test/milvus
1
0
Fork 0
mirror of https://gitee.com/milvus-io/milvus.git synced 2024-11-30 19:08:30 +08:00
Code Issues Actions 11 Packages Projects Releases Wiki Activity

Merge branch 'branch-0.3.1' into 'branch-0.3.1'

Browse Source 
MS-266 Improve topk reduce time by using multi-threads

See merge request megasearch/milvus!271

Former-commit-id: c5b0ce9ebbd2a60fe7797b38996a70293c577789
This commit is contained in:
jinhai 2019-07-24 17:52:29 +08:00
commit 4a6b1779f6
6 changed files with 248 additions and 58 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
cpp/conf/server_config.template
View File

@ -8,6 +8,8 @@ db_config:
db_path: @MILVUS_DB_PATH@ # milvus data storage path
db_slave_path: # secondry data storage path, split by semicolon
parallel_reduce: true # use multi-threads to reduce topk result
# URI format: dialect://username:password@host:port/database
# All parts except dialect are optional, but you MUST include the delimiters
# Currently dialect supports mysql or sqlite

1
cpp/src/cache/CacheMgr.cpp vendored
View File

@ -49,7 +49,6 @@ DataObjPtr CacheMgr::GetItem(const std::string& key) {
engine::Index_ptr CacheMgr::GetIndex(const std::string& key) {
DataObjPtr obj = GetItem(key);
if(obj != nullptr) {
SERVER_LOG_ERROR << "Can't get object from key: " << key;
return obj->data();
}

20
cpp/src/db/DBImpl.cpp
View File

@ -89,7 +89,7 @@ DBImpl::DBImpl(const Options& options)
meta_ptr_ = DBMetaImplFactory::Build(options.meta, options.mode);
mem_mgr_ = MemManagerFactory::Build(meta_ptr_, options_);
if (options.mode != Options::MODE::READ_ONLY) {
ENGINE_LOG_INFO << "StartTimerTasks";
ENGINE_LOG_TRACE << "StartTimerTasks";
StartTimerTasks();
}
@ -297,7 +297,7 @@ void DBImpl::StartMetricTask() {
return;
}
ENGINE_LOG_DEBUG << "Start metric task";
ENGINE_LOG_TRACE << "Start metric task";
server::Metrics::GetInstance().KeepingAliveCounterIncrement(METRIC_ACTION_INTERVAL);
int64_t cache_usage = cache::CpuCacheMgr::GetInstance()->CacheUsage();
@ -312,7 +312,7 @@ void DBImpl::StartMetricTask() {
server::Metrics::GetInstance().GPUMemoryUsageGaugeSet();
server::Metrics::GetInstance().OctetsSet();
ENGINE_LOG_DEBUG << "Metric task finished";
ENGINE_LOG_TRACE << "Metric task finished";
}
void DBImpl::StartCompactionTask() {
@ -322,8 +322,6 @@ void DBImpl::StartCompactionTask() {
return;
}
ENGINE_LOG_DEBUG << "Serialize insert cache";
//serialize memory data
std::set<std::string> temp_table_ids;
mem_mgr_->Serialize(temp_table_ids);
@ -331,7 +329,9 @@ void DBImpl::StartCompactionTask() {
compact_table_ids_.insert(id);
}
ENGINE_LOG_DEBUG << "Insert cache serialized";
if(!temp_table_ids.empty()) {
SERVER_LOG_DEBUG << "Insert cache serialized";
}
//compactiong has been finished?
if(!compact_thread_results_.empty()) {
@ -433,7 +433,7 @@ Status DBImpl::BackgroundMergeFiles(const std::string& table_id) {
}
void DBImpl::BackgroundCompaction(std::set<std::string> table_ids) {
ENGINE_LOG_DEBUG << " Background compaction thread start";
ENGINE_LOG_TRACE << " Background compaction thread start";
Status status;
for (auto& table_id : table_ids) {
@ -452,7 +452,7 @@ void DBImpl::BackgroundCompaction(std::set<std::string> table_ids) {
}
meta_ptr_->CleanUpFilesWithTTL(ttl);
ENGINE_LOG_DEBUG << " Background compaction thread exit";
ENGINE_LOG_TRACE << " Background compaction thread exit";
}
void DBImpl::StartBuildIndexTask(bool force) {
@ -581,7 +581,7 @@ Status DBImpl::BuildIndexByTable(const std::string& table_id) {
}
void DBImpl::BackgroundBuildIndex() {
ENGINE_LOG_DEBUG << " Background build index thread start";
ENGINE_LOG_TRACE << " Background build index thread start";
std::unique_lock<std::mutex> lock(build_index_mutex_);
meta::TableFilesSchema to_index_files;
@ -599,7 +599,7 @@ void DBImpl::BackgroundBuildIndex() {
}
}
ENGINE_LOG_DEBUG << " Background build index thread exit";
ENGINE_LOG_TRACE << " Background build index thread exit";
}
Status DBImpl::DropAll() {

