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383 lines
15 KiB
C++
383 lines
15 KiB
C++
// Copyright (C) 2019-2020 Zilliz. All rights reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
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// with the License. You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software distributed under the License
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// is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
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// or implied. See the License for the specific language governing permissions and limitations under the License
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#include <random>
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#include <algorithm>
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#include <numeric>
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#include <thread>
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#include <queue>
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#include "segcore/SegmentNaive.h"
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#include <knowhere/index/vector_index/adapter/VectorAdapter.h>
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#include <knowhere/index/vector_index/VecIndexFactory.h>
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#include <faiss/utils/distances.h>
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#include "query/generated/ExecPlanNodeVisitor.h"
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#include "segcore/SegmentSmallIndex.h"
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#include "query/PlanNode.h"
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#include "query/PlanImpl.h"
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#include "segcore/Reduce.h"
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#include "utils/tools.h"
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namespace milvus::segcore {
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int64_t
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SegmentSmallIndex::PreInsert(int64_t size) {
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auto reserved_begin = record_.reserved.fetch_add(size);
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return reserved_begin;
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}
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int64_t
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SegmentSmallIndex::PreDelete(int64_t size) {
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auto reserved_begin = deleted_record_.reserved.fetch_add(size);
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return reserved_begin;
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}
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auto
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SegmentSmallIndex::get_deleted_bitmap(int64_t del_barrier,
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Timestamp query_timestamp,
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int64_t insert_barrier,
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bool force) -> std::shared_ptr<DeletedRecord::TmpBitmap> {
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auto old = deleted_record_.get_lru_entry();
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if (!force || old->bitmap_ptr->count() == insert_barrier) {
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if (old->del_barrier == del_barrier) {
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return old;
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}
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}
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auto current = old->clone(insert_barrier);
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current->del_barrier = del_barrier;
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auto bitmap = current->bitmap_ptr;
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if (del_barrier < old->del_barrier) {
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for (auto del_index = del_barrier; del_index < old->del_barrier; ++del_index) {
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// get uid in delete logs
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auto uid = deleted_record_.uids_[del_index];
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// map uid to corresponding offsets, select the max one, which should be the target
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// the max one should be closest to query_timestamp, so the delete log should refer to it
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int64_t the_offset = -1;
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auto [iter_b, iter_e] = uid2offset_.equal_range(uid);
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for (auto iter = iter_b; iter != iter_e; ++iter) {
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auto offset = iter->second;
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if (record_.timestamps_[offset] < query_timestamp) {
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Assert(offset < insert_barrier);
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the_offset = std::max(the_offset, offset);
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}
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}
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// if not found, skip
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if (the_offset == -1) {
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continue;
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}
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// otherwise, clear the flag
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bitmap->clear(the_offset);
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}
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return current;
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} else {
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for (auto del_index = old->del_barrier; del_index < del_barrier; ++del_index) {
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// get uid in delete logs
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auto uid = deleted_record_.uids_[del_index];
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// map uid to corresponding offsets, select the max one, which should be the target
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// the max one should be closest to query_timestamp, so the delete log should refer to it
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int64_t the_offset = -1;
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auto [iter_b, iter_e] = uid2offset_.equal_range(uid);
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for (auto iter = iter_b; iter != iter_e; ++iter) {
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auto offset = iter->second;
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if (offset >= insert_barrier) {
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continue;
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}
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if (record_.timestamps_[offset] < query_timestamp) {
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Assert(offset < insert_barrier);
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the_offset = std::max(the_offset, offset);
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}
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}
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// if not found, skip
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if (the_offset == -1) {
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continue;
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}
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// otherwise, set the flag
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bitmap->set(the_offset);
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}
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this->deleted_record_.insert_lru_entry(current);
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}
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return current;
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}
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Status
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SegmentSmallIndex::Insert(int64_t reserved_begin,
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int64_t size,
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const int64_t* uids_raw,
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const Timestamp* timestamps_raw,
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const RowBasedRawData& entities_raw) {
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Assert(entities_raw.count == size);
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// step 1: check schema if valid
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if (entities_raw.sizeof_per_row != schema_->get_total_sizeof()) {
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std::string msg = "entity length = " + std::to_string(entities_raw.sizeof_per_row) +
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", schema length = " + std::to_string(schema_->get_total_sizeof());
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throw std::runtime_error(msg);
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}
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// step 2: sort timestamp
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auto raw_data = reinterpret_cast<const char*>(entities_raw.raw_data);
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auto len_per_row = entities_raw.sizeof_per_row;
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std::vector<std::tuple<Timestamp, idx_t, int64_t>> ordering;
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ordering.resize(size);
