mirror of
https://gitee.com/milvus-io/milvus.git
synced 2024-12-04 12:59:23 +08:00
d599407e2b
Signed-off-by: xige-16 <xi.ge@zilliz.com>
779 lines
27 KiB
C++
779 lines
27 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 <iostream>
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#include <string>
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#include <random>
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#include <gtest/gtest.h>
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#include <chrono>
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#include "pb/service_msg.pb.h"
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#include "segcore/reduce_c.h"
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#include <index/knowhere/knowhere/index/vector_index/helpers/IndexParameter.h>
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#include <index/knowhere/knowhere/index/vector_index/adapter/VectorAdapter.h>
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#include <index/knowhere/knowhere/index/vector_index/VecIndexFactory.h>
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#include <index/knowhere/knowhere/index/vector_index/IndexIVFPQ.h>
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#include <common/LoadIndex.h>
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namespace chrono = std::chrono;
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TEST(CApiTest, CollectionTest) {
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auto schema_tmp_conf = "";
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auto collection = NewCollection(schema_tmp_conf);
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DeleteCollection(collection);
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}
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TEST(CApiTest, GetCollectionNameTest) {
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auto schema_tmp_conf = "";
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auto collection = NewCollection(schema_tmp_conf);
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auto name = GetCollectionName(collection);
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assert(strcmp(name, "default-collection") == 0);
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DeleteCollection(collection);
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}
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TEST(CApiTest, SegmentTest) {
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auto schema_tmp_conf = "";
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auto collection = NewCollection(schema_tmp_conf);
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auto segment = NewSegment(collection, 0);
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DeleteCollection(collection);
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DeleteSegment(segment);
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}
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TEST(CApiTest, InsertTest) {
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auto schema_tmp_conf = "";
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auto collection = NewCollection(schema_tmp_conf);
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auto segment = NewSegment(collection, 0);
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std::vector<char> raw_data;
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std::vector<uint64_t> timestamps;
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std::vector<int64_t> uids;
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int N = 10000;
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std::default_random_engine e(67);
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for (int i = 0; i < N; ++i) {
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uids.push_back(100000 + i);
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timestamps.push_back(0);
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// append vec
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float vec[16];
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for (auto& x : vec) {
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x = e() % 2000 * 0.001 - 1.0;
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}
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raw_data.insert(raw_data.end(), (const char*)std::begin(vec), (const char*)std::end(vec));
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int age = e() % 100;
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raw_data.insert(raw_data.end(), (const char*)&age, ((const char*)&age) + sizeof(age));
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}
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auto line_sizeof = (sizeof(int) + sizeof(float) * 16);
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auto offset = PreInsert(segment, N);
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auto res = Insert(segment, offset, N, uids.data(), timestamps.data(), raw_data.data(), (int)line_sizeof, N);
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assert(res.error_code == Success);
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DeleteCollection(collection);
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DeleteSegment(segment);
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}
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TEST(CApiTest, DeleteTest) {
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auto schema_tmp_conf = "";
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auto collection = NewCollection(schema_tmp_conf);
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auto segment = NewSegment(collection, 0);