108
cpp/src/db/scheduler/task/SearchTask.cpp
View File

@ -5,14 +5,60 @@
******************************************************************************/
#include "SearchTask.h"
#include "metrics/Metrics.h"
#include "utils/Log.h"
#include "db/Log.h"
#include "utils/TimeRecorder.h"
#include <thread>
namespace zilliz {
namespace milvus {
namespace engine {
namespace {
static constexpr size_t PARALLEL_REDUCE_THRESHOLD = 10000;
static constexpr size_t PARALLEL_REDUCE_BATCH = 1000;
bool NeedParallelReduce(uint64_t nq, uint64_t topk) {
server::ServerConfig &config = server::ServerConfig::GetInstance();
server::ConfigNode& db_config = config.GetConfig(server::CONFIG_DB);
bool need_parallel = db_config.GetBoolValue(server::CONFIG_DB_PARALLEL_REDUCE, true);
if(!need_parallel) {
return false;
}
return nq*topk >= PARALLEL_REDUCE_THRESHOLD;
}
void ParallelReduce(std::function<void(size_t, size_t)>& reduce_function, size_t max_index) {
size_t reduce_batch = PARALLEL_REDUCE_BATCH;
auto thread_count = std::thread::hardware_concurrency() - 1; //not all core do this work
if(thread_count > 0) {
reduce_batch = max_index/thread_count + 1;
}
ENGINE_LOG_DEBUG << "use " << thread_count <<
" thread parallelly do reduce, each thread process " << reduce_batch << " vectors";
std::vector<std::shared_ptr<std::thread> > thread_array;
size_t from_index = 0;
while(from_index < max_index) {
size_t to_index = from_index + reduce_batch;
if(to_index > max_index) {
to_index = max_index;
}
auto reduce_thread = std::make_shared<std::thread>(reduce_function, from_index, to_index);
thread_array.push_back(reduce_thread);
from_index = to_index;
}
for(auto& thread_ptr : thread_array) {
thread_ptr->join();
}
}
void CollectDurationMetrics(int index_type, double total_time) {
switch(index_type) {
case meta::TableFileSchema::RAW: {
@ -32,7 +78,7 @@ void CollectDurationMetrics(int index_type, double total_time) {
std::string GetMetricType() {
server::ServerConfig &config = server::ServerConfig::GetInstance();
server::ConfigNode engine_config = config.GetConfig(server::CONFIG_ENGINE);
server::ConfigNode& engine_config = config.GetConfig(server::CONFIG_ENGINE);
return engine_config.GetValue(server::CONFIG_METRICTYPE, "L2");
}
@ -51,7 +97,7 @@ std::shared_ptr<IScheduleTask> SearchTask::Execute() {
return nullptr;
}
SERVER_LOG_DEBUG << "Searching in file id:" << index_id_<< " with "
ENGINE_LOG_DEBUG << "Searching in file id:" << index_id_<< " with "
<< search_contexts_.size() << " tasks";
server::TimeRecorder rc("DoSearch file id:" + std::to_string(index_id_));
@ -79,6 +125,9 @@ std::shared_ptr<IScheduleTask> SearchTask::Execute() {
auto spec_k = index_engine_->Count() < context->topk() ? index_engine_->Count() : context->topk();
SearchTask::ClusterResult(output_ids, output_distence, context->nq(), spec_k, result_set);
span = rc.RecordSection("cluster result for context:" + context->Identity());
context->AccumReduceCost(span);
//step 4: pick up topk result
SearchTask::TopkResult(result_set, inner_k, metric_l2, context->GetResult());
