SQL 服务器 - 使用 PIVOT 聚合
SQL Server - using aggregations with PIVOT
我在使用 PIVOT 功能时遇到了一些困难。我有来自 14 个不同的组装站的生产数据。我想按主组件对它们进行分组，并在 table 中显示每个子组件的状态。细目如下：
原始数据样本：
+-----------------------+------------------+-----------------+-------------+-----------+------------+-------------------------+-------------------------+-----------+
| ID | OrderID | ProductionOrder | Workstation | Status | Date | StartTime | EndTime | TotalTime |
+-----------------------+------------------+-----------------+-------------+-----------+------------+-------------------------+-------------------------+-----------+
| 60127429_1000_1_S120 | 60127429_1000_1 | 108100 | S120 | Completed | 05/12/2020 | 2020-05-12 12:44:00.000 | 2020-05-12 13:02:00.000 | 18 |
| 60127429_1000_1_S090 | 60127429_1000_1 | 108100 | S090 | Completed | 05/12/2020 | 2020-05-12 12:20:00.000 | 2020-05-12 12:44:00.000 | 24 |
| 60127429_1000_1_S080 | 60127429_1000_1 | 108100 | S080 | Completed | 05/12/2020 | 2020-05-12 10:40:00.000 | 2020-05-12 10:47:00.000 | 7 |
| 60127429_1000_1_S035 | 60127429_1000_1 | 108100 | S035 | Completed | 05/13/2020 | 2020-05-13 10:39:00.000 | 2020-05-13 12:40:00.000 | 121 |
| 60127527_2000_1_S120 | 60127527_2000_1 | 883331 | S120 | Completed | 05/12/2020 | 2020-05-12 12:09:00.000 | 2020-05-12 12:28:00.000 | 19 |
| 60127527_2000_1_S090 | 60127527_2000_1 | 883331 | S090 | Completed | 05/12/2020 | 2020-05-12 11:47:00.000 | 2020-05-12 12:06:00.000 | 19 |
| 60127527_2000_1_S080 | 60127527_2000_1 | 883331 | S080 | Completed | 05/12/2020 | 2020-05-12 10:31:00.000 | 2020-05-12 10:38:00.000 | 7 |
| 60127527_2000_1_S070 | 60127527_2000_1 | 883331 | S070 | Completed | 05/12/2020 | 2020-05-12 09:24:04.400 | 2020-05-12 09:24:00.000 | 0 |
| 60127527_5025_1_S020 | 60127527_5000_1 | 880051 | S020 | Completed | 05/12/2020 | 2020-05-12 07:14:04.550 | 2020-05-12 07:34:00.000 | 20 |
| 60127527_5000_1_S120 | 60127527_5000_1 | 880049 | S120 | Completed | 05/12/2020 | 2020-05-12 09:57:00.000 | 2020-05-12 10:17:00.000 | 20 |
| 60127527_5000_1_S090 | 60127527_5000_1 | 880049 | S090 | Completed | 05/12/2020 | 2020-05-12 09:38:00.000 | 2020-05-12 09:53:00.000 | 15 |
| 60127527_5000_1_S070 | 60127527_5000_1 | 880049 | S070 | Completed | 05/12/2020 | 2020-05-12 09:23:00.000 | 2020-05-12 10:25:00.000 | 62 |
| 60128137_11025_1_S020 | 60128137_11000_1 | 108338 | S020 | Completed | 05/14/2020 | 2020-05-14 10:04:09.877 | 2020-05-14 10:28:00.000 | 24 |
| 60128137_11025_1_S010 | 60128137_11000_1 | 108338 | S010 | Completed | 05/14/2020 | 2020-05-14 07:55:00.000 | 2020-05-14 08:48:00.000 | 53 |
| 60128137_11000_1_S120 | 60128137_11000_1 | 108333 | S120 | Completed | 05/18/2020 | 2020-05-18 08:24:00.000 | 2020-05-18 09:54:00.000 | 90 |
| 60128137_11000_1_S110 | 60128137_11000_1 | 108333 | S110 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_11000_1_S090 | 60128137_11000_1 | 108333 | S090 | Completed | 05/18/2020 | 2020-05-18 07:52:00.000 | 2020-05-18 08:11:00.000 | 19 |
| 60128137_11000_1_S080 | 60128137_11000_1 | 108333 | S080 | Completed | 05/18/2020 | 2020-05-18 07:21:00.000 | 2020-05-18 07:27:00.000 | 6 |
