如何在postgresql中的datetime列上联接两个表，并且它们在一个唯一的列中出现datetime的所有寄存器？

问题描述 投票：0回答：1

我有两个表：

TABLE_MACHINE_1

datetime,            sensor_1
2017-10-01 21:00:00, 1.18047
2017-10-01 21:15:00, 1.18023
2017-10-01 21:30:00, 1.18059
2017-10-01 21:45:00, 1.18067
2017-10-01 22:00:00, 1.18056
2017-10-01 22:15:00, 1.18147
2017-10-01 22:30:00, 1.18104
2017-10-01 22:45:00, 1.18111
2017-10-01 23:00:00, 1.18103
2017-10-01 23:15:00, 1.18072
2017-10-01 23:30:00, 1.18083
2017-10-01 23:45:00, 1.18079
2017-10-02 00:00:00, 1.17996
2017-10-02 00:15:00, 1.17987
2017-10-02 00:30:00, 1.17968
2017-10-02 00:45:00, 1.17893
2017-10-02 01:00:00, 1.17852
2017-10-02 01:15:00, 1.17833

TABLE_MACHINE_2

datetime,            sensor_2
2017-10-01 21:45:00, 112.1
2017-10-01 22:00:00, 133.2
2017-10-01 22:15:00, 143.5
2017-10-01 22:30:00, 154.9
2017-10-01 22:45:00, 166.1
2017-10-01 23:30:00, 123.1
2017-10-01 23:45:00, 134.1
2017-10-02 00:00:00, 188.3
2017-10-02 01:00:00, 192.9
2017-10-02 01:15:00, 105.3
2017-10-02 01:30:00, 172.9
2017-10-02 01:45:00, 145.3
2017-10-02 02:00:00, 174.9
2017-10-02 02:15:00, 155.3

而且我期望结果如何：

希望加入

datetime,            sensor_1  sensor_2
2017-10-01 21:00:00, 1.18047,  NULL
2017-10-01 21:15:00, 1.18023,  NULL
2017-10-01 21:30:00, 1.18059,  NULL
2017-10-01 21:45:00, 1.18067,  112.1
2017-10-01 22:00:00, 1.18056,  133.2
2017-10-01 22:15:00, 1.18147,  143.5
2017-10-01 22:30:00, 1.18104,  154.9
2017-10-01 22:45:00, 1.18111,  166.1
2017-10-01 23:00:00, 1.18103,  NULL
2017-10-01 23:15:00, 1.18072,  NULL
2017-10-01 23:30:00, 1.18083,  123.1
2017-10-01 23:45:00, 1.18079,  134.1
2017-10-02 00:00:00, 1.17996,  188.3
2017-10-02 00:15:00, 1.17987,  105.3
2017-10-02 00:30:00, 1.17968,  NULL
2017-10-02 00:45:00, 1.17893,  NULL
2017-10-02 01:00:00, 1.17852,  NULL
2017-10-02 01:15:00, 1.17833,  NULL
2017-10-02 01:30:00, NULL   ,  172.9
2017-10-02 01:45:00, NULL   ,  145.3
2017-10-02 02:00:00, NULL   ,  174.9
2017-10-02 02:15:00, NULL   ,  155.3

