| // Licensed to the Apache Software Foundation (ASF) under one |
| // or more contributor license agreements. See the NOTICE file |
| // distributed with this work for additional information |
| // regarding copyright ownership. The ASF licenses this file |
| // to you under the Apache License, Version 2.0 (the |
| // "License"); you may not use this file except in compliance |
| // with the License. You may obtain a copy of the License at |
| // |
| // http://www.apache.org/licenses/LICENSE-2.0 |
| // |
| // Unless required by applicable law or agreed to in writing, |
| // software distributed under the License is distributed on an |
| // "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| // KIND, either express or implied. See the License for the |
| // specific language governing permissions and limitations |
| // under the License. |
| |
| #include "storage/compaction/collection_similarity.h" |
| |
| #include "core/column/column_nullable.h" |
| #include "core/column/column_vector.h" |
| |
| namespace doris { |
| #include "common/compile_check_begin.h" |
| |
| void CollectionSimilarity::collect(segment_v2::rowid_t row_id, float score) { |
| _bm25_scores[row_id] += score; |
| } |
| |
| void CollectionSimilarity::get_bm25_scores(roaring::Roaring* row_bitmap, |
| IColumn::MutablePtr& scores, |
| std::unique_ptr<std::vector<uint64_t>>& row_ids, |
| const ScoreRangeFilterPtr& filter) const { |
| std::vector<float> filtered_scores; |
| filtered_scores.reserve(row_bitmap->cardinality()); |
| |
| roaring::Roaring new_bitmap; |
| |
| for (uint32_t row_id : *row_bitmap) { |
| auto it = _bm25_scores.find(row_id); |
| float score = (it != _bm25_scores.end()) ? it->second : 0.0F; |
| if (filter && !filter->pass(score)) { |
| continue; |
| } |
| row_ids->push_back(row_id); |
| filtered_scores.push_back(score); |
| new_bitmap.add(row_id); |
| } |
| |
| size_t num_results = row_ids->size(); |
| auto score_column = ColumnFloat32::create(num_results); |
| if (num_results > 0) { |
| memcpy(score_column->get_data().data(), filtered_scores.data(), |
| num_results * sizeof(float)); |
| } |
| |
| *row_bitmap = std::move(new_bitmap); |
| auto null_map = ColumnUInt8::create(num_results, 0); |
| scores = ColumnNullable::create(std::move(score_column), std::move(null_map)); |
| } |
| |
| void CollectionSimilarity::get_topn_bm25_scores(roaring::Roaring* row_bitmap, |
| IColumn::MutablePtr& scores, |
| std::unique_ptr<std::vector<uint64_t>>& row_ids, |
| OrderType order_type, size_t top_k, |
| const ScoreRangeFilterPtr& filter) const { |
| std::vector<std::pair<uint32_t, float>> top_k_results; |
| |
| if (order_type == OrderType::DESC) { |
| find_top_k_scores<OrderType::DESC>(row_bitmap, _bm25_scores, top_k, top_k_results, filter); |
| } else { |
| find_top_k_scores<OrderType::ASC>(row_bitmap, _bm25_scores, top_k, top_k_results, filter); |
| } |
| |
| size_t num_results = top_k_results.size(); |
| auto score_column = ColumnFloat32::create(num_results); |
| auto& score_data = score_column->get_data(); |
| |
| row_ids->resize(num_results); |
| roaring::Roaring new_bitmap; |
| |
| for (size_t i = 0; i < num_results; ++i) { |
| (*row_ids)[i] = top_k_results[i].first; |
| score_data[i] = top_k_results[i].second; |
| new_bitmap.add(top_k_results[i].first); |
| } |
| |
| *row_bitmap = std::move(new_bitmap); |
| auto null_map = ColumnUInt8::create(num_results, 0); |
| scores = ColumnNullable::create(std::move(score_column), std::move(null_map)); |
| } |
| |
| template <OrderType order> |
| void CollectionSimilarity::find_top_k_scores(const roaring::Roaring* row_bitmap, |
| const ScoreMap& all_scores, size_t top_k, |
| std::vector<std::pair<uint32_t, float>>& top_k_results, |
| const ScoreRangeFilterPtr& filter) const { |
| if (top_k <= 0) { |
| return; |
| } |
| |
| auto pair_comp = [](const std::pair<uint32_t, float>& a, const std::pair<uint32_t, float>& b) { |
| if constexpr (order == OrderType::DESC) { |
| return a.second > b.second; |
| } else { |
| return a.second < b.second; |
| } |
| }; |
| |
| std::priority_queue<std::pair<uint32_t, float>, std::vector<std::pair<uint32_t, float>>, |
| decltype(pair_comp)> |
| top_k_heap(pair_comp); |
| |
| std::vector<uint32_t> zero_score_ids; |
| |
| for (uint32_t row_id : *row_bitmap) { |
| auto it = all_scores.find(row_id); |
| float score = (it != all_scores.end()) ? it->second : 0.0F; |
| |
| if (filter && !filter->pass(score)) { |
| continue; |
| } |
| |
| if (score == 0.0F) { |
| zero_score_ids.push_back(row_id); |
| continue; |
| } |
| |
| if (top_k_heap.size() < top_k) { |
| top_k_heap.emplace(row_id, score); |
| } else if (pair_comp({row_id, score}, top_k_heap.top())) { |
| top_k_heap.pop(); |
| top_k_heap.emplace(row_id, score); |
| } |
| } |
| |
| top_k_results.reserve(top_k); |
| while (!top_k_heap.empty()) { |
| top_k_results.push_back(top_k_heap.top()); |
| top_k_heap.pop(); |
| } |
| std::ranges::reverse(top_k_results); |
| |
| if constexpr (order == OrderType::DESC) { |
| // DESC: high scores first, then zeros at the end |
| size_t remaining = top_k - top_k_results.size(); |
| for (size_t i = 0; i < remaining && i < zero_score_ids.size(); ++i) { |
| top_k_results.emplace_back(zero_score_ids[i], 0.0F); |
| } |
| } else { |
| // ASC: zeros first, then low scores |
| std::vector<std::pair<uint32_t, float>> final_results; |
| final_results.reserve(top_k); |
| |
| size_t zero_count = std::min(top_k, zero_score_ids.size()); |
| for (size_t i = 0; i < zero_count; ++i) { |
| final_results.emplace_back(zero_score_ids[i], 0.0F); |
| } |
| |
| size_t remaining = top_k - final_results.size(); |
| for (size_t i = 0; i < remaining && i < top_k_results.size(); ++i) { |
| final_results.push_back(top_k_results[i]); |
| } |
| |
| top_k_results = std::move(final_results); |
| } |
| } |
| |
| #include "common/compile_check_end.h" |
| } // namespace doris |