| 60128137_11000_1_S070 | 60128137_11000_1 | 108333 | S070 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_11000_1_S060 | 60128137_11000_1 | 108333 | S060 | Completed | 05/14/2020 | 2020-05-14 07:33:00.000 | 2020-05-14 08:03:00.000 | 30 |
| 60128137_11000_1_S050 | 60128137_11000_1 | 108333 | S050 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_11000_1_S040 | 60128137_11000_1 | 108333 | S040 | Completed | 05/13/2020 | 2020-05-13 10:34:00.000 | 2020-05-13 12:15:00.000 | 101 |
| 60128137_11000_1_S035 | 60128137_11000_1 | 108333 | S035 | Completed | 05/13/2020 | 2020-05-13 07:58:00.000 | 2020-05-13 08:29:00.000 | 31 |
| 60128137_11000_1_S030 | 60128137_11000_1 | 108333 | S030 | Completed | 05/13/2020 | 2020-05-13 09:46:00.000 | 2020-05-13 09:51:00.000 | 5 |
| 60128137_2025_1_S020 | 60128137_2000_1 | 108334 | S020 | Completed | 05/13/2020 | 2020-05-13 14:42:04.890 | 2020-05-13 15:06:00.000 | 24 |
| 60128137_2025_1_S010 | 60128137_2000_1 | 108334 | S010 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_2000_1_S120 | 60128137_2000_1 | 108329 | S120 | Completed | 05/14/2020 | 2020-05-14 13:13:00.000 | 2020-05-14 14:24:00.000 | 71 |
| 60128137_2000_1_S110 | 60128137_2000_1 | 108329 | S110 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_2000_1_S090 | 60128137_2000_1 | 108329 | S090 | Completed | 05/14/2020 | 2020-05-14 12:37:00.000 | 2020-05-14 13:04:00.000 | 27 |
| 60128137_2000_1_S080 | 60128137_2000_1 | 108329 | S080 | Completed | 05/14/2020 | 2020-05-14 12:03:00.000 | 2020-05-14 12:27:00.000 | 24 |
| 60128137_2000_1_S070 | 60128137_2000_1 | 108329 | S070 | Completed | 05/14/2020 | 2020-05-14 07:56:00.000 | 2020-05-14 12:09:00.000 | 253 |
| 60128137_2000_1_S060 | 60128137_2000_1 | 108329 | S060 | Completed | 05/13/2020 | 2020-05-13 12:38:00.000 | 2020-05-13 12:57:00.000 | 19 |
| 60128137_2000_1_S050 | 60128137_2000_1 | 108329 | S050 | Completed | 05/14/2020 | 2020-05-14 07:28:39.143 | 2020-05-14 07:30:00.000 | 2 |
| 60128137_2000_1_S040 | 60128137_2000_1 | 108329 | S040 | Completed | 05/13/2020 | 2020-05-13 08:26:00.000 | 2020-05-13 08:58:00.000 | 32 |
| 60128137_2000_1_S035 | 60128137_2000_1 | 108329 | S035 | Completed | 05/12/2020 | 2020-05-12 14:41:00.000 | 2020-05-12 15:02:00.000 | 21 |
| 60128137_2000_1_S030 | 60128137_2000_1 | 108329 | S030 | Completed | 05/13/2020 | 2020-05-13 07:47:00.000 | 2020-05-13 08:21:00.000 | 34 |
| 60128137_4000_1_S080 | 60128137_4000_1 | 108330 | S080 | Completed | 05/18/2020 | 2020-05-18 09:19:00.000 | 2020-05-18 09:29:00.000 | 10 |
| 60128137_4000_1_S070 | 60128137_4000_1 | 108330 | S070 | Completed | 05/18/2020 | 2020-05-18 07:10:00.000 | 2020-05-18 08:51:00.000 | 101 |
| 60128137_4000_1_S060 | 60128137_4000_1 | 108330 | S060 | Completed | 05/13/2020 | 2020-05-13 12:59:00.000 | 2020-05-13 13:17:00.000 | 18 |
| 60128137_4000_1_S050 | 60128137_4000_1 | 108330 | S050 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_4000_1_S040 | 60128137_4000_1 | 108330 | S040 | Completed | 05/13/2020 | 2020-05-13 09:57:00.000 | 2020-05-13 10:01:00.000 | 4 |
| 60128137_4000_1_S035 | 60128137_4000_1 | 108330 | S035 | Completed | 05/12/2020 | 2020-05-12 14:25:00.000 | 2020-05-12 15:14:00.000 | 49 |
