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547 lines
18 KiB
C++
547 lines
18 KiB
C++
/*******************************************************************************
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* Copyright 上海赜睿信息科技有限公司(Zilliz) - All Rights Reserved
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* Unauthorized copying of this file, via any medium is strictly prohibited.
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* Proprietary and confidential.
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******************************************************************************/
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#include "DBImpl.h"
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#include "DBMetaImpl.h"
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#include "Env.h"
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#include "EngineFactory.h"
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#include "metrics/Metrics.h"
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#include "scheduler/SearchScheduler.h"
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#include <assert.h>
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#include <chrono>
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#include <thread>
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#include <iostream>
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#include <cstring>
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#include <easylogging++.h>
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#include <cache/CpuCacheMgr.h>
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namespace zilliz {
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namespace vecwise {
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namespace engine {
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namespace {
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void CollectInsertMetrics(double total_time, size_t n, bool succeed) {
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double avg_time = total_time / n;
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for (int i = 0; i < n; ++i) {
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server::Metrics::GetInstance().AddVectorsDurationHistogramOberve(avg_time);
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}
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// server::Metrics::GetInstance().add_vector_duration_seconds_quantiles().Observe((average_time));
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if (succeed) {
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server::Metrics::GetInstance().AddVectorsSuccessTotalIncrement(n);
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server::Metrics::GetInstance().AddVectorsSuccessGaugeSet(n);
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}
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else {
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server::Metrics::GetInstance().AddVectorsFailTotalIncrement(n);
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server::Metrics::GetInstance().AddVectorsFailGaugeSet(n);
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}
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}
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void CollectQueryMetrics(double total_time, size_t nq) {
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for (int i = 0; i < nq; ++i) {
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server::Metrics::GetInstance().QueryResponseSummaryObserve(total_time);
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}
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auto average_time = total_time / nq;
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server::Metrics::GetInstance().QueryVectorResponseSummaryObserve(average_time, nq);
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server::Metrics::GetInstance().QueryVectorResponsePerSecondGaugeSet(double (nq) / total_time);
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}
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void CollectFileMetrics(int file_type, size_t file_size, double total_time) {
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switch(file_type) {
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case meta::TableFileSchema::RAW:
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case meta::TableFileSchema::TO_INDEX: {
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server::Metrics::GetInstance().SearchRawDataDurationSecondsHistogramObserve(total_time);
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server::Metrics::GetInstance().RawFileSizeHistogramObserve(file_size);
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server::Metrics::GetInstance().RawFileSizeTotalIncrement(file_size);
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server::Metrics::GetInstance().RawFileSizeGaugeSet(file_size);
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break;
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}
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default: {
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server::Metrics::GetInstance().SearchIndexDataDurationSecondsHistogramObserve(total_time);
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server::Metrics::GetInstance().IndexFileSizeHistogramObserve(file_size);
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server::Metrics::GetInstance().IndexFileSizeTotalIncrement(file_size);
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server::Metrics::GetInstance().IndexFileSizeGaugeSet(file_size);
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break;
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}
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}
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}
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}
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DBImpl::DBImpl(const Options& options)
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: env_(options.env),
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options_(options),
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bg_compaction_scheduled_(false),
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shutting_down_(false),
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bg_build_index_started_(false),
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pMeta_(new meta::DBMetaImpl(options_.meta)),
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pMemMgr_(new MemManager(pMeta_, options_)) {
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StartTimerTasks(options_.memory_sync_interval);
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}
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Status DBImpl::CreateTable(meta::TableSchema& table_schema) {
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return pMeta_->CreateTable(table_schema);
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}
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Status DBImpl::DescribeTable(meta::TableSchema& table_schema) {
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return pMeta_->DescribeTable(table_schema);
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}
