我需要按照第二天的11:00到10:00的时间段选择值的总和，按ID分组。
这是我的表1：
date value id
"2017-03-29 11:00:00" "453" "id1"
"2017-03-29 12:00:00" "000" "id1"
"2017-03-29 13:00:00" "234" "id1"
"2017-03-29 14:00:00" "000" "id1"
"2017-03-29 15:00:00" "000" "id1"
"2017-03-29 16:00:00" "222" "id1"
"2017-03-29 17:00:00" "000" "id1"
"2017-03-29 18:00:00" "000" "id1"
"2017-03-29 19:00:00" "000" "id1"
"2017-03-29 20:00:00" "000" "id1"
"2017-03-29 21:00:00" "000" "id1"
"2017-03-29 22:00:00" "000" "id1"
"2017-03-29 23:00:00" "123" "id1"
"2017-03-30 00:00:00" "000" "id1"
"2017-03-30 01:00:00" "000" "id1"
"2017-03-30 02:00:00" "000" "id1"
"2017-03-30 03:00:00" "000" "id1"
"2017-03-30 04:00:00" "000" "id1"
"2017-03-30 05:00:00" "000" "id1"
"2017-03-30 07:00:00" "000" "id1"
"2017-03-30 08:00:00" "000" "id1"
"2017-03-30 09:00:00" "000" "id1"
"2017-03-30 10:00:00" "333" "id1"
"2017-03-30 11:00:00" "000" "id1"
"2017-03-30 12:00:00" "123" "id1"
"2017-03-30 13:00:00" "000" "id1"
"2017-03-30 14:00:00" "000" "id1"
"2017-03-30 15:00:00" "000" "id1"
"2017-03-30 16:00:00" "000" "id1"
"2017-03-30 18:00:00" "000" "id1"
"2017-03-30 19:00:00" "000" "id1"
"2017-03-30 20:00:00" "000" "id1"
"2017-03-30 21:00:00" "000" "id1"
"2017-03-30 22:00:00" "000" "id1"
"2017-03-30 23:00:00" "000" "id1"
"2017-03-31 00:00:00" "000" "id1"
"2017-03-31 01:00:00" "000" "id1"
"2017-03-31 02:00:00" "000" "id1"
"2017-03-31 03:00:00" "000" "id1"
"2017-03-31 04:00:00" "000" "id1"
"2017-03-31 05:00:00" "000" "id1"
"2017-03-31 06:00:00" "000" "id1"
"2017-03-31 07:00:00" "000" "id1"
"2017-03-31 08:00:00" "000" "id1"
"2017-03-31 09:00:00" "000" "id1"
"2017-03-29 12:00:00" "756" "id2"
"2017-03-29 13:00:00" "701" "id2"
"2017-03-29 14:00:00" "758" "id2"
"2017-03-29 15:00:00" "867" "id2"
"2017-03-29 16:00:00" "924" "id2"
"2017-03-29 17:00:00" "871" "id2"
"2017-03-29 18:00:00" "817" "id2"
"2017-03-29 19:00:00" "109" "id2"
"2017-03-29 20:00:00" "131" "id2"
"2017-03-29 21:00:00" "126" "id2"
"2017-03-29 22:00:00" "120" "id2"
"2017-03-29 23:00:00" "120" "id2"
"2017-03-30 00:00:00" "930" "id2"
"2017-03-30 01:00:00" "108" "id2"
"2017-03-30 09:00:00" "867" "id2"
"2017-03-30 10:00:00" "808" "id2"
"2017-03-30 11:00:00" "756" "id2"
"2017-03-30 12:00:00" "758" "id2"
"2017-03-30 13:00:00" "866" "id2"
"2017-03-30 14:00:00" "981" "id2"
"2017-03-30 15:00:00" "981" "id2"
"2017-03-30 16:00:00" "872" "id2"
"2017-03-30 17:00:00" "928" "id2"
"2017-03-30 18:00:00" "109" "id2"
"2017-03-30 19:00:00" "115" "id2"
"2017-03-30 20:00:00" "121" "id2"
"2017-03-30 21:00:00" "131" "id2"
"2017-03-30 22:00:00" "148" "id2"
