search::attribute {
class IAttributeVector;
class ReferenceAttribute;
class ImportedAttributeVector;
class SearchContextParams;
/**
* Search context exposing iteraton over an imported attribute vector.
*
* Iterator doc id matching is performed via the GID->LID indirection of the
* associated reference attribute. This means that if the _referenced_ document
* matches the search term, the doc id of the _referring_ document will be
* considered a match.
*/
class ImportedSearchContext : public ISearchContext {
using AtomicTargetLid = vespalib::datastore::AtomicValueWrapper<uint32_t>;
using TargetLids = vespalib::ConstArrayRef<AtomicTargetLid>;
const ImportedAttributeVector& _imported_attribute;
vespalib::string _queryTerm;
bool _useSearchCache;
std::shared_ptr<BitVectorSearchCache::Entry> _searchCacheLookup;
IDocumentMetaStoreContext::IReadGuard::SP _dmsReadGuardFallback;
const ReferenceAttribute& _reference_attribute;
const IAttributeVector &_target_attribute;
std::unique_ptr<ISearchContext> _target_search_context;
TargetLids _targetLids;
uint32_t _target_docid_limit;
PostingListMerger<int32_t> _merger;
SearchContextParams _params;
mutable std::atomic<bool> _zero_hits;
static constexpr uint32_t MIN_TARGET_HITS_FOR_APPROXIMATION = 50;
uint32_t getTargetLid(uint32_t lid) const {
// Check range to avoid reading memory beyond end of mapping array
uint32_t target_lid = lid < _targetLids.size() ? _targetLids[lid].load_acquire() : 0u;
// Check target range
return target_lid < _target_docid_limit ? target_lid : 0u;
}
void makeMergedPostings(bool isFilter);
void considerAddSearchCacheEntry();
uint32_t calc_approx_hits(uint32_t target_approx_hits) const;
uint32_t calc_exact_hits() const;
public:
ImportedSearchContext(std::unique_ptr<QueryTermSimple> term,
const SearchContextParams& params,
const ImportedAttributeVector& imported_attribute,
const attribute::IAttributeVector &target_attribute);
~ImportedSearchContext() override;
std::unique_ptr<queryeval::SearchIterator>
createIterator(fef::TermFieldMatchData* matchData, bool strict) override;
HitEstimate calc_hit_estimate() const override;
void fetchPostings(const queryeval::ExecuteInfo &execInfo, bool strict) override;
bool valid() const override;
Int64Range getAsIntegerTerm() const override;
DoubleRange getAsDoubleTerm() const override;
const QueryTermUCS4 * queryTerm() const override;
const vespalib::string& attributeName() const override;
using DocId = uint32_t;
int32_t find(DocId docId, int32_t elemId, int32_t& weight) const {
return _target_search_context->find(getTargetLid(docId), elemId, weight);
}
int32_t find(DocId docId, int32_t elemId) const {
return _target_search_context->find(getTargetLid(docId), elemId);
}
int32_t onFind(uint32_t docId, int32_t elemId, int32_t &weight) const override { return find(docId, elemId, weight); }
int32_t onFind(uint32_t docId, int32_t elemId) const override { return find(docId, elemId); }
const ReferenceAttribute& attribute() const noexcept { return _reference_attribute; }
const ISearchContext &target_search_context() const noexcept {
return *_target_search_context;
}
uint32_t get_committed_docid_limit() const noexcept override;
};
}
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