按类型划分的每月余额

Question

我在 SQL-Server 中有一个表，其中包含几条输入和输出值记录，其中包含类型和日期列。

类似的东西：

DATE       |INPUT  |OUTPUT |TYPE
2018-01-10 | 256.35|       |A
2018-02-05 |       |  35.00|B
2018-02-15 |  65.30|       |A
2018-03-20 | 158.00|       |B
2018-04-02 |       |  63.32|B
2018-05-12 |       | 128.12|A
2018-06-20 |       |   7.35|B

我需要帮助来进行查询以返回每种类型的输入和输出的总和（作为余额），但它应该在每个月底返回该总和，即：

YEAR|MONTH|TYPE|BALANCE
2018|    1|A   | 256.35
2018|    1|B   |   0.00
2018|    2|A   | 321.65
2018|    2|B   | -35.00
2018|    3|A   | 321.65
2018|    3|B   | 123.00
2018|    4|A   | 321.65
2018|    4|B   |  59.68
2018|    5|A   | 193.53
2018|    5|B   |  59.68
2018|    6|A   | 193.53
2018|    6|B   |  52.33
2018|    7|A   | 193.53
2018|    7|B   |  52.33

不要忘记，每个月的余额都会受到上月余额的影响，或者说，每个月的余额不仅是当月的变动，也是之前所有月份的变动。

还应该注意的是，它应该包括一年/类型的每个月的记录（直到当前日期），即使给定的月份/类型没有变动，从第一个月/年开始最旧的运动并在实际日期结束（在本例中为 2018 年 7 月）。

Answer 1

结果实现了，你去吧：

declare @min_month datetime=(select dateadd(month,datediff(month,0,min([DATE])),0) from _yourtable)
declare @max_month datetime=(select dateadd(month,datediff(month,0,max([DATE])),0) from _yourtable)

;WITH months(d) AS (
  select @min_month
  UNION ALL
  SELECT dateadd(month,1,d) -- Recursion
  FROM months
  where dateadd(month,1,d)<=getdate()
)
select distinct
    year(m.d) as YEAR,
    month(m.d) as MONTH,
    types.v as [TYPE]
    ,sum(isnull(t.[INPUT],0)-isnull(t.[OUTPUT],0)) over (partition by types.v order by m.d)
from months m
cross join (select distinct type from _yourtable)types(v)
left join _yourtable t on dateadd(month,datediff(month,0,t.[DATE]),0)=m.d and types.v=t.TYPE
order by m.d,type
option(maxrecursion 0)

Answer 2

您可以使用 Lag 功能，下面的代码可能会有所帮助：

select year(date), month(date), type
, sum(input-output) + isnull(lag(sum(input-output),1,0) over(order by year(date), month(date), type), 0)
from test group by year(date), month(date), type

Answer 3

假设您的源数据是您最初提供的结构（即：这不是另一个查询的结果），这是一个相当简单的转换，它使用日期表和通过有序sum 的运行总计。

如果您已经有日期表，则可以删除此脚本中的前 2 个 ctes：

declare @t table(DateValue date,InputAmount decimal(8,2),OutputAmount decimal(8,2),ProdType nvarchar(1));
insert into @t values
 ('2018-01-10',256.35,null,'A')
,('2018-02-05',null, 35.00,'B')
,('2018-02-15', 65.30,null,'A')
,('2018-03-20',158.00,null,'B')
,('2018-04-02',null, 63.32,'B')
,('2018-05-12',null,128.12,'A')
,('2018-06-20',null,  7.35,'B')
;

-- Min date can just be min date in the source table, but the max date should be the month end of the max date in the source table0
declare @MinDate date = (select min(DateValue) from @t);
declare @MaxDate date = (select max(dateadd(day,-1,dateadd(month,datediff(month,0,DateValue)+1,0))) from @t);

with n(n) as (select * from (values(1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) t(t))   -- Using a tally table, built a table of dates
    ,d(d) as (select top(select datediff(day,@MinDate,@MaxDate)+1) dateadd(day,row_number() over (order by (select null))-1,@MinDate) from n n1,n n2,n n3, n n4)
    ,m as (select p.ProdType                                                        -- Then join to the source data to create a date value for each posible day for each product type
                    ,d.d
                    ,dateadd(day,-1,dateadd(month,datediff(month,0,d)+1,0)) as m    -- And calculate a running total using a windowed aggregate
                    ,sum(isnull(t.InputAmount,0) - isnull(t.OutputAmount,0)) over (partition by p.ProdType order by d.d) as RunningTotal
            from d
                cross join (select distinct ProdType
                            from @t
                            ) as p
                left join @t as t
                    on d.d = t.DateValue
                        and p.ProdType = t.ProdType
            )
select m
        ,ProdType
        ,RunningTotal as Balance
from m
where m = d
order by m.d
        ,m.ProdType;

输出：

+-------------------------+----------+---------+
|            m            | ProdType | Balance |
+-------------------------+----------+---------+
| 2018-01-31 00:00:00.000 | A        |  256.35 |
| 2018-01-31 00:00:00.000 | B        |    0.00 |
| 2018-02-28 00:00:00.000 | A        |  321.65 |
| 2018-02-28 00:00:00.000 | B        |  -35.00 |
| 2018-03-31 00:00:00.000 | A        |  321.65 |
| 2018-03-31 00:00:00.000 | B        |  123.00 |
| 2018-04-30 00:00:00.000 | A        |  321.65 |
| 2018-04-30 00:00:00.000 | B        |   59.68 |
| 2018-05-31 00:00:00.000 | A        |  193.53 |
| 2018-05-31 00:00:00.000 | B        |   59.68 |
| 2018-06-30 00:00:00.000 | A        |  193.53 |
| 2018-06-30 00:00:00.000 | B        |   52.33 |
+-------------------------+----------+---------+