按 (channel, month, status) 统计订单数。
month 是 order_ts 所在月份的第一天，类型为日期（例如 2026-03-01）。channel 为 null 的订单单独成一组（channel 输出 null）。n_orders 是该组的订单行数。排序（ordered: true）：依次按 channel、month、status、n_orders 升序，null 排在最后。（前三列已经能唯一确定一行。）
考点：分组键和排序键都不手写列名，用“按所有非聚合列分组”“按所有列排序”的写法。判题只看结果。
输入
orders(order_id, customer_id, order_ts, status, channel)输出
列为 channel, month, status, n_orders，按上面的顺序排列。
orders shop/orders
| # | order_idint64 | customer_idint64 | order_tsdatetime | statusstring | channelstring |
|---|---|---|---|---|---|
| 1 | 1001 | 39 | 2026-01-01 19:38:00 | paid | app |
| 2 | 1002 | 16 | 2026-01-17 14:07:00 | paid | app |
| 3 | 1003 | 4 | 2026-01-08 15:40:20 | cancelled | web |
| 4 | 1004 | 2 | 2026-05-23 10:48:58 | paid | null |
| 5 | 1005 | 12 | 2026-06-22 11:07:22 | paid | store |
| 6 | 1006 | 17 | 2026-08-15 05:15:25 | paid | web |
| 7 | 1007 | 9 | 2026-06-11 01:00:32 | refunded | store |
| 8 | 1008 | 45 | 2026-09-19 20:47:10 | paid | web |
| 9 | 1009 | 2 | 2025-10-05 04:53:38 | paid | app |
| 10 | 1010 | 4 | 2026-02-19 01:39:54 | paid | app |
| 11 | 1011 | 28 | 2026-03-05 03:04:45 | refunded | store |
| 12 | 1012 | 2 | 2026-08-01 07:09:17 | paid | web |
| 13 | 1013 | 26 | 2026-01-22 03:48:14 | refunded | store |
| 14 | 1014 | 2 | 2026-02-09 01:41:41 | paid | app |
| 15 | 1015 | 5 | 2026-08-03 19:49:04 | refunded | web |
| 16 | 1016 | 26 | 2026-02-16 00:43:43 | refunded | app |
| 17 | 1017 | 9 | 2025-12-06 04:48:57 | pending | app |
| 18 | 1018 | 999 | 2026-05-19 12:13:43 | paid | store |
| 19 | 1019 | 26 | 2026-02-05 15:02:26 | paid | store |
| 20 | 1020 | 44 | 2025-11-24 11:19:00 | cancelled | web |
| # | channelString | monthDate | statusString | n_ordersInt64 |
|---|---|---|---|---|
| 1 | app | 2025-08-01 | paid | 2 |
| 2 | app | 2025-09-01 | cancelled | 1 |
| 3 | app | 2025-10-01 | cancelled | 1 |
| 4 | app | 2025-10-01 | paid | 3 |
| 5 | app | 2025-11-01 | cancelled | 1 |
| 6 | app | 2025-11-01 | paid | 1 |
| 7 | app | 2025-12-01 | paid | 6 |
| 8 | app | 2025-12-01 | pending | 1 |
| 9 | app | 2026-01-01 | paid | 6 |
| 10 | app | 2026-01-01 | pending | 1 |
| 11 | app | 2026-01-01 | refunded | 2 |
| 12 | app | 2026-02-01 | cancelled | 1 |
| 13 | app | 2026-02-01 | paid | 7 |
| 14 | app | 2026-02-01 | refunded | 2 |
| 15 | app | 2026-03-01 | cancelled | 1 |
| 16 | app | 2026-03-01 | paid | 2 |
| 17 | app | 2026-04-01 | cancelled | 4 |
| 18 | app | 2026-04-01 | paid | 3 |
| 19 | app | 2026-04-01 | refunded | 1 |
| 20 | app | 2026-05-01 | cancelled | 1 |
| 21 | app | 2026-05-01 | paid | 4 |
| 22 | app | 2026-06-01 | cancelled | 1 |
| 23 | app | 2026-06-01 | paid | 2 |
| 24 | app | 2026-06-01 | pending | 1 |
| 25 | app | 2026-06-01 | refunded | 2 |
| 26 | app | 2026-07-01 | paid | 8 |
| 27 | app | 2026-07-01 | pending | 1 |
| 28 | app | 2026-07-01 | refunded | 1 |
| 29 | app | 2026-08-01 | paid | 1 |
| 30 | app | 2026-08-01 | pending | 2 |
| 31 | app | 2026-09-01 | cancelled | 1 |
| 32 | phone | 2025-12-01 | paid | 1 |
| 33 | phone | 2026-01-01 | paid | 3 |
| 34 | phone | 2026-04-01 | cancelled | 1 |
| 35 | phone | 2026-04-01 | paid | 1 |
| 36 | phone | 2026-05-01 | paid | 1 |
| 37 | phone | 2026-07-01 | pending | 1 |
| 38 | phone | 2026-09-01 | paid | 1 |
| 39 | store | 2025-08-01 | paid | 1 |
| 40 | store | 2025-09-01 | paid | 1 |
| 41 | store | 2025-10-01 | cancelled | 1 |
| 42 | store | 2025-11-01 | paid | 1 |
| 43 | store | 2025-12-01 | paid | 2 |
| 44 | store | 2026-01-01 | paid | 3 |
| 45 | store | 2026-01-01 | pending | 1 |
| 46 | store | 2026-01-01 | refunded | 1 |
| 47 | store | 2026-02-01 | paid | 4 |
| 48 | store | 2026-03-01 | cancelled | 1 |
| 49 | store | 2026-03-01 | pending | 2 |
| 50 | store | 2026-03-01 | refunded | 2 |