389 lines
13 KiB
Go
389 lines
13 KiB
Go
package services
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import (
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"context"
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"fmt"
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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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// StatisticsAggregateService 统计聚合服务接口
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// 负责统计数据的聚合和计算
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type StatisticsAggregateService interface {
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// 实时统计
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UpdateRealtimeMetric(ctx context.Context, metricType, metricName string, value float64) error
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GetRealtimeMetrics(ctx context.Context, metricType string) (map[string]float64, error)
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// 历史统计聚合
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AggregateHourlyMetrics(ctx context.Context, date time.Time) error
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AggregateDailyMetrics(ctx context.Context, date time.Time) error
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AggregateWeeklyMetrics(ctx context.Context, date time.Time) error
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AggregateMonthlyMetrics(ctx context.Context, date time.Time) error
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// 统计查询
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GetMetricsByType(ctx context.Context, metricType string, startDate, endDate time.Time) ([]*entities.StatisticsMetric, error)
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GetMetricsByDimension(ctx context.Context, metricType, dimension string, startDate, endDate time.Time) ([]*entities.StatisticsMetric, error)
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// 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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}
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// StatisticsAggregateServiceImpl 统计聚合服务实现
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type StatisticsAggregateServiceImpl struct {
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metricRepo repositories.StatisticsRepository
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logger *zap.Logger
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}
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// NewStatisticsAggregateService 创建统计聚合服务
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func NewStatisticsAggregateService(
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metricRepo repositories.StatisticsRepository,
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logger *zap.Logger,
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) StatisticsAggregateService {
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return &StatisticsAggregateServiceImpl{
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metricRepo: metricRepo,
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logger: logger,
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}
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}
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// UpdateRealtimeMetric 更新实时统计指标
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func (s *StatisticsAggregateServiceImpl) UpdateRealtimeMetric(ctx context.Context, metricType, metricName string, value float64) error {
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if metricType == "" {
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return fmt.Errorf("指标类型不能为空")
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}
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if metricName == "" {
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return fmt.Errorf("指标名称不能为空")
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}
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// 创建或更新实时指标
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metric, err := entities.NewStatisticsMetric(metricType, metricName, "realtime", value, time.Now())
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if err != nil {
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s.logger.Error("创建统计指标失败",
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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("创建统计指标失败: %w", err)
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}
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// 保存到数据库
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err = s.metricRepo.Save(ctx, metric)
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if err != nil {
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s.logger.Error("保存统计指标失败",
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zap.String("metric_id", metric.ID),
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zap.Error(err))
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return fmt.Errorf("保存统计指标失败: %w", err)
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}
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s.logger.Info("实时统计指标更新成功",
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zap.String("metric_type", metricType),
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zap.String("metric_name", metricName),
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zap.Float64("value", value))
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return nil
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}
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// GetRealtimeMetrics 获取实时统计指标
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func (s *StatisticsAggregateServiceImpl) GetRealtimeMetrics(ctx context.Context, metricType string) (map[string]float64, error) {
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if metricType == "" {
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return nil, fmt.Errorf("指标类型不能为空")
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}
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// 获取今天的实时指标
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today := time.Now().Truncate(24 * time.Hour)
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tomorrow := today.Add(24 * time.Hour)
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metrics, err := s.metricRepo.FindByTypeAndDateRange(ctx, metricType, today, tomorrow)
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if err != nil {
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s.logger.Error("查询实时统计指标失败",
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zap.String("metric_type", metricType),
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zap.Error(err))
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return nil, fmt.Errorf("查询实时统计指标失败: %w", err)
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}
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// 转换为map格式
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result := make(map[string]float64)
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for _, metric := range metrics {
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if metric.Dimension == "realtime" {
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result[metric.MetricName] = metric.Value
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}
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}
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return result, nil
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}
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// AggregateHourlyMetrics 聚合小时级统计指标
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func (s *StatisticsAggregateServiceImpl) AggregateHourlyMetrics(ctx context.Context, date time.Time) error {
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s.logger.Info("开始聚合小时级统计指标", zap.Time("date", date))
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// 获取指定小时的所有实时指标
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startTime := date.Truncate(time.Hour)
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endTime := startTime.Add(time.Hour)
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// 聚合不同类型的指标
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metricTypes := []string{"api_calls", "users", "finance", "products", "certification"}
