/*
 * @file  WorkflowRunner.h
 * @brief 目前不能在WorkflowRunner中使用Logger(Log4cxx),因为目前这个阶段还没有设置Logger类型，后期把它重构成C++类，可以这么用。
 *  Created on: 2011-6-17
 *      Author: John.Huang
 */

#ifndef PAI_FRAME_WORKFLOWENGINE_WORKFLOWRUNNER_H
#define PAI_FRAME_WORKFLOWENGINE_WORKFLOWRUNNER_H

#include "Module.h"
#include "MutiParallModule.h"
#include "ModuleSelfSplitSupport.h"
#include "Buffer.h"
#include "pb_gen/splitInfo.pb.h"
#include <set>
#include <vector>
#include <string>
#include <iostream>
#include <map>

using namespace pai::module;

typedef struct workflow_modify_input_filter workflow_modify_input_filter;
typedef struct workflow_del_input_filter workflow_del_input_filter;
typedef struct workflow_input_info workflow_input_info;
typedef struct workflow_output_filter workflow_output_filter;
typedef struct workflow_info workflow_info;
/**
 * 修改Filter类型
 */
enum ModifyFilterType
{
    //没有过滤参数集合
    NO_FILTER,
    //有过滤参数集合，但是没有排序关键字
    NO_ORDER_KEY,
    //有过滤参数集合，有排序关键字
    HAS_ORDER__KEY
};

struct workflow_modify_input_filter
{
    /*
    * ModifyFilter类型
    * 0:没有filteritems
    *   先判断是否有node(id="files[*].traceselection"),否则需要添加;然后Add新的filteritem
    * 1:没有排序关键字的filteritem
    *   在node(id="files[*].traceselection")添加filteritem子节点
    * 2:有排序关键字的filteritem
    *   重新设置设param_item_id(id=“files[*].traceselection[*]”)的CUSTOM节点的子节点(start,end)
    */
    ModifyFilterType modify_filter_type;
    std::string param_item_id;
    std::string key;
    std::string start;
    std::string end;
    //increment default;
    //exclude default
    //And/Or default
    workflow_modify_input_filter(): modify_filter_type(), param_item_id(), key(), start(), end(){}
    void Print(int index = 0)
    {
       std::cout << "\t\tworkflow_modify_input_filter(" << index << "):" << std::endl;
       std::cout << "\t\t{" << std::endl;
       std::cout << "\t\t\tmodify_filter_type=" <<  static_cast<int>(modify_filter_type) << std::endl;
       std::cout << "\t\t\tparam_item_id=" << param_item_id << std::endl;
       std::cout << "\t\t\tkey=" << key << std::endl;
       std::cout << "\t\t\tstart=" << start << std::endl;
       std::cout << "\t\t\tend=" << end << std::endl;
       std::cout << "\t\t}" << std::endl;
    };
    bool equal(workflow_modify_input_filter& other)
    {
    	if(param_item_id.compare(other.param_item_id) != 0)
    		return false;
    	if(key.compare(other.key) != 0)
    		return false;
    	if(start.compare(other.start) != 0)
    	    return false;
    	if(end.compare(other.end) != 0)
    	    return false;
    	if(modify_filter_type != other.modify_filter_type)
    		return false;
    	return true;
    }
};

struct workflow_del_input_filter
{
    std::string param_item_id;
    workflow_del_input_filter():param_item_id(){}
    void Print(int index = 0)
    {
       std::cout << "\t\tworkflow_del_input_filter(" << index << "):" << std::endl;
       std::cout << "\t\t{" << std::endl;
       std::cout << "\t\t\tparam_item_id=" << param_item_id << std::endl;
       std::cout << "\t\t}" << std::endl;
    };
    bool equal(workflow_del_input_filter& other)
    {
    	if(param_item_id.compare(other.param_item_id)!=0)
    		return false;
    	return true;
    };
};

