tamakyi
c9b426acbb
BoxTrend 的回答那条 SQL 复用了 d.day（基于 created_at 的日期表达式）做 GROUP BY， 但 WHERE 过滤用的是 answered_at。于是「40 天前创建、昨天才回答」的提问被排除在 窗口外（created_at < from），昨天的回答数里不出现；「今天创建、明天回答」的又 被记到今天。趋势图里的「每日回答数」根本不是「某天被回答了多少」。 单独构造 answerDay（基于 COALESCE(answered_at, updated_at)），WHERE / GROUP BY / SELECT 三者口径一致。PG 用 to_char(... AT TIME ZONE INTERVAL ...)，MySQL 用 CONVERT_TZ，与 analyticsDialectFor 对 created_at 的处理对称。 新增 box_analytics_test.go：构造「40 天前创建、昨天回答」的提问，断言计入昨天， 并做变异验证（改回 d.day → 测试失败）。
234 lines
8.2 KiB
Go
234 lines
8.2 KiB
Go
// Copyright 2026 tamakyi. All rights reserved.
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// Use of this source code is governed by a MIT-style
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// license that can be found in the LICENSE file.
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package db
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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/pkg/errors"
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"gorm.io/gorm"
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)
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// BoxAnalyticsStore 是「箱主数据面板」里提问侧的聚合查询（访问侧见 BoxViewsStore）。
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//
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// 与 SiteAnalyticsStore 分开：那个是站方看的全站数据（不含任何单箱维度），
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// 这个是箱主看自己的。两边的 SQL 都按 user_id 走，混在一个接口里会让
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// 「全站聚合整天缓存」和「箱主实时看自己的」两种缓存策略纠缠在一起。
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type BoxAnalyticsStore interface {
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// BoxTrend 返回 [from, to] 内每天的提问数与回答数。只返回有数据的天，缺日由上层补零。
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BoxTrend(ctx context.Context, userID uint, from, to time.Time) ([]BoxDayCount, error)
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// BoxHours 返回 since 之后该箱收到提问的 24 小时分布（下标 0..23）。
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BoxHours(ctx context.Context, userID uint, since time.Time) ([24]int64, error)
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// BoxFunnel 返回该箱的提问处理漏斗。
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BoxFunnel(ctx context.Context, userID uint) (*BoxFunnel, error)
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}
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// BoxDayCount 某一天的提问 / 回答计数。
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type BoxDayCount struct {
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Day time.Time `gorm:"column:day"`
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Questions int64 `gorm:"column:questions"`
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Answers int64 `gorm:"column:answers"`
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}
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// BoxFunnel 箱主的提问处理漏斗与响应速度。
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type BoxFunnel struct {
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Total int64 // 全部提问
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Answered int64 // 已回答
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ReadOnly int64 // 已读未答
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Unread int64 // 未读未答
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Private int64 // 私密提问
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Anonymous int64 // 匿名（未登录）提问
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Pinned int64 // 置顶
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// 响应速度只统计已回答且 answered_at 有值的行（历史行退回 updated_at，
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// 会有偏高，见 answered_at 的注释）。
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RepliedIn24h int64
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AvgReplyHour float64
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// LastQuestionAt / LastAnswerAt 用于「你多久没看提问箱了」这类提示。
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LastQuestionAt *time.Time
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LastAnswerAt *time.Time
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}
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var BoxAnalytics BoxAnalyticsStore
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var _ BoxAnalyticsStore = (*boxAnalytics)(nil)
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func NewBoxAnalyticsStore(db *gorm.DB) BoxAnalyticsStore {
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return &boxAnalytics{db}
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}
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type boxAnalytics struct {
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*gorm.DB
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}
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func (db *boxAnalytics) BoxTrend(ctx context.Context, userID uint, from, to time.Time) ([]BoxDayCount, error) {
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d := analyticsDialectFor(db.DB, from)
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from, to = dayOnly(from), dayOnly(to).AddDate(0, 0, 1)
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// 提问按 created_at 分组；回答必须按 answered_at（空则退回 updated_at）分组。
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// 两条 SQL 的 day 表达式不同：d.day 是 created_at 的日期，回答那条要基于
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// COALESCE(answered_at, updated_at)，否则「40 天前创建、昨天才回答」的提问
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// 会被排除在窗口外，「今天创建、明天回答」的会被记到今天 —— 趋势图里的
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// 「每日回答数」就不是「某天被回答了多少」。
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answerDay := analyticsLocalize("COALESCE(answered_at, updated_at)", from)
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if db.Dialector.Name() == "mysql" {
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answerDay = fmt.Sprintf("DATE_FORMAT(CONVERT_TZ(COALESCE(answered_at, updated_at), '+00:00', '%s'), '%%Y-%%m-%%d')", analyticsTZOffset(from))
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} else {
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answerDay = fmt.Sprintf("to_char(%s, 'YYYY-MM-DD')", answerDay)
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}
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// 提问与回答分两条 SQL 再在内存里合并：一条 SQL 里同时按 created_at 和
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// answered_at 分组要写成两条子查询再 FULL JOIN，MySQL 没有 FULL JOIN，
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// 而两张结果集都很小，合并成本可以忽略。
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type row struct {
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Key string
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N int64
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}
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var qs, as []row
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if err := db.WithContext(ctx).Model(&Question{}).
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Select(d.day+" AS key, COUNT(*) AS n").
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Where("user_id = ? AND created_at >= ? AND created_at < ?", userID, from, to).
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Group(d.day).
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Scan(&qs).Error; err != nil {
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return nil, errors.Wrap(err, "aggregate box questions by day")
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}
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if err := db.WithContext(ctx).Model(&Question{}).
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Select(answerDay+" AS key, COUNT(*) AS n").
