我有两个表, orders &订购历史记录,订单表具有订单号和订单>订购日期,这是实际下订单的日期。
这在以下模式和演示数据中得到了证明;
CREATE TABLE #Orders
(
OrderNumber INT,
OrderDate DATETIME
)
INSERT INTO #Orders (OrderNumber,OrderDate)
VALUES
(001,'2019-04-16 07:08:08.567'),
(002,'2019-03-22 07:08:08.567'),
(003,'2019-06-30 07:08:08.567'),
(004,'2019-01-05 07:08:08.567'),
(005,'2019-02-19 07:08:08.567')
订购审核表还包含订单号和事件日期,这是订单状态更改的日期。
这在以下模式和演示数据中证明了这一点。
CREATE TABLE #Order_Audit
(
OrderNumber INT,
EventDate DATETIME,
Status INT
)
INSERT INTO #Order_Audit (OrderNumber,EventDate,Status)
VALUES
(001,'2019-04-16 07:08:08.567',1),
(001,'2019-04-19 07:08:08.567',2),
(001,'2019-04-22 07:08:08.567',3),
(001,'2019-04-28 07:08:08.567',4),
(001,'2019-04-30 07:08:08.567',5),
(002,'2019-03-22 07:08:08.567',1),
(002,'2019-03-24 07:08:08.567',2),
(002,'2019-03-26 07:08:08.567',3),
(002,'2019-04-01 07:08:08.567',4),
(002,'2019-04-10 07:08:08.567',5),
(003,'2019-06-30 07:08:08.567',1),
(003,'2019-07-15 07:08:08.567',2),
(003,'2019-07-19 07:08:08.567',3),
(003,'2019-07-20 07:08:08.567',4),
(003,'2019-07-21 07:08:08.567',5),
(004,'2019-01-05 07:08:08.567',1),
(004,'2019-01-06 07:08:08.567',2),
(004,'2019-01-07 07:08:08.567',3),
(004,'2019-01-08 07:08:08.567',4),
(004,'2019-01-09 07:08:08.567',5),
(005,'2019-02-19 07:08:08.567',1),
(005,'2019-03-19 07:08:08.567',2),
(005,'2019-03-21 07:08:08.567',3),
(005,'2019-03-22 07:08:08.567',4),
(005,'2019-03-23 07:08:08.567',5)
以下是我目前有的查询,它将为我提供事件日期> 订购日期之间的区别。
查询已简化,但是包括关键列。这将在 SQL Server 2012 SP4
上执行SELECT
O.OrderNumber,
DATEDIFF(DAY,O.OrderDate,OA.EventDate) AS [Day-Diff]
FROM #Orders O
INNER JOIN #Order_Audit OA ON OA.OrderNumber = O.OrderNumber
上面的查询输出
|---------------------|------------------|
| OrderNumber | DayDiff |
|---------------------|------------------|
| 001 | 0 |
|---------------------|------------------|
| 001 | 3 |
|---------------------|------------------|
| 001 | 6 |
|---------------------|------------------|
| 001 | 12 |
|---------------------|------------------|
| 001 | 14 |
|---------------------|------------------|
| 002 | 0 |
|---------------------|------------------|
| 002 | 2 |
|---------------------|------------------|
| 002 | 4 |
|---------------------|------------------|
| 002 | 10 |
|---------------------|------------------|
| 002 | 19 |
|---------------------|------------------|
我真正需要的是一个查询,它将输出更多类似于此
|---------------------|------------------|
| OrderNumber | DayDiff |
|---------------------|------------------|
| 001 | |
|---------------------|------------------|
| 001 | |
|---------------------|------------------|
| 001 | |
|---------------------|------------------|
| 001 | |
|---------------------|------------------|
| 001 | |
|---------------------|------------------|
| Total | 14 |
|---------------------|------------------|
| 002 | |
|---------------------|------------------|
| 002 | |
|---------------------|------------------|
| 002 | |
|---------------------|------------------|
| 002 | |
|---------------------|------------------|
| 002 | |
|---------------------|------------------|
| Total | 19 |
|---------------------|------------------|
但是,我无法弄清楚如何获得订购日期和最新事件日期之间的区别事件(如上所示( - 我什至不确定在T -SQL中是否可以在应用级别进行处理。
您可以在下面尝试一下。我创建了总标签为订购 总计订购的总标签。
SELECT
CAST(O.OrderNumber AS VARCHAR) + ' Total' OrderNumber,
MAX(DATEDIFF(DAY,O.OrderDate,OA.EventDate)) AS [Day-Diff]
FROM #Orders O
INNER JOIN #Order_Audit OA ON OA.OrderNumber = O.OrderNumber
GROUP BY CAST(O.OrderNumber AS VARCHAR) + ' Total'
UNION ALL
SELECT
CAST(O.OrderNumber AS VARCHAR) OrderNumber,
NULL AS [Day-Diff]
FROM #Orders O
INNER JOIN #Order_Audit OA ON OA.OrderNumber = O.OrderNumber
ORDER BY 1
对于总数,您可以group by ordernumber
获取最后一个eventdate
,然后找到相应的orderdate
的区别。
然后使用联合所有:
select t.OrderNumber, t.DayDiff
from (
select ordernumber nr, cast(ordernumber as varchar(10)) OrderNumber, null DayDiff, 0 col
from order_audit
union all
select a.ordernumber nr, 'Total', datediff(day, o.orderdate, a.eventdate) DayDiff, 1 col
from orders o inner join (
select
ordernumber, max(eventdate) eventdate
from order_audit
group by ordernumber
) a on a.ordernumber = o.ordernumber
) t
order by t.nr, t.col
请参阅演示。
结果:
> OrderNumber | DayDiff
> :---------- | ------:
> 1 |
> 1 |
> 1 |
> 1 |
> 1 |
> Total | 14
> 2 |
> 2 |
> 2 |
> 2 |
> 2 |
> Total | 19
> 3 |
> 3 |
> 3 |
> 3 |
> 3 |
> Total | 21
> 4 |
> 4 |
> 4 |
> 4 |
> 4 |
> Total | 4
> 5 |
> 5 |
> 5 |
> 5 |
> 5 |
> Total | 32