"2017-03-30 23:00:00" "132" "id2"
"2017-03-31 00:00:00" "115" "id2"
"2017-03-31 01:00:00" "120" "id2"
"2017-03-31 02:00:00" "137" "id2"
"2017-03-31 03:00:00" "137" "id2"
"2017-03-31 04:00:00" "132" "id2"
"2017-03-31 05:00:00" "126" "id2"
"2017-03-31 06:00:00" "126" "id2"
"2017-03-31 07:00:00" "104" "id2"
"2017-03-31 08:00:00" "874" "id2"
"2017-03-31 09:00:00" "651" "id2"
"2017-03-31 10:00:00" "540" "id2"
结果表应如下所示：
date_period value_sum id
"2017-03-29 11:00:00 - 2017-03-30 10:00:00" 1365 "id1"
"2017-03-30 11:00:00 - 2017-03-31 10:00:00" 123 "id1"
"2017-03-29 11:00:00 - 2017-03-30 10:00:00" 9013 "id2"
"2017-03-30 11:00:00 - 2017-03-31 10:00:00" 9834 "id2"
表1这只是一个例子，真实的桌子有很多ID和大日期从2015年到2017年，不仅从2017-03-29到2017-03-31。我需要按第二天的11:00到10:00按时间段选择所有值的总和，按ID分组。
Oracle和MSSQL中应该有2个解决方案。
答案 0 :(得分：1)
我认为以下查询将帮助您解决问题，如果您有任何其他问题，请告诉我
DECLARE @ProductTotals TABLE
(
Daytime Datetime,
ProductID int,
id nvarchar(50)
)
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 11:00:00',453,'id1')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-04-30 12:00:00',568,'id1')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-05-31 13:00:00',500,'id1')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 11:00:00',586,'id2')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 12:00:00',895,'id2')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 13:00:00',452,'id2')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 11:00:00',875,'id3')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 12:00:00',586,'id3')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 13:00:00',784,'id3')
SELECT sum(t.sumid) AS sumid,
T.id,
T.Duration from(
SELECT p.ProductID AS sumid,
p.id,
Duration = cast(DATEADD(DAY, DATEDIFF(DAY, 0, Daytime), '10:00:00') AS varchar)+' - ' + cast(DATEADD(DAY, DATEDIFF(DAY, -1, Daytime), '11:00:00') AS varchar)
FROM @ProductTotals p
GROUP BY p.id,
p.Daytime,
p.ProductID
HAVING Daytime > DATEADD(DAY, DATEDIFF(DAY, 0, Daytime), '10:00:00')
AND Daytime < DATEADD(DAY, DATEDIFF(DAY, -1, Daytime), '11:00:00')
)T
group by T.id,t.Duration
OutPut is Given below
568 id1 Apr 30 2017 10:00AM - May 1 2017 11:00AM
453 id1 Mar 29 2017 10:00AM - Mar 30 2017 11:00AM
1933 id2 Mar 29 2017 10:00AM - Mar 30 2017 11:00AM
2245 id3 Mar 29 2017 10:00AM - Mar 30 2017 11:00AM
500 id1 May 31 2017 10:00AM - Jun 1 2017 11:00AM
答案 1 :(得分：1)
检查此答案是否有效
DECLARE @ProductTotals TABLE
(
Daytime Datetime,
ProductID int,
id nvarchar(50)
)
