511 lines
16 KiB
Go
511 lines
16 KiB
Go
package services
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import (
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"context"
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"fmt"
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"math"
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"time"
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"go.uber.org/zap"
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"tyapi-server/internal/domains/statistics/entities"
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"tyapi-server/internal/domains/statistics/repositories"
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)
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// StatisticsCalculationService 统计计算服务接口
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// 负责各种统计计算和分析
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type StatisticsCalculationService interface {
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// 基础统计计算
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CalculateTotal(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (float64, error)
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CalculateAverage(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (float64, error)
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CalculateMax(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (float64, error)
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CalculateMin(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (float64, error)
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// 高级统计计算
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CalculateGrowthRate(ctx context.Context, metricType, metricName string, currentPeriod, previousPeriod time.Time) (float64, error)
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CalculateTrend(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (string, error)
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CalculateCorrelation(ctx context.Context, metricType1, metricName1, metricType2, metricName2 string, startDate, endDate time.Time) (float64, error)
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// 业务指标计算
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CalculateSuccessRate(ctx context.Context, startDate, endDate time.Time) (float64, error)
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CalculateConversionRate(ctx context.Context, startDate, endDate time.Time) (float64, error)
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CalculateRetentionRate(ctx context.Context, startDate, endDate time.Time) (float64, error)
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// 时间序列分析
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CalculateMovingAverage(ctx context.Context, metricType, metricName string, startDate, endDate time.Time, windowSize int) ([]float64, error)
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CalculateSeasonality(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (map[string]float64, error)
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}
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// StatisticsCalculationServiceImpl 统计计算服务实现
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type StatisticsCalculationServiceImpl struct {
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metricRepo repositories.StatisticsRepository
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logger *zap.Logger
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}
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// NewStatisticsCalculationService 创建统计计算服务
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func NewStatisticsCalculationService(
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metricRepo repositories.StatisticsRepository,
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logger *zap.Logger,
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) StatisticsCalculationService {
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return &StatisticsCalculationServiceImpl{
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metricRepo: metricRepo,
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logger: logger,
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}
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}
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// CalculateTotal 计算总值
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func (s *StatisticsCalculationServiceImpl) CalculateTotal(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (float64, error) {
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if metricType == "" || metricName == "" {
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return 0, fmt.Errorf("指标类型和名称不能为空")
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}
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metrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, startDate, endDate)
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if err != nil {
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s.logger.Error("查询指标失败",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Error(err))
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return 0, fmt.Errorf("查询指标失败: %w", err)
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}
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var total float64
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for _, metric := range metrics {
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total += metric.Value
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}
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s.logger.Info("计算总值完成",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Float64("total", total))
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return total, nil
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}
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// CalculateAverage 计算平均值
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func (s *StatisticsCalculationServiceImpl) CalculateAverage(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (float64, error) {
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if metricType == "" || metricName == "" {
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return 0, fmt.Errorf("指标类型和名称不能为空")
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}
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metrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, startDate, endDate)
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if err != nil {
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s.logger.Error("查询指标失败",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Error(err))
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return 0, fmt.Errorf("查询指标失败: %w", err)
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}
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if len(metrics) == 0 {
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return 0, nil
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}
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var total float64
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for _, metric := range metrics {
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total += metric.Value
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}
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average := total / float64(len(metrics))
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s.logger.Info("计算平均值完成",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Float64("average", average))
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return average, nil
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}
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// CalculateMax 计算最大值
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func (s *StatisticsCalculationServiceImpl) CalculateMax(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (float64, error) {
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if metricType == "" || metricName == "" {
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return 0, fmt.Errorf("指标类型和名称不能为空")
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}
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metrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, startDate, endDate)
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if err != nil {
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s.logger.Error("查询指标失败",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Error(err))
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return 0, fmt.Errorf("查询指标失败: %w", err)
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}
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if len(metrics) == 0 {
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return 0, nil
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}
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max := metrics[0].Value
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for _, metric := range metrics {
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if metric.Value > max {
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max = metric.Value
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}
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}
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s.logger.Info("计算最大值完成",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Float64("max", max))
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return max, nil
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}
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// CalculateMin 计算最小值
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func (s *StatisticsCalculationServiceImpl) CalculateMin(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (float64, error) {
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if metricType == "" || metricName == "" {
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return 0, fmt.Errorf("指标类型和名称不能为空")
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}
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metrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, startDate, endDate)
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if err != nil {