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long delete_row_ids[] = {100000, 100001, 100002};
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unsigned long delete_timestamps[] = {0, 0, 0};
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auto offset = PreDelete(segment, 3);
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auto del_res = Delete(segment, offset, 3, delete_row_ids, delete_timestamps);
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assert(del_res.error_code == Success);
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DeleteCollection(collection);
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DeleteSegment(segment);
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}
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TEST(CApiTest, SearchTest) {
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auto schema_tmp_conf = "";
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auto collection = NewCollection(schema_tmp_conf);
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auto segment = NewSegment(collection, 0);
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std::vector<char> raw_data;
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std::vector<uint64_t> timestamps;
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std::vector<int64_t> uids;
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int N = 10000;
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std::default_random_engine e(67);
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for (int i = 0; i < N; ++i) {
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uids.push_back(100000 + i);
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timestamps.push_back(0);
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// append vec
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float vec[16];
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for (auto& x : vec) {
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x = e() % 2000 * 0.001 - 1.0;
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}
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raw_data.insert(raw_data.end(), (const char*)std::begin(vec), (const char*)std::end(vec));
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int age = e() % 100;
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raw_data.insert(raw_data.end(), (const char*)&age, ((const char*)&age) + sizeof(age));
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}
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auto line_sizeof = (sizeof(int) + sizeof(float) * 16);
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auto offset = PreInsert(segment, N);
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auto ins_res = Insert(segment, offset, N, uids.data(), timestamps.data(), raw_data.data(), (int)line_sizeof, N);
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assert(ins_res.error_code == Success);
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const char* dsl_string = R"(
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{
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"bool": {
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"vector": {
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"fakevec": {
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"metric_type": "L2",
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"params": {
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"nprobe": 10
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},
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"query": "$0",
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"topk": 10
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}
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}
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}
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})";
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namespace ser = milvus::proto::service;
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int num_queries = 10;
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int dim = 16;
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std::normal_distribution<double> dis(0, 1);
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ser::PlaceholderGroup raw_group;
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auto value = raw_group.add_placeholders();
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value->set_tag("$0");
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value->set_type(ser::PlaceholderType::VECTOR_FLOAT);
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for (int i = 0; i < num_queries; ++i) {
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std::vector<float> vec;
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for (int d = 0; d < dim; ++d) {
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vec.push_back(dis(e));
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}
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// std::string line((char*)vec.data(), (char*)vec.data() + vec.size() * sizeof(float));
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value->add_values(vec.data(), vec.size() * sizeof(float));
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}
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auto blob = raw_group.SerializeAsString();
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void* plan = nullptr;
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auto status = CreatePlan(collection, dsl_string, &plan);
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assert(status.error_code == Success);
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void* placeholderGroup = nullptr;