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 11:00:00',453,'id1')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-04-30 12:00:00',568,'id1')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-05-31 13:00:00',500,'id1')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 11:00:00',586,'id2')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 12:00:00',895,'id2')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 13:00:00',452,'id2')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 11:00:00',875,'id3')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 12:00:00',586,'id3')
INSERT INTO @ProductTotals (Daytime,ProductID, id) values('2017-03-29 13:00:00',784,'id3')
;with cte(id, duration, productsum)
as (
select id, Duration = cast(DATEADD(day, DATEDIFF(day, 0, Daytime), '10:00:00') as varchar) +' - ' + cast(DATEADD(day, DATEDIFF(day, -1, Daytime), '11:00:00') as varchar),
ProductSum = sum(ProductId) from @ProductTotals
group by id,
Daytime having Daytime > DATEADD(day, DATEDIFF(day, 0, Daytime), '10:00:00')
and Daytime < DATEADD(day, DATEDIFF(day, -1, Daytime), '11:00:00')
)
select id, Duration, ProductSum = Sum(ProductSum) from cte group by id,Duration order by id
id Duration ProductSum
id1 Apr 30 2017 10:00AM - May 1 2017 11:00AM 568
id1 Mar 29 2017 10:00AM - Mar 30 2017 11:00AM 453
id1 May 31 2017 10:00AM - Jun 1 2017 11:00AM 500
id2 Mar 29 2017 10:00AM - Mar 30 2017 11:00AM 1933
id3 Mar 29 2017 10:00AM - Mar 30 2017 11:00AM 2245
答案 2 :(得分：0)
逻辑上你想要做以下事情： 取日期值，减去11小时，（将所有时间转移到相同的＆＃39;天＆＃39;） 将结果日期时间转换为天。 （即删除时间组件） 这为您提供了一个＆＃34; ReportingDate＆＃34;
然后根据ReportingDate＆amp; amp; ID
答案 3 :(得分：0)
MSSQL的解决方案。
初始数据：
DECLARE @Data TABLE
(
[date] DATETIME,
[value] INT,
[id] NVARCHAR(MAX)
);
INSERT INTO @Data
VALUES
({ ts'2017-03-29 11:00:00' }, 453, 'id1'),
({ ts'2017-03-29 12:00:00' }, 000, 'id1'),
({ ts'2017-03-29 13:00:00' }, 234, 'id1'),
({ ts'2017-03-29 14:00:00' }, 000, 'id1'),
({ ts'2017-03-29 15:00:00' }, 000, 'id1'),
({ ts'2017-03-29 16:00:00' }, 222, 'id1'),
({ ts'2017-03-29 17:00:00' }, 000, 'id1'),
({ ts'2017-03-29 18:00:00' }, 000, 'id1'),
({ ts'2017-03-29 19:00:00' }, 000, 'id1'),
({ ts'2017-03-29 20:00:00' }, 000, 'id1'),
({ ts'2017-03-29 21:00:00' }, 000, 'id1'),
({ ts'2017-03-29 22:00:00' }, 000, 'id1'),
({ ts'2017-03-29 23:00:00' }, 123, 'id1'),
({ ts'2017-03-30 00:00:00' }, 000, 'id1'),
({ ts'2017-03-30 01:00:00' }, 000, 'id1'),
({ ts'2017-03-30 02:00:00' }, 000, 'id1'),
({ ts'2017-03-30 03:00:00' }, 000, 'id1'),
({ ts'2017-03-30 04:00:00' }, 000, 'id1'),
({ ts'2017-03-30 05:00:00' }, 000, 'id1'),
({ ts'2017-03-30 07:00:00' }, 000, 'id1'),
