fix: enhance monitoring metrics with latest sample aggregation and derived metrics calculations

server/internal/tenant/app/monitoring_callback_service_test.go

@@ -1,6 +1,7 @@
 package app
 
 import (
+	"context"
 	"database/sql"
 	"encoding/json"
 	"errors"
@@ -9,6 +10,8 @@ import (
 	"time"
 
 	"github.com/google/uuid"
+	"github.com/stretchr/testify/assert"
+	"github.com/stretchr/testify/require"
 )
 
 func TestDecideHeartbeatPrimaryLease(t *testing.T) {
@@ -111,6 +114,42 @@ func TestMonitoringHeartbeatPrimaryLeaseMetrics(t *testing.T) {
 	}
 }
 
+func TestLoadMonitoringBrandDailyAggregateUsesLatestQuestionPlatformSamples(t *testing.T) {
+	tx := &captureDailyMonitorTaskTx{}
+
+	_, err := (&MonitoringCallbackService{}).loadMonitoringBrandDailyAggregate(
+		context.Background(),
+		tx,
+		3,
+		3,
+		time.Date(2026, 6, 29, 0, 0, 0, 0, monitoringBusinessLocation()),
+	)
+
+	require.NoError(t, err)
+	require.Len(t, tx.queryRowSQLs, 5)
+	combined := normalizeSQLWhitespace(strings.Join(tx.queryRowSQLs, " "))
+	assert.Contains(t, combined, "SELECT DISTINCT ON (business_date, question_id, ai_platform_id)")
+	assert.Contains(t, combined, "p.brand_mentioned IS TRUE AND p.sentiment_label = 'positive'")
+}
+
+func TestLoadMonitoringPlatformDailyAggregatesUsesLatestQuestionPlatformSamples(t *testing.T) {
+	tx := &captureDailyMonitorTaskTx{}
+
+	_, err := (&MonitoringCallbackService{}).loadMonitoringPlatformDailyAggregates(
+		context.Background(),
+		tx,
+		3,
+		3,
+		time.Date(2026, 6, 29, 0, 0, 0, 0, monitoringBusinessLocation()),
+		[]monitoringPlatformMetadata{{ID: "doubao", Name: "豆包"}},
+	)
+
+	require.NoError(t, err)
+	require.GreaterOrEqual(t, len(tx.querySQLs), 2)
+	combined := normalizeSQLWhitespace(strings.Join(tx.querySQLs, " "))
+	assert.Contains(t, combined, "SELECT DISTINCT ON (business_date, question_id, ai_platform_id)")
+}
+
 func TestDecideMonitoringHeartbeatSnapshot(t *testing.T) {
 	now := time.Date(2026, 4, 24, 3, 0, 0, 0, time.UTC)
 	base := monitoringPlatformAccessSnapshotState{

server/internal/tenant/app/monitoring_daily_task_worker_test.go

@@ -2,6 +2,7 @@ package app
 
 import (
 	"context"
+	"database/sql"
 	"net/http"
 	"net/http/httptest"
 	"runtime"
@@ -745,7 +746,12 @@ type captureDailyMonitorTaskTx struct {
 	queryCalled bool
 	querySQL    string
 	queryArgs   []any
-	commandTag  pgconn.CommandTag
+	querySQLs   []string
+	queryArgses []any
+
+	queryRowSQLs   []string
+	queryRowArgses [][]any
+	commandTag     pgconn.CommandTag
 }
 
 func (tx *captureDailyMonitorTaskTx) Begin(context.Context) (pgx.Tx, error) { return tx, nil }
@@ -773,9 +779,13 @@ func (tx *captureDailyMonitorTaskTx) Query(_ context.Context, sql string, argume
 	tx.queryCalled = true
 	tx.querySQL = sql
 	tx.queryArgs = arguments
+	tx.querySQLs = append(tx.querySQLs, sql)
+	tx.queryArgses = append(tx.queryArgses, arguments...)
 	return emptyDailyMonitorRows{}, nil
 }
-func (tx *captureDailyMonitorTaskTx) QueryRow(context.Context, string, ...any) pgx.Row {
+func (tx *captureDailyMonitorTaskTx) QueryRow(_ context.Context, sql string, arguments ...any) pgx.Row {
+	tx.queryRowSQLs = append(tx.queryRowSQLs, sql)
+	tx.queryRowArgses = append(tx.queryRowArgses, arguments)
 	return boolDailyMonitorRow(true)
 }
 func (tx *captureDailyMonitorTaskTx) Conn() *pgx.Conn { return nil }
@@ -785,9 +795,18 @@ var _ pgx.Tx = (*captureDailyMonitorTaskTx)(nil)
 type boolDailyMonitorRow bool
 