struct workflow_input_info
{
    //inputmodule runtime_id
    std::string module_context_id;
    //inputmodule 需要修改的filter参数项目
    std::vector<workflow_modify_input_filter> modify_filters;
    //inputmodule 需要删除的filter参数项目
    std::vector<workflow_del_input_filter> del_filters;
    workflow_input_info():module_context_id(), modify_filters(), del_filters(){}
    void Print(int index = 0)
    {
       std::cout << "\tworkflow_input_info(" << index << "):" << std::endl;
       std::cout << "\t{" << std::endl;
       std::cout << "\t\tmodule_context_id=" <<  module_context_id << std::endl;
       std::cout << "\t\tmodify_filters:" << std::endl;
       std::cout << "\t\t[" << std::endl;
       size_t modify_size = modify_filters.size();
       for(size_t i = 0;i < modify_size;i++)
       {
           workflow_modify_input_filter modify = modify_filters.at(i);
           modify.Print(static_cast<int>(i));
       }
       std::cout << "\t\t]" << std::endl;
       std::cout << "\t\tdel_filters:" << std::endl;
       std::cout << "\t\t[" << std::endl;
       size_t del_size = del_filters.size();
       for(size_t i = 0;i < del_size;i++)
       {
           workflow_del_input_filter del = del_filters.at(i);
           del.Print(static_cast<int>(i));
       }
       std::cout << "\t\t]" << std::endl;
       std::cout << "\t}" << std::endl;
    };
    bool equal(workflow_input_info& other)
    {
    	if(module_context_id.compare(other.module_context_id)!=0)
    	    return false;
    	if(modify_filters.size() != other.modify_filters.size())
    		return false;
    	else if(modify_filters.size() > 0)
    		for(size_t i = 0;i < modify_filters.size();i++)
    		{
    			workflow_modify_input_filter modify = modify_filters.at(i);
    			if(!modify.equal(other.modify_filters.at(i)))
    				return false;
    		}
    	if(del_filters.size() != other.del_filters.size())
    		return false;
    	else if(del_filters.size() > 0)
    		for(size_t i = 0;i < del_filters.size();i++)
    	    {
    			workflow_del_input_filter del = del_filters.at(i);
    	    	if(!del.equal(other.del_filters.at(i)))
    	    		return false;
    	    }
    	return true;
    }
};

struct workflow_output_filter
{
    std::string param_item_id;
    std::string filenames;
    workflow_output_filter():param_item_id(), filenames(){}
    void Print(int index = 0)
    {
      std::cout << "\t\tworkflow_output_filter(" << index << "):" << std::endl;
      std::cout << "\t\t{" << std::endl;
      std::cout << "\t\t\tparam_item_id=" << param_item_id << std::endl;
      std::cout << "\t\t\tfilenames=" << filenames << std::endl;
      std::cout << "\t\t}" << std::endl;
    };
    bool equal(workflow_output_filter& other)
    {
    	if(param_item_id.compare(other.param_item_id)!=0)
    	    return false;
    	if(filenames.compare(other.filenames)!=0)
    	    return false;
    	return true;
    }
};

struct workflow_output_info
{
    //outputmodule runtime_id
    std::string module_context_id;
    //outputmodule 需要重新设置过滤参数项
    std::vector<workflow_output_filter> filters;
    workflow_output_info():module_context_id(), filters(){}
    void Print(int index = 0)
    {
       std::cout << "\tworkflow_output_info(" << index << "):" << std::endl;
       std::cout << "\t{" << std::endl;
       std::cout << "\t\tmodule_context_id=" <<  module_context_id << std::endl;
       std::cout << "\t\tfilters:" << std::endl;
       std::cout << "\t\t[" << std::endl;
       size_t size = filters.size();
       for(size_t i = 0;i < size;i++)
       {
           workflow_output_filter filter = filters.at(i);
           filter.Print(static_cast<int>(i));
       }
       std::cout << "\t\t]" << std::endl;
       std::cout << "\t}" << std::endl;
    };
    bool equal(workflow_output_info& other)
    {
    	if(module_context_id.compare(other.module_context_id) != 0)
    		return false;
    	if(filters.size() != other.filters.size())
    		return false;
    	else if(filters.size() > 0)
    		for(size_t i=0; i<filters.size(); i++)
    		{
    			workflow_output_filter filter = filters.at(i);
    			if(!filter.equal(other.filters.at(i)))
    				return false;
    		}
    	return true;
    }
};

