Question

我的原始数据看起来像这样

enter image description here

我想将其展开以使报告看起来像这样

enter image description here

如何在TSQL中将其像这样从左到右按顺序旋转？

以下是生成数据的TSQL

Declare @ProcessHistory Table ( Id Int, ProcessId Int, LocationId Int, StartTime DateTime, EndTime DateTime, Duration Time (0) )
Insert Into @ProcessHistory Values
(2, 13, 0, '2012-01-27 12:23:35.373', '2012-01-27 12:23:35.963', '00:00:00'),
(3, 13, 10, '2012-01-27 12:23:35.373', '2012-01-27 12:23:35.633', '00:00:00'),
(4, 13, 20, '2012-01-27 12:23:35.633', '2012-01-27 12:23:35.633', '00:00:00'),
(5, 13, 30, '2012-01-27 12:23:35.633', '2012-01-27 12:23:35.657', '00:00:00'),
(6, 13, 40, '2012-01-27 12:23:35.657', '2012-01-27 12:23:35.847', '00:00:00'),
(7, 13, 50, '2012-01-27 12:23:35.847', '2012-01-27 12:23:35.950', '00:00:00'),
(8, 13, 60, '2012-01-27 12:23:35.950', '2012-01-27 12:23:35.963', '00:00:00'),
(218, 13, 0, '2012-01-27 22:05:34.650', '2012-01-27 22:05:37.297', '00:00:03'),
(219, 13, 10, '2012-01-27 22:05:34.653', '2012-01-27 22:05:35.453', '00:00:01'),
(220, 13, 20, '2012-01-27 22:05:35.457', '2012-01-27 22:05:35.463', '00:00:00'),
(221, 13, 30, '2012-01-27 22:05:35.467', '2012-01-27 22:05:35.570', '00:00:00'),
(222, 13, 40, '2012-01-27 22:05:35.570', '2012-01-27 22:05:35.620', '00:00:00'),
(223, 13, 50, '2012-01-27 22:05:35.620', '2012-01-27 22:05:37.280', '00:00:02'),
(224, 13, 60, '2012-01-27 22:05:37.283', '2012-01-27 22:05:37.293', '00:00:00'),
(434, 13, 0, '2012-01-29 04:35:32.370', '2012-01-29 04:35:36.913', '00:00:04'),
(435, 13, 10, '2012-01-29 04:35:32.400', '2012-01-29 04:35:33.817', '00:00:01'),
(436, 13, 20, '2012-01-29 04:35:33.883', '2012-01-29 04:35:33.933', '00:00:00'),
(437, 13, 30, '2012-01-29 04:35:33.933', '2012-01-29 04:35:34.153', '00:00:01'),
(438, 13, 40, '2012-01-29 04:35:34.180', '2012-01-29 04:35:34.660', '00:00:00'),
(439, 13, 50, '2012-01-29 04:35:34.727', '2012-01-29 04:35:36.700', '00:00:02'),
(440, 13, 60, '2012-01-29 04:35:36.763', '2012-01-29 04:35:36.853', '00:00:00'),
(650, 13, 0, '2012-01-29 22:19:18.297', '2012-01-29 22:19:22.103', '00:00:04'),
(651, 13, 10, '2012-01-29 22:19:18.297', '2012-01-29 22:19:19.450', '00:00:01'),
(652, 13, 20, '2012-01-29 22:19:19.453', '2012-01-29 22:19:19.473', '00:00:00'),
(653, 13, 30, '2012-01-29 22:19:19.473', '2012-01-29 22:19:19.493', '00:00:00'),
(654, 13, 40, '2012-01-29 22:19:19.493', '2012-01-29 22:19:19.537', '00:00:00'),
(655, 13, 50, '2012-01-29 22:19:19.537', '2012-01-29 22:19:22.073', '00:00:03'),
(656, 13, 60, '2012-01-29 22:19:22.073', '2012-01-29 22:19:22.083', '00:00:00'),
(866, 13, 0, '2012-01-30 11:09:21.437', '2012-01-30 11:09:24.163', '00:00:03'),
(867, 13, 10, '2012-01-30 11:09:21.437', '2012-01-30 11:09:22.437', '00:00:01'),
(868, 13, 20, '2012-01-30 11:09:22.440', '2012-01-30 11:09:22.443', '00:00:00'),
(869, 13, 30, '2012-01-30 11:09:22.447', '2012-01-30 11:09:22.490', '00:00:00'),
(870, 13, 40, '2012-01-30 11:09:22.490', '2012-01-30 11:09:22.670', '00:00:00'),