 func (r boolDailyMonitorRow) Scan(dest ...any) error {
-	if len(dest) == 1 {
-		if value, ok := dest[0].(*bool); ok {
+	for _, target := range dest {
+		switch value := target.(type) {
+		case *bool:
 			*value = bool(r)
+		case *int64:
+			*value = 0
+		case *string:
+			*value = ""
+		case *sql.NullTime:
+			*value = sql.NullTime{}
+		case *sql.NullString:
+			*value = sql.NullString{}
 		}
 	}
 	return nil

server/internal/tenant/app/monitoring_projection.go

@@ -173,12 +173,20 @@ func (s *MonitoringCallbackService) loadMonitoringBrandDailyAggregate(ctx contex
 
 	if err := tx.QueryRow(ctx, `
 		SELECT COUNT(*), MAX(completed_at)
-		FROM question_monitor_runs
-		WHERE tenant_id = $1
-		  AND brand_id = $2
-		  AND collector_type = $3
-		  AND business_date = $4::date
-		  AND status = 'succeeded'
+		FROM (
+			SELECT DISTINCT ON (business_date, question_id, ai_platform_id)
+				completed_at,
+				updated_at,
+				created_at,
+				id
+			FROM question_monitor_runs
+			WHERE tenant_id = $1
+			  AND brand_id = $2
+			  AND collector_type = $3
+			  AND business_date = $4::date
+			  AND status = 'succeeded'
+			ORDER BY business_date, question_id, ai_platform_id, COALESCE(completed_at, updated_at, created_at) DESC NULLS LAST, id DESC
+		) latest_runs
 	`, tenantID, brandID, monitoringCollectorType, dateText).Scan(&agg.ActualSampleCount, &agg.SnapshotUpdatedAt); err != nil {
 		return agg, monitoringInternalError(50041, "run_projection_lookup_failed", "failed to load monitoring run counts", err)
 	}
@@ -188,15 +196,27 @@ func (s *MonitoringCallbackService) loadMonitoringBrandDailyAggregate(ctx contex
 			COUNT(*) FILTER (WHERE p.brand_mentioned IS TRUE)::bigint,
 			COUNT(*) FILTER (WHERE p.brand_mention_position = 'top1')::bigint,
 			COUNT(*) FILTER (WHERE p.first_recommended IS TRUE)::bigint,
-			COUNT(*) FILTER (WHERE p.sentiment_label = 'positive')::bigint
-		FROM question_monitor_runs r
+			COUNT(*) FILTER (WHERE p.brand_mentioned IS TRUE AND p.sentiment_label = 'positive')::bigint
+		FROM (
+			SELECT DISTINCT ON (business_date, question_id, ai_platform_id)
+				id,
+				tenant_id,
+				business_date,
+				question_id,
+				ai_platform_id,
+				completed_at,
+				updated_at,
+				created_at
+			FROM question_monitor_runs
+			WHERE tenant_id = $1
+			  AND brand_id = $2
+			  AND collector_type = $3
+			  AND business_date = $4::date
+			  AND status = 'succeeded'
+			ORDER BY business_date, question_id, ai_platform_id, COALESCE(completed_at, updated_at, created_at) DESC NULLS LAST, id DESC
+		) r
 		LEFT JOIN question_monitor_parse_results p
 			ON p.tenant_id = r.tenant_id AND p.run_id = r.id
-		WHERE r.tenant_id = $1
-		  AND r.brand_id = $2
-		  AND r.collector_type = $3
-		  AND r.business_date = $4::date
-		  AND r.status = 'succeeded'
 	`, tenantID, brandID, monitoringCollectorType, dateText).Scan(
 		&agg.MentionedCount,
 		&agg.Top1MentionedCount,
@@ -280,14 +300,24 @@ func (s *MonitoringCallbackService) loadMonitoringPlatformDailyAggregates(ctx co
 			COUNT(*) FILTER (WHERE p.brand_mentioned IS TRUE)::bigint AS mentioned_count,
 			COUNT(*) FILTER (WHERE p.brand_mention_position = 'top1')::bigint AS top1_mentioned_count,
 			MAX(r.completed_at) AS last_sampled_at
-		FROM question_monitor_runs r
+		FROM (
+			SELECT DISTINCT ON (business_date, question_id, ai_platform_id)
+				id,
+				tenant_id,
+				ai_platform_id,
+				completed_at,
+				updated_at,
+				created_at
+			FROM question_monitor_runs
+			WHERE tenant_id = $1
+			  AND brand_id = $2
+			  AND collector_type = $3
+			  AND business_date = $4::date
+			  AND status = 'succeeded'
+			ORDER BY business_date, question_id, ai_platform_id, COALESCE(completed_at, updated_at, created_at) DESC NULLS LAST, id DESC
+		) r
 		LEFT JOIN question_monitor_parse_results p
 			ON p.tenant_id = r.tenant_id AND p.run_id = r.id
-		WHERE r.tenant_id = $1
-		  AND r.brand_id = $2
-		  AND r.collector_type = $3
-		  AND r.business_date = $4::date
-		  AND r.status = 'succeeded'
 		GROUP BY r.ai_platform_id
 	`, tenantID, brandID, monitoringCollectorType, dateText)
 	if err != nil {

