基于列的日期范围

问题描述 投票：1回答：1

我想按ITEM和STATUS将下面的数据分组，但是对于下面的示例，由于状态又要切换回去，因此期望3行。

目前我使用的是MIN(FROM_DT) AND MAX(TO_DATE)，但只得到2行，STATUS列中只有2个不同的值。

预期结果：

ITEM    FROM_DT     TO_DT       STATUS
ITEM1   02/01/2020  15/05/2020  0
ITEM1   15/05/2020  18/05/2020  1
ITEM1   18/05/2020  31/12/9999  0

样本数据：

CREATE TABLE [dbo].[AH_TEMP](
    [ITEM] [varchar](24) NULL,
    [FROM_DT] [datetime] NULL,
    [TO_DT] [datetime] NULL,
    [EXCL] [bit] NULL
) ON [PRIMARY]
GO

INSERT INTO AH_TEMP 
VALUES  
    ('ITEM1','2020-01-02 22:57:01.200','2020-01-07 22:54:52.930','0'),
    ('ITEM1','2020-01-07 22:57:21.950','2020-02-03 22:54:30.500','0'),
    ('ITEM1','2020-02-03 22:58:21.180','2020-03-02 22:54:27.253','0'),
    ('ITEM1','2020-03-02 22:56:30.737','2020-03-18 17:21:23.390','0'),
    ('ITEM1','2020-03-18 17:21:23.403','2020-03-19 09:05:38.060','0'),
    ('ITEM1','2020-03-19 09:05:38.063','2020-03-19 13:57:03.567','0'),
    ('ITEM1','2020-03-19 13:57:03.570','2020-03-19 23:01:41.403','0'),
    ('ITEM1','2020-03-19 23:03:49.900','2020-03-20 23:02:25.437','0'),
    ('ITEM1','2020-03-20 23:04:53.610','2020-04-01 22:59:39.220','0'),
    ('ITEM1','2020-04-01 23:01:45.620','2020-05-01 22:59:09.153','0'),
    ('ITEM1','2020-05-01 23:01:11.980','2020-05-14 14:30:21.930','0'),
    ('ITEM1','2020-05-14 14:30:21.930','2020-05-14 22:57:24.753','0'),
    ('ITEM1','2020-05-14 22:59:17.623','2020-05-15 17:48:34.000','0'),
    ('ITEM1','2020-05-15 17:48:35.000','2020-05-15 22:57:15.923','0'),
    ('ITEM1','2020-05-15 22:59:11.933','2020-05-16 22:54:31.750','1'),
    ('ITEM1','2020-05-16 22:56:26.793','2020-05-18 22:55:01.050','1'),
    ('ITEM1','2020-05-18 23:00:23.103','2020-05-21 22:55:24.400','0'),
    ('ITEM1','2020-05-21 22:57:01.723','2020-06-01 23:00:21.823','0'),
    ('ITEM1','2020-06-01 23:03:12.467','2020-06-08 22:55:20.393','0'),
    ('ITEM1','2020-06-08 22:58:27.710','9999-12-31 00:00:00.000','0');

返回：

+-------+-------------------------+-------------------------+--------+
| ITEM  |         FROM_DT         |          TO_DT          | STATUS |
+-------+-------------------------+-------------------------+--------+
| ITEM1 | 2020-01-02 22:57:01.200 | 2020-01-07 22:54:52.930 |      0 |
| ITEM1 | 2020-01-07 22:57:21.950 | 2020-02-03 22:54:30.500 |      0 |
| ITEM1 | 2020-02-03 22:58:21.180 | 2020-03-02 22:54:27.253 |      0 |
| ITEM1 | 2020-03-02 22:56:30.737 | 2020-03-18 17:21:23.390 |      0 |
| ITEM1 | 2020-03-18 17:21:23.403 | 2020-03-19 09:05:38.060 |      0 |
| ITEM1 | 2020-03-19 09:05:38.063 | 2020-03-19 13:57:03.567 |      0 |
| ITEM1 | 2020-03-19 13:57:03.570 | 2020-03-19 23:01:41.403 |      0 |
| ITEM1 | 2020-03-19 23:03:49.900 | 2020-03-20 23:02:25.437 |      0 |
| ITEM1 | 2020-03-20 23:04:53.610 | 2020-04-01 22:59:39.220 |      0 |
| ITEM1 | 2020-04-01 23:01:45.620 | 2020-05-01 22:59:09.153 |      0 |
| ITEM1 | 2020-05-01 23:01:11.980 | 2020-05-14 14:30:21.930 |      0 |
| ITEM1 | 2020-05-14 14:30:21.930 | 2020-05-14 22:57:24.753 |      0 |
| ITEM1 | 2020-05-14 22:59:17.623 | 2020-05-15 17:48:34.000 |      0 |
| ITEM1 | 2020-05-15 17:48:35.000 | 2020-05-15 22:57:15.923 |      0 |
| ITEM1 | 2020-05-15 22:59:11.933 | 2020-05-16 22:54:31.750 |      1 |
| ITEM1 | 2020-05-16 22:56:26.793 | 2020-05-18 22:55:01.050 |      1 |
| ITEM1 | 2020-05-18 23:00:23.103 | 2020-05-21 22:55:24.400 |      0 |
| ITEM1 | 2020-05-21 22:57:01.723 | 2020-06-01 23:00:21.823 |      0 |
| ITEM1 | 2020-06-01 23:03:12.467 | 2020-06-08 22:55:20.393 |      0 |
| ITEM1 | 2020-06-08 22:58:27.710 | 9999-12-31 00:00:00.000 |      0 |
+-------+-------------------------+-------------------------+--------+
sql-server tsql date group-by gaps-and-islands
1个回答
1
投票