+-----------------------+------------------+-----------------+-------------+-----------+------------+-------------------------+-------------------------+-----------+
我使用这段代码来透视数据：
SELECT *
FROM
(
SELECT master.[Customer],
master.[OrderID],
master.[SalesOrderNo],
master.[LineNo],
master.[OrderQty],
master.[Workstation],
master.[Status],
master.ShipDate
FROM
[dbo].[MES Master Data] as master
WHERE [ParentID] IN
(
SELECT TOP (20) [ParentID]
FROM [MES Master Data]
WHERE EndTime IS NOT NULL AND DATEDIFF(DAY, [EndTime], GETDATE()) < 2
Group By [ParentID]
ORDER BY MAX([Workstation]) DESC, MAX([EndTime]) DESC
)
) AS SourceTable PIVOT(MAX([Status]) FOR [Workstation] IN([S010],
[S020],
[S025],
[S030],
[S035],
[S040],
[S050],
[S060],
[S070],
[S080],
[S090],
[S100],
[S110],
[S120])) AS PivotTable
这个效果比较好。我认为我过滤 table 的逻辑可能会更好。我试图只获取最近两天处理过的订单，并且只查看那些至少有一个站点处于 started 或 completed 状态的订单。
这是我查看视图时数据的样子：
+------------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+----------+---------+-----------+
| OrderID | S010 | S020 | S025 | S030 | S035 | S040 | S050 | S060 | S070 | S080 | S090 | S100 | S110 | S120 |
+------------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+----------+---------+-----------+
| 60128569_5000_1 | Planned | Planned | Started | Completed | Completed | Completed | Planned | Completed | Planned | Inactive | Inactive | Inactive | Planned | Inactive |
| 60129128_2000_1 | Completed | Completed | NULL | Completed | Completed | Completed | Completed | Completed | Planned | Completed | Completed | NULL | Planned | Completed |
| 60129128_2000_2 | Completed | Completed | NULL | Completed | Completed | Completed | Planned | Completed | Completed | Completed | Completed | NULL | Planned | Completed |
| 60129438_2000_1 | Planned | Started | Completed | Completed | Completed | Completed | Completed | Completed | Planned | Completed | Completed | Inactive | Planned | Started |
| 60129438_2000_2 | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Planned | Started | Inactive | Planned | Inactive |
| 60129428_12000_1 | Planned | Completed | NULL | Completed | Completed | Completed | Completed | Completed | Planned | Completed | Completed | NULL | Planned | Completed |
| 60129428_13000_1 | Completed | Completed | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60129428_5000_1 | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60129428_8000_1 | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Started | Completed | Completed | Inactive | Planned | Started |
| 60128369_1000_1 | Planned | Completed | Completed | Planned | Planned | Completed | Completed | Completed | Planned | Completed | Completed | Planned | Planned | Completed |
| 60128369_1000_2 | Completed | Completed | Completed | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60128369_1000_3 | Inactive | Completed | Completed | Planned | Completed | Planned | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60128369_2000_1 | Planned | Completed | Completed | Completed | Completed | Completed | Planned | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60128137_11000_1 | Completed | Completed | NULL | Completed | Completed | Completed | Planned | Completed | Planned | Completed | Completed | NULL | Planned | Completed |