struct workflow_info {

	std::string id;
	TaskInfo taskInfo;
	//inputmodule 因为切片重新设置的参数项信息
	std::vector<workflow_input_info> inputs;
	//outputmodule 因为切片重新设置的参数项信息
	std::vector<workflow_output_info> outputs;
	//用于统计到回调函数
	Callback cb_update_module_progress;
	workflow_info():id(), taskInfo(), inputs(), outputs(), cb_update_module_progress(){}
	void Print()
	{
	    std::cout << "workflow_info:" << std::endl;
	    std::cout << "{"  << std::endl;
	    std::cout << "\tid=" <<  id << std::endl;
	    std::cout << "\tjob_id=" <<  taskInfo.job_id << std::endl;
	    std::cout << "\tattempt_id=" <<  taskInfo.attempt_id << std::endl;
	    std::cout << "\thostname=" <<  taskInfo.hostname << std::endl;
	    std::cout << "\tinputs:" << std::endl;
	    std::cout << "\t[" << std::endl;
        size_t inputs_size = inputs.size();
	    for( size_t i = 0;i < inputs_size;i++)
	    {
	        workflow_input_info input = inputs.at(i);
	        input.Print(static_cast<int>(i));
	    }
	    std::cout << "\t]" << std::endl;
        std::cout << "\toutputs:" << std::endl;
        std::cout << "\t[" << std::endl;
        size_t outputs_size = outputs.size();
        for( size_t i = 0;i < outputs_size;i++)
        {
            workflow_output_info output = outputs.at(i);
            output.Print(static_cast<int>(i));
        }
        std::cout << "\t]" << std::endl;
        std::cout << "}" << std::endl;
	};
};

struct ReduceInfo
{
	TaskInfo taskInfo;
	//outputmodule 因为切片重新设置的参数项信息
	std::vector<workflow_output_info> outputs;
	//prevision hadoop jobid
	std::string preJobId;
	std::map<std::string,std::string> parameters;
    //用于统计到回调函数
    Callback cb_update_module_progress;
    ReduceInfo():taskInfo(), outputs(), preJobId(), parameters(), cb_update_module_progress()
    {}
	void Print()
	{
		std::cout << "ReduceInfo:" << std::endl;
		std::cout << "{"  << std::endl;
		std::cout << "\tjob_id=" <<  taskInfo.job_id << std::endl;
		std::cout << "\tattempt_id=" <<  taskInfo.attempt_id << std::endl;
		std::cout << "\thostname=" <<  taskInfo.hostname << std::endl;
		std::cout << "\tpreJobId=" <<  preJobId << std::endl;
		std::cout << "\tparameters size=" <<  parameters.size() << std::endl;
		for(std::map<std::string,std::string>::iterator iter = parameters.begin();iter!=parameters.end();++iter){
			std::cout << "\toparam[" << iter->first <<"]=" << iter->second << std::endl;
		}
		std::cout << "\toutputs size=" << outputs.size()  << std::endl;
		std::cout << "\t{"  << std::endl;
		size_t outputs_size = outputs.size();
		for( size_t i = 0;i < outputs_size;i++)
		{
			workflow_output_info output = outputs.at(i);
			output.Print(static_cast<int>(i));
		}
		std::cout << "\t}"  << std::endl;
		std::cout << "}" << std::endl;
	};
};