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Where("user_id = ? AND answer <> '' AND COALESCE(answered_at, updated_at) >= ? AND COALESCE(answered_at, updated_at) < ?",
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userID, from, to).
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Group(answerDay).
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Scan(&as).Error; err != nil {
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return nil, errors.Wrap(err, "aggregate box answers by day")
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}
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// 用 map 合并，最后仍交给上层按日期补零（上层最清楚要展示哪些天）。
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byDay := make(map[string]*BoxDayCount, len(qs))
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order := make([]string, 0, len(qs)+len(as))
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get := func(key string) *BoxDayCount {
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if v, ok := byDay[key]; ok {
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return v
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}
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t, err := time.ParseInLocation("2006-01-02", key, from.Location())
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if err != nil {
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t = from
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}
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v := &BoxDayCount{Day: t}
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byDay[key] = v
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order = append(order, key)
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return v
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}
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for _, r := range qs {
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get(r.Key).Questions = r.N
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}
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for _, r := range as {
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get(r.Key).Answers = r.N
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}
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out := make([]BoxDayCount, 0, len(order))
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for _, key := range order {
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out = append(out, *byDay[key])
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}
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return out, nil
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}
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func (db *boxAnalytics) BoxHours(ctx context.Context, userID uint, since time.Time) ([24]int64, error) {
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var out [24]int64
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d := analyticsDialectFor(db.DB, since)
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var rows []struct {
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Hr int
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N int64
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}
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if err := db.WithContext(ctx).Model(&Question{}).
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Select(d.hour+" AS hr, COUNT(*) AS n").
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Where("user_id = ? AND created_at >= ?", userID, since).
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Group(d.hour).
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Scan(&rows).Error; err != nil {
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return out, errors.Wrap(err, "aggregate box question hours")
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}
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for _, r := range rows {
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if r.Hr >= 0 && r.Hr < 24 {
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out[r.Hr] = r.N
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}
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}
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return out, nil
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}
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func (db *boxAnalytics) BoxFunnel(ctx context.Context, userID uint) (*BoxFunnel, error) {
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out := &BoxFunnel{}
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var totals struct {
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Total int64 `gorm:"column:total"`
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Answered int64 `gorm:"column:answered"`
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ReadOnly int64 `gorm:"column:read_only"`
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Unread int64 `gorm:"column:unread"`
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Private int64 `gorm:"column:private"`
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Anonymous int64 `gorm:"column:anonymous"`
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Pinned int64 `gorm:"column:pinned"`
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LastQ *time.Time `gorm:"column:last_q"`
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LastA *time.Time `gorm:"column:last_a"`
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}
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if err := db.WithContext(ctx).Model(&Question{}).
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Select(`COUNT(*) AS total,
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COALESCE(SUM(CASE WHEN answer <> '' THEN 1 ELSE 0 END), 0) AS answered,
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COALESCE(SUM(CASE WHEN answer = '' AND is_read THEN 1 ELSE 0 END), 0) AS read_only,
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COALESCE(SUM(CASE WHEN answer = '' AND NOT is_read THEN 1 ELSE 0 END), 0) AS unread,
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COALESCE(SUM(CASE WHEN is_private THEN 1 ELSE 0 END), 0) AS private,
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COALESCE(SUM(CASE WHEN asker_user_id = 0 THEN 1 ELSE 0 END), 0) AS anonymous,
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COALESCE(SUM(CASE WHEN is_pinned THEN 1 ELSE 0 END), 0) AS pinned,
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MAX(created_at) AS last_q,
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MAX(CASE WHEN answer <> '' THEN COALESCE(answered_at, updated_at) END) AS last_a`).
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Where("user_id = ?", userID).
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Scan(&totals).Error; err != nil {
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return nil, errors.Wrap(err, "aggregate box funnel")
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}
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out.Total = totals.Total
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out.Answered = totals.Answered
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out.ReadOnly = totals.ReadOnly
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out.Unread = totals.Unread
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out.Private = totals.Private
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out.Anonymous = totals.Anonymous
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out.Pinned = totals.Pinned
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out.LastQuestionAt = totals.LastQ
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out.LastAnswerAt = totals.LastA
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// 响应速度：answered_at 为空的历史行退回 updated_at（口径偏大，只用于展示大致量级）。
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replyMinutes := boxReplyMinutesExpr(db.DB, out.LastAnswerAt)
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if replyMinutes == "" {
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return out, nil
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}
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var speed struct {
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In24h int64 `gorm:"column:in_24h"`
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Avg *float64 `gorm:"column:avg_min"`
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}
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if err := db.WithContext(ctx).Model(&Question{}).
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Select(fmt.Sprintf(`COALESCE(SUM(CASE WHEN %[1]s <= 1440 THEN 1 ELSE 0 END), 0) AS in_24h,
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AVG(%[1]s) AS avg_min`, replyMinutes)).
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Where("user_id = ? AND answer <> ''", userID).
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Scan(&speed).Error; err != nil {
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return nil, errors.Wrap(err, "aggregate box reply speed")
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}
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out.RepliedIn24h = speed.In24h
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if speed.Avg != nil && *speed.Avg > 0 {
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out.AvgReplyHour = *speed.Avg / 60
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}
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return out, nil
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}
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// boxReplyMinutesExpr 返回「回答耗时（分钟）」的 SQL 表达式。
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//
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// 与 analyticsDialectFor 里的 replyMin 口径一致，但这里必须能固定到箱主自己那张表：
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// 表达式里出现的列名都来自 questions 表，不需要额外限定。
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func boxReplyMinutesExpr(db *gorm.DB, at *time.Time) string {
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now := time.Now()
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if at != nil {
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now = *at
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}
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d := analyticsDialectFor(db, now)
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return d.replyMin
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}
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