(871, 13, 50, '2012-01-30 11:09:22.670', '2012-01-30 11:09:24.150', '00:00:02'),
(872, 13, 60, '2012-01-30 11:09:24.150', '2012-01-30 11:09:24.163', '00:00:00'),
(1038, 13, 0, '2012-01-30 23:12:51.240', '2012-01-30 23:12:54.837', '00:00:03'),
(1039, 13, 10, '2012-01-30 23:12:51.240', '2012-01-30 23:12:52.663', '00:00:01'),
(1040, 13, 20, '2012-01-30 23:12:52.667', '2012-01-30 23:12:52.680', '00:00:00'),
(1041, 13, 30, '2012-01-30 23:12:52.683', '2012-01-30 23:12:52.733', '00:00:00'),
(1042, 13, 40, '2012-01-30 23:12:52.733', '2012-01-30 23:12:53.003', '00:00:01'),
(1043, 13, 50, '2012-01-30 23:12:53.003', '2012-01-30 23:12:54.813', '00:00:01'),
(1044, 13, 60, '2012-01-30 23:12:54.817', '2012-01-30 23:12:54.833', '00:00:00'),
(1254, 13, 0, '2012-01-31 23:08:30.760', '2012-01-31 23:08:33.787', '00:00:03'),
(1255, 13, 10, '2012-01-31 23:08:30.763', '2012-01-31 23:08:31.733', '00:00:01'),
(1256, 13, 20, '2012-01-31 23:08:31.737', '2012-01-31 23:08:31.743', '00:00:00'),
(1257, 13, 30, '2012-01-31 23:08:31.743', '2012-01-31 23:08:31.800', '00:00:00'),
(1258, 13, 40, '2012-01-31 23:08:31.800', '2012-01-31 23:08:31.940', '00:00:00'),
(1259, 13, 50, '2012-01-31 23:08:31.943', '2012-01-31 23:08:33.627', '00:00:02'),
(1260, 13, 60, '2012-01-31 23:08:33.627', '2012-01-31 23:08:33.783', '00:00:00'),
(1470, 13, 0, '2012-02-02 04:03:14.497', '2012-02-02 04:03:17.323', '00:00:03'),
(1471, 13, 10, '2012-02-02 04:03:14.497', '2012-02-02 04:03:15.257', '00:00:01'),
(1472, 13, 20, '2012-02-02 04:03:15.257', '2012-02-02 04:03:15.263', '00:00:00'),
(1473, 13, 30, '2012-02-02 04:03:15.267', '2012-02-02 04:03:15.360', '00:00:00'),
(1474, 13, 40, '2012-02-02 04:03:15.360', '2012-02-02 04:03:15.637', '00:00:00'),
(1475, 13, 50, '2012-02-02 04:03:15.640', '2012-02-02 04:03:17.310', '00:00:02'),
(1476, 13, 60, '2012-02-02 04:03:17.310', '2012-02-02 04:03:17.320', '00:00:00'),
(1686, 13, 0, '2012-02-02 10:30:32.460', '2012-02-02 10:30:35.197', '00:00:03'),
(1687, 13, 10, '2012-02-02 10:30:32.463', '2012-02-02 10:30:33.487', '00:00:01'),
(1688, 13, 20, '2012-02-02 10:30:33.490', '2012-02-02 10:30:33.493', '00:00:00'),
(1689, 13, 30, '2012-02-02 10:30:33.497', '2012-02-02 10:30:33.517', '00:00:00'),
(1690, 13, 40, '2012-02-02 10:30:33.520', '2012-02-02 10:30:33.547', '00:00:00'),
(1691, 13, 50, '2012-02-02 10:30:33.550', '2012-02-02 10:30:35.180', '00:00:02'),
(1692, 13, 60, '2012-02-02 10:30:35.180', '2012-02-02 10:30:35.190', '00:00:00'),
(1858, 13, 0, '2012-02-02 22:20:36.840', '2012-02-02 22:20:39.997', '00:00:03'),
(1859, 13, 10, '2012-02-02 22:20:36.843', '2012-02-02 22:20:37.853', '00:00:01'),
(1860, 13, 20, '2012-02-02 22:20:37.857', '2012-02-02 22:20:37.863', '00:00:00'),
(1861, 13, 30, '2012-02-02 22:20:37.863', '2012-02-02 22:20:37.930', '00:00:00'),
(1862, 13, 40, '2012-02-02 22:20:37.933', '2012-02-02 22:20:38.317', '00:00:01'),
(1863, 13, 50, '2012-02-02 22:20:38.320', '2012-02-02 22:20:39.980', '00:00:01'),