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status = ParsePlaceholderGroup(plan, blob.data(), blob.length(), &placeholderGroup);
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assert(status.error_code == Success);
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std::vector<CPlaceholderGroup> placeholderGroups;
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placeholderGroups.push_back(placeholderGroup);
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timestamps.clear();
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timestamps.push_back(1);
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CQueryResult search_result;
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auto res = Search(segment, plan, placeholderGroups.data(), timestamps.data(), 1, &search_result);
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assert(res.error_code == Success);
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DeletePlan(plan);
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DeletePlaceholderGroup(placeholderGroup);
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DeleteQueryResult(search_result);
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DeleteCollection(collection);
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DeleteSegment(segment);
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}
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// TEST(CApiTest, BuildIndexTest) {
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// auto schema_tmp_conf = "";
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// auto collection = NewCollection(schema_tmp_conf);
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// auto segment = NewSegment(collection, 0);
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//
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// std::vector<char> raw_data;
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// std::vector<uint64_t> timestamps;
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// std::vector<int64_t> uids;
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// int N = 10000;
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// std::default_random_engine e(67);
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// for (int i = 0; i < N; ++i) {
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// uids.push_back(100000 + i);
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// timestamps.push_back(0);
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// // append vec
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// float vec[16];
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// for (auto& x : vec) {
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// x = e() % 2000 * 0.001 - 1.0;
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// }
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// raw_data.insert(raw_data.end(), (const char*)std::begin(vec), (const char*)std::end(vec));
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// int age = e() % 100;
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// raw_data.insert(raw_data.end(), (const char*)&age, ((const char*)&age) + sizeof(age));
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// }
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//
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// auto line_sizeof = (sizeof(int) + sizeof(float) * 16);
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//
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// auto offset = PreInsert(segment, N);
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//
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// auto ins_res = Insert(segment, offset, N, uids.data(), timestamps.data(), raw_data.data(), (int)line_sizeof, N);
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// assert(ins_res == 0);
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//
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// // TODO: add index ptr
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// Close(segment);
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// BuildIndex(collection, segment);
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//
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// const char* dsl_string = R"(
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// {
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// "bool": {
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// "vector": {
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// "fakevec": {
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// "metric_type": "L2",
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// "params": {
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// "nprobe": 10
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// },
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// "query": "$0",
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// "topk": 10
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// }
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// }
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// }
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// })";
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//
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// namespace ser = milvus::proto::service;
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// int num_queries = 10;
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// int dim = 16;
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// std::normal_distribution<double> dis(0, 1);
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// ser::PlaceholderGroup raw_group;
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// auto value = raw_group.add_placeholders();