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for _, metricType := range metricTypes {
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err := s.aggregateMetricsByType(ctx, metricType, startTime, endTime, "hourly")
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if err != nil {
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s.logger.Error("聚合小时级指标失败",
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zap.String("metric_type", metricType),
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zap.Error(err))
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return fmt.Errorf("聚合小时级指标失败: %w", err)
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}
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}
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s.logger.Info("小时级统计指标聚合完成", zap.Time("date", date))
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return nil
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}
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// AggregateDailyMetrics 聚合日级统计指标
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func (s *StatisticsAggregateServiceImpl) AggregateDailyMetrics(ctx context.Context, date time.Time) error {
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s.logger.Info("开始聚合日级统计指标", zap.Time("date", date))
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// 获取指定日期的所有小时级指标
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startTime := date.Truncate(24 * time.Hour)
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endTime := startTime.Add(24 * time.Hour)
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// 聚合不同类型的指标
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metricTypes := []string{"api_calls", "users", "finance", "products", "certification"}
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for _, metricType := range metricTypes {
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err := s.aggregateMetricsByType(ctx, metricType, startTime, endTime, "daily")
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if err != nil {
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s.logger.Error("聚合日级指标失败",
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zap.String("metric_type", metricType),
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zap.Error(err))
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return fmt.Errorf("聚合日级指标失败: %w", err)
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}
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}
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s.logger.Info("日级统计指标聚合完成", zap.Time("date", date))
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return nil
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}
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// AggregateWeeklyMetrics 聚合周级统计指标
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func (s *StatisticsAggregateServiceImpl) AggregateWeeklyMetrics(ctx context.Context, date time.Time) error {
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s.logger.Info("开始聚合周级统计指标", zap.Time("date", date))
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// 获取指定周的所有日级指标
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startTime := date.Truncate(24 * time.Hour)
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endTime := startTime.Add(7 * 24 * time.Hour)
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// 聚合不同类型的指标
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metricTypes := []string{"api_calls", "users", "finance", "products", "certification"}
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for _, metricType := range metricTypes {
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err := s.aggregateMetricsByType(ctx, metricType, startTime, endTime, "weekly")
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if err != nil {
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s.logger.Error("聚合周级指标失败",
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zap.String("metric_type", metricType),
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zap.Error(err))
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return fmt.Errorf("聚合周级指标失败: %w", err)
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}
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}
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s.logger.Info("周级统计指标聚合完成", zap.Time("date", date))
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return nil
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}
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// AggregateMonthlyMetrics 聚合月级统计指标
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func (s *StatisticsAggregateServiceImpl) AggregateMonthlyMetrics(ctx context.Context, date time.Time) error {
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s.logger.Info("开始聚合月级统计指标", zap.Time("date", date))
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// 获取指定月的所有日级指标
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startTime := date.Truncate(24 * time.Hour)
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endTime := startTime.AddDate(0, 1, 0)
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// 聚合不同类型的指标
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metricTypes := []string{"api_calls", "users", "finance", "products", "certification"}
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for _, metricType := range metricTypes {
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err := s.aggregateMetricsByType(ctx, metricType, startTime, endTime, "monthly")
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if err != nil {
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s.logger.Error("聚合月级指标失败",
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zap.String("metric_type", metricType),
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zap.Error(err))
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return fmt.Errorf("聚合月级指标失败: %w", err)
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}
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}
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s.logger.Info("月级统计指标聚合完成", zap.Time("date", date))
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return nil
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}
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// GetMetricsByType 根据类型获取统计指标
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func (s *StatisticsAggregateServiceImpl) GetMetricsByType(ctx context.Context, metricType string, startDate, endDate time.Time) ([]*entities.StatisticsMetric, error) {
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if metricType == "" {
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return nil, fmt.Errorf("指标类型不能为空")
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}
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metrics, err := s.metricRepo.FindByTypeAndDateRange(ctx, metricType, startDate, endDate)
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if err != nil {
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s.logger.Error("查询统计指标失败",
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zap.String("metric_type", metricType),
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zap.Time("start_date", startDate),
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zap.Time("end_date", endDate),
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zap.Error(err))
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return nil, fmt.Errorf("查询统计指标失败: %w", err)
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}
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return metrics, nil
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}
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// GetMetricsByDimension 根据维度获取统计指标
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func (s *StatisticsAggregateServiceImpl) GetMetricsByDimension(ctx context.Context, metricType, dimension string, startDate, endDate time.Time) ([]*entities.StatisticsMetric, error) {
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if metricType == "" {
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return nil, fmt.Errorf("指标类型不能为空")
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}
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if dimension == "" {
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return nil, fmt.Errorf("统计维度不能为空")
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}
