data_set.h

/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
 *
 * Licensed 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. */

#pragma once

#include <ThreadPool.h>
#include <fstream>
#include <memory>
#include <mutex>  // NOLINT
#include <set>
#include <string>
#include <thread>  // NOLINT
#include <unordered_set>
#include <utility>
#include <vector>

#include "paddle/fluid/framework/data_feed.h"

namespace paddle {
namespace framework {

// Dataset is a abstract class, which defines user interfaces
// Example Usage:
//    Dataset* dataset = DatasetFactory::CreateDataset("InMemoryDataset")
//    dataset->SetFileList(std::vector<std::string>{"a.txt", "b.txt"})
//    dataset->SetThreadNum(1)
//    dataset->CreateReaders();
//    dataset->SetDataFeedDesc(your_data_feed_desc);
//    dataset->LoadIntoMemory();
//    dataset->SetTrainerNum(2);
//    dataset->GlobalShuffle();
class Dataset {
 public:
  Dataset() {}
  virtual ~Dataset() {}
  // set file list
  virtual void SetFileList(const std::vector<std::string>& filelist) = 0;
  // set readers' num
  virtual void SetThreadNum(int thread_num) = 0;
  // set workers' num
  virtual void SetTrainerNum(int trainer_num) = 0;
  // set fleet send batch size
  virtual void SetFleetSendBatchSize(int64_t size) = 0;
  // set fs name and ugi
  virtual void SetHdfsConfig(const std::string& fs_name,
                             const std::string& fs_ugi) = 0;
  // set customized download command, such as using afs api
  virtual void SetDownloadCmd(const std::string& download_cmd) = 0;
  // set data fedd desc, which contains:
  //   data feed name, batch size, slots
  virtual void SetDataFeedDesc(const std::string& data_feed_desc_str) = 0;
  // set channel num
  virtual void SetChannelNum(int channel_num) = 0;
  // set parse ins id
  virtual void SetParseInsId(bool parse_ins_id) = 0;
  virtual void SetParseContent(bool parse_content) = 0;
  // set merge by ins id
  virtual void SetMergeByInsId(int merge_size) = 0;
  virtual void SetGenerateUniqueFeasign(bool gen_uni_feasigns) = 0;
  // set fea eval mode
  virtual void SetFeaEval(bool fea_eval, int record_candidate_size) = 0;
  // get file list
  virtual const std::vector<std::string>& GetFileList() = 0;
  // get thread num
  virtual int GetThreadNum() = 0;
  // get worker num
  virtual int GetTrainerNum() = 0;
  // get fleet send batch size
  virtual int64_t GetFleetSendBatchSize() = 0;
  // get hdfs config
  virtual std::pair<std::string, std::string> GetHdfsConfig() = 0;
  // get download cmd
  virtual std::string GetDownloadCmd() = 0;
  // get data fedd desc
  virtual const paddle::framework::DataFeedDesc& GetDataFeedDesc() = 0;
  // get channel num
  virtual int GetChannelNum() = 0;
  // get readers, the reader num depend both on thread num
  // and filelist size
  virtual std::vector<paddle::framework::DataFeed*> GetReaders() = 0;
  // create input channel and output channel
  virtual void CreateChannel() = 0;
  // register message handler between workers
  virtual void RegisterClientToClientMsgHandler() = 0;
  // load all data into memory
  virtual void LoadIntoMemory() = 0;
  // load all data into memory in async mode
  virtual void PreLoadIntoMemory() = 0;
  // wait async load done
  virtual void WaitPreLoadDone() = 0;
  // release all memory data
  virtual void ReleaseMemory() = 0;
  // local shuffle data
  virtual void LocalShuffle() = 0;
  // global shuffle data
  virtual void GlobalShuffle(int thread_num = -1) = 0;
  // for slots shuffle
  virtual void SlotsShuffle(const std::set<std::string>& slots_to_replace) = 0;
  virtual void GetRandomData(const std::set<uint16_t>& slots_to_replace,
                             std::vector<Record>* result) = 0;
  // create readers
  virtual void CreateReaders() = 0;
  // destroy readers
  virtual void DestroyReaders() = 0;
  // get memory data size
  virtual int64_t GetMemoryDataSize() = 0;
  // get shuffle data size
  virtual int64_t GetShuffleDataSize() = 0;
  // merge by ins id
  virtual void MergeByInsId() = 0;
  virtual void GenerateLocalTablesUnlock(int table_id, int feadim,
                                         int read_thread_num,
                                         int consume_thread_num,
                                         int shard_num) = 0;
  virtual void ClearLocalTables() = 0;
  // create preload readers
  virtual void CreatePreLoadReaders() = 0;
  // destroy preload readers after prelaod done
  virtual void DestroyPreLoadReaders() = 0;
  // set preload thread num
  virtual void SetPreLoadThreadNum(int thread_num) = 0;
  // seperate train thread and dataset thread
  virtual void DynamicAdjustChannelNum(int channel_num,
                                       bool discard_remaining_ins = false) = 0;
  virtual void DynamicAdjustReadersNum(int thread_num) = 0;
  // set fleet send sleep seconds
  virtual void SetFleetSendSleepSeconds(int seconds) = 0;

 protected:
  virtual int ReceiveFromClient(int msg_type, int client_id,
                                const std::string& msg) = 0;
};

