如何使用 clickhouse select 日期时间数据中的特定日期？

Question

我的 clickhouse 数据库中有多个日期时间，我正在尝试在查询中使用 'group by' 选项以按特定间隔 select 日期。例如，我的数据库：（列的类型是 DateTime64(3, 'UTC')

worktime
--------------------
2020-01-11 14:57:24.000
2020-01-11 16:57:24.000
2020-01-11 17:56:36.000
2020-01-11 18:04:36.000
2020-01-11 19:07:48.000
2020-01-11 20:46:48.000
2020-01-12 02:23:00.000
2020-01-12 02:35:00.000
2020-01-12 02:44:12.000
2020-01-12 02:46:24.000
2020-01-12 03:07:12.000
2020-01-12 03:26:00.000
2020-01-12 03:29:00.000
2020-01-12 03:37:00.000
2020-01-13 03:54:48.000
2020-01-13 04:15:24.000
2020-01-13 04:35:36.000
2020-01-13 04:46:12.000
2020-01-13 05:08:00.000
2020-01-13 05:13:00.000
2020-01-13 05:21:12.000
2020-01-13 05:32:24.000
2020-01-13 03:54:48.000
2020-01-13 04:15:24.000
2020-01-13 04:35:36.000
2020-01-13 04:46:12.000
2020-01-13 05:08:00.000
2020-01-14 05:13:00.000
2020-01-14 05:21:12.000
2020-01-14 05:32:24.000
2020-01-14 03:54:48.000
2020-01-15 04:15:24.000
2020-01-15 04:35:36.000
2020-01-15 04:46:12.000
2020-01-15 05:08:00.000
2020-01-16 05:13:00.000
2020-01-16 05:21:12.000
2020-01-16 05:32:24.000
2020-01-16 03:54:48.000
2020-01-16 04:15:24.000
2020-01-17 04:35:36.000
2020-01-17 04:46:12.000
2020-01-17 05:08:00.000
2020-01-17 05:13:00.000
2020-01-18 05:21:12.000
2020-01-18 05:32:24.000

我想要的结果是按特定间隔对日期进行分组

首先我没有任何间隔地尝试

SELECT worktime FROM test2 GROUP BY worktime

它确实给了我分组日期的结果，但我想添加特定的间隔（比如 3 天、4 天、12 小时..）

我在谷歌上搜索并找到了一种使用 'interval' 函数的方法，但它并没有像我希望的那样工作..

SELECT worktime FROM test2 GROUP BY worktime - interval 3 day as worktime

但我没有得到 3 天间隔结果:(（我得到的结果与 selecting 所有日期相同）

抱歉，我的问题太模糊了，我是 clickhouse 的新手，我几乎迷路了:(

我想要间隔日期分组的结果（例如2天）

2020-01-11, 2020-01-13, 2020-01-15 . . .

Answer 1

试试这个查询：

SELECT 
  -- toStartOfInterval(worktime, INTERVAL 3 DAY) interval
  toStartOfInterval(worktime, INTERVAL 2 DAY) interval  
FROM (
  /* emulate the test dataset */
  SELECT toDateTime64(dt, 3) AS worktime
  FROM (
    SELECT arrayJoin([
      '2020-01-11 14:57:24.000',
      '2020-01-11 16:57:24.000',
      '2020-01-11 17:56:36.000',
      '2020-01-11 18:04:36.000',
      '2020-01-11 19:07:48.000',
      '2020-01-11 20:46:48.000',
      '2020-01-12 02:23:00.000',
      '2020-01-12 02:35:00.000',
      '2020-01-12 02:44:12.000',
      '2020-01-12 02:46:24.000',
      '2020-01-12 03:07:12.000',
      '2020-01-12 03:26:00.000',
      '2020-01-12 03:29:00.000',
      '2020-01-12 03:37:00.000',
      '2020-01-13 03:54:48.000',
      '2020-01-13 04:15:24.000',
      '2020-01-13 04:35:36.000',
      '2020-01-13 04:46:12.000',
      '2020-01-13 05:08:00.000',
      '2020-01-13 05:13:00.000',
      '2020-01-13 05:21:12.000',
      '2020-01-13 05:32:24.000',
      '2020-01-13 03:54:48.000',
      '2020-01-13 04:15:24.000',
      '2020-01-13 04:35:36.000',
      '2020-01-13 04:46:12.000',
      '2020-01-13 05:08:00.000',
      '2020-01-14 05:13:00.000',
      '2020-01-14 05:21:12.000',
      '2020-01-14 05:32:24.000',
      '2020-01-14 03:54:48.000',
      '2020-01-15 04:15:24.000',
      '2020-01-15 04:35:36.000',
      '2020-01-15 04:46:12.000',
      '2020-01-15 05:08:00.000',
      '2020-01-16 05:13:00.000',
      '2020-01-16 05:21:12.000',
      '2020-01-16 05:32:24.000',
      '2020-01-16 03:54:48.000',
      '2020-01-16 04:15:24.000',
      '2020-01-17 04:35:36.000',
      '2020-01-17 04:46:12.000',
      '2020-01-17 05:08:00.000',
      '2020-01-17 05:13:00.000',
      '2020-01-18 05:21:12.000',
      '2020-01-18 05:32:24.000']) AS dt))
GROUP BY interval
ORDER BY interval

/*
-- INTERVAL 3 DAY 
┌────────────interval─┐
│ 2020-01-09 00:00:00 │
│ 2020-01-12 00:00:00 │
│ 2020-01-15 00:00:00 │
│ 2020-01-18 00:00:00 │
└─────────────────────┘

-- INTERVAL 2 DAY
┌────────────interval─┐
│ 2020-01-11 00:00:00 │
│ 2020-01-13 00:00:00 │
│ 2020-01-15 00:00:00 │
│ 2020-01-17 00:00:00 │
└─────────────────────┘
*/

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