| 60128137_4000_1 | Planned | Completed | NULL | Completed | Completed | Completed | Planned | Completed | Completed | Completed | Completed | NULL | Planned | Completed |
| 60129588_1000_1 | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60128174_1000_1 | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60128174_2000_1 | Planned | Started | Completed | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60129024_28000_1 | Planned | Suspended | Completed | Completed | Completed | Completed | Started | Completed | Planned | Inactive | Inactive | Inactive | Planned | Inactive |
| 60129614_4000_1 | Planned | Completed | NULL | Completed | Completed | Completed | Started | Completed | Started | Inactive | Inactive | NULL | Planned | Inactive |
| 60129614_4000_2 | Completed | Completed | NULL | Completed | Completed | Completed | Started | Completed | Planned | Inactive | Inactive | NULL | Planned | Inactive |
| 60129614_4000_3 | Completed | Suspended | NULL | Completed | Completed | Completed | Started | Completed | Planned | Inactive | Inactive | NULL | Planned | Inactive |
| 60129614_4000_4 | Inactive | Suspended | NULL | Completed | Completed | Suspended | Inactive | Completed | Planned | Inactive | Inactive | NULL | Planned | Inactive |
| 60128601_1000_1 | Planned | Planned | Planned | Completed | Completed | Completed | Planned | Completed | Planned | Inactive | Inactive | Inactive | Planned | Inactive |
| 60128603_2000_1 | Planned | Planned | NULL | Completed | Planned | Completed | Planned | Completed | Planned | Inactive | Inactive | NULL | Planned | Inactive |
| 60128603_3000_1 | Planned | Planned | Planned | Completed | Planned | Completed | Planned | Planned | Inactive | Inactive | Inactive | Inactive | Planned | Inactive |
| 60128603_7000_1 | Inactive | Inactive | Inactive | Completed | Planned | Started | Inactive | Inactive | Inactive | Inactive | Inactive | Inactive | Planned | Inactive |
+------------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+----------+---------+-----------+
以下是我想改进的地方：
- 过滤原始
Master Data，只显示至少有一个站点状态为 started 或 completed 的全部订单。通过仅显示最近两天内具有 EndTime 的那些订单来进一步过滤。
- 添加另一个名为 "LastActiveStation" 的列，它将显示订单处理的最新站点。 （生产流程是线性的，从 S010 -> S120。）
- 添加另一个名为 "LastActiveTime" 的列，它将显示 "LastActiveStation"
中电台的最新 EndTime
我真的在为最后两颗子弹而苦苦挣扎。无论我做什么，我似乎都无法正确聚合。
提前感谢您阅读冗长的 post，如果有任何帮助，我将不胜感激。
诀窍是在透视后将额外的字段合并回去。我喜欢用 Common Table Expressions 将它们分开以使其更具可读性，请参见下面的示例。请注意，第一个（巨大的）cte 只是以可用的形式获取您的示例数据，真正的工作从 cteDateLimit 开始。您不想一遍又一遍地调用 GETDATE 和 DATEADD，定义一次限制并在后续 CTE 中使用它。
;with cteData as (
SELECT * FROM (VALUES ('60127429_1000_1_S120', '60127429_1000_1', '108100', 'S120', 'Completed', '05/12/2020', '2020-05-12 12:44:00.000', '2020-05-12 13:02:00.000', '18')
,('60127429_1000_1_S090', '60127429_1000_1', '108100', 'S090', 'Completed', '05/12/2020', '2020-05-12 12:20:00.000', '2020-05-12 12:44:00.000', '24')
,('60127429_1000_1_S080', '60127429_1000_1', '108100', 'S080', 'Completed', '05/12/2020', '2020-05-12 10:40:00.000', '2020-05-12 10:47:00.000', '7')