server/internal/tenant/app/monitoring_service.go

@@ -349,6 +349,21 @@ type monitoringDerivedMetrics struct {
 	ByQuestion     map[int64]monitoringDerivedRateStats
 }
 
+type monitoringDerivedSampleKey struct {
+	Date       string
+	PlatformID string
+	QuestionID int64
+}
+
+type monitoringDerivedParseSample struct {
+	BusinessDate time.Time
+	PlatformID   string
+	QuestionID   int64
+	EventAt      sql.NullTime
+	RunID        int64
+	Summary      monitoringAnswerParseSummary
+}
+
 type monitoringPlatformMetadata struct {
 	ID   string
 	Name string
@@ -2239,7 +2254,7 @@ func (stats *monitoringDerivedRateStats) add(summary monitoringAnswerParseSummar
 	if summary.FirstRecommended {
 		stats.FirstRecommend++
 	}
-	if summary.SentimentLabel == "positive" {
+	if summary.BrandMentioned && summary.SentimentLabel == "positive" {
 		stats.PositiveMentions++
 	}
 }
@@ -2264,6 +2279,71 @@ func (stats monitoringDerivedRateStats) positiveMentionRate() *float64 {
 	return divideAsPointer(stats.PositiveMentions, stats.Total)
 }
 
+func addMonitoringDerivedParseSample(metrics *monitoringDerivedMetrics, sample monitoringDerivedParseSample) {
+	if metrics == nil {
+		return
+	}
+
+	dateKey := sample.BusinessDate.Format("2006-01-02")
+	dateStats := metrics.ByDate[dateKey]
+	dateStats.add(sample.Summary)
+	metrics.ByDate[dateKey] = dateStats
+
+	platformStatsByDate, ok := metrics.ByDatePlatform[dateKey]
+	if !ok {
+		platformStatsByDate = make(map[string]monitoringDerivedRateStats)
+		metrics.ByDatePlatform[dateKey] = platformStatsByDate
+	}
+	platformStats := platformStatsByDate[sample.PlatformID]
+	platformStats.add(sample.Summary)
+	platformStatsByDate[sample.PlatformID] = platformStats
+
+	questionStatsByDate, ok := metrics.ByDateQuestion[dateKey]
+	if !ok {
+		questionStatsByDate = make(map[int64]monitoringDerivedRateStats)
+		metrics.ByDateQuestion[dateKey] = questionStatsByDate
+	}
+	questionStatsForDate := questionStatsByDate[sample.QuestionID]
+	questionStatsForDate.add(sample.Summary)
+	questionStatsByDate[sample.QuestionID] = questionStatsForDate
+
+	questionStats := metrics.ByQuestion[sample.QuestionID]
+	questionStats.add(sample.Summary)
+	metrics.ByQuestion[sample.QuestionID] = questionStats
+}
+
+func monitoringDerivedParseSampleIsNewer(candidate, existing monitoringDerivedParseSample) bool {
+	if candidate.EventAt.Valid && existing.EventAt.Valid && !candidate.EventAt.Time.Equal(existing.EventAt.Time) {
+		return candidate.EventAt.Time.After(existing.EventAt.Time)
+	}
+	if candidate.EventAt.Valid != existing.EventAt.Valid {
+		return candidate.EventAt.Valid
+	}
+	return candidate.RunID > existing.RunID
+}
+
+func upsertLatestMonitoringDerivedParseSample(samples map[monitoringDerivedSampleKey]monitoringDerivedParseSample, sample monitoringDerivedParseSample) {
+	if samples == nil {
+		return
+	}
+	key := monitoringDerivedSampleKey{
+		Date:       sample.BusinessDate.Format("2006-01-02"),
+		PlatformID: sample.PlatformID,
+		QuestionID: sample.QuestionID,
+	}
+	if existing, ok := samples[key]; !ok || monitoringDerivedParseSampleIsNewer(sample, existing) {
+		samples[key] = sample
+	}
+}
+
+func buildMonitoringDerivedMetricsFromLatestSamples(samples map[monitoringDerivedSampleKey]monitoringDerivedParseSample) monitoringDerivedMetrics {
+	metrics := newMonitoringDerivedMetrics()
+	for _, sample := range samples {
+		addMonitoringDerivedParseSample(&metrics, sample)
+	}
+	return metrics
+}
+
 func (s *MonitoringService) loadDerivedParseMetrics(
 	ctx context.Context,
 	tenantID, brandID int64,
@@ -2280,35 +2360,51 @@ func (s *MonitoringService) loadDerivedParseMetrics(
 