// DatasetImpl is the implementation of Dataset,
// it holds memory data if user calls load_into_memory
template <typename T>
class DatasetImpl : public Dataset {
 public:
  DatasetImpl();
  virtual ~DatasetImpl() {}

  virtual void SetFileList(const std::vector<std::string>& filelist);
  virtual void SetThreadNum(int thread_num);
  virtual void SetTrainerNum(int trainer_num);
  virtual void SetFleetSendBatchSize(int64_t size);
  virtual void SetHdfsConfig(const std::string& fs_name,
                             const std::string& fs_ugi);
  virtual void SetDownloadCmd(const std::string& download_cmd);
  virtual void SetDataFeedDesc(const std::string& data_feed_desc_str);
  virtual void SetChannelNum(int channel_num);
  virtual void SetParseInsId(bool parse_ins_id);
  virtual void SetParseContent(bool parse_content);
  virtual void SetMergeByInsId(int merge_size);
  virtual void SetGenerateUniqueFeasign(bool gen_uni_feasigns);
  virtual void SetFeaEval(bool fea_eval, int record_candidate_size);
  virtual const std::vector<std::string>& GetFileList() { return filelist_; }
  virtual int GetThreadNum() { return thread_num_; }
  virtual int GetTrainerNum() { return trainer_num_; }
  virtual Channel<T> GetInputChannel() { return input_channel_; }
  virtual int64_t GetFleetSendBatchSize() { return fleet_send_batch_size_; }
  virtual std::pair<std::string, std::string> GetHdfsConfig() {
    return std::make_pair(fs_name_, fs_ugi_);
  }
  virtual std::string GetDownloadCmd();
  virtual const paddle::framework::DataFeedDesc& GetDataFeedDesc() {
    return data_feed_desc_;
  }
  virtual int GetChannelNum() { return channel_num_; }
  virtual std::vector<paddle::framework::DataFeed*> GetReaders();
  virtual void CreateChannel();
  virtual void RegisterClientToClientMsgHandler();
  virtual void LoadIntoMemory();
  virtual void PreLoadIntoMemory();
  virtual void WaitPreLoadDone();
  virtual void ReleaseMemory();
  virtual void LocalShuffle();
  virtual void GlobalShuffle(int thread_num = -1);
  virtual void SlotsShuffle(const std::set<std::string>& slots_to_replace) {}
  virtual void GetRandomData(const std::set<uint16_t>& slots_to_replace,
                             std::vector<Record>* result) {}
  virtual void CreateReaders();
  virtual void DestroyReaders();
  virtual int64_t GetMemoryDataSize();
  virtual int64_t GetShuffleDataSize();
  virtual void MergeByInsId() {}
  virtual void GenerateLocalTablesUnlock(int table_id, int feadim,
                                         int read_thread_num,
                                         int consume_thread_num,
                                         int shard_num) {}
  virtual void ClearLocalTables() {}
  virtual void CreatePreLoadReaders();
  virtual void DestroyPreLoadReaders();
  virtual void SetPreLoadThreadNum(int thread_num);
  virtual void DynamicAdjustChannelNum(int channel_num,
                                       bool discard_remaining_ins = false);
  virtual void DynamicAdjustReadersNum(int thread_num);
  virtual void SetFleetSendSleepSeconds(int seconds);

 protected:
  virtual int ReceiveFromClient(int msg_type, int client_id,
                                const std::string& msg);
  std::vector<std::shared_ptr<paddle::framework::DataFeed>> readers_;
  std::vector<std::shared_ptr<paddle::framework::DataFeed>> preload_readers_;
  paddle::framework::Channel<T> input_channel_;
  int channel_num_;
  std::vector<paddle::framework::Channel<T>> multi_output_channel_;
  std::vector<paddle::framework::Channel<T>> multi_consume_channel_;
  std::vector<std::unordered_set<uint64_t>> local_tables_;
  // when read ins, we put ins from one channel to the other,
  // and when finish reading, we set cur_channel = 1 - cur_channel,
  // so if cur_channel=0, all data are in output_channel, else consume_channel
  int cur_channel_;
  std::vector<T> slots_shuffle_original_data_;
  RecordCandidateList slots_shuffle_rclist_;
  int thread_num_;
  int pull_sparse_to_local_thread_num_;
  paddle::framework::DataFeedDesc data_feed_desc_;
  int trainer_num_;
  std::vector<std::string> filelist_;
  size_t file_idx_;
  std::mutex mutex_for_pick_file_;
  std::string fs_name_;
  std::string fs_ugi_;
  int64_t fleet_send_batch_size_;
  int64_t fleet_send_sleep_seconds_;
  std::vector<std::thread> preload_threads_;
  bool merge_by_insid_;
  bool parse_ins_id_;
  bool parse_content_;
  size_t merge_size_;
  bool slots_shuffle_fea_eval_ = false;
  bool gen_uni_feasigns_ = false;
  int preload_thread_num_;
  std::mutex global_index_mutex_;
  int64_t global_index_ = 0;
  std::vector<std::shared_ptr<ThreadPool>> consume_task_pool_;
};

// use std::vector<MultiSlotType> or Record as data type
class MultiSlotDataset : public DatasetImpl<Record> {
 public:
  MultiSlotDataset() {}
  virtual void MergeByInsId();
  virtual void GenerateLocalTablesUnlock(int table_id, int feadim,
                                         int read_thread_num,
                                         int consume_thread_num, int shard_num);
  virtual void ClearLocalTables() {
    for (auto& t : local_tables_) {
      t.clear();
      std::unordered_set<uint64_t>().swap(t);
    }
    std::vector<std::unordered_set<uint64_t>>().swap(local_tables_);
  }
  virtual void SlotsShuffle(const std::set<std::string>& slots_to_replace);
  virtual void GetRandomData(const std::set<uint16_t>& slots_to_replace,
                             std::vector<Record>* result);
  virtual ~MultiSlotDataset() {}
};

}  // end namespace framework
}  // end namespace paddle