对每一个有事件的日期,统计**截至当天(含)**一共有多少个不同的用户出现过(任何事件类型都算)。
- 日期取
ts的日历日(列day,日期类型)。 - 只输出至少有一条事件的日期;某天虽然有事件、但都是老用户时,
cum_users与前一个输出日相同。 - 同一用户无论出现多少次、在多少天出现,都只算一次。
输入
events(event_id, user_id, ts, event_type, page)
输出
列为 day, cum_users(整数),按 day 升序排列。
对每一个有事件的日期,统计**截至当天(含)**一共有多少个不同的用户出现过(任何事件类型都算)。
ts 的日历日(列 day,日期类型)。cum_users 与前一个输出日相同。输入
events(event_id, user_id, ts, event_type, page)输出
列为 day, cum_users(整数),按 day 升序排列。
events web/events
| # | event_idint64 | user_idint64 | tsdatetime | event_typestring | pagestring |
|---|---|---|---|---|---|
| 1 | 1 | 53 | 2026-06-03 17:57:33 | login | /home |
| 2 | 2 | 53 | 2026-06-04 15:21:00 | visit | /home |
| 3 | 3 | 53 | 2026-06-04 15:22:00 | view | /product/303 |
| 4 | 4 | 53 | 2026-06-04 15:32:04 | add_to_cart | /cart |
| 5 | 5 | 56 | 2026-06-05 23:24:19 | login | /home |
| 6 | 6 | 56 | 2026-06-05 23:29:18 | view | /product/202 |
| 7 | 7 | 56 | 2026-06-05 23:36:15 | view | /product/202 |
| 8 | 8 | 56 | 2026-06-05 23:47:36 | add_to_cart | /cart |
| 9 | 9 | 56 | 2026-06-05 23:56:24 | checkout | /checkout |
| 10 | 10 | 56 | 2026-06-06 19:14:00 | visit | /home |
| 11 | 11 | 56 | 2026-06-06 19:22:53 | view | /product/303 |
| 12 | 12 | 56 | 2026-06-06 19:25:12 | view | /home |
| 13 | 13 | 56 | 2026-06-06 19:28:25 | add_to_cart | /cart |
| 14 | 14 | 29 | 2026-06-07 10:40:01 | login | /home |
| 15 | 15 | 29 | 2026-06-07 10:46:43 | view | /product/303 |
| 16 | 16 | 29 | 2026-06-07 11:04:46 | add_to_cart | /cart |
| 17 | 17 | 29 | 2026-06-07 11:09:25 | checkout | /checkout |
| 18 | 18 | 34 | 2026-06-07 12:57:49 | login | /home |
| 19 | 19 | 34 | 2026-06-07 13:03:57 | view | /product/202 |
| 20 | 20 | 34 | 2026-06-07 13:11:07 | view | /home |
| # | dayDate | cum_usersDecimal(precision=38, scale=0) |
|---|---|---|
| 1 | 2026-06-03 | 1.0 |
| 2 | 2026-06-04 | 1.0 |
| 3 | 2026-06-05 | 2.0 |
| 4 | 2026-06-06 | 2.0 |
| 5 | 2026-06-07 | 4.0 |
| 6 | 2026-06-08 | 4.0 |
| 7 | 2026-06-10 | 4.0 |
| 8 | 2026-06-15 | 5.0 |
| 9 | 2026-06-17 | 6.0 |
| 10 | 2026-06-18 | 8.0 |
| 11 | 2026-06-19 | 8.0 |
| 12 | 2026-06-20 | 10.0 |
| 13 | 2026-06-21 | 10.0 |
| 14 | 2026-06-22 | 10.0 |
| 15 | 2026-06-23 | 11.0 |
| 16 | 2026-06-24 | 13.0 |
| 17 | 2026-06-25 | 13.0 |
| 18 | 2026-06-27 | 13.0 |
| 19 | 2026-06-29 | 14.0 |
| 20 | 2026-06-30 | 14.0 |
| 21 | 2026-07-01 | 15.0 |
| 22 | 2026-07-02 | 16.0 |
| 23 | 2026-07-03 | 16.0 |
| 24 | 2026-07-04 | 17.0 |
| 25 | 2026-07-05 | 17.0 |
| 26 | 2026-07-06 | 18.0 |
| 27 | 2026-07-08 | 18.0 |
| 28 | 2026-07-09 | 18.0 |
| 29 | 2026-07-10 | 19.0 |
| 30 | 2026-07-11 | 19.0 |
| 31 | 2026-07-13 | 19.0 |
| 32 | 2026-07-14 | 20.0 |
| 33 | 2026-07-15 | 21.0 |
| 34 | 2026-07-16 | 21.0 |
| 35 | 2026-07-17 | 22.0 |
| 36 | 2026-07-19 | 23.0 |
| 37 | 2026-07-20 | 23.0 |
| 38 | 2026-07-21 | 23.0 |
| 39 | 2026-07-22 | 23.0 |
| 40 | 2026-07-23 | 24.0 |
| 41 | 2026-07-24 | 24.0 |
| 42 | 2026-07-25 | 24.0 |
| 43 | 2026-07-26 | 25.0 |
| 44 | 2026-07-28 | 25.0 |
| 45 | 2026-07-29 | 26.0 |
| 46 | 2026-07-30 | 27.0 |
| 47 | 2026-08-01 | 27.0 |
| 48 | 2026-08-02 | 27.0 |
| 49 | 2026-08-03 | 27.0 |
| 50 | 2026-08-04 | 27.0 |