 	rows, err := s.monitoringPool.Query(ctx, `
 		SELECT
+			r.id,
 			r.business_date,
 			r.ai_platform_id,
 			r.question_id,
+			r.event_at,
 			r.raw_answer_text,
 			p.brand_mentioned,
 			p.brand_mention_position,
 			p.first_recommended,
 			p.sentiment_label,
 			p.matched_brand_terms
-		FROM question_monitor_runs r
+		FROM (
+			SELECT DISTINCT ON (business_date, question_id, ai_platform_id)
+				id,
+				tenant_id,
+				business_date,
+				ai_platform_id,
+				question_id,
+				raw_answer_text,
+				COALESCE(completed_at, updated_at, created_at) AS event_at
+			FROM question_monitor_runs
+			WHERE tenant_id = $1
+			  AND brand_id = $2
+			  AND collector_type = $3
+			  AND status = 'succeeded'
+			  AND business_date BETWEEN $4::date AND $5::date
+			  AND ($6::bigint[] IS NULL OR question_id = ANY($6))
+			  AND ($7::text[] IS NULL OR ai_platform_id = ANY($7))
+			ORDER BY business_date, question_id, ai_platform_id, COALESCE(completed_at, updated_at, created_at) DESC NULLS LAST, id DESC
+		) r
 		LEFT JOIN question_monitor_parse_results p
 			ON p.tenant_id = r.tenant_id AND p.run_id = r.id
-		WHERE r.tenant_id = $1
-		  AND r.brand_id = $2
-		  AND r.collector_type = $3
-		  AND r.status = 'succeeded'
-		  AND r.business_date BETWEEN $4::date AND $5::date
-		  AND ($6::bigint[] IS NULL OR r.question_id = ANY($6))
-		  AND ($7::text[] IS NULL OR r.ai_platform_id = ANY($7))
 	`, tenantID, brandID, monitoringCollectorType, startDate.Format("2006-01-02"), endDate.Format("2006-01-02"), nullableInt64Array(questionIDs), nullableStringArray(platformQueryIDs))
 	if err != nil {
 		return metrics, response.ErrInternal(50041, "query_failed", "failed to load monitoring derived parse metrics")
 	}
 	defer rows.Close()
 
+	samples := make(map[monitoringDerivedSampleKey]monitoringDerivedParseSample)
 	for rows.Next() {
+		var runID int64
 		var businessDate time.Time
 		var platformID string
 		var questionID int64
+		var eventAt sql.NullTime
 		var answerText sql.NullString
 		var brandMentioned sql.NullBool
 		var brandMentionPosition sql.NullString
@@ -2316,9 +2412,11 @@ func (s *MonitoringService) loadDerivedParseMetrics(
 		var sentimentLabel sql.NullString
 		var matchedBrandTermsJSON []byte
 		if scanErr := rows.Scan(
+			&runID,
 			&businessDate,
 			&platformID,
 			&questionID,
+			&eventAt,
 			&answerText,
 			&brandMentioned,
 			&brandMentionPosition,
@@ -2345,39 +2443,21 @@ func (s *MonitoringService) loadDerivedParseMetrics(
 			},
 		)
 