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// value->set_tag("$0");
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// value->set_type(ser::PlaceholderType::VECTOR_FLOAT);
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// for (int i = 0; i < num_queries; ++i) {
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// std::vector<float> vec;
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// for (int d = 0; d < dim; ++d) {
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// vec.push_back(dis(e));
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// }
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// // std::string line((char*)vec.data(), (char*)vec.data() + vec.size() * sizeof(float));
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// value->add_values(vec.data(), vec.size() * sizeof(float));
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// }
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// auto blob = raw_group.SerializeAsString();
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//
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// auto plan = CreatePlan(collection, dsl_string);
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// auto placeholderGroup = ParsePlaceholderGroup(plan, blob.data(), blob.length());
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// std::vector<CPlaceholderGroup> placeholderGroups;
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// placeholderGroups.push_back(placeholderGroup);
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// timestamps.clear();
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// timestamps.push_back(1);
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//
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// auto search_res = Search(segment, plan, placeholderGroups.data(), timestamps.data(), 1);
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//
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// DeletePlan(plan);
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// DeletePlaceholderGroup(placeholderGroup);
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// DeleteQueryResult(search_res);
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// DeleteCollection(collection);
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// DeleteSegment(segment);
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//}
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TEST(CApiTest, IsOpenedTest) {
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auto schema_tmp_conf = "";
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auto collection = NewCollection(schema_tmp_conf);
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auto segment = NewSegment(collection, 0);
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auto is_opened = IsOpened(segment);
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assert(is_opened);
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DeleteCollection(collection);
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DeleteSegment(segment);
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}
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TEST(CApiTest, CloseTest) {
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auto schema_tmp_conf = "";
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auto collection = NewCollection(schema_tmp_conf);
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auto segment = NewSegment(collection, 0);
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auto status = Close(segment);
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assert(status == 0);
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DeleteCollection(collection);
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DeleteSegment(segment);
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}
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TEST(CApiTest, GetMemoryUsageInBytesTest) {
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auto schema_tmp_conf = "";
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auto collection = NewCollection(schema_tmp_conf);
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auto segment = NewSegment(collection, 0);
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auto old_memory_usage_size = GetMemoryUsageInBytes(segment);
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std::cout << "old_memory_usage_size = " << old_memory_usage_size << std::endl;
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std::vector<char> raw_data;
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std::vector<uint64_t> timestamps;
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std::vector<int64_t> uids;
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int N = 10000;
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std::default_random_engine e(67);
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for (int i = 0; i < N; ++i) {
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uids.push_back(100000 + i);
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timestamps.push_back(0);
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// append vec
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float vec[16];
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for (auto& x : vec) {
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x = e() % 2000 * 0.001 - 1.0;
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}
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raw_data.insert(raw_data.end(), (const char*)std::begin(vec), (const char*)std::end(vec));
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int age = e() % 100;
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raw_data.insert(raw_data.end(), (const char*)&age, ((const char*)&age) + sizeof(age));
