mirror of
https://gitee.com/milvus-io/milvus.git
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14ef405a6b
Signed-off-by: yudong.cai <yudong.cai@zilliz.com>
124 lines
3.8 KiB
C++
124 lines
3.8 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 <cstdint>
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#include <benchmark/benchmark.h>
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#include <string>
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#include "segcore/SegmentGrowing.h"
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#include "segcore/SegmentSealed.h"
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#include "test_utils/DataGen.h"
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using namespace milvus;
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using namespace milvus::query;
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using namespace milvus::segcore;
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static int dim = 768;
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const auto schema = []() {
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auto schema = std::make_shared<Schema>();
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schema->AddDebugField("fakevec", DataType::VECTOR_FLOAT, dim, MetricType::METRIC_L2);
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return schema;
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}();
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const auto plan = [] {
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std::string dsl = R"({
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"bool": {
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"must": [
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{
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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": 5
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}
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}
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}
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]
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}
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})";
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auto plan = CreatePlan(*schema, dsl);
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return plan;
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}();
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auto ph_group = [] {
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auto num_queries = 10;
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auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, 1024);
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auto ph_group = ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
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return ph_group;
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}();
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static void
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Search_SmallIndex(benchmark::State& state) {
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// schema->AddDebugField("age", DataType::FLOAT);
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static int64_t N = 1024 * 32;
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const auto dataset_ = [] {
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auto dataset_ = DataGen(schema, N);
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return dataset_;
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}();
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auto is_small_index = state.range(0);
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auto chunk_rows = state.range(1) * 1024;
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auto segconf = SegcoreConfig::default_config();
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segconf.set_chunk_rows(chunk_rows);
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auto segment = CreateGrowingSegment(schema, segconf);
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if (!is_small_index) {
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segment->disable_small_index();
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}
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segment->PreInsert(N);
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ColumnBasedRawData raw_data;
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raw_data.columns_ = dataset_.cols_;
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raw_data.count = N;
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segment->Insert(0, N, dataset_.row_ids_.data(), dataset_.timestamps_.data(), raw_data);
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Timestamp time = 10000000;
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for (auto _ : state) {
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auto qr = segment->Search(plan.get(), *ph_group, time);
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}
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}
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BENCHMARK(Search_SmallIndex)->MinTime(5)->ArgsProduct({{true, false}, {8, 16, 32}});
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static void
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Search_Sealed(benchmark::State& state) {
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auto segment = CreateSealedSegment(schema);
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static int64_t N = 1024 * 1024;
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const auto dataset_ = [] {
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auto dataset_ = DataGen(schema, N);
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return dataset_;
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}();
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SealedLoader(dataset_, *segment);
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auto choice = state.range(0);
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if (choice == 0) {
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// Brute Force
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} else if (choice == 1) {
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// ivf
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auto vec = (const float*)dataset_.cols_[0].data();
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auto indexing = GenIndexing(N, dim, vec);
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LoadIndexInfo info;
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info.index = indexing;
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info.field_id = (*schema)[FieldName("fakevec")].get_id().get();
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info.index_params["index_type"] = "IVF";
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info.index_params["index_mode"] = "CPU";
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info.index_params["metric_type"] = MetricTypeToName(MetricType::METRIC_L2);
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segment->LoadIndex(info);
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}
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Timestamp time = 10000000;
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for (auto _ : state) {
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auto qr = segment->Search(plan.get(), *ph_group, time);
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}
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}
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BENCHMARK(Search_Sealed)->MinTime(5)->Arg(1)->Arg(0);
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