({ ts'2017-03-30 08:00:00' }, 000, 'id1'),
({ ts'2017-03-30 09:00:00' }, 000, 'id1'),
({ ts'2017-03-30 10:00:00' }, 333, 'id1'),
({ ts'2017-03-30 11:00:00' }, 000, 'id1'),
({ ts'2017-03-30 12:00:00' }, 123, 'id1'),
({ ts'2017-03-30 13:00:00' }, 000, 'id1'),
({ ts'2017-03-30 14:00:00' }, 000, 'id1'),
({ ts'2017-03-30 15:00:00' }, 000, 'id1'),
({ ts'2017-03-30 16:00:00' }, 000, 'id1'),
({ ts'2017-03-30 18:00:00' }, 000, 'id1'),
({ ts'2017-03-30 19:00:00' }, 000, 'id1'),
({ ts'2017-03-30 20:00:00' }, 000, 'id1'),
({ ts'2017-03-30 21:00:00' }, 000, 'id1'),
({ ts'2017-03-30 22:00:00' }, 000, 'id1'),
({ ts'2017-03-30 23:00:00' }, 000, 'id1'),
({ ts'2017-03-31 00:00:00' }, 000, 'id1'),
({ ts'2017-03-31 01:00:00' }, 000, 'id1'),
({ ts'2017-03-31 02:00:00' }, 000, 'id1'),
({ ts'2017-03-31 03:00:00' }, 000, 'id1'),
({ ts'2017-03-31 04:00:00' }, 000, 'id1'),
({ ts'2017-03-31 05:00:00' }, 000, 'id1'),
({ ts'2017-03-31 06:00:00' }, 000, 'id1'),
({ ts'2017-03-31 07:00:00' }, 000, 'id1'),
({ ts'2017-03-31 08:00:00' }, 000, 'id1'),
({ ts'2017-03-31 09:00:00' }, 000, 'id1'),
({ ts'2017-03-29 12:00:00' }, 756, 'id2'),
({ ts'2017-03-29 13:00:00' }, 701, 'id2'),
({ ts'2017-03-29 14:00:00' }, 758, 'id2'),
({ ts'2017-03-29 15:00:00' }, 867, 'id2'),
({ ts'2017-03-29 16:00:00' }, 924, 'id2'),
({ ts'2017-03-29 17:00:00' }, 871, 'id2'),
({ ts'2017-03-29 18:00:00' }, 817, 'id2'),
({ ts'2017-03-29 19:00:00' }, 109, 'id2'),
({ ts'2017-03-29 20:00:00' }, 131, 'id2'),
({ ts'2017-03-29 21:00:00' }, 126, 'id2'),
({ ts'2017-03-29 22:00:00' }, 120, 'id2'),
({ ts'2017-03-29 23:00:00' }, 120, 'id2'),
({ ts'2017-03-30 00:00:00' }, 930, 'id2'),
({ ts'2017-03-30 01:00:00' }, 108, 'id2'),
({ ts'2017-03-30 09:00:00' }, 867, 'id2'),
({ ts'2017-03-30 10:00:00' }, 808, 'id2'),
({ ts'2017-03-30 11:00:00' }, 756, 'id2'),
({ ts'2017-03-30 12:00:00' }, 758, 'id2'),
({ ts'2017-03-30 13:00:00' }, 866, 'id2'),
({ ts'2017-03-30 14:00:00' }, 981, 'id2'),
({ ts'2017-03-30 15:00:00' }, 981, 'id2'),
({ ts'2017-03-30 16:00:00' }, 872, 'id2'),
({ ts'2017-03-30 17:00:00' }, 928, 'id2'),
({ ts'2017-03-30 18:00:00' }, 109, 'id2'),
({ ts'2017-03-30 19:00:00' }, 115, 'id2'),
({ ts'2017-03-30 20:00:00' }, 121, 'id2'),
({ ts'2017-03-30 21:00:00' }, 131, 'id2'),
({ ts'2017-03-30 22:00:00' }, 148, 'id2'),
({ ts'2017-03-30 23:00:00' }, 132, 'id2'),
({ ts'2017-03-31 00:00:00' }, 115, 'id2'),
({ ts'2017-03-31 01:00:00' }, 120, 'id2'),
({ ts'2017-03-31 02:00:00' }, 137, 'id2'),
({ ts'2017-03-31 03:00:00' }, 137, 'id2'),
({ ts'2017-03-31 04:00:00' }, 132, 'id2'),