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}
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auto line_sizeof = (sizeof(int) + sizeof(float) * 16);
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auto offset = PreInsert(segment, N);
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auto res = Insert(segment, offset, N, uids.data(), timestamps.data(), raw_data.data(), (int)line_sizeof, N);
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assert(res.error_code == Success);
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auto memory_usage_size = GetMemoryUsageInBytes(segment);
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std::cout << "new_memory_usage_size = " << memory_usage_size << std::endl;
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assert(memory_usage_size == 2785280);
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DeleteCollection(collection);
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DeleteSegment(segment);
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}
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namespace {
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auto
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generate_data(int N) {
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std::vector<float> raw_data;
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std::vector<uint64_t> timestamps;
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std::vector<int64_t> uids;
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std::default_random_engine er(42);
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std::uniform_real_distribution<> distribution(0.0, 1.0);
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std::default_random_engine ei(42);
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for (int i = 0; i < N; ++i) {
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uids.push_back(10 * N + i);
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timestamps.push_back(0);
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// append vec
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float vec[16];
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for (auto& x : vec) {
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x = distribution(er);
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}
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raw_data.insert(raw_data.end(), std::begin(vec), std::end(vec));
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int age = ei() % 100;
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raw_data.insert(raw_data.end(), (const char*)&age, ((const char*)&age) + sizeof(age));
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}
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return std::make_tuple(raw_data, timestamps, uids);
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}
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} // namespace
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// TEST(CApiTest, TestSearchPreference) {
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// auto schema_tmp_conf = "";
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// auto collection = NewCollection(schema_tmp_conf);
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// auto segment = NewSegment(collection, 0);
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//
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// auto beg = chrono::high_resolution_clock::now();
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// auto next = beg;
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// int N = 1000 * 1000 * 10;
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// auto [raw_data, timestamps, uids] = generate_data(N);
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// auto line_sizeof = (sizeof(int) + sizeof(float) * 16);
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//
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// next = chrono::high_resolution_clock::now();
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// std::cout << "generate_data: " << chrono::duration_cast<chrono::milliseconds>(next - beg).count() << "ms"
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// << std::endl;
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// beg = next;
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//
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// auto offset = PreInsert(segment, N);
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// auto res = Insert(segment, offset, N, uids.data(), timestamps.data(), raw_data.data(), (int)line_sizeof, N);
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// assert(res == 0);
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// next = chrono::high_resolution_clock::now();
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// std::cout << "insert: " << chrono::duration_cast<chrono::milliseconds>(next - beg).count() << "ms" << std::endl;
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// beg = next;
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//
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// auto N_del = N / 100;
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// std::vector<uint64_t> del_ts(N_del, 100);
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// auto pre_off = PreDelete(segment, N_del);
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// Delete(segment, pre_off, N_del, uids.data(), del_ts.data());
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//
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// next = chrono::high_resolution_clock::now();