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Status DBImpl::HasTable(const std::string& table_id, bool& has_or_not) {
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return pMeta_->HasTable(table_id, has_or_not);
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}
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Status DBImpl::InsertVectors(const std::string& table_id_,
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size_t n, const float* vectors, IDNumbers& vector_ids_) {
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auto start_time = METRICS_NOW_TIME;
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Status status = pMemMgr_->InsertVectors(table_id_, n, vectors, vector_ids_);
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auto end_time = METRICS_NOW_TIME;
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double total_time = METRICS_MICROSECONDS(start_time,end_time);
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// std::chrono::microseconds time_span = std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time);
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// double average_time = double(time_span.count()) / n;
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CollectInsertMetrics(total_time, n, status.ok());
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return status;
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}
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Status DBImpl::Query(const std::string &table_id, size_t k, size_t nq,
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const float *vectors, QueryResults &results) {
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auto start_time = METRICS_NOW_TIME;
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meta::DatesT dates = {meta::Meta::GetDate()};
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Status result = Query(table_id, k, nq, vectors, dates, results);
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auto end_time = METRICS_NOW_TIME;
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auto total_time = METRICS_MICROSECONDS(start_time,end_time);
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CollectQueryMetrics(total_time, nq);
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return result;
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}
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Status DBImpl::Query(const std::string& table_id, size_t k, size_t nq,
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const float* vectors, const meta::DatesT& dates, QueryResults& results) {
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#if 0
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return QuerySync(table_id, k, nq, vectors, dates, results);
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#else
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return QueryAsync(table_id, k, nq, vectors, dates, results);
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#endif
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}
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Status DBImpl::QuerySync(const std::string& table_id, size_t k, size_t nq,
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const float* vectors, const meta::DatesT& dates, QueryResults& results) {
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meta::DatePartionedTableFilesSchema files;
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auto status = pMeta_->FilesToSearch(table_id, dates, files);
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if (!status.ok()) { return status; }
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LOG(DEBUG) << "Search DateT Size=" << files.size();
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meta::TableFilesSchema index_files;
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meta::TableFilesSchema raw_files;
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for (auto &day_files : files) {
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for (auto &file : day_files.second) {
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file.file_type_ == meta::TableFileSchema::INDEX ?
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index_files.push_back(file) : raw_files.push_back(file);
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}
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}
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int dim = 0;
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if (!index_files.empty()) {
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dim = index_files[0].dimension_;
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} else if (!raw_files.empty()) {
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dim = raw_files[0].dimension_;
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} else {
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LOG(DEBUG) << "no files to search";
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return Status::OK();
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}
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{
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// [{ids, distence}, ...]
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using SearchResult = std::pair<std::vector<long>, std::vector<float>>;
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std::vector<SearchResult> batchresult(nq); // allocate nq cells.
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auto cluster = [&](long *nns, float *dis, const int& k) -> void {
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for (int i = 0; i < nq; ++i) {
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auto f_begin = batchresult[i].first.cbegin();
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auto s_begin = batchresult[i].second.cbegin();
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batchresult[i].first.insert(f_begin, nns + i * k, nns + i * k + k);
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batchresult[i].second.insert(s_begin, dis + i * k, dis + i * k + k);
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}
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};
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// Allocate Memory
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float *output_distence;
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long *output_ids;
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output_distence = (float *) malloc(k * nq * sizeof(float));
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output_ids = (long *) malloc(k * nq * sizeof(long));
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memset(output_distence, 0, k * nq * sizeof(float));
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memset(output_ids, 0, k * nq * sizeof(long));
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long search_set_size = 0;
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auto search_in_index = [&](meta::TableFilesSchema& file_vec) -> void {
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for (auto &file : file_vec) {
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ExecutionEnginePtr index = EngineFactory::Build(file.dimension_, file.location_, (EngineType)file.engine_type_);
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index->Load();
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auto file_size = index->PhysicalSize();