({ ts'2017-03-31 05:00:00' }, 126, 'id2'),
({ ts'2017-03-31 06:00:00' }, 126, 'id2'),
({ ts'2017-03-31 07:00:00' }, 104, 'id2'),
({ ts'2017-03-31 08:00:00' }, 874, 'id2'),
({ ts'2017-03-31 09:00:00' }, 651, 'id2'),
({ ts'2017-03-31 10:00:00' }, 540, 'id2');
解决方案查询：
SELECT
CONVERT(VARCHAR(255), CAST(DATEADD(HOUR, 11, CAST(CAST(DATEADD(HOUR, -11, [date])
AS DATE) AS DATETIME)) AS DATETIME), 120) + ' - ' +
CONVERT(VARCHAR(255), CAST(DATEADD(HOUR, 11 + 23, CAST(CAST(DATEADD(HOUR, -11, [date])
AS DATE) AS DATETIME)) AS DATETIME), 120) AS date_period,
SUM([value]) AS value_sum, [id]
FROM @Data AS [Data]
WHERE CAST(DATEADD(HOUR, -11, [date]) AS TIME) <= CAST({ t'23:00:00'} AS TIME)
GROUP BY CAST(DATEADD(HOUR, -11, [date]) AS DATE), [id]
结果：
date_period value_sum id
----------------------------------------------- ----------- --------
2017-03-29 11:00:00 - 2017-03-30 10:00:00 1365 id1
2017-03-30 11:00:00 - 2017-03-31 10:00:00 123 id1
2017-03-29 11:00:00 - 2017-03-30 10:00:00 9013 id2
2017-03-30 11:00:00 - 2017-03-31 10:00:00 9960 id2
答案 4 :(得分：0)
此解决方案正常：
SELECT t4.id, (t3.sumid + t4.sumid) as summ, t3.Duration_id FROM(
/* 1st day sum start from from 11:00:00 to 00:00:00*/
(SELECT sum(t.sumid) AS sumid,
T.id,
T.Duration, T.Duration_id as Duration_id from(
SELECT p.Value AS sumid,
p.id,
Duration = 'from ' + cast(DATEADD(DAY, DATEDIFF(DAY, 0, Daytime), '11:00:00') AS varchar),
Duration_id = 'from ' + cast(DATEADD(DAY, DATEDIFF(DAY, 0, Daytime), '11:00:00') AS varchar) + ' to ' + cast(DATEADD(DAY, DATEDIFF(DAY, -1, Daytime), '10:00:00') AS varchar)+id
FROM ProductTotals p
GROUP BY p.id,
p.Daytime,
p.Value
HAVING Daytime >= DATEADD(DAY, DATEDIFF(DAY, 0, Daytime), '11:00:00')
)T
group by T.id,t.Duration, t.Duration_id)t3
/* 1st day sum stop from 11:00:00 to 00:00:00*/
INNER JOIN
/* 2nd day sum start from 00:00:00 to 10:00:00*/
(SELECT sum(t2.sumid) AS sumid,
T2.id,
T2.Duration, t2.Duration_id as Duration_id from(
SELECT p.Value AS sumid,
p.id,
Duration = 'from ' + cast(DATEADD(DAY, DATEDIFF(DAY, 0, Daytime), '10:00:00') AS varchar),
Duration_id = 'from ' + cast(DATEADD(DAY, DATEDIFF(DAY, 1, Daytime), '11:00:00') AS varchar) + ' to ' + cast(DATEADD(DAY, DATEDIFF(DAY, 0, Daytime), '10:00:00') AS varchar)+id
FROM ProductTotals p
GROUP BY p.id,
p.Daytime,
p.Value
HAVING Daytime <= DATEADD(DAY, DATEDIFF(DAY, 0, Daytime), '10:00:00')
/* 2nd day sum stop from 00:00:00 to 10:00:00*/
)T2
group by T2.id, t2.Duration, t2.Duration_id)t4
ON T3.Duration_id = T4.Duration_id
)
order by t4.id, t3.Duration_id