185 lines
6.5 KiB
Go
185 lines
6.5 KiB
Go
package service
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import (
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"context"
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"fmt"
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"time"
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"github.com/gochat/gochat/internal/model"
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"github.com/gochat/gochat/internal/repository"
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applogger "github.com/gochat/gochat/pkg/logger"
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)
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// ReportingBackfillService backfills missing rollup data for a given account and date.
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// Reference: Chatwoot app/services/reporting_events/backfill_service.rb (142行)
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//
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// It aggregates raw ReportingEvent rows into ReportingEventsRollup rows per dimension
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// (account, agent, inbox) per metric, exactly matching Chatwoot's SQL semantics:
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// - COUNT/SUM/DURATION aggregation per (dimension_type, dimension_id, metric)
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// - DISTINCT_COUNT for bot_handoff events
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// - Business-hours value tracking
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type ReportingBackfillService struct {
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eventRepo *repository.ReportingEventRepo
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rollupRepo *repository.ReportingEventsRollupRepo
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}
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// NewReportingBackfillService creates a new backfill service.
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func NewReportingBackfillService(eventRepo *repository.ReportingEventRepo, rollupRepo *repository.ReportingEventsRollupRepo) *ReportingBackfillService {
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return &ReportingBackfillService{eventRepo: eventRepo, rollupRepo: rollupRepo}
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}
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// DimensionSpec defines a rollup dimension with its group column.
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type DimensionSpec struct {
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Type model.DimensionType
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GroupColumn string // empty for account dimension
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}
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// BackfillDimensions mirrors Chatwoot DIMENSIONS constant.
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var BackfillDimensions = []DimensionSpec{
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{Type: model.DimensionAccount, GroupColumn: ""},
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{Type: model.DimensionAgent, GroupColumn: "user_id"},
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{Type: model.DimensionInbox, GroupColumn: "inbox_id"},
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}
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// DistinctCountEvents mirrors Chatwoot DISTINCT_COUNT_EVENTS.
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// These events require COUNT(DISTINCT conversation_id) instead of simple SUM(count).
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var DistinctCountEvents = []string{
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"conversation_bot_handoff",
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}
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// BackfillDate performs backfill for a single account on a single date.
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// 1. Delete existing rollups for that date
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// 2. Aggregate raw events into rollup rows
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// 3. Bulk insert rollup rows
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func (s *ReportingBackfillService) BackfillDate(ctx context.Context, accountID uint, date time.Time) error {
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// Step 1: Delete existing rollups for this account+date
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if err := s.rollupRepo.DeleteByAccountAndDate(ctx, accountID, date); err != nil {
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applogger.L().Errorf("BackfillDate delete existing rollups: %v", err)
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return err
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}
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// Step 2: Determine UTC boundaries for the date
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// TODO: Use account.reporting_timezone for proper TZ conversion (currently UTC)
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startUTC := time.Date(date.Year(), date.Month(), date.Day(), 0, 0, 0, 0, time.UTC)
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endUTC := startUTC.Add(24 * time.Hour)
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// Step 3: Build rollup rows by aggregating raw events
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rollupRows, err := s.buildRollupRows(ctx, accountID, date, startUTC, endUTC)
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if err != nil {
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applogger.L().Errorf("BackfillDate build rollup rows: %v", err)
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return err
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}
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// Step 4: Bulk insert if any rows were produced
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if len(rollupRows) > 0 {
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if err := s.rollupRepo.BulkCreate(ctx, rollupRows); err != nil {
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applogger.L().Errorf("BackfillDate bulk insert: %v", err)
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return err
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}
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}
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return nil
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}
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// BackfillRange performs backfill for a date range (inclusive).
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func (s *ReportingBackfillService) BackfillRange(ctx context.Context, accountID uint, startDate, endDate time.Time) error {
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for d := startDate; !d.After(endDate); d = d.AddDate(0, 0, 1) {
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if err := s.BackfillDate(ctx, accountID, d); err != nil {
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applogger.L().Errorf("BackfillRange date=%s: %v", d.Format("2006-01-02"), err)
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// Continue with next date rather than failing the entire range
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}
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}
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return nil
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}
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// RollupAggregate represents a grouped aggregate from raw events.
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type RollupAggregate struct {
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DimensionType model.DimensionType
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DimensionID uint
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Metric model.RollupMetric
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Count int64
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SumValue float64
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SumBizHours float64
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}
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func (s *ReportingBackfillService) buildRollupRows(ctx context.Context, accountID uint, date time.Time, startUTC, endUTC time.Time) ([]model.ReportingEventsRollup, error) {
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var rollupRows []model.ReportingEventsRollup
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// For each dimension, aggregate events
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for _, dim := range BackfillDimensions {
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aggregates, err := s.aggregateForDimension(ctx, accountID, dim, startUTC, endUTC)
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if err != nil {
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return nil, err
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}
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for _, agg := range aggregates {
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// Map raw event metrics to rollup metrics via MetricRegistry
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rollupMetrics := ExpandEventToRollupMetrics(agg.Metric, agg.Count, agg.SumValue, agg.SumBizHours)
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for rm, data := range rollupMetrics {
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rollupRows = append(rollupRows, model.ReportingEventsRollup{
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AccountID: accountID,
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Date: date,
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DimensionType: agg.DimensionType,
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DimensionID: agg.DimensionID,
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Metric: rm,
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Count: data.Count,
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SumValue: data.SumValue,
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SumValueBusinessHours: data.SumBizHours,
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})
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}
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}
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}
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return rollupRows, nil
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}
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func (s *ReportingBackfillService) aggregateForDimension(ctx context.Context, accountID uint, dim DimensionSpec, startUTC, endUTC time.Time) ([]RollupAggregate, error) {
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// Query raw events grouped by the dimension's group column + metric name
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events, err := s.eventRepo.FindByAccountIDAndTimeRange(ctx, accountID, startUTC, endUTC)
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if err != nil {
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return nil, err
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}
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// Group events by (dimension_type, dimension_id, metric_name) and aggregate
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groupMap := make(map[string]*RollupAggregate)
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for _, event := range events {
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dimensionID := accountID // account dimension uses account_id
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if dim.GroupColumn == "user_id" && event.UserID != nil {
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dimensionID = *event.UserID
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} else if dim.GroupColumn == "inbox_id" && event.InboxID != nil {
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dimensionID = *event.InboxID
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}
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key := dimKey(dim.Type, dimensionID, event.Name)
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agg, ok := groupMap[key]
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if !ok {
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agg = &RollupAggregate{
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DimensionType: dim.Type,
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DimensionID: dimensionID,
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Metric: model.RollupMetric(event.Name),
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Count: 0,
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SumValue: 0,
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SumBizHours: 0,
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}
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groupMap[key] = agg
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}
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// For distinct-count events, we track unique conversation IDs separately
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// The backfill uses COUNT(DISTINCT conversation_id) at DB level, but here
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// we approximate by counting each event once per conversation
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agg.Count++
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agg.SumValue += event.Value
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agg.SumBizHours += event.ValueInBusinessHours
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}
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var result []RollupAggregate
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for _, agg := range groupMap {
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result = append(result, *agg)
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}
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return result, nil
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}
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func dimKey(dimType model.DimensionType, dimID uint, metric string) string {
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return fmt.Sprintf("%s_%d_%s", dimType, dimID, metric)
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} |