Select 具有重叠条件的不同记录

Question

我想查询 select '2017-01-01' 和 '2017-03-01' 之间的日期计数无论如何，是否可以在不使用 case 语句的情况下分别计算“2017-01-01”、“2017-02-01”和“2017-03-01”。

有点像使用 group by

Answer 1

SELECT date, count(*) FROM table WHERE date>='2017-01-01' AND date<='2017-03-01' GROUP BY date;

或者您可以更改包含或不包含的日期

Answer 2

您需要函数 date_trunc。它会将您的 dates/timestamps 截断为月份。

daniel=> select date_trunc('month', '2017-01-31'::date);
     date_trunc  
---------------------
 2017-01-01 00:00:00
(1 row)

daniel=> select date_trunc('month', '2017-03-17'::date);
     date_trunc  
---------------------
 2017-03-01 00:00:00
(1 row)

即查询将类似于：

SELECT
    date_trunc('month', date) as 'month',
    count(*)                  as 'count'
FROM
    table
WHERE
    date_trunc('month', date) >= '2017-01-01'
        AND
    date_trunc('month', date) <= '2017-03-01'
GROUP BY
    date_trunc('month', date);

如果您需要生成时间序列，请在 row_number() over () 和任何具有足够行的 table 中使用，例如 system_tables:

daniel=> select '2017-01-01'::DATE + cast(row_number() over () - 1 as interval month) from system_tables limit 5;
      ?column?
---------------------
 2017-01-01 00:00:00
 2017-02-01 00:00:00
 2017-03-01 00:00:00
 2017-04-01 00:00:00
 2017-05-01 00:00:00
(5 rows)

您也可以尝试 TIMESERIES 填充间隙：

SELECT ts AS 'date' FROM (
    SELECT '2017-01-01'::TIMESTAMP AS tm
        UNION
    SELECT '2017-01-03'::TIMESTAMP AS tm) AS t
TIMESERIES ts AS '8 hours' OVER (ORDER BY tm);

daniel=> \e
        date
---------------------
 2017-01-01 00:00:00
 2017-01-01 08:00:00
 2017-01-01 16:00:00
 2017-01-02 00:00:00
 2017-01-02 08:00:00
 2017-01-02 16:00:00
 2017-01-03 00:00:00
(7 rows)

现在，让我们将所有内容组合在一起，计算每个月的天数 date_trunc:

SELECT
    date_trunc('month', T.date) AS 'MONTH',
    count(*)                    AS 'COUNT'
FROM (
    SELECT ts::DATE AS 'date' FROM (
        SELECT '2017-01-01'::TIMESTAMP AS tm
            UNION ALL
        SELECT '2017-03-01'::TIMESTAMP AS tm
    ) AS S
    TIMESERIES ts AS '8 hours' OVER (ORDER BY tm)
) AS T
GROUP BY 1
ORDER BY 1;

daniel=> \e
        MONTH        | COUNT
---------------------+-------
 2017-01-01 00:00:00 |    93
 2017-02-01 00:00:00 |    84
 2017-03-01 00:00:00 |     1
(3 rows)

Select 具有重叠条件的不同记录

Select Distinct Records with overlapping conditions

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