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search_set_size += file_size;
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LOG(DEBUG) << "Search file_type " << file.file_type_ << " Of Size: "
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<< file_size/(1024*1024) << " M";
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int inner_k = index->Count() < k ? index->Count() : k;
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auto start_time = METRICS_NOW_TIME;
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index->Search(nq, vectors, inner_k, output_distence, output_ids);
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auto end_time = METRICS_NOW_TIME;
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auto total_time = METRICS_MICROSECONDS(start_time, end_time);
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CollectFileMetrics(file.file_type_, file_size, total_time);
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cluster(output_ids, output_distence, inner_k); // cluster to each query
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memset(output_distence, 0, k * nq * sizeof(float));
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memset(output_ids, 0, k * nq * sizeof(long));
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}
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};
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auto topk_cpu = [](const std::vector<float> &input_data,
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const int &k,
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float *output_distence,
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long *output_ids) -> void {
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std::map<float, std::vector<int>> inverted_table;
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for (int i = 0; i < input_data.size(); ++i) {
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if (inverted_table.count(input_data[i]) == 1) {
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auto& ori_vec = inverted_table[input_data[i]];
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ori_vec.push_back(i);
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}
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else {
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inverted_table[input_data[i]] = std::vector<int>{i};
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}
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}
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int count = 0;
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for (auto &item : inverted_table){
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if (count == k) break;
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for (auto &id : item.second){
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output_distence[count] = item.first;
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output_ids[count] = id;
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if (++count == k) break;
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}
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}
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};
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auto cluster_topk = [&]() -> void {
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QueryResult res;
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for (auto &result_pair : batchresult) {
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auto &dis = result_pair.second;
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auto &nns = result_pair.first;
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topk_cpu(dis, k, output_distence, output_ids);
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int inner_k = dis.size() < k ? dis.size() : k;
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for (int i = 0; i < inner_k; ++i) {
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res.emplace_back(std::make_pair(nns[output_ids[i]], output_distence[i])); // mapping
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}
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results.push_back(res); // append to result list
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res.clear();
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memset(output_distence, 0, k * nq * sizeof(float));
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memset(output_ids, 0, k * nq * sizeof(long));
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}
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};
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search_in_index(raw_files);
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search_in_index(index_files);
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LOG(DEBUG) << "Search Overall Set Size=" << search_set_size << " M";
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cluster_topk();
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free(output_distence);
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free(output_ids);
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}
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if (results.empty()) {
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return Status::NotFound("Group " + table_id + ", search result not found!");
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}
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return Status::OK();
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}
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Status DBImpl::QueryAsync(const std::string& table_id, size_t k, size_t nq,
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const float* vectors, const meta::DatesT& dates, QueryResults& results) {
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//step 1: get files to search
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meta::DatePartionedTableFilesSchema files;
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auto status = pMeta_->FilesToSearch(table_id, dates, files);
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if (!status.ok()) { return status; }
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LOG(DEBUG) << "Search DateT Size=" << files.size();
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SearchContextPtr context = std::make_shared<SearchContext>(k, nq, vectors);
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for (auto &day_files : files) {
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for (auto &file : day_files.second) {
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TableFileSchemaPtr file_ptr = std::make_shared<meta::TableFileSchema>(file);
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context->AddIndexFile(file_ptr);
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}
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}
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//step 2: put search task to scheduler
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SearchScheduler& scheduler = SearchScheduler::GetInstance();
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scheduler.ScheduleSearchTask(context);
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context->WaitResult();
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//step 3: construct results
