16

我有一张这样的桌子：

Number   Price    Type       Date         Time
------   -----    ----    ----------    ---------
23456    0,665     SV     2014/02/02     08:00:02
23457    1,3       EC     2014/02/02     07:50:45
23460    0,668     SV     2014/02/02     07:36:34

对于每个 EC，我需要上一个/下一个 SV 价格。在这种情况下，查询很简单。

Select Lag(price, 1, price) over (order by date desc, time desc),
Lead(price, 1, price) over (order by date desc, time desc)
from ITEMS

但是，有一些特殊情况，其中两行或多行是 EC 类型：

Number   Price    Type       Date         Time
------   -----    ----    ----------    ---------
23456    0,665     SV     2014/02/02     08:00:02
23457    1,3       EC     2014/02/02     07:50:45
23658    2,4       EC     2014/02/02     07:50:45
23660    2,4       EC     2014/02/02     07:50:48
23465    0,668     SV     2014/02/02     07:36:34

在这种情况下我可以使用领先/滞后吗？如果没有，我是否必须使用子查询？

4

3 回答 3

13

您的问题（以及 Anon 的出色回答）是 island and gaps 的 SQL 的一部分。在这个答案中，我将尝试详细检查“row_number() 魔法”。

我根据球赛中的事件做了一个简单的例子。对于每个事件，我们希望打印上一季度和下一季度的相关消息：

create table TestTable (id int identity, event varchar(64));
insert TestTable values
    ('Start of Q1'),
    ('Free kick'),
    ('Goal'),
    ('End of Q1'),
    ('Start of Q2'),
    ('Penalty'),
    ('Miss'),
    ('Yellow card'),
    ('End of Q2');

这是一个展示“row_number() 魔术”方法的查询：

; with  grouped as
        (
        select  *
        ,       row_number() over (order by id) as rn1
        ,       row_number() over (
                    partition by case when event like '%of Q[1-4]' then 1 end 
                    order by id) as rn2
        from    TestTable
        )
,       order_in_group as
        (
        select  *
        ,       rn1-rn2 as group_nr
        ,       row_number() over (partition by rn1-rn2 order by id) as rank_asc
        ,       row_number() over (partition by rn1-rn2 order by id desc)
                    as rank_desc
        from    grouped
        )
select  *
,       lag(event, rank_asc) over (order by id) as last_event_of_prev_group
,       lead(event, rank_desc) over (order by id) as first_event_of_next_group
from    order_in_group
order by
        id
  • 第一个称为“分组”的 CTE 计算两个row_number()s。第一个是1 2 3表中的每一行。第二个row_number()将暂停公告放在一个列表中，将其他事件放在第二个列表中。两者之间的区别，rn1 - rn2对于游戏的每个部分来说都是独一无二的。检查示例输出中的差异很有帮助：它在group_nr列中。您会看到每个值对应于游戏的一个部分。
  • 第二个称为“order_in_group”的 CTE 确定当前行在其岛或间隙内的位置。对于 3 行的岛，位置1 2 3按升序排列，3 2 1按降序排列。
  • lag()最后，我们知道足以告诉我们lead()跳多远。我们必须滞后rank_asc行才能找到上一节的最后一行。要找到下一部分的第一行，我们必须引导rank_desc行。

希望这有助于澄清差距和岛屿的“魔力”。 这是 SQL Fiddle 的一个工作示例。

于 2014-02-14T18:04:07.377 回答
8

Yes, you can use LEAD/LAG. You just need to precalculate how far to jump with a little ROW_NUMBER() magic.