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// std::cout << "delete1: " << chrono::duration_cast<chrono::milliseconds>(next - beg).count() << "ms" << std::endl;
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// beg = next;
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//
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// auto row_count = GetRowCount(segment);
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// assert(row_count == N);
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//
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// std::vector<long> result_ids(10 * 16);
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// std::vector<float> result_distances(10 * 16);
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//
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// CQueryInfo queryInfo{1, 10, "fakevec"};
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// auto sea_res =
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// Search(segment, queryInfo, 104, (float*)raw_data.data(), 16, result_ids.data(), result_distances.data());
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//
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// // ASSERT_EQ(sea_res, 0);
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// // ASSERT_EQ(result_ids[0], 10 * N);
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// // ASSERT_EQ(result_distances[0], 0);
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//
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// next = chrono::high_resolution_clock::now();
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// std::cout << "query1: " << chrono::duration_cast<chrono::milliseconds>(next - beg).count() << "ms" << std::endl;
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// beg = next;
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// sea_res = Search(segment, queryInfo, 104, (float*)raw_data.data(), 16, result_ids.data(),
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// result_distances.data());
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//
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// // ASSERT_EQ(sea_res, 0);
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// // ASSERT_EQ(result_ids[0], 10 * N);
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// // ASSERT_EQ(result_distances[0], 0);
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//
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// next = chrono::high_resolution_clock::now();
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// std::cout << "query2: " << chrono::duration_cast<chrono::milliseconds>(next - beg).count() << "ms" << std::endl;
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// beg = next;
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//
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// // Close(segment);
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// // BuildIndex(segment);
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//
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// next = chrono::high_resolution_clock::now();
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// std::cout << "build index: " << chrono::duration_cast<chrono::milliseconds>(next - beg).count() << "ms"
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// << std::endl;
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// beg = next;
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//
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// std::vector<int64_t> result_ids2(10);
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// std::vector<float> result_distances2(10);
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//
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// sea_res =
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// Search(segment, queryInfo, 104, (float*)raw_data.data(), 16, result_ids2.data(), result_distances2.data());
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//
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// // sea_res = Search(segment, nullptr, 104, result_ids2.data(),
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// // result_distances2.data());
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//
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// next = chrono::high_resolution_clock::now();
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// std::cout << "search10: " << chrono::duration_cast<chrono::milliseconds>(next - beg).count() << "ms" << std::endl;
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// beg = next;
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//
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// sea_res =
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// Search(segment, queryInfo, 104, (float*)raw_data.data(), 16, result_ids2.data(), result_distances2.data());
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//
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// next = chrono::high_resolution_clock::now();
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// std::cout << "search11: " << chrono::duration_cast<chrono::milliseconds>(next - beg).count() << "ms" << std::endl;
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// beg = next;
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//
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// // std::cout << "case 1" << std::endl;
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// // for (int i = 0; i < 10; ++i) {
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// // std::cout << result_ids[i] << "->" << result_distances[i] << std::endl;
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// // }
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// // std::cout << "case 2" << std::endl;
