我正在尝试使用递归CTE +窗口函数来查找一系列买入/卖出订单的最后结果。
首先,这里有一些命名法:
不幸的是,由于系统的工作方式,我不会在退回物品时得到成本,因此找出订单的最后结果很复杂(我们最终还是卖掉了)。我需要将购买与销售相匹配,这通常很有效。但是,当它失败时会出现如下情况,并且我试图在一次传递中找到一种方法,可能使用递归CTE。
这是一些代码。
DECLARE @tablea TABLE (field_id int, field_number CHAR(3), field_date datetime, field_inserted DATETIME, field_sale varchar(4))
INSERT INTO @tablea
VALUES
(1, 100, '20170311','20170311 01:00:00', 'Buy'),
(1, 100, '20170311','20170311 01:01:00', 'Retu'),
(1, 100, '20170311','20170311 01:02:00', 'Buy'),
(1, 100, '20170311','20170311 01:03:00', 'Retu'),
(1, 100, '20170311','20170311 01:02:01', 'buy'),
(2, 100, '20170311','20170311 01:03:00', 'REtu'),
(1, 110, '20170311','20170311 01:03:00', 'Buy');
现在删除随后返回的购买。 ISNULL是因为我是NOT IN将忽略_lead / _lag值为NULL的所有行。
WITH cte AS
(SELECT
ROW_NUMBER() OVER (PARTITION BY field_id, field_number, field_date ORDER BY field_inserted) AS row_num,
field_id,
field_number,
field_date,
field_sale,
lead(field_sale) OVER (PARTITION BY field_id, field_number, field_date ORDER BY field_inserted) AS field_sale_lead,
lag(field_sale) OVER (PARTITION BY field_id, field_number, field_date ORDER BY field_inserted) AS field_sale_lag
FROM @tablea
)
SELECT * FROM cte
WHERE NOT (cte.field_sale = 'Buy' AND ISNULL(field_sale_lead,'') = 'Retu')--AND field_sale_lead IS NOT null)
AND NOT (cte.field_sale = 'Retu' AND ISNULL(field_sale_lag,'') = 'buy' )--AND field_sale_lag IS NOT NULL)
我觉得很沾沾自喜,以为我拥有它。然而,这是一个简单的案例。购买,退货,购买,退货。让我们试试另一个案例,买入买入回报,这仍然有效,但显然会导致净值为0 ..
DECLARE @tablea TABLE (field_id int, field_number CHAR(3), field_date datetime, field_inserted DATETIME, field_sale varchar(4))
INSERT INTO @tablea
VALUES
(1, 100, '20170311','20170311 01:00:00', 'Buy'),
(1, 100, '20170311','20170311 01:01:00', 'Buy'),
(1, 100, '20170311','20170311 01:02:00', 'Retu'),
(1, 100, '20170311','20170311 01:03:00', 'Retu'),
(2, 100, '20170311','20170311 01:03:00', 'Buy'),
(1, 110, '20170311','20170311 01:03:00', 'Buy');
WITH cte AS
(SELECT
ROW_NUMBER() OVER (PARTITION BY field_id, field_number, field_date ORDER BY field_inserted) AS row_num,
field_id,
field_number,
field_date,
field_sale,
lead(field_sale) OVER (PARTITION BY field_id, field_number, field_date ORDER BY field_inserted) AS field_sale_lead,
lag(field_sale) OVER (PARTITION BY field_id, field_number, field_date ORDER BY field_inserted) AS field_sale_lag
FROM @tablea
)
SELECT * FROM cte
WHERE NOT (cte.field_sale = 'Buy' AND ISNULL(field_sale_lead,'') = 'sell')--AND field_sale_lead IS NOT null)
AND NOT (cte.field_sale = 'sell' AND ISNULL(field_sale_lag,'') = 'buy' )--AND field_sale_lag IS NOT NULL)
但是,当你这样做时,你会发现它找到了直接匹配,但是现在还有买入/回报对,我想取消它。
就在这时我被卡住了。我以前做过递归CTE,但无论出于什么原因,我都无法弄清楚如何递归并使其取消1/1/100和4/1/100。我设法做的就是让它在递归上窒息。
DECLARE @tablea TABLE (field_id int, field_number CHAR(3), field_date datetime, field_inserted DATETIME, field_sale varchar(4))
INSERT INTO @tablea
VALUES
(1, 100, '20170311','20170311 01:00:00', 'Buy'),
(1, 100, '20170311','20170311 01:01:00', 'Buy'),
(1, 100, '20170311','20170311 01:02:00', 'Retu'),
(1, 100, '20170311','20170311 01:03:00', 'Retu'),
(2, 100, '20170311','20170311 01:03:00', 'Buy'),
(1, 110, '20170311','20170311 01:03:00', 'Buy');
WITH cte AS
(SELECT
ROW_NUMBER() OVER (PARTITION BY field_id, field_number, field_date ORDER BY field_inserted) AS row_num,
field_id,
field_number,
field_date,
field_sale,
field_inserted,
lead(field_sale) OVER (PARTITION BY field_id, field_number, field_date ORDER BY field_inserted) AS field_sale_lead,
lag(field_sale) OVER (PARTITION BY field_id, field_number, field_date ORDER BY field_inserted) AS field_sale_lag