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auto& context_result = context->GetResult();
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results.swap(context_result);
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return Status::OK();
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}
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void DBImpl::StartTimerTasks(int interval) {
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bg_timer_thread_ = std::thread(&DBImpl::BackgroundTimerTask, this, interval);
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}
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void DBImpl::BackgroundTimerTask(int interval) {
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Status status;
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server::SystemInfo::GetInstance().Init();
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while (true) {
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if (!bg_error_.ok()) break;
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if (shutting_down_.load(std::memory_order_acquire)) break;
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std::this_thread::sleep_for(std::chrono::seconds(interval));
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server::Metrics::GetInstance().KeepingAliveCounterIncrement(interval);
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int64_t cache_usage = cache::CpuCacheMgr::GetInstance()->CacheUsage();
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int64_t cache_total = cache::CpuCacheMgr::GetInstance()->CacheCapacity();
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server::Metrics::GetInstance().CacheUsageGaugeSet(cache_usage*100/cache_total);
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long size;
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Size(size);
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server::Metrics::GetInstance().DataFileSizeGaugeSet(size);
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server::Metrics::GetInstance().CPUUsagePercentSet();
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server::Metrics::GetInstance().RAMUsagePercentSet();
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server::Metrics::GetInstance().GPUPercentGaugeSet();
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server::Metrics::GetInstance().GPUMemoryUsageGaugeSet();
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TrySchedule();
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}
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}
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void DBImpl::TrySchedule() {
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if (bg_compaction_scheduled_) return;
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if (!bg_error_.ok()) return;
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bg_compaction_scheduled_ = true;
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env_->Schedule(&DBImpl::BGWork, this);
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}
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void DBImpl::BGWork(void* db_) {
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reinterpret_cast<DBImpl*>(db_)->BackgroundCall();
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}
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void DBImpl::BackgroundCall() {
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std::lock_guard<std::mutex> lock(mutex_);
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assert(bg_compaction_scheduled_);
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if (!bg_error_.ok() || shutting_down_.load(std::memory_order_acquire))
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return ;
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BackgroundCompaction();
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bg_compaction_scheduled_ = false;
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bg_work_finish_signal_.notify_all();
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}
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Status DBImpl::MergeFiles(const std::string& table_id, const meta::DateT& date,
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const meta::TableFilesSchema& files) {
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meta::TableFileSchema table_file;
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table_file.table_id_ = table_id;
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table_file.date_ = date;
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Status status = pMeta_->CreateTableFile(table_file);
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if (!status.ok()) {
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LOG(INFO) << status.ToString() << std::endl;
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return status;
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}
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ExecutionEnginePtr index =
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EngineFactory::Build(table_file.dimension_, table_file.location_, (EngineType)table_file.engine_type_);
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meta::TableFilesSchema updated;
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long index_size = 0;
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for (auto& file : files) {
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auto start_time = METRICS_NOW_TIME;
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index->Merge(file.location_);
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auto file_schema = file;
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auto end_time = METRICS_NOW_TIME;
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auto total_time = METRICS_MICROSECONDS(start_time,end_time);
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server::Metrics::GetInstance().MemTableMergeDurationSecondsHistogramObserve(total_time);
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file_schema.file_type_ = meta::TableFileSchema::TO_DELETE;
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updated.push_back(file_schema);
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LOG(DEBUG) << "Merging file " << file_schema.file_id_;
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index_size = index->Size();
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if (index_size >= options_.index_trigger_size) break;
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}
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index->Serialize();
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if (index_size >= options_.index_trigger_size) {
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table_file.file_type_ = meta::TableFileSchema::TO_INDEX;
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} else {
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table_file.file_type_ = meta::TableFileSchema::RAW;
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}
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table_file.size_ = index_size;
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updated.push_back(table_file);
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status = pMeta_->UpdateTableFiles(updated);