-		dateKey := businessDate.Format("2006-01-02")
-		dateStats := metrics.ByDate[dateKey]
-		dateStats.add(summary)
-		metrics.ByDate[dateKey] = dateStats
-
-		platformStatsByDate, ok := metrics.ByDatePlatform[dateKey]
-		if !ok {
-			platformStatsByDate = make(map[string]monitoringDerivedRateStats)
-			metrics.ByDatePlatform[dateKey] = platformStatsByDate
-		}
-		platformStats := platformStatsByDate[platformID]
-		platformStats.add(summary)
-		platformStatsByDate[platformID] = platformStats
-
-		questionStatsByDate, ok := metrics.ByDateQuestion[dateKey]
-		if !ok {
-			questionStatsByDate = make(map[int64]monitoringDerivedRateStats)
-			metrics.ByDateQuestion[dateKey] = questionStatsByDate
-		}
-		questionStatsForDate := questionStatsByDate[questionID]
-		questionStatsForDate.add(summary)
-		questionStatsByDate[questionID] = questionStatsForDate
-
-		questionStats := metrics.ByQuestion[questionID]
-		questionStats.add(summary)
-		metrics.ByQuestion[questionID] = questionStats
+		upsertLatestMonitoringDerivedParseSample(samples, monitoringDerivedParseSample{
+			BusinessDate: businessDate,
+			PlatformID:   platformID,
+			QuestionID:   questionID,
+			EventAt:      eventAt,
+			RunID:        runID,
+			Summary:      summary,
+		})
 	}
 
 	if err := rows.Err(); err != nil {
 		return metrics, response.ErrInternal(50041, "scan_failed", "failed to iterate monitoring derived metrics")
 	}
 
-	return metrics, nil
+	return buildMonitoringDerivedMetricsFromLatestSamples(samples), nil
 }
 
