Esempio n. 1
0
void forward_index::impl::uninvert(const inverted_index& inv_idx)
{
    io::compressed_file_reader inv_reader{inv_idx.index_name()
                                              + idx_->impl_->files[POSTINGS],
                                          io::default_compression_reader_func};

    term_id t_id{0};
    chunk_handler<forward_index> handler{idx_->index_name()};
    {
        auto producer = handler.make_producer();
        while (inv_reader.has_next())
        {
            inverted_pdata_type pdata{t_id};
            pdata.read_compressed(inv_reader);
            producer(pdata.primary_key(), pdata.counts());
            ++t_id;
        }
    }

    handler.merge_chunks();
    compressed_postings_to_libsvm(inv_idx.num_docs());
}
Esempio n. 2
0
std::vector<std::pair<doc_id, double>>
ranker::score(inverted_index& idx, corpus::document& query,
              uint64_t num_results /* = 10 */,
              const std::function<bool(doc_id d_id)>& filter /* return true */)
{
    if (query.counts().empty())
        idx.tokenize(query);

    score_data sd{idx,            idx.avg_doc_length(),
                  idx.num_docs(), idx.total_corpus_terms(),
                  query};

    // zeros out elements and (if necessary) resizes the vector; this eliminates
    // constructing a new vector each query for the same index
    results_.assign(sd.num_docs, std::numeric_limits<double>::lowest());

    for (auto& tpair : query.counts())
    {
        term_id t_id{idx.get_term_id(tpair.first)};
        auto pdata = idx.search_primary(t_id);
        sd.doc_count = pdata->counts().size();
        sd.t_id = t_id;
        sd.query_term_count = tpair.second;
        sd.corpus_term_count = idx.total_num_occurences(sd.t_id);
        for (auto& dpair : pdata->counts())
        {
            sd.d_id = dpair.first;
            sd.doc_term_count = dpair.second;
            sd.doc_size = idx.doc_size(dpair.first);
            sd.doc_unique_terms = idx.unique_terms(dpair.first);

            // if this is the first time we've seen this document, compute
            // its initial score
            if (results_[dpair.first] == std::numeric_limits<double>::lowest())
                results_[dpair.first] = initial_score(sd);

            results_[dpair.first] += score_one(sd);
        }
    }

    using doc_pair = std::pair<doc_id, double>;
    auto doc_pair_comp = [](const doc_pair& a, const doc_pair& b)
    { return a.second > b.second; };

    std::priority_queue<doc_pair,
                        std::vector<doc_pair>,
                        decltype(doc_pair_comp)> pq{doc_pair_comp};
    for (uint64_t id = 0; id < results_.size(); ++id)
    {
        if (!filter(doc_id{id}))
            continue;

        pq.emplace(doc_id{id}, results_[id]);
        if (pq.size() > num_results)
            pq.pop();
    }

    std::vector<doc_pair> sorted;
    while (!pq.empty())
    {
        sorted.emplace_back(pq.top());
        pq.pop();
    }
    std::reverse(sorted.begin(), sorted.end());

    return sorted;
}