,('60127429_1000_1_S035', '60127429_1000_1', '108100', 'S035', 'Completed', '05/13/2020', '2020-05-13 10:39:00.000', '2020-05-13 12:40:00.000', '121')
,('60127527_2000_1_S120', '60127527_2000_1', '883331', 'S120', 'Completed', '05/12/2020', '2020-05-12 12:09:00.000', '2020-05-12 12:28:00.000', '19')
,('60127527_2000_1_S090', '60127527_2000_1', '883331', 'S090', 'Completed', '05/12/2020', '2020-05-12 11:47:00.000', '2020-05-12 12:06:00.000', '19')
,('60127527_2000_1_S080', '60127527_2000_1', '883331', 'S080', 'Completed', '05/12/2020', '2020-05-12 10:31:00.000', '2020-05-12 10:38:00.000', '7')
,('60127527_2000_1_S070', '60127527_2000_1', '883331', 'S070', 'Completed', '05/12/2020', '2020-05-12 09:24:04.400', '2020-05-12 09:24:00.000', '0')
,('60127527_5025_1_S020', '60127527_5000_1', '880051', 'S020', 'Completed', '05/12/2020', '2020-05-12 07:14:04.550', '2020-05-12 07:34:00.000', '20')
,('60127527_5000_1_S120', '60127527_5000_1', '880049', 'S120', 'Completed', '05/12/2020', '2020-05-12 09:57:00.000', '2020-05-12 10:17:00.000', '20')
,('60127527_5000_1_S090', '60127527_5000_1', '880049', 'S090', 'Completed', '05/12/2020', '2020-05-12 09:38:00.000', '2020-05-12 09:53:00.000', '15')
,('60127527_5000_1_S070', '60127527_5000_1', '880049', 'S070', 'Completed', '05/12/2020', '2020-05-12 09:23:00.000', '2020-05-12 10:25:00.000', '62')
,('60128137_11025_1_S020', '60128137_11000_1', '108338', 'S020', 'Completed', '05/14/2020', '2020-05-14 10:04:09.877', '2020-05-14 10:28:00.000', '24')
,('60128137_11025_1_S010', '60128137_11000_1', '108338', 'S010', 'Completed', '05/14/2020', '2020-05-14 07:55:00.000', '2020-05-14 08:48:00.000', '53')
,('60128137_11000_1_S120', '60128137_11000_1', '108333', 'S120', 'Completed', '05/18/2020', '2020-05-18 08:24:00.000', '2020-05-18 09:54:00.000', '90')
,('60128137_11000_1_S110', '60128137_11000_1', '108333', 'S110', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_11000_1_S090', '60128137_11000_1', '108333', 'S090', 'Completed', '05/18/2020', '2020-05-18 07:52:00.000', '2020-05-18 08:11:00.000', '19')
,('60128137_11000_1_S080', '60128137_11000_1', '108333', 'S080', 'Completed', '05/18/2020', '2020-05-18 07:21:00.000', '2020-05-18 07:27:00.000', '6')
,('60128137_11000_1_S070', '60128137_11000_1', '108333', 'S070', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_11000_1_S060', '60128137_11000_1', '108333', 'S060', 'Completed', '05/14/2020', '2020-05-14 07:33:00.000', '2020-05-14 08:03:00.000', '30')
,('60128137_11000_1_S050', '60128137_11000_1', '108333', 'S050', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_11000_1_S040', '60128137_11000_1', '108333', 'S040', 'Completed', '05/13/2020', '2020-05-13 10:34:00.000', '2020-05-13 12:15:00.000', '101')
,('60128137_11000_1_S035', '60128137_11000_1', '108333', 'S035', 'Completed', '05/13/2020', '2020-05-13 07:58:00.000', '2020-05-13 08:29:00.000', '31')
,('60128137_11000_1_S030', '60128137_11000_1', '108333', 'S030', 'Completed', '05/13/2020', '2020-05-13 09:46:00.000', '2020-05-13 09:51:00.000', '5')
,('60128137_2025_1_S020', '60128137_2000_1', '108334', 'S020', 'Completed', '05/13/2020', '2020-05-13 14:42:04.890', '2020-05-13 15:06:00.000', '24')