 func decodeMonitoringMatchedBrandTerms(raw []byte) []string {
@@ -2608,18 +2688,30 @@ func (s *MonitoringService) loadOverviewRunAggregate(
 			COUNT(*) FILTER (WHERE p.brand_mentioned IS TRUE)::bigint AS mentioned_count,
 			COUNT(*) FILTER (WHERE p.brand_mention_position = 'top1')::bigint AS top1_mentioned_count,
 			COUNT(*) FILTER (WHERE p.first_recommended IS TRUE)::bigint AS first_recommended_count,
-			COUNT(*) FILTER (WHERE p.sentiment_label = 'positive')::bigint AS positive_mentioned_count,
+			COUNT(*) FILTER (WHERE p.brand_mentioned IS TRUE AND p.sentiment_label = 'positive')::bigint AS positive_mentioned_count,
 			MAX(r.completed_at) AS last_sampled_at
-		FROM question_monitor_runs r
+		FROM (
+			SELECT DISTINCT ON (business_date, question_id, ai_platform_id)
+				id,
+				tenant_id,
+				business_date,
+				question_id,
+				ai_platform_id,
+				completed_at,
+				updated_at,
+				created_at
+			FROM question_monitor_runs
+			WHERE tenant_id = $1
+			  AND brand_id = $2
+			  AND collector_type = $3
+			  AND status = 'succeeded'
+			  AND business_date BETWEEN $4::date AND $5::date
+			  AND question_id = ANY($6)
+			  AND ($7::text[] IS NULL OR ai_platform_id = ANY($7))
+			ORDER BY business_date, question_id, ai_platform_id, COALESCE(completed_at, updated_at, created_at) DESC NULLS LAST, id DESC
+		) r
 		LEFT JOIN question_monitor_parse_results p
 			ON p.tenant_id = r.tenant_id AND p.run_id = r.id
-		WHERE r.tenant_id = $1
-		  AND r.brand_id = $2
-		  AND r.collector_type = $3
-		  AND r.status = 'succeeded'
-		  AND r.business_date BETWEEN $4::date AND $5::date
-		  AND r.question_id = ANY($6)
-		  AND ($7::text[] IS NULL OR r.ai_platform_id = ANY($7))
 		GROUP BY r.business_date
 		ORDER BY r.business_date DESC
 	`, tenantID, brandID, monitoringCollectorType, startDate.Format("2006-01-02"), endDate.Format("2006-01-02"), questionIDs, nullableStringArray(platformIDs))
@@ -3136,15 +3228,25 @@ func (s *MonitoringService) loadPlatformBreakdownFromRuns(ctx context.Context, t
 			COUNT(*) FILTER (WHERE p.brand_mentioned IS TRUE)::bigint AS mentioned_count,
 			COUNT(*) FILTER (WHERE p.brand_mention_position = 'top1')::bigint AS top1_mentioned_count,
 			MAX(r.completed_at) AS last_sampled_at
-		FROM question_monitor_runs r
+		FROM (
+			SELECT DISTINCT ON (business_date, question_id, ai_platform_id)
+				id,
+				tenant_id,
+				ai_platform_id,
+				completed_at,
+				updated_at,
+				created_at
+			FROM question_monitor_runs
+			WHERE tenant_id = $1
+			  AND brand_id = $2
+			  AND collector_type = $3
+			  AND business_date = $4::date
+			  AND status = 'succeeded'
+			  AND question_id = ANY($5)
+			ORDER BY business_date, question_id, ai_platform_id, COALESCE(completed_at, updated_at, created_at) DESC NULLS LAST, id DESC
+		) r
 		LEFT JOIN question_monitor_parse_results p
 			ON p.tenant_id = r.tenant_id AND p.run_id = r.id
-		WHERE r.tenant_id = $1
-		  AND r.brand_id = $2
-		  AND r.collector_type = $3
-		  AND r.business_date = $4::date
-		  AND r.status = 'succeeded'
-		  AND r.question_id = ANY($5)
 		GROUP BY r.ai_platform_id
 	`, tenantID, brandID, monitoringCollectorType, dateKey, questionIDs)
 	if err != nil {
@@ -3192,6 +3294,7 @@ func (s *MonitoringService) loadPlatformBreakdownFromRuns(ctx context.Context, t
 		if platformStats, ok := derived.ByDatePlatform[dateKey][platform.ID]; ok && platformStats.hasSamples() {
 			item.MentionRate = pointerFloat64ToNull(platformStats.mentionRate())
 			item.Top1MentionRate = pointerFloat64ToNull(platformStats.top1MentionRate())
+			item.ActualSampleCount = platformStats.Total
 		}
 		breakdown = append(breakdown, MonitoringPlatformDaily{
 			AIPlatformID:         platform.ID,
@@ -3236,11 +3339,15 @@ func (s *MonitoringService) loadHotQuestions(
 	platformQueryIDs := monitoringPlatformQueryIDs(aiPlatformID)
 
 	rows, err := s.monitoringPool.Query(ctx, `
-		WITH stats AS (
-			SELECT
+		WITH latest_runs AS (
+			SELECT DISTINCT ON (r.question_id, r.ai_platform_id)
 				r.question_id,
-				AVG(CASE WHEN p.brand_mentioned IS TRUE THEN 1 ELSE 0 END)::double precision AS mention_rate,
-				MAX(r.completed_at) AS last_sampled_at
+				r.ai_platform_id,
+				r.question_hash,
+				r.completed_at,
+				r.updated_at,
+				r.created_at,
+				p.brand_mentioned
 			FROM question_monitor_runs r
 			LEFT JOIN question_monitor_parse_results p
 				ON p.tenant_id = r.tenant_id AND p.run_id = r.id
@@ -3251,21 +3358,22 @@ func (s *MonitoringService) loadHotQuestions(
 			  AND r.business_date = $4::date
 			  AND r.question_id = ANY($5)
 			  AND ($6::text[] IS NULL OR r.ai_platform_id = ANY($6))
-			GROUP BY r.question_id
+			ORDER BY r.question_id, r.ai_platform_id, COALESCE(r.completed_at, r.updated_at, r.created_at) DESC NULLS LAST, r.id DESC
+		),
+		stats AS (
+			SELECT
+				question_id,
+				AVG(CASE WHEN brand_mentioned IS TRUE THEN 1 ELSE 0 END)::double precision AS mention_rate,
+				MAX(completed_at) AS last_sampled_at
+			FROM latest_runs
+			GROUP BY question_id
 		),
 		latest_hash AS (
 			SELECT DISTINCT ON (r.question_id)
 				r.question_id,
 				r.question_hash
-			FROM question_monitor_runs r
-			WHERE r.tenant_id = $1
-			  AND r.brand_id = $2
-			  AND r.collector_type = $3
-			  AND r.status = 'succeeded'
-			  AND r.business_date = $4::date
-			  AND r.question_id = ANY($5)
-			  AND ($6::text[] IS NULL OR r.ai_platform_id = ANY($6))
-			ORDER BY r.question_id, r.business_date DESC, COALESCE(r.completed_at, r.updated_at, r.created_at) DESC NULLS LAST, r.id DESC
+			FROM latest_runs r
+			ORDER BY r.question_id, COALESCE(r.completed_at, r.updated_at, r.created_at) DESC NULLS LAST
 		)
 		SELECT
 			s.question_id,