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LOG(DEBUG) << "New merged file " << table_file.file_id_ <<
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" of size=" << index->PhysicalSize()/(1024*1024) << " M";
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index->Cache();
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return status;
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}
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Status DBImpl::BackgroundMergeFiles(const std::string& table_id) {
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meta::DatePartionedTableFilesSchema raw_files;
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auto status = pMeta_->FilesToMerge(table_id, raw_files);
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if (!status.ok()) {
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return status;
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}
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bool has_merge = false;
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for (auto& kv : raw_files) {
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auto files = kv.second;
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if (files.size() <= options_.merge_trigger_number) {
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continue;
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}
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has_merge = true;
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MergeFiles(table_id, kv.first, kv.second);
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}
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pMeta_->Archive();
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TryBuildIndex();
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pMeta_->CleanUpFilesWithTTL(1);
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return Status::OK();
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}
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Status DBImpl::BuildIndex(const meta::TableFileSchema& file) {
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meta::TableFileSchema table_file;
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table_file.table_id_ = file.table_id_;
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table_file.date_ = file.date_;
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Status status = pMeta_->CreateTableFile(table_file);
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if (!status.ok()) {
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return status;
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}
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ExecutionEnginePtr to_index = EngineFactory::Build(file.dimension_, file.location_, (EngineType)file.engine_type_);
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to_index->Load();
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auto start_time = METRICS_NOW_TIME;
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auto index = to_index->BuildIndex(table_file.location_);
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auto end_time = METRICS_NOW_TIME;
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auto total_time = METRICS_MICROSECONDS(start_time, end_time);
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server::Metrics::GetInstance().BuildIndexDurationSecondsHistogramObserve(total_time);
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table_file.file_type_ = meta::TableFileSchema::INDEX;
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table_file.size_ = index->Size();
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auto to_remove = file;
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to_remove.file_type_ = meta::TableFileSchema::TO_DELETE;
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meta::TableFilesSchema update_files = {to_remove, table_file};
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pMeta_->UpdateTableFiles(update_files);
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LOG(DEBUG) << "New index file " << table_file.file_id_ << " of size "
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<< index->PhysicalSize()/(1024*1024) << " M"
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<< " from file " << to_remove.file_id_;
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index->Cache();
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pMeta_->Archive();
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return Status::OK();
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}
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void DBImpl::BackgroundBuildIndex() {
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std::lock_guard<std::mutex> lock(build_index_mutex_);
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assert(bg_build_index_started_);
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meta::TableFilesSchema to_index_files;
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pMeta_->FilesToIndex(to_index_files);
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Status status;
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for (auto& file : to_index_files) {
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/* LOG(DEBUG) << "Buiding index for " << file.location; */
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status = BuildIndex(file);
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if (!status.ok()) {
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bg_error_ = status;
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return;
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}
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}
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/* LOG(DEBUG) << "All Buiding index Done"; */
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bg_build_index_started_ = false;
|
|
bg_build_index_finish_signal_.notify_all();
|
|
}
|
|
|
|
Status DBImpl::TryBuildIndex() {
|
|
if (bg_build_index_started_) return Status::OK();
|
|
if (shutting_down_.load(std::memory_order_acquire)) return Status::OK();
|
|
bg_build_index_started_ = true;
|
|
std::thread build_index_task(&DBImpl::BackgroundBuildIndex, this);
|
|
build_index_task.detach();
|
|
return Status::OK();
|
|
}
|
|
|
|
void DBImpl::BackgroundCompaction() {
|
|
std::vector<std::string> table_ids;
|
|
pMemMgr_->Serialize(table_ids);
|
|
|
|
Status status;
|
|
for (auto table_id : table_ids) {
|
|
status = BackgroundMergeFiles(table_id);
|
|
if (!status.ok()) {
|
|
bg_error_ = status;
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
|
|
Status DBImpl::DropAll() {
|
|
return pMeta_->DropAll();
|
|
}
|
|
|
|
Status DBImpl::Size(long& result) {
|
|
return pMeta_->Size(result);
|
|
}
|
|
|
|
DBImpl::~DBImpl() {
|
|
{
|
|
std::unique_lock<std::mutex> lock(mutex_);
|
|
shutting_down_.store(true, std::memory_order_release);
|
|
while (bg_compaction_scheduled_) {
|
|
bg_work_finish_signal_.wait(lock);
|
|
}
|
|
}
|
|
{
|
|
std::unique_lock<std::mutex> lock(build_index_mutex_);
|
|
while (bg_build_index_started_) {
|
|
bg_build_index_finish_signal_.wait(lock);
|
|
}
|
|
}
|
|
bg_timer_thread_.join();
|
|
std::vector<std::string> ids;
|
|
pMemMgr_->Serialize(ids);
|
|
env_->Stop();
|
|
}
|
|
|
|
} // namespace engine
|
|
} // namespace vecwise
|
|
} // namespace zilliz
|