,('60128137_2025_1_S010', '60128137_2000_1', '108334', 'S010', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_2000_1_S120', '60128137_2000_1', '108329', 'S120', 'Completed', '05/14/2020', '2020-05-14 13:13:00.000', '2020-05-14 14:24:00.000', '71')
,('60128137_2000_1_S110', '60128137_2000_1', '108329', 'S110', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_2000_1_S090', '60128137_2000_1', '108329', 'S090', 'Completed', '05/14/2020', '2020-05-14 12:37:00.000', '2020-05-14 13:04:00.000', '27')
,('60128137_2000_1_S080', '60128137_2000_1', '108329', 'S080', 'Completed', '05/14/2020', '2020-05-14 12:03:00.000', '2020-05-14 12:27:00.000', '24')
,('60128137_2000_1_S070', '60128137_2000_1', '108329', 'S070', 'Completed', '05/14/2020', '2020-05-14 07:56:00.000', '2020-05-14 12:09:00.000', '253')
,('60128137_2000_1_S060', '60128137_2000_1', '108329', 'S060', 'Completed', '05/13/2020', '2020-05-13 12:38:00.000', '2020-05-13 12:57:00.000', '19')
,('60128137_2000_1_S050', '60128137_2000_1', '108329', 'S050', 'Completed', '05/14/2020', '2020-05-14 07:28:39.143', '2020-05-14 07:30:00.000', '2')
,('60128137_2000_1_S040', '60128137_2000_1', '108329', 'S040', 'Completed', '05/13/2020', '2020-05-13 08:26:00.000', '2020-05-13 08:58:00.000', '32')
,('60128137_2000_1_S035', '60128137_2000_1', '108329', 'S035', 'Completed', '05/12/2020', '2020-05-12 14:41:00.000', '2020-05-12 15:02:00.000', '21')
,('60128137_2000_1_S030', '60128137_2000_1', '108329', 'S030', 'Completed', '05/13/2020', '2020-05-13 07:47:00.000', '2020-05-13 08:21:00.000', '34')
,('60128137_4000_1_S080', '60128137_4000_1', '108330', 'S080', 'Completed', '05/18/2020', '2020-05-18 09:19:00.000', '2020-05-18 09:29:00.000', '10')
,('60128137_4000_1_S070', '60128137_4000_1', '108330', 'S070', 'Completed', '05/18/2020', '2020-05-18 07:10:00.000', '2020-05-18 08:51:00.000', '101')
,('60128137_4000_1_S060', '60128137_4000_1', '108330', 'S060', 'Completed', '05/13/2020', '2020-05-13 12:59:00.000', '2020-05-13 13:17:00.000', '18')
,('60128137_4000_1_S050', '60128137_4000_1', '108330', 'S050', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_4000_1_S040', '60128137_4000_1', '108330', 'S040', 'Completed', '05/13/2020', '2020-05-13 09:57:00.000', '2020-05-13 10:01:00.000', '4')
,('60128137_4000_1_S035', '60128137_4000_1', '108330', 'S035', 'Completed', '05/12/2020', '2020-05-12 14:25:00.000', '2020-05-12 15:14:00.000', '49')
) as DataIn(ID, OrderID, ProductionOrder, Workstation, WorkStatus, ProcDate, StartTime, EndTime, TotalTime)
),cteDateLimit as ( SELECT DATEADD(DAY, -6, GETDATE()) as DayLimit
), cteFiltOrder as (
SELECT DISTINCT OrderID FROM cteData as D CROSS JOIN cteDateLimit as L
WHERE D.EndTime >= L.DayLimit
AND EXISTS (SELECT * FROM cteData as D2 WHERE D.OrderID = D2.OrderID
AND D2.WorkStatus IN ('Completed', 'Started'))
--NOTE: Your spec as written passes a part with a new EndTime and an older WorkStatus,
--If you want to require the COMPLETED or STARTED to be in the time limit also
-- then replace the whole EXISTS clause with D.WorkStatus IN ('Completed', 'Started')