但是如果我做FULL OUTER JOIN可以得到：

在DATETIME从FROM TABLE_MACHINE_1完全外部联接TABLE_MACHINE_2

datetime,            sensor_1, datetime,            sensor_2
2017-10-01 21:00:00, 1.18047,  NULL,                NULL  
2017-10-01 21:15:00, 1.18023,  NULL,                NULL 
2017-10-01 21:30:00, 1.18059,  NULL,                NULL 
2017-10-01 21:45:00, 1.18067,  2017-10-01 21:45:00, 112.1
2017-10-01 22:00:00, 1.18056,  2017-10-01 22:00:00, 133.2
2017-10-01 22:15:00, 1.18147,  2017-10-01 22:15:00, 143.5
2017-10-01 22:30:00, 1.18104,  2017-10-01 22:30:00, 154.9
2017-10-01 22:45:00, 1.18111,  2017-10-01 22:45:00, 166.1
2017-10-01 23:00:00, 1.18103,  NULL,                NULL 
2017-10-01 23:15:00, 1.18072,  NULL,                NULL 
2017-10-01 23:30:00, 1.18083,  2017-10-01 23:30:00, 123.1
2017-10-01 23:45:00, 1.18079,  2017-10-01 23:45:00, 134.1
2017-10-02 00:00:00, 1.17996,  2017-10-02 00:00:00, 188.3
2017-10-02 00:15:00, 1.17987,  NULL,                NULL 
2017-10-02 00:30:00, 1.17968,  NULL,                NULL 
2017-10-02 00:45:00, 1.17893,  NULL,                NULL 
2017-10-02 01:00:00, 1.17852,  2017-10-02 01:00:00, 192.9
2017-10-02 01:15:00, 1.17833,  2017-10-02 01:15:00, 105.3
NULL,                NULL,     2017-10-02 01:30:00, 172.9 
NULL,                NULL,     2017-10-02 01:45:00, 145.3
NULL,                NULL,     2017-10-02 02:00:00, 174.9 
NULL,                NULL,     2017-10-02 02:15:00, 155.3

我需要在postgresql中的一个查询中解决它，并且我尝试使用完全外部join子句不成功。

我已经考虑过以下解决方案，但是我无法实现它，因为在传递变量“ generate_series”时出现错误：

  1. 创建一个变量来存储每个表的最长日期。

      datetime_end := to_char(now()::date,'YYY-MM-DD');

  2. 将变量传递给以下查询：

      SELECT generate_series(
      timestamp without time zone '2017-10-01',
      timestamp without time zone datetime_end,
      '15 minute');
    1. 要在两个表之前先左移查询。

提前感谢。

postgresql function datetime variables jointable
1个回答
0
投票

您想要full outer join 和 coalesce()：

select 
    coalesce(t1.datetime, t2.datetime) datetime,
    t1.sensor_1,
    t2.sensor_2
from table_machine_1 t1
full outer join table_machine_2 t2 
    on t1.datetime = t2.datetime

Demo on DB Fiddle：

| datetime            | sensor_1 | sensor_2 |
| ------------------- | -------- | -------- |
| 2017-10-01 21:00:00 | 1.18047  |          |
| 2017-10-01 21:15:00 | 1.18023  |          |
| 2017-10-01 21:30:00 | 1.18059  |          |
| 2017-10-01 21:45:00 | 1.18067  | 112.1    |
| 2017-10-01 22:00:00 | 1.18056  | 133.2    |
| 2017-10-01 22:15:00 | 1.18147  | 143.5    |
| 2017-10-01 22:30:00 | 1.18104  | 154.9    |
| 2017-10-01 22:45:00 | 1.18111  | 166.1    |
| 2017-10-01 23:00:00 | 1.18103  |          |
| 2017-10-01 23:15:00 | 1.18072  |          |
| 2017-10-01 23:30:00 | 1.18083  | 123.1    |
| 2017-10-01 23:45:00 | 1.18079  | 134.1    |
| 2017-10-02 00:00:00 | 1.17996  | 188.3    |
| 2017-10-02 00:15:00 | 1.17987  |          |
| 2017-10-02 00:30:00 | 1.17968  |          |
| 2017-10-02 00:45:00 | 1.17893  |          |
| 2017-10-02 01:00:00 | 1.17852  | 192.9    |
| 2017-10-02 01:15:00 | 1.17833  | 105.3    |
| 2017-10-02 02:00:00 |          | 174.9    |
| 2017-10-02 01:30:00 |          | 172.9    |
| 2017-10-02 01:45:00 |          | 145.3    |
| 2017-10-02 02:15:00 |          | 155.3    |
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