package services

import (
	"context"
	"fmt"
	"time"

	"go.uber.org/zap"

	"tyapi-server/internal/domains/statistics/entities"
	"tyapi-server/internal/domains/statistics/repositories"
)

// StatisticsAggregateService 统计聚合服务接口
// 负责统计数据的聚合和计算
type StatisticsAggregateService interface {
	// 实时统计
	UpdateRealtimeMetric(ctx context.Context, metricType, metricName string, value float64) error
	GetRealtimeMetrics(ctx context.Context, metricType string) (map[string]float64, error)
	
	// 历史统计聚合
	AggregateHourlyMetrics(ctx context.Context, date time.Time) error
	AggregateDailyMetrics(ctx context.Context, date time.Time) error
	AggregateWeeklyMetrics(ctx context.Context, date time.Time) error
	AggregateMonthlyMetrics(ctx context.Context, date time.Time) error
	
	// 统计查询
	GetMetricsByType(ctx context.Context, metricType string, startDate, endDate time.Time) ([]*entities.StatisticsMetric, error)
	GetMetricsByDimension(ctx context.Context, metricType, dimension string, startDate, endDate time.Time) ([]*entities.StatisticsMetric, error)
	
	// 统计计算
	CalculateGrowthRate(ctx context.Context, metricType, metricName string, currentPeriod, previousPeriod time.Time) (float64, error)
	CalculateTrend(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (string, error)
}

// StatisticsAggregateServiceImpl 统计聚合服务实现
type StatisticsAggregateServiceImpl struct {
	metricRepo repositories.StatisticsRepository
	logger     *zap.Logger
}

// NewStatisticsAggregateService 创建统计聚合服务
func NewStatisticsAggregateService(
	metricRepo repositories.StatisticsRepository,
	logger *zap.Logger,
) StatisticsAggregateService {
	return &StatisticsAggregateServiceImpl{
		metricRepo: metricRepo,
		logger:     logger,
	}
}

// UpdateRealtimeMetric 更新实时统计指标
func (s *StatisticsAggregateServiceImpl) UpdateRealtimeMetric(ctx context.Context, metricType, metricName string, value float64) error {
	if metricType == "" {
		return fmt.Errorf("指标类型不能为空")
	}
	if metricName == "" {
		return fmt.Errorf("指标名称不能为空")
	}

	// 创建或更新实时指标
	metric, err := entities.NewStatisticsMetric(metricType, metricName, "realtime", value, time.Now())
	if err != nil {
		s.logger.Error("创建统计指标失败", 
			zap.String("metric_type", metricType),
			zap.String("metric_name", metricName),
			zap.Error(err))
		return fmt.Errorf("创建统计指标失败: %w", err)
	}

	// 保存到数据库
	err = s.metricRepo.Save(ctx, metric)
	if err != nil {
		s.logger.Error("保存统计指标失败", 
			zap.String("metric_id", metric.ID),
			zap.Error(err))
		return fmt.Errorf("保存统计指标失败: %w", err)
	}

	s.logger.Info("实时统计指标更新成功",
		zap.String("metric_type", metricType),
		zap.String("metric_name", metricName),
		zap.Float64("value", value))

	return nil
}

// GetRealtimeMetrics 获取实时统计指标
func (s *StatisticsAggregateServiceImpl) GetRealtimeMetrics(ctx context.Context, metricType string) (map[string]float64, error) {
	if metricType == "" {
		return nil, fmt.Errorf("指标类型不能为空")
	}

	// 获取今天的实时指标
	today := time.Now().Truncate(24 * time.Hour)
	tomorrow := today.Add(24 * time.Hour)

	metrics, err := s.metricRepo.FindByTypeAndDateRange(ctx, metricType, today, tomorrow)
	if err != nil {
		s.logger.Error("查询实时统计指标失败", 
			zap.String("metric_type", metricType),
			zap.Error(err))
		return nil, fmt.Errorf("查询实时统计指标失败: %w", err)
	}

	// 转换为map格式
	result := make(map[string]float64)
	for _, metric := range metrics {
		if metric.Dimension == "realtime" {
			result[metric.MetricName] = metric.Value
		}
	}

	return result, nil
}

// AggregateHourlyMetrics 聚合小时级统计指标
func (s *StatisticsAggregateServiceImpl) AggregateHourlyMetrics(ctx context.Context, date time.Time) error {
	s.logger.Info("开始聚合小时级统计指标", zap.Time("date", date))

	// 获取指定小时的所有实时指标
	startTime := date.Truncate(time.Hour)
	endTime := startTime.Add(time.Hour)