), cteLastOp as (--Figure out the last operation you did on the part
SELECT D.ID as LastID , D.OrderID as LastOrdID
, ROW_NUMBER () OVER (PARTITION BY D.OrderID ORDER BY ENDTIME DESC) as RowNewness
FROM cteData as D INNER JOIN cteFiltOrder as F on F.OrderID = D.OrderID
), cteExtra as (--Capture details of the last operation to merge back in after pivot
SELECT D.OrderID, D.Workstation as LastActiveStation
, D.EndTime as LastActiveTime
FROM cteData as D INNER JOIN cteLastOp as L on L.LastID = D.ID
WHERE L.RowNewness = 1
), cteFiltered as ( --Get all operations on the Order
SELECT D.*
FROM cteData as D INNER JOIN cteLastOp as L ON L.LastOrdID = D.OrderID
WHERE L.RowNewness = 1
), ctePivot as ( --generate teh pivot, it can only handle 1 non-pivot field
SELECT * FROM (SELECT OrderID, Workstation, WorkStatus FROM cteFiltered) as SourceTable
PIVOT (MAX(WorkStatus) FOR Workstation IN ([S010],[S020]
,[S025],[S030],[S035],[S040],[S050],[S060],[S070]
,[S080],[S090],[S100],[S110],[S120])) AS PivotTable
)SELECT E.LastActiveStation , E.LastActiveTime , P.*
FROM ctePivot as P INNER JOIN cteExtra as E on P.OrderID = E.OrderID
基本流程是首先定义您的日期限制，然后使用它来获取至少有一个操作处于已完成或已启动状态并且在过去 2 天内有一些步骤结束的 OrderID 列表。请注意，我在这里使用了 6 天，因为我得到的时间太少，只需将 -6 更改为 -2 或其他任何内容即可。
下一步是找到每个 OrderID 的最后一个操作，我使用 ROW_NUMBER ordered on EndTime descending 来标识最后一个，如果你只想添加一个排除，例如，排除"Planned" 考虑运营。
您还可以插入更多 CTE，以生成有关 OrderID 的额外信息，例如花费的总时间。当你在 cteExtra 中合并时，只需添加一个新的 CTE 并在最后合并它。
接下来，我将符合日期选择标准的 OrderID 列表加入到整个数据集，因此我只处理将出现在输出中的行，我将其称为 cteFiltered
下一步 PIVOT 并将 OrderID 和旋转的工作站存储在 ctePivot
最后一步是将我们在 cteExtra 中捕获的有关 orderID 的额外信息合并回 Pivot 以获得完整输出。
我在使用 PIVOT 功能时遇到了一些困难。我有来自 14 个不同的组装站的生产数据。我想按主组件对它们进行分组，并在 table 中显示每个子组件的状态。细目如下：
原始数据样本：
+-----------------------+------------------+-----------------+-------------+-----------+------------+-------------------------+-------------------------+-----------+
| ID | OrderID | ProductionOrder | Workstation | Status | Date | StartTime | EndTime | TotalTime |
+-----------------------+------------------+-----------------+-------------+-----------+------------+-------------------------+-------------------------+-----------+
| 60127429_1000_1_S120 | 60127429_1000_1 | 108100 | S120 | Completed | 05/12/2020 | 2020-05-12 12:44:00.000 | 2020-05-12 13:02:00.000 | 18 |
| 60127429_1000_1_S090 | 60127429_1000_1 | 108100 | S090 | Completed | 05/12/2020 | 2020-05-12 12:20:00.000 | 2020-05-12 12:44:00.000 | 24 |
| 60127429_1000_1_S080 | 60127429_1000_1 | 108100 | S080 | Completed | 05/12/2020 | 2020-05-12 10:40:00.000 | 2020-05-12 10:47:00.000 | 7 |
| 60127429_1000_1_S035 | 60127429_1000_1 | 108100 | S035 | Completed | 05/13/2020 | 2020-05-13 10:39:00.000 | 2020-05-13 12:40:00.000 | 121 |
| 60127527_2000_1_S120 | 60127527_2000_1 | 883331 | S120 | Completed | 05/12/2020 | 2020-05-12 12:09:00.000 | 2020-05-12 12:28:00.000 | 19 |
| 60127527_2000_1_S090 | 60127527_2000_1 | 883331 | S090 | Completed | 05/12/2020 | 2020-05-12 11:47:00.000 | 2020-05-12 12:06:00.000 | 19 |
| 60127527_2000_1_S080 | 60127527_2000_1 | 883331 | S080 | Completed | 05/12/2020 | 2020-05-12 10:31:00.000 | 2020-05-12 10:38:00.000 | 7 |