通过使用lag检测状态变化，然后sum状态变化，我们可以将该总和分组以提供所需的分组。

declare @Test table (ITEM varchar(24), FROM_DT date, TO_DT date, [STATUS] bit)

INSERT INTO @test VALUES  ('ITEM1','2020-01-02 22:57:01.200','2020-01-07 22:54:52.930','0');
INSERT INTO @test VALUES  ('ITEM1','2020-01-07 22:57:21.950','2020-02-03 22:54:30.500','0');
INSERT INTO @test VALUES  ('ITEM1','2020-02-03 22:58:21.180','2020-03-02 22:54:27.253','0');
INSERT INTO @test VALUES  ('ITEM1','2020-03-02 22:56:30.737','2020-03-18 17:21:23.390','0');
INSERT INTO @test VALUES  ('ITEM1','2020-03-18 17:21:23.403','2020-03-19 09:05:38.060','0');
INSERT INTO @test VALUES  ('ITEM1','2020-03-19 09:05:38.063','2020-03-19 13:57:03.567','0');
INSERT INTO @test VALUES  ('ITEM1','2020-03-19 13:57:03.570','2020-03-19 23:01:41.403','0');
INSERT INTO @test VALUES  ('ITEM1','2020-03-19 23:03:49.900','2020-03-20 23:02:25.437','0');
INSERT INTO @test VALUES  ('ITEM1','2020-03-20 23:04:53.610','2020-04-01 22:59:39.220','0');
INSERT INTO @test VALUES  ('ITEM1','2020-04-01 23:01:45.620','2020-05-01 22:59:09.153','0');
INSERT INTO @test VALUES  ('ITEM1','2020-05-01 23:01:11.980','2020-05-14 14:30:21.930','0');
INSERT INTO @test VALUES  ('ITEM1','2020-05-14 14:30:21.930','2020-05-14 22:57:24.753','0');
INSERT INTO @test VALUES  ('ITEM1','2020-05-14 22:59:17.623','2020-05-15 17:48:34.000','0');
INSERT INTO @test VALUES  ('ITEM1','2020-05-15 17:48:35.000','2020-05-15 22:57:15.923','0');
INSERT INTO @test VALUES  ('ITEM1','2020-05-15 22:59:11.933','2020-05-16 22:54:31.750','1');
INSERT INTO @test VALUES  ('ITEM1','2020-05-16 22:56:26.793','2020-05-18 22:55:01.050','1');
INSERT INTO @test VALUES  ('ITEM1','2020-05-18 23:00:23.103','2020-05-21 22:55:24.400','0');
INSERT INTO @test VALUES  ('ITEM1','2020-05-21 22:57:01.723','2020-06-01 23:00:21.823','0');
INSERT INTO @test VALUES  ('ITEM1','2020-06-01 23:03:12.467','2020-06-08 22:55:20.393','0');
INSERT INTO @test VALUES  ('ITEM1','2020-06-08 22:58:27.710','9999-12-31 00:00:00.000','0');

select ITEM, min(FROM_DT), max(TO_DT), [STATUS]
from (
  select *
    , sum(case when coalesce(lag,0) <> [STATUS] then 1 else 0 end) over (order by FROM_DT, TO_DT) GroupBy
  from (
    select *
      , lag([STATUS]) over (order by FROM_DT) lag
    from @Test
  ) X
) Y
group by ITEM, GroupBy, [STATUS]
order by ITEM, GroupBy;

给予：

ITEM    FROM_DT                 TO_DT                   STATUS
ITEM1   2020-01-02 22:57:01.200 2020-05-15 22:57:15.923 0
ITEM1   2020-05-15 22:59:11.933 2020-05-18 22:55:01.050 1
ITEM1   2020-05-18 23:00:23.103 9999-12-31 00:00:00.000 0
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