@ -86,7 +135,7 @@ std::shared_ptr<IScheduleTask> SearchTask::Execute() {
context->AccumReduceCost(span);
} catch (std::exception& ex) {
SERVER_LOG_ERROR << "SearchTask encounter exception: " << ex.what();
ENGINE_LOG_ERROR << "SearchTask encounter exception: " << ex.what();
context->IndexSearchDone(index_id_);//mark as done avoid dead lock, even search failed
continue;
}
@ -112,23 +161,32 @@ Status SearchTask::ClusterResult(const std::vector<long> &output_ids,
if(output_ids.size() < nq*topk || output_distence.size() < nq*topk) {
std::string msg = "Invalid id array size: " + std::to_string(output_ids.size()) +
" distance array size: " + std::to_string(output_distence.size());
SERVER_LOG_ERROR << msg;
ENGINE_LOG_ERROR << msg;
return Status::Error(msg);
}
result_set.clear();
result_set.reserve(nq);
for (auto i = 0; i < nq; i++) {
SearchContext::Id2DistanceMap id_distance;
id_distance.reserve(topk);
for (auto k = 0; k < topk; k++) {
uint64_t index = i * topk + k;
if(output_ids[index] < 0) {
continue;
result_set.resize(nq);
std::function<void(size_t, size_t)> reduce_worker = [&](size_t from_index, size_t to_index) {
for (auto i = from_index; i < to_index; i++) {
SearchContext::Id2DistanceMap id_distance;
id_distance.reserve(topk);
for (auto k = 0; k < topk; k++) {
uint64_t index = i * topk + k;
if(output_ids[index] < 0) {
continue;
}
id_distance.push_back(std::make_pair(output_ids[index], output_distence[index]));
}
id_distance.push_back(std::make_pair(output_ids[index], output_distence[index]));
result_set[i] = id_distance;
}
result_set.emplace_back(id_distance);
};
if(NeedParallelReduce(nq, topk)) {
ParallelReduce(reduce_worker, nq);
} else {
reduce_worker(0, nq);
}
return Status::OK();
@ -140,7 +198,7 @@ Status SearchTask::MergeResult(SearchContext::Id2DistanceMap &distance_src,
bool ascending) {
//Note: the score_src and score_target are already arranged by score in ascending order
if(distance_src.empty()) {
SERVER_LOG_WARNING << "Empty distance source array";
ENGINE_LOG_WARNING << "Empty distance source array";
return Status::OK();
}
@ -218,14 +276,22 @@ Status SearchTask::TopkResult(SearchContext::ResultSet &result_src,
if (result_src.size() != result_target.size()) {
std::string msg = "Invalid result set size";
SERVER_LOG_ERROR << msg;
ENGINE_LOG_ERROR << msg;
return Status::Error(msg);
}
for (size_t i = 0; i < result_src.size(); i++) {
SearchContext::Id2DistanceMap &score_src = result_src[i];
SearchContext::Id2DistanceMap &score_target = result_target[i];
SearchTask::MergeResult(score_src, score_target, topk, ascending);
std::function<void(size_t, size_t)> ReduceWorker = [&](size_t from_index, size_t to_index) {
for (size_t i = from_index; i < to_index; i++) {
SearchContext::Id2DistanceMap &score_src = result_src[i];
SearchContext::Id2DistanceMap &score_target = result_target[i];
SearchTask::MergeResult(score_src, score_target, topk, ascending);
}
};
if(NeedParallelReduce(result_src.size(), topk)) {
ParallelReduce(ReduceWorker, result_src.size());
} else {
ReduceWorker(0, result_src.size());
}
return Status::OK();