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s.logger.Error("查询指标失败",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Error(err))
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return 0, fmt.Errorf("查询指标失败: %w", err)
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}
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if len(metrics) == 0 {
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return 0, nil
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}
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min := metrics[0].Value
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for _, metric := range metrics {
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if metric.Value < min {
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min = metric.Value
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}
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}
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s.logger.Info("计算最小值完成",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Float64("min", min))
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return min, nil
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}
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// CalculateGrowthRate 计算增长率
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func (s *StatisticsCalculationServiceImpl) CalculateGrowthRate(ctx context.Context, metricType, metricName string, currentPeriod, previousPeriod time.Time) (float64, error) {
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if metricType == "" || metricName == "" {
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return 0, fmt.Errorf("指标类型和名称不能为空")
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}
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// 获取当前周期的总值
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currentTotal, err := s.CalculateTotal(ctx, metricType, metricName, currentPeriod, currentPeriod.Add(24*time.Hour))
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if err != nil {
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return 0, fmt.Errorf("计算当前周期总值失败: %w", err)
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}
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// 获取上一周期的总值
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previousTotal, err := s.CalculateTotal(ctx, metricType, metricName, previousPeriod, previousPeriod.Add(24*time.Hour))
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if err != nil {
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return 0, fmt.Errorf("计算上一周期总值失败: %w", err)
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}
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// 计算增长率
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if previousTotal == 0 {
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if currentTotal > 0 {
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return 100, nil // 从0增长到正数，增长率为100%
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}
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return 0, nil // 都是0，增长率为0%
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}
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growthRate := ((currentTotal - previousTotal) / previousTotal) * 100
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s.logger.Info("计算增长率完成",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Float64("growth_rate", growthRate))
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return growthRate, nil
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}
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// CalculateTrend 计算趋势
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func (s *StatisticsCalculationServiceImpl) CalculateTrend(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (string, error) {
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if metricType == "" || metricName == "" {
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return "", fmt.Errorf("指标类型和名称不能为空")
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}
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metrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, startDate, endDate)
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if err != nil {
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s.logger.Error("查询指标失败",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Error(err))
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return "", fmt.Errorf("查询指标失败: %w", err)
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}
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if len(metrics) < 2 {
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return "insufficient_data", nil // 数据不足
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}
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// 按时间排序
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sortMetricsByDateCalc(metrics)
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// 计算趋势
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firstValue := metrics[0].Value
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lastValue := metrics[len(metrics)-1].Value
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var trend string
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if lastValue > firstValue {
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trend = "increasing" // 上升趋势
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} else if lastValue < firstValue {
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trend = "decreasing" // 下降趋势
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} else {
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trend = "stable" // 稳定趋势
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}
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s.logger.Info("计算趋势完成",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.String("trend", trend))
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return trend, nil
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}
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// CalculateCorrelation 计算相关性
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func (s *StatisticsCalculationServiceImpl) CalculateCorrelation(ctx context.Context, metricType1, metricName1, metricType2, metricName2 string, startDate, endDate time.Time) (float64, error) {
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if metricType1 == "" || metricName1 == "" || metricType2 == "" || metricName2 == "" {
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return 0, fmt.Errorf("指标类型和名称不能为空")
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}
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// 获取两个指标的数据
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metrics1, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType1, metricName1, startDate, endDate)
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if err != nil {
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return 0, fmt.Errorf("查询指标1失败: %w", err)
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}
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metrics2, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType2, metricName2, startDate, endDate)
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if err != nil {
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return 0, fmt.Errorf("查询指标2失败: %w", err)
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}
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if len(metrics1) != len(metrics2) || len(metrics1) < 2 {
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return 0, fmt.Errorf("数据点数量不足或不对称")
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}
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// 计算皮尔逊相关系数
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correlation := s.calculatePearsonCorrelation(metrics1, metrics2)
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s.logger.Info("计算相关性完成",
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zap.String("metric1", metricType1+"."+metricName1),
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zap.String("metric2", metricType2+"."+metricName2),
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zap.Float64("correlation", correlation))
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return correlation, nil
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}
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// CalculateSuccessRate 计算成功率
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func (s *StatisticsCalculationServiceImpl) CalculateSuccessRate(ctx context.Context, startDate, endDate time.Time) (float64, error) {
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// 获取成功调用次数
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successTotal, err := s.CalculateTotal(ctx, "api_calls", "success_count", startDate, endDate)
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if err != nil {
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return 0, fmt.Errorf("计算成功调用次数失败: %w", err)
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}
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// 获取总调用次数
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totalCalls, err := s.CalculateTotal(ctx, "api_calls", "total_count", startDate, endDate)
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if err != nil {
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return 0, fmt.Errorf("计算总调用次数失败: %w", err)
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}
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if totalCalls == 0 {
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return 0, nil
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}
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successRate := (successTotal / totalCalls) * 100
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s.logger.Info("计算成功率完成",
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zap.Float64("success_rate", successRate))
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return successRate, nil
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}
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// CalculateConversionRate 计算转化率
