// Licensed to the Apache Software Foundation (ASF) under one // or more contributor license agreements. See the NOTICE file // distributed with this work for additional information // regarding copyright ownership. The ASF licenses this file // to you under the Apache License, Version 2.0 (the // "License"); you may not use this file except in compliance // with the License. You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, // software distributed under the License is distributed on an // "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY // KIND, either express or implied. See the License for the // specific language governing permissions and limitations // under the License. #include "db/engine/ExecutionEngineImpl.h" #include "cache/CpuCacheMgr.h" #include "cache/GpuCacheMgr.h" #include "knowhere/common/Config.h" #include "metrics/Metrics.h" #include "scheduler/Utils.h" #include "server/Config.h" #include "utils/CommonUtil.h" #include "utils/Exception.h" #include "utils/Log.h" #include "wrapper/ConfAdapter.h" #include "wrapper/ConfAdapterMgr.h" #include "wrapper/VecImpl.h" #include "wrapper/VecIndex.h" #include #include #include //#define ON_SEARCH namespace milvus { namespace engine { class CachedQuantizer : public cache::DataObj { public: explicit CachedQuantizer(knowhere::QuantizerPtr data) : data_(std::move(data)) { } knowhere::QuantizerPtr Data() { return data_; } int64_t Size() override { return data_->size; } private: knowhere::QuantizerPtr data_; }; ExecutionEngineImpl::ExecutionEngineImpl(uint16_t dimension, const std::string& location, EngineType index_type, MetricType metric_type, int32_t nlist) : location_(location), dim_(dimension), index_type_(index_type), metric_type_(metric_type), nlist_(nlist) { index_ = CreatetVecIndex(EngineType::FAISS_IDMAP); if (!index_) { throw Exception(DB_ERROR, "Unsupported index type"); } TempMetaConf temp_conf; temp_conf.gpu_id = gpu_num_; temp_conf.dim = dimension; temp_conf.metric_type = (metric_type_ == MetricType::IP) ? knowhere::METRICTYPE::IP : knowhere::METRICTYPE::L2; auto adapter = AdapterMgr::GetInstance().GetAdapter(index_->GetType()); auto conf = adapter->Match(temp_conf); auto ec = std::static_pointer_cast(index_)->Build(conf); if (ec != KNOWHERE_SUCCESS) { throw Exception(DB_ERROR, "Build index error"); } } ExecutionEngineImpl::ExecutionEngineImpl(VecIndexPtr index, const std::string& location, EngineType index_type, MetricType metric_type, int32_t nlist) : index_(std::move(index)), location_(location), index_type_(index_type), metric_type_(metric_type), nlist_(nlist) { } VecIndexPtr ExecutionEngineImpl::CreatetVecIndex(EngineType type) { std::shared_ptr index; switch (type) { case EngineType::FAISS_IDMAP: { index = GetVecIndexFactory(IndexType::FAISS_IDMAP); break; } case EngineType::FAISS_IVFFLAT: { #ifdef MILVUS_CPU_VERSION index = GetVecIndexFactory(IndexType::FAISS_IVFFLAT_CPU); #else index = GetVecIndexFactory(IndexType::FAISS_IVFFLAT_MIX); #endif break; } case EngineType::FAISS_IVFSQ8: { #ifdef MILVUS_CPU_VERSION index = GetVecIndexFactory(IndexType::FAISS_IVFSQ8_CPU); #else index = GetVecIndexFactory(IndexType::FAISS_IVFSQ8_MIX); #endif break; } case EngineType::NSG_MIX: { index = GetVecIndexFactory(IndexType::NSG_MIX); break; } case EngineType::FAISS_IVFSQ8H: { index = GetVecIndexFactory(IndexType::FAISS_IVFSQ8_HYBRID); break; } case EngineType::FAISS_PQ: { #ifdef MILVUS_CPU_VERSION index = GetVecIndexFactory(IndexType::FAISS_IVFPQ_CPU); #else index = GetVecIndexFactory(IndexType::FAISS_IVFPQ_MIX); #endif break; } default: { ENGINE_LOG_ERROR << "Unsupported index type"; return nullptr; } } return index; } void ExecutionEngineImpl::HybridLoad() const { if (index_type_ != EngineType::FAISS_IVFSQ8H) { return; } if (index_->GetType() == IndexType::FAISS_IDMAP) { ENGINE_LOG_WARNING << "HybridLoad with type FAISS_IDMAP, ignore"; return; } const std::string key = location_ + ".quantizer"; std::vector gpus = scheduler::get_gpu_pool(); // cache hit { const int64_t NOT_FOUND = -1; int64_t device_id = NOT_FOUND; knowhere::QuantizerPtr quantizer = nullptr; for (auto& gpu : gpus) { auto cache = cache::GpuCacheMgr::GetInstance(gpu); if (auto cached_quantizer = cache->GetIndex(key)) { device_id = gpu; quantizer = std::static_pointer_cast(cached_quantizer)->Data(); } } if (device_id != NOT_FOUND) { index_->SetQuantizer(quantizer); return; } } // cache miss { std::vector all_free_mem; for (auto& gpu : gpus) { auto cache = cache::GpuCacheMgr::GetInstance(gpu); auto free_mem = cache->CacheCapacity() - cache->CacheUsage(); all_free_mem.push_back(free_mem); } auto max_e = std::max_element(all_free_mem.begin(), all_free_mem.end()); auto best_index = std::distance(all_free_mem.begin(), max_e); auto best_device_id = gpus[best_index]; auto quantizer_conf = std::make_shared(); quantizer_conf->mode = 1; quantizer_conf->gpu_id = best_device_id; auto quantizer = index_->LoadQuantizer(quantizer_conf); if (quantizer == nullptr) { ENGINE_LOG_ERROR << "quantizer is nullptr"; } index_->SetQuantizer(quantizer); auto cache_quantizer = std::make_shared(quantizer); cache::GpuCacheMgr::GetInstance(best_device_id)->InsertItem(key, cache_quantizer); } } void ExecutionEngineImpl::HybridUnset() const { if (index_type_ != EngineType::FAISS_IVFSQ8H) { return; } if (index_->GetType() == IndexType::FAISS_IDMAP) { return; } index_->UnsetQuantizer(); } Status ExecutionEngineImpl::AddWithIds(int64_t n, const float* xdata, const int64_t* xids) { auto status = index_->Add(n, xdata, xids); return status; } size_t ExecutionEngineImpl::Count() const { if (index_ == nullptr) { ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, return count 0"; return 0; } return index_->Count(); } size_t ExecutionEngineImpl::Size() const { return (size_t)(Count() * Dimension()) * sizeof(float); } size_t ExecutionEngineImpl::Dimension() const { if (index_ == nullptr) { ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, return dimension " << dim_; return dim_; } return index_->Dimension(); } size_t ExecutionEngineImpl::PhysicalSize() const { return server::CommonUtil::GetFileSize(location_); } Status ExecutionEngineImpl::Serialize() { auto status = write_index(index_, location_); return status; } Status ExecutionEngineImpl::Load(bool to_cache) { index_ = std::static_pointer_cast(cache::CpuCacheMgr::GetInstance()->GetIndex(location_)); bool already_in_cache = (index_ != nullptr); if (!already_in_cache) { try { double physical_size = PhysicalSize(); server::CollectExecutionEngineMetrics metrics(physical_size); index_ = read_index(location_); if (index_ == nullptr) { std::string msg = "Failed to load index from " + location_; ENGINE_LOG_ERROR << msg; return Status(DB_ERROR, msg); } else { ENGINE_LOG_DEBUG << "Disk io from: " << location_; } } catch (std::exception& e) { ENGINE_LOG_ERROR << e.what(); return Status(DB_ERROR, e.what()); } } if (!already_in_cache && to_cache) { Cache(); } return Status::OK(); } Status ExecutionEngineImpl::CopyToGpu(uint64_t device_id, bool hybrid) { #if 0 if (hybrid) { const std::string key = location_ + ".quantizer"; std::vector gpus{device_id}; const int64_t NOT_FOUND = -1; int64_t device_id = NOT_FOUND; // cache hit { knowhere::QuantizerPtr quantizer = nullptr; for (auto& gpu : gpus) { auto cache = cache::GpuCacheMgr::GetInstance(gpu); if (auto cached_quantizer = cache->GetIndex(key)) { device_id = gpu; quantizer = std::static_pointer_cast(cached_quantizer)->Data(); } } if (device_id != NOT_FOUND) { // cache hit auto config = std::make_shared(); config->gpu_id = device_id; config->mode = 2; auto new_index = index_->LoadData(quantizer, config); index_ = new_index; } } if (device_id == NOT_FOUND) { // cache miss std::vector all_free_mem; for (auto& gpu : gpus) { auto cache = cache::GpuCacheMgr::GetInstance(gpu); auto free_mem = cache->CacheCapacity() - cache->CacheUsage(); all_free_mem.push_back(free_mem); } auto max_e = std::max_element(all_free_mem.begin(), all_free_mem.end()); auto best_index = std::distance(all_free_mem.begin(), max_e); device_id = gpus[best_index]; auto pair = index_->CopyToGpuWithQuantizer(device_id); index_ = pair.first; // cache auto cached_quantizer = std::make_shared(pair.second); cache::GpuCacheMgr::GetInstance(device_id)->InsertItem(key, cached_quantizer); } return Status::OK(); } #endif auto index = std::static_pointer_cast(cache::GpuCacheMgr::GetInstance(device_id)->GetIndex(location_)); bool already_in_cache = (index != nullptr); if (already_in_cache) { index_ = index; } else { if (index_ == nullptr) { ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to copy to gpu"; return Status(DB_ERROR, "index is null"); } try { index_ = index_->CopyToGpu(device_id); ENGINE_LOG_DEBUG << "CPU to GPU" << device_id; } catch (std::exception& e) { ENGINE_LOG_ERROR << e.what(); return Status(DB_ERROR, e.what()); } } if (!already_in_cache) { GpuCache(device_id); } return Status::OK(); } Status ExecutionEngineImpl::CopyToIndexFileToGpu(uint64_t device_id) { gpu_num_ = device_id; auto to_index_data = std::make_shared(PhysicalSize()); cache::DataObjPtr obj = std::static_pointer_cast(to_index_data); milvus::cache::GpuCacheMgr::GetInstance(device_id)->InsertItem(location_, obj); return Status::OK(); } Status ExecutionEngineImpl::CopyToCpu() { auto index = std::static_pointer_cast(cache::CpuCacheMgr::GetInstance()->GetIndex(location_)); bool already_in_cache = (index != nullptr); if (already_in_cache) { index_ = index; } else { if (index_ == nullptr) { ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to copy to cpu"; return Status(DB_ERROR, "index is null"); } try { index_ = index_->CopyToCpu(); ENGINE_LOG_DEBUG << "GPU to CPU"; } catch (std::exception& e) { ENGINE_LOG_ERROR << e.what(); return Status(DB_ERROR, e.what()); } } if (!already_in_cache) { Cache(); } return Status::OK(); } ExecutionEnginePtr ExecutionEngineImpl::Clone() { if (index_ == nullptr) { ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to clone"; return nullptr; } auto ret = std::make_shared(dim_, location_, index_type_, metric_type_, nlist_); ret->Init(); ret->index_ = index_->Clone(); return ret; } Status ExecutionEngineImpl::Merge(const std::string& location) { if (location == location_) { return Status(DB_ERROR, "Cannot Merge Self"); } ENGINE_LOG_DEBUG << "Merge index file: " << location << " to: " << location_; auto to_merge = cache::CpuCacheMgr::GetInstance()->GetIndex(location); if (!to_merge) { try { double physical_size = server::CommonUtil::GetFileSize(location); server::CollectExecutionEngineMetrics metrics(physical_size); to_merge = read_index(location); } catch (std::exception& e) { ENGINE_LOG_ERROR << e.what(); return Status(DB_ERROR, e.what()); } } if (index_ == nullptr) { ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to merge"; return Status(DB_ERROR, "index is null"); } if (auto file_index = std::dynamic_pointer_cast(to_merge)) { auto status = index_->Add(file_index->Count(), file_index->GetRawVectors(), file_index->GetRawIds()); if (!status.ok()) { ENGINE_LOG_ERROR << "Merge: Add Error"; } return status; } else { return Status(DB_ERROR, "file index type is not idmap"); } } ExecutionEnginePtr ExecutionEngineImpl::BuildIndex(const std::string& location, EngineType engine_type) { ENGINE_LOG_DEBUG << "Build index file: " << location << " from: " << location_; auto