1
cpp/src/server/ServerConfig.h
View File

@ -29,6 +29,7 @@ static const std::string CONFIG_DB_INDEX_TRIGGER_SIZE = "index_building_threshol
static const std::string CONFIG_DB_ARCHIVE_DISK = "archive_disk_threshold";
static const std::string CONFIG_DB_ARCHIVE_DAYS = "archive_days_threshold";
static const std::string CONFIG_DB_INSERT_BUFFER_SIZE = "insert_buffer_size";
static const std::string CONFIG_DB_PARALLEL_REDUCE = "parallel_reduce";
static const std::string CONFIG_LOG = "log_config";

174
cpp/unittest/db/search_test.cpp
View File

@ -6,6 +6,8 @@
#include <gtest/gtest.h>
#include "db/scheduler/task/SearchTask.h"
#include "utils/TimeRecorder.h"
#include <cmath>
#include <vector>
@ -17,27 +19,33 @@ static constexpr uint64_t NQ = 15;
static constexpr uint64_t TOP_K = 64;
void BuildResult(uint64_t nq,
uint64_t top_k,
uint64_t topk,
bool ascending,
std::vector<long> &output_ids,
std::vector<float> &output_distence) {
output_ids.clear();
output_ids.resize(nq*top_k);
output_ids.resize(nq*topk);
output_distence.clear();
output_distence.resize(nq*top_k);
output_distence.resize(nq*topk);
for(uint64_t i = 0; i < nq; i++) {
for(uint64_t j = 0; j < top_k; j++) {
output_ids[i * top_k + j] = (long)(drand48()*100000);
output_distence[i * top_k + j] = j + drand48();
for(uint64_t j = 0; j < topk; j++) {
output_ids[i * topk + j] = (long)(drand48()*100000);
output_distence[i * topk + j] = ascending ? (j + drand48()) : ((topk - j) + drand48());
}
}
}
void CheckResult(const engine::SearchContext::Id2DistanceMap& src_1,
const engine::SearchContext::Id2DistanceMap& src_2,
const engine::SearchContext::Id2DistanceMap& target) {
const engine::SearchContext::Id2DistanceMap& target,
bool ascending) {
for(uint64_t i = 0; i < target.size() - 1; i++) {
ASSERT_LE(target[i].second, target[i + 1].second);
if(ascending) {
ASSERT_LE(target[i].second, target[i + 1].second);
} else {
ASSERT_GE(target[i].second, target[i + 1].second);
}
}
using ID2DistMap = std::map<long, float>;
@ -57,9 +65,52 @@ void CheckResult(const engine::SearchContext::Id2DistanceMap& src_1,
}
}
void CheckCluster(const std::vector<long>& target_ids,
const std::vector<float>& target_distence,
const engine::SearchContext::ResultSet& src_result,
int64_t nq,
int64_t topk) {
ASSERT_EQ(src_result.size(), nq);
for(int64_t i = 0; i < nq; i++) {
auto& res = src_result[i];
ASSERT_EQ(res.size(), topk);
if(res.empty()) {
continue;
}
ASSERT_EQ(res[0].first, target_ids[i*topk]);
ASSERT_EQ(res[topk - 1].first, target_ids[i*topk + topk - 1]);
}
}
void CheckTopkResult(const engine::SearchContext::ResultSet& src_result,
bool ascending,
int64_t nq,
int64_t topk) {
ASSERT_EQ(src_result.size(), nq);
for(int64_t i = 0; i < nq; i++) {
auto& res = src_result[i];
ASSERT_EQ(res.size(), topk);
if(res.empty()) {
continue;
}
for(int64_t k = 0; k < topk - 1; k++) {
if(ascending) {
ASSERT_LE(res[k].second, res[k + 1].second);
} else {
ASSERT_GE(res[k].second, res[k + 1].second);
}
}
}
}
}
TEST(DBSearchTest, TOPK_TEST) {
bool ascending = true;
std::vector<long> target_ids;
std::vector<float> target_distence;
engine::SearchContext::ResultSet src_result;
@ -67,19 +118,19 @@ TEST(DBSearchTest, TOPK_TEST) {
ASSERT_FALSE(status.ok());
ASSERT_TRUE(src_result.empty());
BuildResult(NQ, TOP_K, target_ids, target_distence);
BuildResult(NQ, TOP_K, ascending, target_ids, target_distence);
status = engine::SearchTask::ClusterResult(target_ids, target_distence, NQ, TOP_K, src_result);
ASSERT_TRUE(status.ok());
ASSERT_EQ(src_result.size(), NQ);
engine::SearchContext::ResultSet target_result;
status = engine::SearchTask::TopkResult(target_result, TOP_K, true, target_result);
status = engine::SearchTask::TopkResult(target_result, TOP_K, ascending, target_result);
ASSERT_TRUE(status.ok());
status = engine::SearchTask::TopkResult(target_result, TOP_K, true, src_result);
status = engine::SearchTask::TopkResult(target_result, TOP_K, ascending, src_result);
ASSERT_FALSE(status.ok());
status = engine::SearchTask::TopkResult(src_result, TOP_K, true, target_result);
status = engine::SearchTask::TopkResult(src_result, TOP_K, ascending, target_result);
ASSERT_TRUE(status.ok());
ASSERT_TRUE(src_result.empty());
ASSERT_EQ(target_result.size(), NQ);
@ -87,21 +138,21 @@ TEST(DBSearchTest, TOPK_TEST) {
std::vector<long> src_ids;
std::vector<float> src_distence;
uint64_t wrong_topk = TOP_K - 10;
BuildResult(NQ, wrong_topk, src_ids, src_distence);
BuildResult(NQ, wrong_topk, ascending, src_ids, src_distence);
status = engine::SearchTask::ClusterResult(src_ids, src_distence, NQ, wrong_topk, src_result);
ASSERT_TRUE(status.ok());
status = engine::SearchTask::TopkResult(src_result, TOP_K, true, target_result);
status = engine::SearchTask::TopkResult(src_result, TOP_K, ascending, target_result);
ASSERT_TRUE(status.ok());
for(uint64_t i = 0; i < NQ; i++) {
ASSERT_EQ(target_result[i].size(), TOP_K);
}
wrong_topk = TOP_K + 10;
BuildResult(NQ, wrong_topk, src_ids, src_distence);
BuildResult(NQ, wrong_topk, ascending, src_ids, src_distence);
status = engine::SearchTask::TopkResult(src_result, TOP_K, true, target_result);
status = engine::SearchTask::TopkResult(src_result, TOP_K, ascending, target_result);
ASSERT_TRUE(status.ok());
for(uint64_t i = 0; i < NQ; i++) {
ASSERT_EQ(target_result[i].size(), TOP_K);
@ -109,6 +160,7 @@ TEST(DBSearchTest, TOPK_TEST) {
}
TEST(DBSearchTest, MERGE_TEST) {
bool ascending = true;
std::vector<long> target_ids;
std::vector<float> target_distence;
std::vector<long> src_ids;
@ -116,8 +168,8 @@ TEST(DBSearchTest, MERGE_TEST) {
engine::SearchContext::ResultSet src_result, target_result;
uint64_t src_count = 5, target_count = 8;
BuildResult(1, src_count, src_ids, src_distence);
BuildResult(1, target_count, target_ids, target_distence);
BuildResult(1, src_count, ascending, src_ids, src_distence);
BuildResult(1, target_count, ascending, target_ids, target_distence);
auto status = engine::SearchTask::ClusterResult(src_ids, src_distence, 1, src_count, src_result);
ASSERT_TRUE(status.ok());
status = engine::SearchTask::ClusterResult(target_ids, target_distence, 1, target_count, target_result);
@ -126,37 +178,107 @@ TEST(DBSearchTest, MERGE_TEST) {
{
engine::SearchContext::Id2DistanceMap src = src_result[0];
engine::SearchContext::Id2DistanceMap target = target_result[0];
status = engine::SearchTask::MergeResult(src, target, 10, true);
status = engine::SearchTask::MergeResult(src, target, 10, ascending);
ASSERT_TRUE(status.ok());
ASSERT_EQ(target.size(), 10);
CheckResult(src_result[0], target_result[0], target);
CheckResult(src_result[0], target_result[0], target, ascending);
}
{
engine::SearchContext::Id2DistanceMap src = src_result[0];
engine::SearchContext::Id2DistanceMap target;