struct JobInfo
{
	//outputmodule 因为切片重新设置的参数项信息
	std::vector<workflow_output_info> outputs;
	bool isReduceWorkflow;
	TaskInfo taskInfo;
	JobInfo():outputs(), isReduceWorkflow(), taskInfo(){}
	void Print()
	{
		std::cout << "JobInfo:" << std::endl;
		std::cout << "{"  << std::endl;
		std::cout << "\tisReduceWorkflow=" <<  isReduceWorkflow << std::endl;
		std::cout << "\tjob_id=" <<  taskInfo.job_id << std::endl;
		std::cout << "\tattempt_id=" <<  taskInfo.attempt_id << std::endl;
		std::cout << "\thostname=" <<  taskInfo.hostname << std::endl;
		std::cout << "\toutputs size=" << outputs.size()  << std::endl;
		std::cout << "\t{" << std::endl;
		for(size_t i=0; i<outputs.size(); i++)
		{
			outputs.at(i).Print(static_cast<int>(i));
		}
		std::cout << "\t}" << std::endl;
		std::cout << "}" << std::endl;
	};
	bool equal(JobInfo& other)
	{
		if(isReduceWorkflow != other.isReduceWorkflow)
			return false;
		if(taskInfo.job_id.compare(other.taskInfo.job_id) != 0)
			return false;
		if(taskInfo.attempt_id.compare(other.taskInfo.attempt_id) != 0)
			return false;
		if(taskInfo.hostname.compare(other.taskInfo.hostname) != 0)
			return false;

		//compare outputs
		if(outputs.size() != other.outputs.size())
			return false;
		for(size_t i=0; i<outputs.size(); i++)
		{
			if(!outputs.at(i).equal(other.outputs.at(i)))
			{
				return false;
			}
		}
		return true;
	}
};

/**
 * 在所有子工作流运行前，执行此方法。
 */
void BeforeJob(const JobInfo& workflow);
/**
 * 在所有子工作流运行后，执行此方法。
 */
void AfterJob(const JobInfo& workflow);
/**
 * 运行工作流Reduce
 */
void RunReduce(const ReduceInfo& reduce);
/**
 * abortJob
 */
void AbortJob(const JobInfo& job,const bool isFailed);
/**
 * abortTask
 */
void AbortTask(const JobInfo& job);


//****************************************************************
//                  below refactor part of workflowrunner
//****************************************************************
namespace pai {
namespace workflow {
/**
 * @brief workflow执行器
 * 目前主要对于工作流各种阶段，为Job提供执行服务
 */
class WorkflowRunner
{
public:
	WorkflowRunner():m_workflow(),m_reduce(),m_config(),m_split(NULL),firstStartedModules(),split_msg_(NULL){
	};
	void SetWorkflowInfo(const workflow_info& workflow){
		this->m_workflow = workflow;
	};
	workflow_info GetWorkflowInfo() const{
		return this->m_workflow;
	};
	Split* GetModuleSelfSplit() const{
		return this->m_split;
	}
    void SetModuleSelfSplit(Split* split){
    	m_split = split;
    };
	void SetReduceInfo(const ReduceInfo& reduce){
		this->m_reduce = reduce;
	};
	ReduceInfo GetReduceInfo() const{
		return this->m_reduce;
	}
	void SetConfiguration(const std::map<std::string,std::string>& config){
		this->m_config = config;
	};
	inline void SetSplitMessage(google::protobuf::Message* s){
	    split_msg_=s;
	}
	/**
	 * 运行Map工作流
	 */
	void RunWorkflow();
	/**
	 * 运行Reduce工作流
	 */
	void RunReduce();

	void BeforeJob(const JobInfo& job);

	void AfterJob(const JobInfo& job);
	/**
	 * abortJob:
	 * @param[job] the job's info
	 * @param[isFailed] if the job is failed or killed
	 */
	void AbortJob(const JobInfo& job,const bool isFailed);

	void AbortTask(const JobInfo& job);


private:
    bool IsFirstStartModule(CModule* module);
    bool IsOutputModule(CModule* module){
    	if(module->GetClassName() == "COutputModule")
    		return true;
    	else
    		return false;
    };
    bool IsUseModuleSelfSplit(){
    	if(m_split!=NULL)
    		return true;
    	else
    		return false;
    };
    WorkflowRunner(const WorkflowRunner & runner);
	WorkflowRunner & operator=(const WorkflowRunner & runner);
private:
	workflow_info m_workflow;
	ReduceInfo m_reduce;
	std::map<std::string,std::string> m_config;
	Split* m_split;
	std::set<std::string> firstStartedModules;
	//it's created by split factory,so need destry it.
	google::protobuf::Message* split_msg_;

};

}
}
#endif