(1864, 13, 60, '2012-02-02 22:20:39.983', '2012-02-02 22:20:39.993', '00:00:00'),
(2030, 13, 0, '2012-02-03 03:45:27.820', '2012-02-03 03:45:30.723', '00:00:03'),
(2031, 13, 10, '2012-02-03 03:45:27.820', '2012-02-03 03:45:28.880', '00:00:01'),
(2032, 13, 20, '2012-02-03 03:45:28.880', '2012-02-03 03:45:28.887', '00:00:00'),
(2033, 13, 30, '2012-02-03 03:45:28.887', '2012-02-03 03:45:28.923', '00:00:00'),
(2034, 13, 40, '2012-02-03 03:45:28.923', '2012-02-03 03:45:29.123', '00:00:01'),
(2035, 13, 50, '2012-02-03 03:45:29.127', '2012-02-03 03:45:30.707', '00:00:01'),
(2036, 13, 60, '2012-02-03 03:45:30.707', '2012-02-03 03:45:30.720', '00:00:00'),
(2246, 13, 0, '2012-02-06 10:25:28.507', '2012-02-06 10:25:31.693', '00:00:03'),
(2247, 13, 10, '2012-02-06 10:25:28.507', '2012-02-06 10:25:29.503', '00:00:01'),
(2248, 13, 20, '2012-02-06 10:25:29.503', '2012-02-06 10:25:29.523', '00:00:00'),
(2249, 13, 30, '2012-02-06 10:25:29.523', '2012-02-06 10:25:29.570', '00:00:00'),
(2250, 13, 40, '2012-02-06 10:25:29.570', '2012-02-06 10:25:29.810', '00:00:00'),
(2251, 13, 50, '2012-02-06 10:25:29.810', '2012-02-06 10:25:31.667', '00:00:02'),
(2252, 13, 60, '2012-02-06 10:25:31.667', '2012-02-06 10:25:31.690', '00:00:00'),
(2506, 13, 0, '2012-02-06 22:15:44.787', '2012-02-06 22:15:47.633', '00:00:03'),
(2507, 13, 10, '2012-02-06 22:15:44.787', '2012-02-06 22:15:45.913', '00:00:01'),
(2508, 13, 20, '2012-02-06 22:15:45.913', '2012-02-06 22:15:45.920', '00:00:00'),
(2509, 13, 30, '2012-02-06 22:15:45.923', '2012-02-06 22:15:45.967', '00:00:00'),
(2510, 13, 40, '2012-02-06 22:15:45.970', '2012-02-06 22:15:46.007', '00:00:01'),
(2511, 13, 50, '2012-02-06 22:15:46.007', '2012-02-06 22:15:47.610', '00:00:01'),
(2512, 13, 60, '2012-02-06 22:15:47.610', '2012-02-06 22:15:47.620', '00:00:00'),
(2678, 13, 0, '2012-02-07 03:44:24.393', '2012-02-07 03:44:27.510', '00:00:03'),
(2679, 13, 10, '2012-02-07 03:44:24.393', '2012-02-07 03:44:25.670', '00:00:01'),
(2680, 13, 20, '2012-02-07 03:44:25.673', '2012-02-07 03:44:25.680', '00:00:00'),
(2681, 13, 30, '2012-02-07 03:44:25.680', '2012-02-07 03:44:25.750', '00:00:00'),
(2682, 13, 40, '2012-02-07 03:44:25.753', '2012-02-07 03:44:25.990', '00:00:00'),
(2683, 13, 50, '2012-02-07 03:44:25.993', '2012-02-07 03:44:27.497', '00:00:02'),
(2684, 13, 60, '2012-02-07 03:44:27.500', '2012-02-07 03:44:27.510', '00:00:00'),
(2894, 13, 0, '2012-02-07 10:29:23.753', '2012-02-07 10:29:26.587', '00:00:03'),
(2895, 13, 10, '2012-02-07 10:29:23.753', '2012-02-07 10:29:24.700', '00:00:01'),
(2896, 13, 20, '2012-02-07 10:29:24.700', '2012-02-07 10:29:24.710', '00:00:00'),
(2897, 13, 30, '2012-02-07 10:29:24.710', '2012-02-07 10:29:24.733', '00:00:00'),
(2898, 13, 40, '2012-02-07 10:29:24.733', '2012-02-07 10:29:24.760', '00:00:00'),
(2899, 13, 50, '2012-02-07 10:29:24.760', '2012-02-07 10:29:26.540', '00:00:02'),
(2900, 13, 60, '2012-02-07 10:29:26.540', '2012-02-07 10:29:26.560', '00:00:00')