from_index = std::dynamic_pointer_cast(index_); if (from_index == nullptr) { ENGINE_LOG_ERROR << "ExecutionEngineImpl: from_index is null, failed to build index"; return nullptr; } auto to_index = CreatetVecIndex(engine_type); if (!to_index) { throw Exception(DB_ERROR, "Unsupported index type"); } TempMetaConf temp_conf; temp_conf.gpu_id = gpu_num_; temp_conf.dim = Dimension(); temp_conf.nlist = nlist_; temp_conf.metric_type = (metric_type_ == MetricType::IP) ? knowhere::METRICTYPE::IP : knowhere::METRICTYPE::L2; temp_conf.size = Count(); auto adapter = AdapterMgr::GetInstance().GetAdapter(to_index->GetType()); auto conf = adapter->Match(temp_conf); auto status = to_index->BuildAll(Count(), from_index->GetRawVectors(), from_index->GetRawIds(), conf); if (!status.ok()) { throw Exception(DB_ERROR, status.message()); } return std::make_shared(to_index, location, engine_type, metric_type_, nlist_); } Status ExecutionEngineImpl::Search(int64_t n, const float* data, int64_t k, int64_t nprobe, float* distances, int64_t* labels, bool hybrid) { #if 0 if (index_type_ == EngineType::FAISS_IVFSQ8H) { if (!hybrid) { const std::string key = location_ + ".quantizer"; std::vector gpus = scheduler::get_gpu_pool(); const int64_t NOT_FOUND = -1; int64_t device_id = NOT_FOUND; // cache hit { knowhere::QuantizerPtr quantizer = nullptr; for (auto& gpu : gpus) { auto cache = cache::GpuCacheMgr::GetInstance(gpu); if (auto cached_quantizer = cache->GetIndex(key)) { device_id = gpu; quantizer = std::static_pointer_cast(cached_quantizer)->Data(); } } if (device_id != NOT_FOUND) { // cache hit auto config = std::make_shared(); config->gpu_id = device_id; config->mode = 2; auto new_index = index_->LoadData(quantizer, config); index_ = new_index; } } if (device_id == NOT_FOUND) { // cache miss std::vector all_free_mem; for (auto& gpu : gpus) { auto cache = cache::GpuCacheMgr::GetInstance(gpu); auto free_mem = cache->CacheCapacity() - cache->CacheUsage(); all_free_mem.push_back(free_mem); } auto max_e = std::max_element(all_free_mem.begin(), all_free_mem.end()); auto best_index = std::distance(all_free_mem.begin(), max_e); device_id = gpus[best_index]; auto pair = index_->CopyToGpuWithQuantizer(device_id); index_ = pair.first; // cache auto cached_quantizer = std::make_shared(pair.second); cache::GpuCacheMgr::GetInstance(device_id)->InsertItem(key, cached_quantizer); } } } #endif if (index_ == nullptr) { ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to search"; return Status(DB_ERROR, "index is null"); } ENGINE_LOG_DEBUG << "Search Params: [k] " << k << " [nprobe] " << nprobe; // TODO(linxj): remove here. Get conf from function TempMetaConf temp_conf; temp_conf.k = k; temp_conf.nprobe = nprobe; auto adapter = AdapterMgr::GetInstance().GetAdapter(index_->GetType()); auto conf = adapter->MatchSearch(temp_conf, index_->GetType()); if (hybrid) { HybridLoad(); } auto status = index_->Search(n, data, distances, labels, conf); if (hybrid) { HybridUnset(); } if (!status.ok()) { ENGINE_LOG_ERROR << "Search error"; } return status; } Status ExecutionEngineImpl::Cache() { cache::DataObjPtr obj = std::static_pointer_cast(index_); milvus::cache::CpuCacheMgr::GetInstance()->InsertItem(location_, obj); return Status::OK(); } Status ExecutionEngineImpl::GpuCache(uint64_t gpu_id) { cache::DataObjPtr obj = std::static_pointer_cast(index_); milvus::cache::GpuCacheMgr::GetInstance(gpu_id)->InsertItem(location_, obj); return Status::OK(); } // TODO(linxj): remove. Status ExecutionEngineImpl::Init() { auto gpu_ids = scheduler::get_build_resources(); for (auto id : gpu_ids) { if (gpu_num_ == id) { return Status::OK(); } } std::string msg = "Invalid gpu_num"; return Status(SERVER_INVALID_ARGUMENT, msg); } } // namespace engine } // namespace milvus