server/internal/tenant/app/monitoring_service_date_test.go

@@ -1,6 +1,7 @@
 package app
 
 import (
+	"database/sql"
 	"testing"
 	"time"
 
@@ -234,3 +235,73 @@ func TestApplyDerivedRatesToOverviewSnapshotUsesAllSamplesForMentionRate(t *test
 	assert.InDelta(t, 0.25, snapshot.FirstRecommendRate.Float64, 0.0001)
 	assert.InDelta(t, 0.25, snapshot.PositiveMentionRate.Float64, 0.0001)
 }
+
+func TestBuildMonitoringDerivedMetricsUsesLatestSamplePerQuestionPlatform(t *testing.T) {
+	day := time.Date(2026, 6, 29, 0, 0, 0, 0, monitoringBusinessLocation())
+	questionID := int64(177)
+	samples := map[monitoringDerivedSampleKey]monitoringDerivedParseSample{}
+
+	upsertLatestMonitoringDerivedParseSample(samples, monitoringDerivedParseSample{
+		BusinessDate: day,
+		PlatformID:   "doubao",
+		QuestionID:   questionID,
+		EventAt:      sql.NullTime{Time: day.Add(10 * time.Hour), Valid: true},
+		RunID:        2507,
+		Summary: monitoringAnswerParseSummary{
+			BrandMentioned:       true,
+			BrandMentionPosition: "mentioned",
+		},
+	})
+	upsertLatestMonitoringDerivedParseSample(samples, monitoringDerivedParseSample{
+		BusinessDate: day,
+		PlatformID:   "doubao",
+		QuestionID:   questionID,
+		EventAt:      sql.NullTime{Time: day.Add(11 * time.Hour), Valid: true},
+		RunID:        2628,
+		Summary: monitoringAnswerParseSummary{
+			BrandMentioned:       false,
+			BrandMentionPosition: "not_mentioned",
+		},
+	})
+	upsertLatestMonitoringDerivedParseSample(samples, monitoringDerivedParseSample{
+		BusinessDate: day,
+		PlatformID:   "qwen",
+		QuestionID:   questionID,
+		EventAt:      sql.NullTime{Time: day.Add(10*time.Hour + 30*time.Minute), Valid: true},
+		RunID:        2510,
+		Summary: monitoringAnswerParseSummary{
+			BrandMentioned:       true,
+			BrandMentionPosition: "mentioned",
+		},
+	})
+
+	metrics := buildMonitoringDerivedMetricsFromLatestSamples(samples)
+	stats := metrics.ByDateQuestion["2026-06-29"][questionID]
+
+	require.True(t, stats.hasSamples())
+	assert.Equal(t, int64(2), stats.Total)
+	assert.Equal(t, int64(1), stats.MentionedCount)
+	require.NotNil(t, stats.mentionRate())
+	assert.InDelta(t, 0.5, *stats.mentionRate(), 0.0001)
+}
+
+func TestMonitoringDerivedPositiveMentionRequiresBrandMention(t *testing.T) {
+	var stats monitoringDerivedRateStats
+
+	stats.add(monitoringAnswerParseSummary{
+		BrandMentioned:       false,
+		BrandMentionPosition: "not_mentioned",
+		SentimentLabel:       "positive",
+	})
+	stats.add(monitoringAnswerParseSummary{
+		BrandMentioned:       true,
+		BrandMentionPosition: "mentioned",
+		SentimentLabel:       "positive",
+	})
+
+	assert.Equal(t, int64(2), stats.Total)
+	assert.Equal(t, int64(1), stats.MentionedCount)
+	assert.Equal(t, int64(1), stats.PositiveMentions)
+	require.NotNil(t, stats.positiveMentionRate())
+	assert.InDelta(t, 0.5, *stats.positiveMentionRate(), 0.0001)
+}