	// 聚合不同类型的指标
	metricTypes := []string{"api_calls", "users", "finance", "products", "certification"}
	
	for _, metricType := range metricTypes {
		err := s.aggregateMetricsByType(ctx, metricType, startTime, endTime, "hourly")
		if err != nil {
			s.logger.Error("聚合小时级指标失败", 
				zap.String("metric_type", metricType),
				zap.Error(err))
			return fmt.Errorf("聚合小时级指标失败: %w", err)
		}
	}

	s.logger.Info("小时级统计指标聚合完成", zap.Time("date", date))
	return nil
}

// AggregateDailyMetrics 聚合日级统计指标
func (s *StatisticsAggregateServiceImpl) AggregateDailyMetrics(ctx context.Context, date time.Time) error {
	s.logger.Info("开始聚合日级统计指标", zap.Time("date", date))

	// 获取指定日期的所有小时级指标
	startTime := date.Truncate(24 * time.Hour)
	endTime := startTime.Add(24 * time.Hour)

	// 聚合不同类型的指标
	metricTypes := []string{"api_calls", "users", "finance", "products", "certification"}
	
	for _, metricType := range metricTypes {
		err := s.aggregateMetricsByType(ctx, metricType, startTime, endTime, "daily")
		if err != nil {
			s.logger.Error("聚合日级指标失败", 
				zap.String("metric_type", metricType),
				zap.Error(err))
			return fmt.Errorf("聚合日级指标失败: %w", err)
		}
	}

	s.logger.Info("日级统计指标聚合完成", zap.Time("date", date))
	return nil
}

// AggregateWeeklyMetrics 聚合周级统计指标
func (s *StatisticsAggregateServiceImpl) AggregateWeeklyMetrics(ctx context.Context, date time.Time) error {
	s.logger.Info("开始聚合周级统计指标", zap.Time("date", date))

	// 获取指定周的所有日级指标
	startTime := date.Truncate(24 * time.Hour)
	endTime := startTime.Add(7 * 24 * time.Hour)

	// 聚合不同类型的指标
	metricTypes := []string{"api_calls", "users", "finance", "products", "certification"}
	
	for _, metricType := range metricTypes {
		err := s.aggregateMetricsByType(ctx, metricType, startTime, endTime, "weekly")
		if err != nil {
			s.logger.Error("聚合周级指标失败", 
				zap.String("metric_type", metricType),
				zap.Error(err))
			return fmt.Errorf("聚合周级指标失败: %w", err)
		}
	}

	s.logger.Info("周级统计指标聚合完成", zap.Time("date", date))
	return nil
}

// AggregateMonthlyMetrics 聚合月级统计指标
func (s *StatisticsAggregateServiceImpl) AggregateMonthlyMetrics(ctx context.Context, date time.Time) error {
	s.logger.Info("开始聚合月级统计指标", zap.Time("date", date))

	// 获取指定月的所有日级指标
	startTime := date.Truncate(24 * time.Hour)
	endTime := startTime.AddDate(0, 1, 0)

	// 聚合不同类型的指标
	metricTypes := []string{"api_calls", "users", "finance", "products", "certification"}
	
	for _, metricType := range metricTypes {
		err := s.aggregateMetricsByType(ctx, metricType, startTime, endTime, "monthly")
		if err != nil {
			s.logger.Error("聚合月级指标失败", 
				zap.String("metric_type", metricType),
				zap.Error(err))
			return fmt.Errorf("聚合月级指标失败: %w", err)
		}
	}

	s.logger.Info("月级统计指标聚合完成", zap.Time("date", date))
	return nil
}

// GetMetricsByType 根据类型获取统计指标
func (s *StatisticsAggregateServiceImpl) GetMetricsByType(ctx context.Context, metricType string, startDate, endDate time.Time) ([]*entities.StatisticsMetric, error) {
	if metricType == "" {
		return nil, fmt.Errorf("指标类型不能为空")
	}

	metrics, err := s.metricRepo.FindByTypeAndDateRange(ctx, metricType, startDate, endDate)
	if err != nil {
		s.logger.Error("查询统计指标失败", 
			zap.String("metric_type", metricType),
			zap.Time("start_date", startDate),
			zap.Time("end_date", endDate),
			zap.Error(err))
		return nil, fmt.Errorf("查询统计指标失败: %w", err)
	}

	return metrics, nil
}

// GetMetricsByDimension 根据维度获取统计指标
func (s *StatisticsAggregateServiceImpl) GetMetricsByDimension(ctx context.Context, metricType, dimension string, startDate, endDate time.Time) ([]*entities.StatisticsMetric, error) {
	if metricType == "" {
		return nil, fmt.Errorf("指标类型不能为空")
	}
	if dimension == "" {
		return nil, fmt.Errorf("统计维度不能为空")
	}