FROM @tablea
--)
--SELECT * FROM cte
--WHERE NOT (cte.field_sale = 'Buy' AND ISNULL(field_sale_lead,'') = 'Retu')--AND field_sale_lead IS NOT null)
--AND NOT (cte.field_sale = 'Retu' AND ISNULL(field_sale_lag,'') = 'buy' )--AND field_sale_lag IS NOT NULL)
UNION ALL
SELECT
ROW_NUMBER() OVER (PARTITION BY cte.field_id, cte.field_number, cte.field_date ORDER BY cte.field_inserted) AS row_num,
cte.field_id,
cte.field_number,
cte.field_date,
cte.field_sale,
cte.field_inserted,
lead(cte.field_sale) OVER (PARTITION BY cte.field_id, cte.field_number, cte.field_date ORDER BY cte.field_inserted) AS field_sale_lead,
lag(cte.field_sale) OVER (PARTITION BY cte.field_id, cte.field_number, cte.field_date ORDER BY cte.field_inserted) AS field_sale_lag
FROM @tablea INNER JOIN cte ON cte.field_date = [@tablea].field_date AND cte.field_id = [@tablea].field_id AND cte.field_number = [@tablea].field_number
)
SELECT * FROM cte
WHERE NOT (cte.field_sale = 'Buy' AND ISNULL(field_sale_lead,'') = 'Retu')--AND field_sale_lead IS NOT null)
AND NOT (cte.field_sale = 'Retu' AND ISNULL(field_sale_lag,'') = 'buy' )--AND field_sale_lag IS NOT NULL)
答案 0 :(得分:1)
我们可以使用common table expression和 row_number()
来解决这个没有循环或递归:
如果我正确理解您的问题,您希望删除已退回的销售
,对于每个'retu'
,它应删除最新的'buy'
。
首先,我们将使用id
添加row_number()
到我们的行集,以便我们可以唯一地标识行。
接下来,我们添加由br_rn
分区的field_id, field_number, field_date
(购买/返回行号的缩写),但我们还将 field_sale
添加到分区;我们将按field_inserted desc
订购。
这样我们就可以将每个'retu'
与最新的'buy'
进行匹配,一旦我们能够做到这一点,我们就可以使用not exists()
消除所有对:
;with cte as (
select
id = row_number() over (
order by field_id, field_number, field_date, field_inserted asc
)
, field_id
, field_number
, field_date
, field_inserted
, field_sale
, br_rn = row_number() over (
partition by field_id, field_number, field_date, field_sale
order by field_inserted desc
)
from @tablea
)
select
id
, field_number
, field_date
, field_inserted
, field_sale
from cte
where not exists (
select 1
from cte as i
where i.field_id = cte.field_id
and i.field_number = cte.field_number
and i.field_date = cte.field_date
and i.br_rn = cte.br_rn
and i.id <> cte.id
)
order by id
rextester演示:http://rextester.com/TKXOC61533
对于此输入:
(1, 100, '20170311','20170311 01:00:00', 'Buy')
, (1, 100, '20170311','20170311 01:01:00', 'Buy')
, (1, 100, '20170311','20170311 01:02:00', 'Retu')
, (1, 100, '20170311','20170311 01:03:00', 'Retu')
, (2, 100, '20170311','20170311 01:03:00', 'Buy')
, (1, 110, '20170311','20170311 01:03:00', 'Buy');
返回:
+----+----------+--------------+------------+---------------------+------------+
| id | field_id | field_number | field_date | field_inserted | field_sale |
+----+----------+--------------+------------+---------------------+------------+
| 5 | 1 | 110 | 2017-03-11 | 2017-03-11 01:03:00 | Buy |
| 6 | 2 | 100 | 2017-03-11 | 2017-03-11 01:03:00 | Buy |
+----+----------+--------------+------------+---------------------+------------+
并为此输入:
(1, 100, '20170311','20170311 01:01:00', 'Buy')
, (1, 100, '20170311','20170311 01:02:00', 'Buy')
, (1, 100, '20170311','20170311 01:03:00', 'Buy')
, (1, 100, '20170311','20170311 01:04:00', 'Retu')
, (1, 100, '20170311','20170311 01:05:00', 'Buy')
, (1, 100, '20170311','20170311 01:06:00', 'Retu')
, (1, 100, '20170311','20170311 01:07:00', 'Retu')
, (2, 100, '20170311','20170311 01:03:00', 'Buy')
, (1, 110, '20170311','20170311 01:03:00', 'Buy');
返回:
+----+----------+--------------+------------+---------------------+------------+
| id | field_id | field_number | field_date | field_inserted | field_sale |