status = engine::SearchTask::MergeResult(src, target, 10, true);
status = engine::SearchTask::MergeResult(src, target, 10, ascending);
ASSERT_TRUE(status.ok());
ASSERT_EQ(target.size(), src_count);
ASSERT_TRUE(src.empty());
CheckResult(src_result[0], target_result[0], target);
CheckResult(src_result[0], target_result[0], target, ascending);
}
{
engine::SearchContext::Id2DistanceMap src = src_result[0];
engine::SearchContext::Id2DistanceMap target = target_result[0];
status = engine::SearchTask::MergeResult(src, target, 30, true);
status = engine::SearchTask::MergeResult(src, target, 30, ascending);
ASSERT_TRUE(status.ok());
ASSERT_EQ(target.size(), src_count + target_count);
CheckResult(src_result[0], target_result[0], target);
CheckResult(src_result[0], target_result[0], target, ascending);
}
{
engine::SearchContext::Id2DistanceMap target = src_result[0];
engine::SearchContext::Id2DistanceMap src = target_result[0];
status = engine::SearchTask::MergeResult(src, target, 30, true);
status = engine::SearchTask::MergeResult(src, target, 30, ascending);
ASSERT_TRUE(status.ok());
ASSERT_EQ(target.size(), src_count + target_count);
CheckResult(src_result[0], target_result[0], target);
CheckResult(src_result[0], target_result[0], target, ascending);
}
}
TEST(DBSearchTest, PARALLEL_CLUSTER_TEST) {
bool ascending = true;
std::vector<long> target_ids;
std::vector<float> target_distence;
engine::SearchContext::ResultSet src_result;
auto DoCluster = [&](int64_t nq, int64_t topk) {
server::TimeRecorder rc("DoCluster");
src_result.clear();
BuildResult(nq, topk, ascending, target_ids, target_distence);
rc.RecordSection("build id/dietance map");
auto status = engine::SearchTask::ClusterResult(target_ids, target_distence, nq, topk, src_result);
ASSERT_TRUE(status.ok());
ASSERT_EQ(src_result.size(), nq);
rc.RecordSection("cluster result");
CheckCluster(target_ids, target_distence, src_result, nq, topk);
rc.RecordSection("check result");
};
DoCluster(10000, 1000);
DoCluster(333, 999);
DoCluster(1, 1000);
DoCluster(1, 1);
DoCluster(7, 0);
DoCluster(9999, 1);
DoCluster(10001, 1);
DoCluster(58273, 1234);
}
TEST(DBSearchTest, PARALLEL_TOPK_TEST) {
std::vector<long> target_ids;
std::vector<float> target_distence;
engine::SearchContext::ResultSet src_result;
std::vector<long> insufficient_ids;
std::vector<float> insufficient_distence;
engine::SearchContext::ResultSet insufficient_result;
auto DoTopk = [&](int64_t nq, int64_t topk,int64_t insufficient_topk, bool ascending) {
src_result.clear();
insufficient_result.clear();
server::TimeRecorder rc("DoCluster");
BuildResult(nq, topk, ascending, target_ids, target_distence);
auto status = engine::SearchTask::ClusterResult(target_ids, target_distence, nq, topk, src_result);
rc.RecordSection("cluster result");
BuildResult(nq, insufficient_topk, ascending, insufficient_ids, insufficient_distence);
status = engine::SearchTask::ClusterResult(target_ids, target_distence, nq, insufficient_topk, insufficient_result);
rc.RecordSection("cluster result");
engine::SearchTask::TopkResult(insufficient_result, topk, ascending, src_result);
ASSERT_TRUE(status.ok());
rc.RecordSection("topk");
CheckTopkResult(src_result, ascending, nq, topk);
rc.RecordSection("check result");
};
DoTopk(5, 10, 4, false);
DoTopk(20005, 998, 123, true);
DoTopk(9987, 12, 10, false);
DoTopk(77777, 1000, 1, false);
DoTopk(5432, 8899, 8899, true);
}