	metrics, err := s.metricRepo.FindByTypeDimensionAndDateRange(ctx, metricType, dimension, startDate, endDate)
	if err != nil {
		s.logger.Error("查询统计指标失败", 
			zap.String("metric_type", metricType),
			zap.String("dimension", dimension),
			zap.Time("start_date", startDate),
			zap.Time("end_date", endDate),
			zap.Error(err))
		return nil, fmt.Errorf("查询统计指标失败: %w", err)
	}

	return metrics, nil
}

// CalculateGrowthRate 计算增长率
func (s *StatisticsAggregateServiceImpl) CalculateGrowthRate(ctx context.Context, metricType, metricName string, currentPeriod, previousPeriod time.Time) (float64, error) {
	if metricType == "" || metricName == "" {
		return 0, fmt.Errorf("指标类型和名称不能为空")
	}

	// 获取当前周期的指标值
	currentMetrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, currentPeriod, currentPeriod.Add(24*time.Hour))
	if err != nil {
		return 0, fmt.Errorf("查询当前周期指标失败: %w", err)
	}

	// 获取上一周期的指标值
	previousMetrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, previousPeriod, previousPeriod.Add(24*time.Hour))
	if err != nil {
		return 0, fmt.Errorf("查询上一周期指标失败: %w", err)
	}

	// 计算总值
	var currentValue, previousValue float64
	for _, metric := range currentMetrics {
		currentValue += metric.Value
	}
	for _, metric := range previousMetrics {
		previousValue += metric.Value
	}

	// 计算增长率
	if previousValue == 0 {
		if currentValue > 0 {
			return 100, nil // 从0增长到正数，增长率为100%
		}
		return 0, nil // 都是0，增长率为0%
	}

	growthRate := ((currentValue - previousValue) / previousValue) * 100
	return growthRate, nil
}

// CalculateTrend 计算趋势
func (s *StatisticsAggregateServiceImpl) CalculateTrend(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (string, error) {
	if metricType == "" || metricName == "" {
		return "", fmt.Errorf("指标类型和名称不能为空")
	}

	// 获取时间范围内的指标
	metrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, startDate, endDate)
	if err != nil {
		return "", fmt.Errorf("查询指标失败: %w", err)
	}

	if len(metrics) < 2 {
		return "insufficient_data", nil // 数据不足
	}

	// 按时间排序
	sortMetricsByDate(metrics)

	// 计算趋势
	firstValue := metrics[0].Value
	lastValue := metrics[len(metrics)-1].Value

	if lastValue > firstValue {
		return "increasing", nil // 上升趋势
	} else if lastValue < firstValue {
		return "decreasing", nil // 下降趋势
	} else {
		return "stable", nil // 稳定趋势
	}
}

// aggregateMetricsByType 按类型聚合指标
func (s *StatisticsAggregateServiceImpl) aggregateMetricsByType(ctx context.Context, metricType string, startTime, endTime time.Time, dimension string) error {
	// 获取源数据（实时或小时级数据）
	sourceDimension := "realtime"
	if dimension == "daily" {
		sourceDimension = "hourly"
	} else if dimension == "weekly" || dimension == "monthly" {
		sourceDimension = "daily"
	}

	// 查询源数据
	sourceMetrics, err := s.metricRepo.FindByTypeDimensionAndDateRange(ctx, metricType, sourceDimension, startTime, endTime)
	if err != nil {
		return fmt.Errorf("查询源数据失败: %w", err)
	}

	// 按指标名称分组聚合
	metricGroups := make(map[string][]*entities.StatisticsMetric)
	for _, metric := range sourceMetrics {
		metricGroups[metric.MetricName] = append(metricGroups[metric.MetricName], metric)
	}

	// 聚合每个指标
	for metricName, metrics := range metricGroups {
		var totalValue float64
		for _, metric := range metrics {
			totalValue += metric.Value
		}

		// 创建聚合后的指标
		aggregatedMetric, err := entities.NewStatisticsMetric(metricType, metricName, dimension, totalValue, startTime)
		if err != nil {
			return fmt.Errorf("创建聚合指标失败: %w", err)
		}

		// 保存聚合指标
		err = s.metricRepo.Save(ctx, aggregatedMetric)
		if err != nil {
			return fmt.Errorf("保存聚合指标失败: %w", err)
		}
	}

	return nil
}

// sortMetricsByDate 按日期排序指标
func sortMetricsByDate(metrics []*entities.StatisticsMetric) {
	// 简单的冒泡排序
	n := len(metrics)
	for i := 0; i < n-1; i++ {
		for j := 0; j < n-i-1; j++ {
			if metrics[j].Date.After(metrics[j+1].Date) {
				metrics[j], metrics[j+1] = metrics[j+1], metrics[j]
			}
		}
	}
}