+----+----------+--------------+------------+---------------------+------------+
| 1 | 1 | 100 | 2017-03-11 | 2017-03-11 01:01:00 | Buy |
| 8 | 1 | 110 | 2017-03-11 | 2017-03-11 01:03:00 | Buy |
| 9 | 2 | 100 | 2017-03-11 | 2017-03-11 01:03:00 | Buy |
+----+----------+--------------+------------+---------------------+------------+
输入:
(1, 100, '20170311','20170311 01:01:00', 'Buy')
, (1, 100, '20170311','20170311 01:02:00', 'Buy')
, (1, 100, '20170311','20170311 01:04:00', 'Retu')
, (1, 100, '20170311','20170311 01:05:00', 'Retu')
, (1, 100, '20170312','20170311 01:06:00', 'Buy')
, (1, 100, '20170312','20170311 01:07:00', 'Buy')
, (2, 100, '20170311','20170311 01:03:00', 'Buy')
, (1, 110, '20170311','20170311 01:03:00', 'Buy')
返回:
+----+----------+--------------+------------+---------------------+------------+
| id | field_id | field_number | field_date | field_inserted | field_sale |
+----+----------+--------------+------------+---------------------+------------+
| 5 | 1 | 100 | 2017-03-12 | 2017-03-11 01:06:00 | Buy |
| 6 | 1 | 100 | 2017-03-12 | 2017-03-11 01:07:00 | Buy |
| 7 | 1 | 110 | 2017-03-11 | 2017-03-11 01:03:00 | Buy |
| 8 | 2 | 100 | 2017-03-11 | 2017-03-11 01:03:00 | Buy |
+----+----------+--------------+------------+---------------------+------------+
在我们消除任何配对之前,它可能有助于说明我们正在做什么来看看cte返回的内容。
在我们过滤它之前,只查看需要过滤的集合:
+----+----------+--------------+------------+---------------------+------------+-------+
| id | field_id | field_number | field_date | field_inserted | field_sale | br_rn |
+----+----------+--------------+------------+---------------------+------------+-------+
| 1 | 1 | 100 | 2017-03-11 | 2017-03-11 01:01:00 | Buy | 4 |
| 2 | 1 | 100 | 2017-03-11 | 2017-03-11 01:02:00 | Buy | 3 |
| 3 | 1 | 100 | 2017-03-11 | 2017-03-11 01:03:00 | Buy | 2 |
| 4 | 1 | 100 | 2017-03-11 | 2017-03-11 01:04:00 | Retu | 3 |
| 5 | 1 | 100 | 2017-03-11 | 2017-03-11 01:05:00 | Buy | 1 |
| 6 | 1 | 100 | 2017-03-11 | 2017-03-11 01:06:00 | Retu | 2 |
| 7 | 1 | 100 | 2017-03-11 | 2017-03-11 01:07:00 | Retu | 1 |
+----+----------+--------------+------------+---------------------+------------+-------+
这样看,我们可以很容易地看到'buy'
订单id
1
的{{1}} br_rn
并且没有关联{ {1}}。
答案 1 :(得分:0)
有一点我可以建议在可能的情况下删除一对顺序买入/返回。尝试
DECLARE @tablea TABLE (field_id int, field_number CHAR(3), field_date datetime, field_inserted DATETIME, field_sale varchar(4))
INSERT INTO @tablea
VALUES
(1, 100, '20170311','20170311 01:01:00', 'Buy'),
(1, 100, '20170311','20170311 01:02:00', 'Buy'),
(1, 100, '20170311','20170311 01:03:00', 'Buy'),
(1, 100, '20170311','20170311 01:04:00', 'Retu'),
(1, 100, '20170311','20170311 01:05:00', 'Buy'),
(1, 100, '20170311','20170311 01:06:00', 'Retu'),
(1, 100, '20170311','20170311 01:07:00', 'Retu'),
(2, 100, '20170311','20170311 01:03:00', 'Buy'),
(1, 110, '20170311','20170311 01:03:00', 'Buy');
select * from @tablea
order by field_id,
field_number,
field_inserted
declare @eoj int =1;
while @eoj > 0
begin
WITH cte AS
(
SELECT
case field_sale when 'Buy' then
lead (field_sale) OVER (PARTITION BY field_id, field_number ORDER BY field_inserted)
when 'Retu' then
lag (field_sale) OVER (PARTITION BY field_id, field_number ORDER BY field_inserted)
end nbr_type,
field_id,
field_number,
field_date,
field_sale,
field_inserted
FROM @tablea
)
delete
from cte
where nbr_type is not null and nbr_type <> field_sale;
set @eoj = @@rowcount;
-- check it
select * from @tablea
order by field_id,
field_number,
field_inserted;
end;
它将重复N + 1次,其中N是最长返回序列的长度。在上面的例子中N = 2.