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// #pragma omp parallel for
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for (int i = 0; i < size; ++i) {
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ordering[i] = std::make_tuple(timestamps_raw[i], uids_raw[i], i);
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}
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std::sort(ordering.begin(), ordering.end());
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// step 3: and convert row-base data to column base accordingly
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auto sizeof_infos = schema_->get_sizeof_infos();
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std::vector<int> offset_infos(schema_->size() + 1, 0);
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std::partial_sum(sizeof_infos.begin(), sizeof_infos.end(), offset_infos.begin() + 1);
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std::vector<std::vector<char>> entities(schema_->size());
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for (int fid = 0; fid < schema_->size(); ++fid) {
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auto len = sizeof_infos[fid];
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entities[fid].resize(len * size);
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}
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std::vector<idx_t> uids(size);
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std::vector<Timestamp> timestamps(size);
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// #pragma omp parallel for
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for (int index = 0; index < size; ++index) {
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auto [t, uid, order_index] = ordering[index];
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timestamps[index] = t;
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uids[index] = uid;
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for (int fid = 0; fid < schema_->size(); ++fid) {
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auto len = sizeof_infos[fid];
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auto offset = offset_infos[fid];
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auto src = raw_data + offset + order_index * len_per_row;
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auto dst = entities[fid].data() + index * len;
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memcpy(dst, src, len);
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}
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}
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// step 4: fill into Segment.ConcurrentVector
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record_.timestamps_.set_data(reserved_begin, timestamps.data(), size);
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record_.uids_.set_data(reserved_begin, uids.data(), size);
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for (int fid = 0; fid < schema_->size(); ++fid) {
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record_.entity_vec_[fid]->set_data_raw(reserved_begin, entities[fid].data(), size);
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}
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for (int i = 0; i < uids.size(); ++i) {
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auto uid = uids[i];
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// NOTE: this must be the last step, cannot be put above
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uid2offset_.insert(std::make_pair(uid, reserved_begin + i));
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}
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record_.ack_responder_.AddSegment(reserved_begin, reserved_begin + size);
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indexing_record_.UpdateResourceAck(record_.ack_responder_.GetAck() / DefaultElementPerChunk, record_);
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return Status::OK();
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}
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Status
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SegmentSmallIndex::Delete(int64_t reserved_begin,
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int64_t size,
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const int64_t* uids_raw,
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const Timestamp* timestamps_raw) {
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std::vector<std::tuple<Timestamp, idx_t>> ordering;
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ordering.resize(size);
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// #pragma omp parallel for
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for (int i = 0; i < size; ++i) {
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ordering[i] = std::make_tuple(timestamps_raw[i], uids_raw[i]);
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}
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std::sort(ordering.begin(), ordering.end());
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std::vector<idx_t> uids(size);
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std::vector<Timestamp> timestamps(size);
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// #pragma omp parallel for
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for (int index = 0; index < size; ++index) {
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auto [t, uid] = ordering[index];
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timestamps[index] = t;
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uids[index] = uid;
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}
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deleted_record_.timestamps_.set_data(reserved_begin, timestamps.data(), size);
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deleted_record_.uids_.set_data(reserved_begin, uids.data(), size);
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deleted_record_.ack_responder_.AddSegment(reserved_begin, reserved_begin + size);
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return Status::OK();
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// for (int i = 0; i < size; ++i) {
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// auto key = row_ids[i];
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// auto time = timestamps[i];
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// delete_logs_.insert(std::make_pair(key, time));
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// }
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// return Status::OK();
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}
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Status
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SegmentSmallIndex::Close() {
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if (this->record_.reserved != this->record_.ack_responder_.GetAck()) {
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PanicInfo("insert not ready");
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}
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if (this->deleted_record_.reserved != this->deleted_record_.ack_responder_.GetAck()) {
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PanicInfo("delete not ready");
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}
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state_ = SegmentState::Closed;
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return Status::OK();
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}
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template <typename Type>
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knowhere::IndexPtr
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SegmentSmallIndex::BuildVecIndexImpl(const IndexMeta::Entry& entry) {
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auto offset_opt = schema_->get_offset(entry.field_name);
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Assert(offset_opt.has_value());
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auto offset = offset_opt.value();
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auto field = (*schema_)[offset];
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auto dim = field.get_dim();
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auto indexing = knowhere::VecIndexFactory::GetInstance().CreateVecIndex(entry.type, entry.mode);
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auto& uids = record_.uids_;
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auto entities = record_.get_entity<FloatVector>(offset);
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std::vector<knowhere::DatasetPtr> datasets;
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for (int chunk_id = 0; chunk_id < uids.chunk_size(); ++chunk_id) {
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auto entities_chunk = entities->get_chunk(chunk_id).data();
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int64_t count = chunk_id == uids.chunk_size() - 1 ? record_.reserved - chunk_id * DefaultElementPerChunk
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: DefaultElementPerChunk;
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datasets.push_back(knowhere::GenDataset(count, dim, entities_chunk));
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}
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for (auto& ds : datasets) {
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indexing->Train(ds, entry.config);
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}
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for (auto& ds : datasets) {
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indexing->AddWithoutIds(ds, entry.config);
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}
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return indexing;
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}
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Status