Select * From @ProcessHistory

Answer 1

正如@Norla所说，这在SQL中是非常讨厌的，但是下面应该让你到那里（完全未经测试，顺便说一句，所以可能有一些小鬼）：

首先，您需要构建一个列名列表（这是您的starttime列中的唯一值：

DECLARE @cols NVARCHAR(2000)
SELECT  @cols = COALESCE(@cols + ',[' + startTime+ ']',
                         '[' + startTime+ ']')
FROM    ProcessHistory
ORDER BY startTime

然后，您需要将此字符串提供给动态SQL查询：

DECLARE @query NVARCHAR(4000)
SET @query = N'SELECT processId,locationId, '+@cols +'
               FROM
               (SELECT  t.processId,
                        t.locationId,
                        t.starttime,
                        t.duration
               FROM    ProcessHistory) t PIVOT ( SUM(duration)
                                                 FOR starttime IN ( '+@cols +' )
                                               ) AS pvt'

然后执行：

EXECUTE(@query)

Answer 2

关于原始问题中的评论：

最简单的方法是在Excel中进行转移。 SQL Server将要求您指定数据透视操作中的每个列，您必须动态地执行此操作。（这太糟糕了！）

如果您可以将上面显示的结果导入到Excel工作表中，那么从第一个工作表中读取第二个工作表（在同一个工作簿中）并执行数据透视表，您就是金色。

Answer 3

好的，您的问题需要考虑很多。你需要动态SQL，所以你真的应该首先看一下this link。此外，您的Duration列的数据类型为TIME，因此SUM并不容易，需要执行大量CAST和CONVERT。一旦我这样说，我尝试了这个查询并且运行正常（查看您的预期结果）：

DECLARE @Dates NVARCHAR(MAX)='', @Q NVARCHAR(MAX), @FormatedDates NVARCHAR(MAX) = ''

SELECT  @Dates = @Dates + '[' + CONVERT(VARCHAR(16),StartTime,120) + '],',
        @FormatedDates = @FormatedDates + 'CONVERT(TIME(0),CAST([' + CONVERT(VARCHAR(16),StartTime,120) +'] AS DATETIME)) AS [' + CONVERT(VARCHAR(16),StartTime,120) +'],'
FROM ProcessHistory
GROUP BY CONVERT(VARCHAR(16),StartTime,120)

SELECT  @Dates = LEFT(@Dates,LEN(@Dates)-1),
        @FormatedDates = LEFT(@FormatedDates,LEN(@FormatedDates)-1)

SET @Q = '
SELECT ProcessId, LocationId, '+@FormatedDates+'
FROM (  SELECT  ProcessId, LocationId, CONVERT(VARCHAR(16),StartTime,120) StartTime, 
                CAST(CONVERT(DATETIME,Duration) AS FLOAT) Duration
        FROM ProcessHistory) A
PIVOT (SUM(Duration) FOR StartTime IN ('+@Dates+')) PT'


EXEC sp_executesql @Q

Answer 4

也许是这样的：

测试数据：

CREATE TABLE ProcessHistory ( Id Int, ProcessId Int, LocationId Int, StartTime DateTime, EndTime DateTime, Duration Time (0) )
Insert Into ProcessHistory Values
(2, 13, 0, '2012-01-27 12:23:35.373', '2012-01-27 12:23:35.963', '00:00:00'),
..............................

获取唯一列：

DECLARE @cols VARCHAR(MAX)
;WITH CTE AS
(
    SELECT 
        convert(varchar, tbl.StartTime, 101)+' '+LEFT(convert(varchar, tbl.StartTime, 114),5) AS StartTime
    FROM 
        ProcessHistory AS tbl
), 
CTE2 AS
(
    SELECT
        ROW_Number() OVER(PARTITION BY CTE.StartTime ORDER BY CTE.StartTime DESC) AS RowNbr,
        CTE.StartTime
    FROM
        CTE
)
SELECT
    @cols = COALESCE(@cols + ','+QUOTENAME(StartTime),
                 QUOTENAME(StartTime))
FROM 
    CTE2
WHERE
    CTE2.RowNbr=1

执行动态sql（我选择以秒为单位对持续时间求和）：

DECLARE @query NVARCHAR(4000)=
N'SELECT
    *
FROM
(
    SELECT
        tbl.ProcessId,
        tbl.LocationId,
        DATEDIFF(s, 0, tbl.Duration) AS Duration,
        convert(varchar, tbl.StartTime, 101)+'' ''+LEFT(convert(varchar, tbl.StartTime, 114),5) AS StartTime
    FROM
        ProcessHistory AS tbl
) AS P
PIVOT
(
    SUM(Duration)
    FOR StartTime IN('+@cols+')
) AS Pvt'

EXECUTE(@query)

然后就我而言，我放弃了桌子：

DROP TABLE ProcessHistory

在SQL中进行透视

4 个答案: