milvus/cpp/unittest/db/db_tests.cpp

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////////////////////////////////////////////////////////////////////////////////
// Copyright 上海赜睿信息科技有限公司(Zilliz) - All Rights Reserved
// Unauthorized copying of this file, via any medium is strictly prohibited.
// Proprietary and confidential.
////////////////////////////////////////////////////////////////////////////////
#include <gtest/gtest.h>
#include <thread>
#include <easylogging++.h>
#include <chrono>
#include "db/DB.h"
using namespace zilliz::vecwise;
#define TIMING
#ifdef TIMING
#define INIT_TIMER auto start = std::chrono::high_resolution_clock::now();
#define START_TIMER start = std::chrono::high_resolution_clock::now();
#define STOP_TIMER(name) LOG(DEBUG) << "RUNTIME of " << name << ": " << \
std::chrono::duration_cast<std::chrono::milliseconds>( \
std::chrono::high_resolution_clock::now()-start \
).count() << " ms ";
#else
#define INIT_TIMER
#define START_TIMER
#define STOP_TIMER(name)
#endif
class DBTest : public ::testing::Test {
protected:
virtual void SetUp() {
el::Configurations defaultConf;
defaultConf.setToDefault();
defaultConf.set(el::Level::Debug,
el::ConfigurationType::Format, "[%thread-%datetime-%level]: %msg (%fbase:%line)");
el::Loggers::reconfigureLogger("default", defaultConf);
}
};
namespace {
void ASSERT_STATS(engine::Status& stat) {
ASSERT_TRUE(stat.ok());
if(!stat.ok()) {
std::cout << stat.ToString() << std::endl;
}
}
}
TEST_F(DBTest, DB_TEST) {
static const std::string group_name = "test_group";
static const int group_dim = 256;
engine::Options opt;
opt.memory_sync_interval = 1;
opt.index_trigger_size = 1024*group_dim;
opt.meta.backend_uri = "http://127.0.0.1";
opt.meta.path = "/tmp/vecwise_test/db_test";
engine::DB* db = nullptr;
engine::DB::Open(opt, &db);
ASSERT_TRUE(db != nullptr);
engine::meta::GroupSchema group_info;
group_info.dimension = group_dim;
group_info.group_id = group_name;
engine::Status stat = db->add_group(group_info);
engine::meta::GroupSchema group_info_get;
group_info_get.group_id = group_name;
stat = db->get_group(group_info_get);
ASSERT_STATS(stat);
ASSERT_EQ(group_info_get.dimension, group_dim);
engine::IDNumbers vector_ids;
engine::IDNumbers target_ids;
int d = 256;
int nb = 50;
float *xb = new float[d * nb];
for(int i = 0; i < nb; i++) {
for(int j = 0; j < d; j++) xb[d * i + j] = drand48();
xb[d * i] += i / 2000.;
}
int qb = 1;
float *qxb = new float[d * qb];
for(int i = 0; i < qb; i++) {
for(int j = 0; j < d; j++) qxb[d * i + j] = drand48();
qxb[d * i] += i / 2000.;
}
std::thread search([&]() {
engine::QueryResults results;
int k = 10;
std::this_thread::sleep_for(std::chrono::seconds(2));
INIT_TIMER;
std::stringstream ss;
long count = 0;
for (auto j=0; j<8; ++j) {
ss.str("");
db->count(group_name, count);
ss << "Search " << j << " With Size " << count;
START_TIMER;
stat = db->search(group_name, k, qb, qxb, results);
STOP_TIMER(ss.str());
ASSERT_STATS(stat);
ASSERT_EQ(results[0][0], target_ids[0]);
std::this_thread::sleep_for(std::chrono::seconds(1));
}
});
int loop = 100000;
for (auto i=0; i<loop; ++i) {
if (i==40) {
db->add_vectors(group_name, qb, qxb, target_ids);
} else {
db->add_vectors(group_name, nb, xb, vector_ids);
}
std::this_thread::sleep_for(std::chrono::microseconds(5));
}
search.join();
delete [] xb;
delete [] qxb;
delete db;
engine::DB::Open(opt, &db);
db->drop_all();
delete db;
};
TEST_F(DBTest, SEARCH_TEST) {
static const std::string group_name = "test_group";
static const int group_dim = 256;
engine::Options opt;
opt.meta.backend_uri = "http://127.0.0.1";
opt.meta.path = "/tmp/search_test";
opt.index_trigger_size = 100000 * group_dim;
opt.memory_sync_interval = 1;
opt.merge_trigger_number = 1;
engine::DB* db = nullptr;
engine::DB::Open(opt, &db);
ASSERT_TRUE(db != nullptr);
engine::meta::GroupSchema group_info;
group_info.dimension = group_dim;
group_info.group_id = group_name;
engine::Status stat = db->add_group(group_info);
//ASSERT_STATS(stat);
engine::meta::GroupSchema group_info_get;
group_info_get.group_id = group_name;
stat = db->get_group(group_info_get);
ASSERT_STATS(stat);
ASSERT_EQ(group_info_get.dimension, group_dim);
// prepare raw data
size_t nb = 250000;
size_t nq = 10;
size_t k = 5;
std::vector<float> xb(nb*group_dim);
std::vector<float> xq(nq*group_dim);
std::vector<long> ids(nb);
std::random_device rd;
std::mt19937 gen(rd());
std::uniform_real_distribution<> dis_xt(-1.0, 1.0);
for (size_t i = 0; i < nb*group_dim; i++) {
xb[i] = dis_xt(gen);
if (i < nb){
ids[i] = i;
}
}
for (size_t i = 0; i < nq*group_dim; i++) {
xq[i] = dis_xt(gen);
}
// result data
//std::vector<long> nns_gt(k*nq);
std::vector<long> nns(k*nq); // nns = nearst neg search
//std::vector<float> dis_gt(k*nq);
std::vector<float> dis(k*nq);
// prepare ground-truth
//faiss::Index* index_gt(faiss::index_factory(group_dim, "IDMap,Flat"));
//index_gt->add_with_ids(nb, xb.data(), ids.data());
//index_gt->search(nq, xq.data(), 1, dis_gt.data(), nns_gt.data());
// insert data
const int batch_size = 100;
for (int j = 0; j < nb / batch_size; ++j) {
stat = db->add_vectors(group_name, batch_size, xb.data()+batch_size*j*group_dim, ids);
if (j == 200){ sleep(1);}
ASSERT_STATS(stat);
}
sleep(3); // wait until build index finish
engine::QueryResults results;
stat = db->search(group_name, k, nq, xq.data(), results);
ASSERT_STATS(stat);
// TODO(linxj): add groundTruth assert
delete db;
engine::DB::Open(opt, &db);
db->drop_all();
delete db;
};