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SegmentSmallIndex::BuildIndex(IndexMetaPtr remote_index_meta) {
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if (remote_index_meta == nullptr) {
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std::cout << "WARN: Null index ptr is detected, use default index" << std::endl;
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int dim = 0;
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std::string index_field_name;
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for (auto& field : schema_->get_fields()) {
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if (field.get_data_type() == DataType::VECTOR_FLOAT) {
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dim = field.get_dim();
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index_field_name = field.get_name();
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}
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}
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Assert(dim != 0);
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Assert(!index_field_name.empty());
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auto index_meta = std::make_shared<IndexMeta>(schema_);
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// TODO: this is merge of query conf and insert conf
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// TODO: should be split into multiple configs
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auto conf = milvus::knowhere::Config{
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{milvus::knowhere::meta::DIM, dim}, {milvus::knowhere::IndexParams::nlist, 100},
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{milvus::knowhere::IndexParams::nprobe, 4}, {milvus::knowhere::IndexParams::m, 4},
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{milvus::knowhere::IndexParams::nbits, 8}, {milvus::knowhere::Metric::TYPE, milvus::knowhere::Metric::L2},
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{milvus::knowhere::meta::DEVICEID, 0},
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};
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index_meta->AddEntry("fakeindex", index_field_name, knowhere::IndexEnum::INDEX_FAISS_IVFPQ,
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knowhere::IndexMode::MODE_CPU, conf);
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remote_index_meta = index_meta;
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}
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if (record_.ack_responder_.GetAck() < 1024 * 4) {
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return Status(SERVER_BUILD_INDEX_ERROR, "too few elements");
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}
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AssertInfo(false, "unimplemented");
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return Status::OK();
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#if 0
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index_meta_ = remote_index_meta;
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for (auto& [index_name, entry] : index_meta_->get_entries()) {
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Assert(entry.index_name == index_name);
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const auto& field = (*schema_)[entry.field_name];
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if (field.is_vector()) {
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Assert(field.get_data_type() == engine::DataType::VECTOR_FLOAT);
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auto index_ptr = BuildVecIndexImpl<float>(entry);
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indexings_[index_name] = index_ptr;
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} else {
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throw std::runtime_error("unimplemented");
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}
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}
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index_ready_ = true;
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return Status::OK();
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#endif
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}
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int64_t
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SegmentSmallIndex::GetMemoryUsageInBytes() {
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int64_t total_bytes = 0;
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#if 0
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if (index_ready_) {
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auto& index_entries = index_meta_->get_entries();
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for (auto [index_name, entry] : index_entries) {
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Assert(schema_->operator[](entry.field_name).is_vector());
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auto vec_ptr = std::static_pointer_cast<knowhere::VecIndex>(indexings_[index_name]);
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total_bytes += vec_ptr->IndexSize();
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}
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}
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#endif
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int64_t ins_n = upper_align(record_.reserved, DefaultElementPerChunk);
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total_bytes += ins_n * (schema_->get_total_sizeof() + 16 + 1);
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int64_t del_n = upper_align(deleted_record_.reserved, DefaultElementPerChunk);
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total_bytes += del_n * (16 * 2);
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return total_bytes;
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}
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Status
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SegmentSmallIndex::Search(const query::Plan* plan,
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const query::PlaceholderGroup** placeholder_groups,
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const Timestamp* timestamps,
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int num_groups,
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QueryResult& results) {
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Assert(num_groups == 1);
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query::ExecPlanNodeVisitor visitor(*this, timestamps[0], *placeholder_groups[0]);
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results = visitor.get_moved_result(*plan->plan_node_);
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return Status::OK();
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}
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Status
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SegmentSmallIndex::FillTargetEntry(const query::Plan* plan, QueryResult& results) {
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AssertInfo(plan, "empty plan");
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auto size = results.result_distances_.size();
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Assert(results.internal_seg_offsets_.size() == size);
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Assert(results.result_offsets_.size() == size);
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Assert(results.row_data_.size() == 0);
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if (plan->schema_.get_is_auto_id()) {
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auto& uids = record_.uids_;
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for (int64_t i = 0; i < size; ++i) {
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auto seg_offset = results.internal_seg_offsets_[i];
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auto row_id = seg_offset == -1 ? -1 : uids[seg_offset];
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std::vector<char> blob(sizeof(row_id));
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memcpy(blob.data(), &row_id, sizeof(row_id));
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results.row_data_.emplace_back(std::move(blob));
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}
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} else {
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auto key_offset_opt = schema_->get_primary_key_offset();
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Assert(key_offset_opt.has_value());
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auto key_offset = key_offset_opt.value();
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auto field_meta = schema_->operator[](key_offset);
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Assert(field_meta.get_data_type() == DataType::INT64);
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auto uids = record_.get_entity<int64_t>(key_offset);
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for (int64_t i = 0; i < size; ++i) {
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auto seg_offset = results.internal_seg_offsets_[i];
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auto row_id = seg_offset == -1 ? -1 : uids->operator[](seg_offset);
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std::vector<char> blob(sizeof(row_id));
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memcpy(blob.data(), &row_id, sizeof(row_id));
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results.row_data_.emplace_back(std::move(blob));
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}
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}
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return Status::OK();
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}
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} // namespace milvus::segcore
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