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func (s *StatisticsCalculationServiceImpl) CalculateConversionRate(ctx context.Context, startDate, endDate time.Time) (float64, error) {
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// 获取认证用户数
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certifiedUsers, err := s.CalculateTotal(ctx, "users", "certified_count", startDate, endDate)
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if err != nil {
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return 0, fmt.Errorf("计算认证用户数失败: %w", err)
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}
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// 获取总用户数
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totalUsers, err := s.CalculateTotal(ctx, "users", "total_count", startDate, endDate)
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if err != nil {
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return 0, fmt.Errorf("计算总用户数失败: %w", err)
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}
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if totalUsers == 0 {
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return 0, nil
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}
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conversionRate := (certifiedUsers / totalUsers) * 100
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s.logger.Info("计算转化率完成",
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zap.Float64("conversion_rate", conversionRate))
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return conversionRate, nil
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}
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// CalculateRetentionRate 计算留存率
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func (s *StatisticsCalculationServiceImpl) CalculateRetentionRate(ctx context.Context, startDate, endDate time.Time) (float64, error) {
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// 获取活跃用户数
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activeUsers, err := s.CalculateTotal(ctx, "users", "active_count", startDate, endDate)
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if err != nil {
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return 0, fmt.Errorf("计算活跃用户数失败: %w", err)
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}
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// 获取总用户数
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totalUsers, err := s.CalculateTotal(ctx, "users", "total_count", startDate, endDate)
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if err != nil {
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return 0, fmt.Errorf("计算总用户数失败: %w", err)
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}
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if totalUsers == 0 {
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return 0, nil
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}
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retentionRate := (activeUsers / totalUsers) * 100
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s.logger.Info("计算留存率完成",
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zap.Float64("retention_rate", retentionRate))
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return retentionRate, nil
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}
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// CalculateMovingAverage 计算移动平均
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func (s *StatisticsCalculationServiceImpl) CalculateMovingAverage(ctx context.Context, metricType, metricName string, startDate, endDate time.Time, windowSize int) ([]float64, error) {
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if metricType == "" || metricName == "" {
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return nil, fmt.Errorf("指标类型和名称不能为空")
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}
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if windowSize <= 0 {
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return nil, fmt.Errorf("窗口大小必须大于0")
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}
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metrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, startDate, endDate)
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if err != nil {
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s.logger.Error("查询指标失败",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Error(err))
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return nil, fmt.Errorf("查询指标失败: %w", err)
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}
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if len(metrics) < windowSize {
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return nil, fmt.Errorf("数据点数量不足")
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}
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// 按时间排序
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sortMetricsByDateCalc(metrics)
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// 计算移动平均
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var movingAverages []float64
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for i := windowSize - 1; i < len(metrics); i++ {
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var sum float64
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for j := i - windowSize + 1; j <= i; j++ {
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sum += metrics[j].Value
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}
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average := sum / float64(windowSize)
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movingAverages = append(movingAverages, average)
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}
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s.logger.Info("计算移动平均完成",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Int("window_size", windowSize),
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zap.Int("result_count", len(movingAverages)))
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return movingAverages, nil
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}
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// CalculateSeasonality 计算季节性
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func (s *StatisticsCalculationServiceImpl) CalculateSeasonality(ctx context.Context, metricType, metricName string, startDate, endDate time.Time) (map[string]float64, error) {
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if metricType == "" || metricName == "" {
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return nil, fmt.Errorf("指标类型和名称不能为空")
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}
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metrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, startDate, endDate)
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if err != nil {
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s.logger.Error("查询指标失败",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Error(err))
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return nil, fmt.Errorf("查询指标失败: %w", err)
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}
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if len(metrics) < 7 {
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return nil, fmt.Errorf("数据点数量不足，至少需要7个数据点")
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}
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// 按星期几分组
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weeklyAverages := make(map[string][]float64)
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for _, metric := range metrics {
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weekday := metric.Date.Weekday().String()
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weeklyAverages[weekday] = append(weeklyAverages[weekday], metric.Value)
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}
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// 计算每个星期几的平均值
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seasonality := make(map[string]float64)
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for weekday, values := range weeklyAverages {
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var sum float64
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for _, value := range values {
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sum += value
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}
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seasonality[weekday] = sum / float64(len(values))
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}
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s.logger.Info("计算季节性完成",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Int("weekday_count", len(seasonality)))
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return seasonality, nil
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}
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// calculatePearsonCorrelation 计算皮尔逊相关系数
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func (s *StatisticsCalculationServiceImpl) calculatePearsonCorrelation(metrics1, metrics2 []*entities.StatisticsMetric) float64 {
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n := len(metrics1)
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if n < 2 {
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return 0
|
||
}
|
||
|
||
// 计算均值
|
||
var sum1, sum2 float64
|
||
for i := 0; i < n; i++ {
|
||
sum1 += metrics1[i].Value
|
||
sum2 += metrics2[i].Value
|
||
}
|
||
mean1 := sum1 / float64(n)
|
||
mean2 := sum2 / float64(n)
|
||
|
||
// 计算协方差和方差
|
||
var numerator, denominator1, denominator2 float64
|
||
for i := 0; i < n; i++ {
|
||
diff1 := metrics1[i].Value - mean1
|
||
diff2 := metrics2[i].Value - mean2
|
||
numerator += diff1 * diff2
|
||
denominator1 += diff1 * diff1
|
||
denominator2 += diff2 * diff2
|
||
}
|
||
|
||
// 计算相关系数
|
||
if denominator1 == 0 || denominator2 == 0 {
|
||
return 0
|
||
}
|
||
|
||
correlation := numerator / math.Sqrt(denominator1*denominator2)
|
||
return correlation
|
||
}
|
||
|
||
// sortMetricsByDateCalc 按日期排序指标
|
||
func sortMetricsByDateCalc(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]
|
||
}
|
||
}
|
||
}
|
||
}
|