DECLARE @a TABLE ( number int, price money, type varchar(2),
                   date date, time time)
INSERT @a VALUES
(23456,0.665,'SV','2014/02/02','08:00:02'),
(23457,1.3  ,'EC','2014/02/02','07:50:45'),
(23658,2.4  ,'EC','2014/02/02','07:50:45'),
(23660,2.4  ,'EC','2014/02/02','07:50:48'),
(23465,0.668,'SV','2014/02/02','07:36:34');

; WITH a AS (
     SELECT *,
            ROW_NUMBER() OVER(ORDER BY [date] DESC, [time] DESC) x, 
            ROW_NUMBER() OVER(PARTITION BY 
               CASE [type] WHEN 'SV' THEN 1 ELSE 0 END 
               ORDER BY [date] DESC, [time] DESC) y 
     FROM @a)
 , b AS (
     SELECT *,
            ROW_NUMBER() OVER(PARTITION BY x-y ORDER BY x ASC) z1,
            ROW_NUMBER() OVER(PARTITION BY x-y ORDER BY x DESC) z2 
     FROM a)
SELECT *,
       CASE [type] WHEN 'SV' THEN 
           LAG(price,z1,price) OVER(PARTITION BY [type] ORDER BY x) 
           ELSE LAG(price,z1,price) OVER(ORDER BY x) 
           END,
       CASE [type] WHEN 'SV' THEN 
           LEAD(price,z2,price) OVER(PARTITION BY [type] ORDER BY x) 
           ELSE LEAD(price,z2,price) OVER(ORDER BY x) 
           END
FROM b
ORDER BY x
于 2014-02-14T17:19:32.517 回答
1

这是实现相同结果的另一种方法，但使用对序数进行窗口化的条件最大/最小函数。可以根据适合目的的任何列设置序数，但在这种情况下，我相信 OP 打算将它们设置为Dateand Time。

DROP TABLE IF EXISTS #t;
CREATE TABLE #t (
    Number INT, 
    Price MONEY, 
    Type CHAR(2),
    Date DATE,
    Time TIME(0)
);
INSERT INTO #t VALUES 
(23456, 0.666, 'SV', '2014/02/02', '10:00:02'),
(23457, 1.4  , 'EC', '2014/02/02', '09:50:45'),
(23658, 2.5  , 'EC', '2014/02/02', '09:50:45'),
(23660, 2.5  , 'EC', '2014/02/02', '09:50:48'),
(23465, 0.669, 'SV', '2014/02/02', '09:36:34'),
(23456, 0.665, 'SV', '2014/02/02', '08:00:02'),
(23457, 1.3  , 'EC', '2014/02/02', '07:50:45'),
(23658, 2.4  , 'EC', '2014/02/02', '07:50:45'),
(23660, 2.4  , 'EC', '2014/02/02', '07:50:48'),
(23465, 0.668, 'SV', '2014/02/02', '07:36:34'), -- which one of these?
(23465, 0.670, 'SV', '2014/02/02', '07:36:34'); -- 

WITH time_ordered AS (
    SELECT *, DENSE_RANK() OVER (ORDER BY Date, Time) AS ordinal FROM #t
)
SELECT
    *,
    CASE WHEN Type = 'EC' 
    THEN MAX(CASE WHEN ordinal = preceding_non_EC_ordinal THEN Price END) 
    OVER (PARTITION BY preceding_non_EC_ordinal ORDER BY ordinal ASC) END AS preceding_price,
    CASE WHEN Type = 'EC'
    THEN MIN(CASE WHEN ordinal = following_non_EC_ordinal THEN Price END) 
    OVER (PARTITION BY following_non_EC_ordinal ORDER BY ordinal DESC) END AS following_price
FROM (
    SELECT
        *,
        MAX(CASE WHEN Type <> 'EC' THEN ordinal END) 
        OVER (ORDER BY ordinal ASC) AS preceding_non_EC_ordinal,
        MIN(CASE WHEN Type <> 'EC' THEN ordinal END) 
        OVER (ORDER BY ordinal DESC) AS following_non_EC_ordinal
    FROM time_ordered
) t
ORDER BY Date, Time

请注意，OP 给出的示例已被扩展，以表明散布的序列产生EC预期的结果。在这种情况下，由最早的两个连续行引入的歧义SV将导致选择最大值。设置序数以包含Price是改变此行为的一种可能方法。

SQLFiddle 可以在这里找到：http ://sqlfiddle.com/#!18/85117/1

于 2019-05-28T09:12:10.240 回答