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// // for (int i = 0; i < 10; ++i) {
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// // std::cout << result_ids2[i] << "->" << result_distances2[i] << std::endl;
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// // }
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|
// //
|
|
// // for (auto x : result_ids2) {
|
|
// // ASSERT_GE(x, 10 * N + N_del);
|
|
// // ASSERT_LT(x, 10 * N + N);
|
|
// // }
|
|
//
|
|
// // auto iter = 0;
|
|
// // for(int i = 0; i < result_ids.size(); ++i) {
|
|
// // auto uid = result_ids[i];
|
|
// // auto dis = result_distances[i];
|
|
// // if(uid >= 10 * N + N_del) {
|
|
// // auto uid2 = result_ids2[iter];
|
|
// // auto dis2 = result_distances2[iter];
|
|
// // ASSERT_EQ(uid, uid2);
|
|
// // ASSERT_EQ(dis, dis2);
|
|
// // ++iter;
|
|
// // }
|
|
// // }
|
|
//
|
|
// DeleteCollection(collection);
|
|
// DeleteSegment(segment);
|
|
//}
|
|
|
|
TEST(CApiTest, GetDeletedCountTest) {
|
|
auto schema_tmp_conf = "";
|
|
auto collection = NewCollection(schema_tmp_conf);
|
|
auto segment = NewSegment(collection, 0);
|
|
|
|
long delete_row_ids[] = {100000, 100001, 100002};
|
|
unsigned long delete_timestamps[] = {0, 0, 0};
|
|
|
|
auto offset = PreDelete(segment, 3);
|
|
|
|
auto del_res = Delete(segment, offset, 3, delete_row_ids, delete_timestamps);
|
|
assert(del_res.error_code == Success);
|
|
|
|
// TODO: assert(deleted_count == len(delete_row_ids))
|
|
auto deleted_count = GetDeletedCount(segment);
|
|
assert(deleted_count == 0);
|
|
|
|
DeleteCollection(collection);
|
|
DeleteSegment(segment);
|
|
}
|
|
|
|
TEST(CApiTest, GetRowCountTest) {
|
|
auto schema_tmp_conf = "";
|
|
auto collection = NewCollection(schema_tmp_conf);
|
|
auto segment = NewSegment(collection, 0);
|
|
|
|
int N = 10000;
|
|
auto [raw_data, timestamps, uids] = generate_data(N);
|
|
auto line_sizeof = (sizeof(int) + sizeof(float) * 16);
|
|
auto offset = PreInsert(segment, N);
|
|
auto res = Insert(segment, offset, N, uids.data(), timestamps.data(), raw_data.data(), (int)line_sizeof, N);
|
|
assert(res.error_code == Success);
|
|
|
|
auto row_count = GetRowCount(segment);
|
|
assert(row_count == N);
|
|
|
|
DeleteCollection(collection);
|
|
DeleteSegment(segment);
|
|
}
|
|
|
|
// TEST(CApiTest, SchemaTest) {
|
|
// std::string schema_string =
|
|
// "id: 6873737669791618215\nname: \"collection0\"\nschema: \u003c\n "
|
|
// "field_metas: \u003c\n field_name: \"age\"\n type: INT32\n dim: 1\n \u003e\n "
|
|
// "field_metas: \u003c\n field_name: \"field_1\"\n type: VECTOR_FLOAT\n dim: 16\n \u003e\n"
|
|
// "\u003e\ncreate_time: 1600416765\nsegment_ids: 6873737669791618215\npartition_tags: \"default\"\n";
|
|
//
|
|
// auto collection = NewCollection(schema_string.data());
|
|
// auto segment = NewSegment(collection, 0);
|
|
// DeleteCollection(collection);
|
|
// DeleteSegment(segment);
|
|
//}
|
|
|
|
TEST(CApiTest, MergeInto) {
|
|
std::vector<int64_t> uids;
|
|
std::vector<float> distance;
|
|
|
|
std::vector<int64_t> new_uids;
|
|
std::vector<float> new_distance;
|
|
|
|
int64_t num_queries = 1;
|
|
int64_t topk = 2;
|
|
|
|
uids.push_back(1);
|
|
uids.push_back(2);
|
|
distance.push_back(5);
|
|
distance.push_back(1000);
|
|
|
|
new_uids.push_back(3);
|
|
new_uids.push_back(4);
|
|
new_distance.push_back(2);
|
|
new_distance.push_back(6);
|
|
|
|
auto res = MergeInto(num_queries, topk, distance.data(), uids.data(), new_distance.data(), new_uids.data());
|
|
|
|
ASSERT_EQ(res, 0);
|
|
ASSERT_EQ(uids[0], 3);
|
|
ASSERT_EQ(distance[0], 2);
|
|
ASSERT_EQ(uids[1], 1);
|
|
ASSERT_EQ(distance[1], 5);
|
|
}
|
|
|
|
TEST(CApiTest, Reduce) {
|
|
auto schema_tmp_conf = "";
|
|
auto collection = NewCollection(schema_tmp_conf);
|
|
auto segment = NewSegment(collection, 0);
|
|
|
|
std::vector<char> raw_data;
|
|
std::vector<uint64_t> timestamps;
|
|
std::vector<int64_t> uids;
|
|
int N = 10000;
|
|
std::default_random_engine e(67);
|
|
for (int i = 0; i < N; ++i) {
|
|
uids.push_back(100000 + i);
|
|
timestamps.push_back(0);
|
|
// append vec
|
|
float vec[16];
|
|
for (auto& x : vec) {
|
|
x = e() % 2000 * 0.001 - 1.0;
|
|
}
|
|
raw_data.insert(raw_data.end(), (const char*)std::begin(vec), (const char*)std::end(vec));
|
|
int age = e() % 100;
|
|
raw_data.insert(raw_data.end(), (const char*)&age, ((const char*)&age) + sizeof(age));
|
|
}
|
|
|
|
auto line_sizeof = (sizeof(int) + sizeof(float) * 16);
|
|
|
|
auto offset = PreInsert(segment, N);
|
|
|
|
auto ins_res = Insert(segment, offset, N, uids.data(), timestamps.data(), raw_data.data(), (int)line_sizeof, N);
|
|
assert(ins_res.error_code == Success);
|
|
|
|
const char* dsl_string = R"(
|
|
{
|
|
"bool": {
|
|
"vector": {
|
|
"fakevec": {
|
|
"metric_type": "L2",
|
|
"params": {
|
|
"nprobe": 10
|
|
},
|
|
"query": "$0",
|
|
"topk": 10
|
|
}
|
|
}
|
|
}
|
|
})";
|
|
|
|
namespace ser = milvus::proto::service;
|
|
int num_queries = 10;
|
|
int dim = 16;
|
|
std::normal_distribution<double> dis(0, 1);
|
|
ser::PlaceholderGroup raw_group;
|
|
auto value = raw_group.add_placeholders();
|
|
value->set_tag("$0");
|
|
value->set_type(ser::PlaceholderType::VECTOR_FLOAT);
|
|
for (int i = 0; i < num_queries; ++i) {
|
|
std::vector<float> vec;
|
|
for (int d = 0; d < dim; ++d) {
|
|
vec.push_back(dis(e));
|
|
}
|
|
// std::string line((char*)vec.data(), (char*)vec.data() + vec.size() * sizeof(float));
|
|
value->add_values(vec.data(), vec.size() * sizeof(float));
|
|
}
|
|
auto blob = raw_group.SerializeAsString();
|
|
|
|
void* plan = nullptr;
|
|
|
|
auto status = CreatePlan(collection, dsl_string, &plan);
|
|
assert(status.error_code == Success);
|
|
|
|
void* placeholderGroup = nullptr;
|
|