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metrics, err := s.metricRepo.FindByTypeDimensionAndDateRange(ctx, metricType, dimension, startDate, endDate)
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if err != nil {
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s.logger.Error("查询统计指标失败",
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zap.String("metric_type", metricType),
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zap.String("dimension", dimension),
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zap.Time("start_date", startDate),
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zap.Time("end_date", endDate),
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zap.Error(err))
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return nil, fmt.Errorf("查询统计指标失败: %w", err)
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}
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return metrics, nil
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}
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// CalculateGrowthRate 计算增长率
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func (s *StatisticsAggregateServiceImpl) 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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// 获取当前周期的指标值
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currentMetrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, currentPeriod, currentPeriod.Add(24*time.Hour))
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if err != nil {
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return 0, fmt.Errorf("查询当前周期指标失败: %w", err)
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}
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// 获取上一周期的指标值
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previousMetrics, err := s.metricRepo.FindByTypeNameAndDateRange(ctx, metricType, metricName, previousPeriod, previousPeriod.Add(24*time.Hour))
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if err != nil {
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return 0, fmt.Errorf("查询上一周期指标失败: %w", err)
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}
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// 计算总值
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var currentValue, previousValue float64
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for _, metric := range currentMetrics {
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currentValue += metric.Value
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}
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for _, metric := range previousMetrics {
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previousValue += metric.Value
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}
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// 计算增长率
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if previousValue == 0 {
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if currentValue > 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 := ((currentValue - previousValue) / previousValue) * 100
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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 *StatisticsAggregateServiceImpl) 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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// 获取时间范围内的指标
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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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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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sortMetricsByDate(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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if lastValue > firstValue {
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return "increasing", nil // 上升趋势
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} else if lastValue < firstValue {
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return "decreasing", nil // 下降趋势
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} else {
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return "stable", nil // 稳定趋势
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}
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}
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// aggregateMetricsByType 按类型聚合指标
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func (s *StatisticsAggregateServiceImpl) aggregateMetricsByType(ctx context.Context, metricType string, startTime, endTime time.Time, dimension string) error {
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// 获取源数据（实时或小时级数据）
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sourceDimension := "realtime"
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if dimension == "daily" {
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sourceDimension = "hourly"
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} else if dimension == "weekly" || dimension == "monthly" {
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sourceDimension = "daily"
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}
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// 查询源数据
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sourceMetrics, err := s.metricRepo.FindByTypeDimensionAndDateRange(ctx, metricType, sourceDimension, startTime, endTime)
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if err != nil {
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return fmt.Errorf("查询源数据失败: %w", err)
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}
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// 按指标名称分组聚合
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metricGroups := make(map[string][]*entities.StatisticsMetric)
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for _, metric := range sourceMetrics {
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metricGroups[metric.MetricName] = append(metricGroups[metric.MetricName], metric)
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}
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// 聚合每个指标
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for metricName, metrics := range metricGroups {
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var totalValue float64
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for _, metric := range metrics {
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totalValue += metric.Value
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}
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// 创建聚合后的指标
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aggregatedMetric, err := entities.NewStatisticsMetric(metricType, metricName, dimension, totalValue, startTime)
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if err != nil {
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return fmt.Errorf("创建聚合指标失败: %w", err)
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}
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// 保存聚合指标
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err = s.metricRepo.Save(ctx, aggregatedMetric)
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if err != nil {
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return fmt.Errorf("保存聚合指标失败: %w", err)
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}
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}
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return nil
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}
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// sortMetricsByDate 按日期排序指标
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func sortMetricsByDate(metrics []*entities.StatisticsMetric) {
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// 简单的冒泡排序
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n := len(metrics)
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for i := 0; i < n-1; i++ {
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for j := 0; j < n-i-1; j++ {
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if metrics[j].Date.After(metrics[j+1].Date) {
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metrics[j], metrics[j+1] = metrics[j+1], metrics[j]
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}
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}
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}
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}
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