status = ParsePlaceholderGroup(plan, blob.data(), blob.length(), &placeholderGroup);
|
|
assert(status.error_code == Success);
|
|
|
|
std::vector<CPlaceholderGroup> placeholderGroups;
|
|
placeholderGroups.push_back(placeholderGroup);
|
|
timestamps.clear();
|
|
timestamps.push_back(1);
|
|
|
|
std::vector<CQueryResult> results;
|
|
CQueryResult res1;
|
|
CQueryResult res2;
|
|
auto res = Search(segment, plan, placeholderGroups.data(), timestamps.data(), 1, &res1);
|
|
assert(res.error_code == Success);
|
|
res = Search(segment, plan, placeholderGroups.data(), timestamps.data(), 1, &res2);
|
|
assert(res.error_code == Success);
|
|
results.push_back(res1);
|
|
results.push_back(res2);
|
|
|
|
bool is_selected[1] = {false};
|
|
status = ReduceQueryResults(results.data(), 1, is_selected);
|
|
assert(status.error_code == Success);
|
|
FillTargetEntry(segment, plan, res1);
|
|
void* reorganize_search_result = nullptr;
|
|
status = ReorganizeQueryResults(&reorganize_search_result, placeholderGroups.data(), 1, results.data(), is_selected,
|
|
1, plan);
|
|
assert(status.error_code == Success);
|
|
auto hits_blob_size = GetHitsBlobSize(reorganize_search_result);
|
|
assert(hits_blob_size > 0);
|
|
std::vector<char> hits_blob;
|
|
hits_blob.resize(hits_blob_size);
|
|
GetHitsBlob(reorganize_search_result, hits_blob.data());
|
|
assert(hits_blob.data() != nullptr);
|
|
auto num_queries_group = GetNumQueriesPeerGroup(reorganize_search_result, 0);
|
|
assert(num_queries_group == 10);
|
|
std::vector<int64_t> hit_size_peer_query;
|
|
hit_size_peer_query.resize(num_queries_group);
|
|
GetHitSizePeerQueries(reorganize_search_result, 0, hit_size_peer_query.data());
|
|
assert(hit_size_peer_query[0] > 0);
|
|
|
|
DeletePlan(plan);
|
|
DeletePlaceholderGroup(placeholderGroup);
|
|
DeleteQueryResult(res1);
|
|
DeleteQueryResult(res2);
|
|
DeleteMarshaledHits(reorganize_search_result);
|
|
DeleteCollection(collection);
|
|
DeleteSegment(segment);
|
|
}
|
|
|
|
TEST(CApiTest, LoadIndexInfo) {
|
|
// generator index
|
|
constexpr auto DIM = 16;
|
|
constexpr auto K = 10;
|
|
|
|
auto N = 1024 * 10;
|
|
auto [raw_data, timestamps, uids] = generate_data(N);
|
|
auto indexing = std::make_shared<milvus::knowhere::IVFPQ>();
|
|
auto conf = milvus::knowhere::Config{{milvus::knowhere::meta::DIM, DIM},
|
|
{milvus::knowhere::meta::TOPK, K},
|
|
{milvus::knowhere::IndexParams::nlist, 100},
|
|
{milvus::knowhere::IndexParams::nprobe, 4},
|
|
{milvus::knowhere::IndexParams::m, 4},
|
|
{milvus::knowhere::IndexParams::nbits, 8},
|
|
{milvus::knowhere::Metric::TYPE, milvus::knowhere::Metric::L2},
|
|
{milvus::knowhere::meta::DEVICEID, 0}};
|
|
|
|
auto database = milvus::knowhere::GenDataset(N, DIM, raw_data.data());
|
|
indexing->Train(database, conf);
|
|
indexing->AddWithoutIds(database, conf);
|
|
EXPECT_EQ(indexing->Count(), N);
|
|
EXPECT_EQ(indexing->Dim(), DIM);
|
|
auto binary_set = indexing->Serialize(conf);
|
|
CBinarySet c_binary_set = (CBinarySet)&binary_set;
|
|
|
|
void* c_load_index_info = nullptr;
|
|
auto status = NewLoadIndexInfo(&c_load_index_info);
|
|
assert(status.error_code == Success);
|
|
std::string index_param_key1 = "index_type";
|
|
std::string index_param_value1 = "IVF_PQ";
|
|
status = AppendIndexParam(c_load_index_info, index_param_key1.data(), index_param_value1.data());
|
|
std::string index_param_key2 = "index_mode";
|
|
std::string index_param_value2 = "cpu";
|
|
status = AppendIndexParam(c_load_index_info, index_param_key2.data(), index_param_value2.data());
|
|
assert(status.error_code == Success);
|
|
std::string field_name = "field0";
|
|
status = AppendFieldInfo(c_load_index_info, field_name.data(), 0);
|
|
assert(status.error_code == Success);
|
|
status = AppendIndex(c_load_index_info, c_binary_set);
|
|
assert(status.error_code == Success);
|
|
DeleteLoadIndexInfo(c_load_index_info);
|
|
}
|
|
|
|
TEST(CApiTest, LoadIndex_Search) {
|
|
// generator index
|
|
constexpr auto DIM = 16;
|
|
constexpr auto K = 10;
|
|
|
|
auto N = 1024 * 1024 * 10;
|
|
auto num_query = 100;
|
|
auto [raw_data, timestamps, uids] = generate_data(N);
|
|
auto indexing = std::make_shared<milvus::knowhere::IVFPQ>();
|
|
auto conf = milvus::knowhere::Config{{milvus::knowhere::meta::DIM, DIM},
|
|
{milvus::knowhere::meta::TOPK, K},
|
|
{milvus::knowhere::IndexParams::nlist, 100},
|
|
{milvus::knowhere::IndexParams::nprobe, 4},
|
|
{milvus::knowhere::IndexParams::m, 4},
|
|
{milvus::knowhere::IndexParams::nbits, 8},
|
|
{milvus::knowhere::Metric::TYPE, milvus::knowhere::Metric::L2},
|
|
{milvus::knowhere::meta::DEVICEID, 0}};
|
|
|
|
auto database = milvus::knowhere::GenDataset(N, DIM, raw_data.data());
|
|
indexing->Train(database, conf);
|
|
indexing->AddWithoutIds(database, conf);
|
|
|
|
EXPECT_EQ(indexing->Count(), N);
|
|
EXPECT_EQ(indexing->Dim(), DIM);
|
|
|
|
// serializ index to binarySet
|
|
auto binary_set = indexing->Serialize(conf);
|
|
|
|
// fill loadIndexInfo
|
|
LoadIndexInfo load_index_info;
|
|
auto& index_params = load_index_info.index_params;
|
|
index_params["index_type"] = "IVF_PQ";
|
|
index_params["index_mode"] = "CPU";
|
|
auto mode = milvus::knowhere::IndexMode::MODE_CPU;
|
|
load_index_info.index =
|
|
milvus::knowhere::VecIndexFactory::GetInstance().CreateVecIndex(index_params["index_type"], mode);
|
|
load_index_info.index->Load(binary_set);
|
|
|
|
// search
|
|
auto query_dataset = milvus::knowhere::GenDataset(num_query, DIM, raw_data.data() + DIM * 4200);
|
|
|
|
auto result = indexing->Query(query_dataset, conf, nullptr);
|
|
|
|
auto ids = result->Get<int64_t*>(milvus::knowhere::meta::IDS);
|
|
auto dis = result->Get<float*>(milvus::knowhere::meta::DISTANCE);
|
|
for (int i = 0; i < std::min(num_query * K, 100); ++i) {
|
|
std::cout << ids[i] << "->" << dis[i] << std::endl;
|
|
}
|
|
} |