| 60127527_2000_1_S070 | 60127527_2000_1 | 883331 | S070 | Completed | 05/12/2020 | 2020-05-12 09:24:04.400 | 2020-05-12 09:24:00.000 | 0 |
| 60127527_5025_1_S020 | 60127527_5000_1 | 880051 | S020 | Completed | 05/12/2020 | 2020-05-12 07:14:04.550 | 2020-05-12 07:34:00.000 | 20 |
| 60127527_5000_1_S120 | 60127527_5000_1 | 880049 | S120 | Completed | 05/12/2020 | 2020-05-12 09:57:00.000 | 2020-05-12 10:17:00.000 | 20 |
| 60127527_5000_1_S090 | 60127527_5000_1 | 880049 | S090 | Completed | 05/12/2020 | 2020-05-12 09:38:00.000 | 2020-05-12 09:53:00.000 | 15 |
| 60127527_5000_1_S070 | 60127527_5000_1 | 880049 | S070 | Completed | 05/12/2020 | 2020-05-12 09:23:00.000 | 2020-05-12 10:25:00.000 | 62 |
| 60128137_11025_1_S020 | 60128137_11000_1 | 108338 | S020 | Completed | 05/14/2020 | 2020-05-14 10:04:09.877 | 2020-05-14 10:28:00.000 | 24 |
| 60128137_11025_1_S010 | 60128137_11000_1 | 108338 | S010 | Completed | 05/14/2020 | 2020-05-14 07:55:00.000 | 2020-05-14 08:48:00.000 | 53 |
| 60128137_11000_1_S120 | 60128137_11000_1 | 108333 | S120 | Completed | 05/18/2020 | 2020-05-18 08:24:00.000 | 2020-05-18 09:54:00.000 | 90 |
| 60128137_11000_1_S110 | 60128137_11000_1 | 108333 | S110 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_11000_1_S090 | 60128137_11000_1 | 108333 | S090 | Completed | 05/18/2020 | 2020-05-18 07:52:00.000 | 2020-05-18 08:11:00.000 | 19 |
| 60128137_11000_1_S080 | 60128137_11000_1 | 108333 | S080 | Completed | 05/18/2020 | 2020-05-18 07:21:00.000 | 2020-05-18 07:27:00.000 | 6 |
| 60128137_11000_1_S070 | 60128137_11000_1 | 108333 | S070 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_11000_1_S060 | 60128137_11000_1 | 108333 | S060 | Completed | 05/14/2020 | 2020-05-14 07:33:00.000 | 2020-05-14 08:03:00.000 | 30 |
| 60128137_11000_1_S050 | 60128137_11000_1 | 108333 | S050 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_11000_1_S040 | 60128137_11000_1 | 108333 | S040 | Completed | 05/13/2020 | 2020-05-13 10:34:00.000 | 2020-05-13 12:15:00.000 | 101 |
| 60128137_11000_1_S035 | 60128137_11000_1 | 108333 | S035 | Completed | 05/13/2020 | 2020-05-13 07:58:00.000 | 2020-05-13 08:29:00.000 | 31 |
| 60128137_11000_1_S030 | 60128137_11000_1 | 108333 | S030 | Completed | 05/13/2020 | 2020-05-13 09:46:00.000 | 2020-05-13 09:51:00.000 | 5 |
| 60128137_2025_1_S020 | 60128137_2000_1 | 108334 | S020 | Completed | 05/13/2020 | 2020-05-13 14:42:04.890 | 2020-05-13 15:06:00.000 | 24 |
| 60128137_2025_1_S010 | 60128137_2000_1 | 108334 | S010 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_2000_1_S120 | 60128137_2000_1 | 108329 | S120 | Completed | 05/14/2020 | 2020-05-14 13:13:00.000 | 2020-05-14 14:24:00.000 | 71 |
| 60128137_2000_1_S110 | 60128137_2000_1 | 108329 | S110 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_2000_1_S090 | 60128137_2000_1 | 108329 | S090 | Completed | 05/14/2020 | 2020-05-14 12:37:00.000 | 2020-05-14 13:04:00.000 | 27 |
| 60128137_2000_1_S080 | 60128137_2000_1 | 108329 | S080 | Completed | 05/14/2020 | 2020-05-14 12:03:00.000 | 2020-05-14 12:27:00.000 | 24 |
| 60128137_2000_1_S070 | 60128137_2000_1 | 108329 | S070 | Completed | 05/14/2020 | 2020-05-14 07:56:00.000 | 2020-05-14 12:09:00.000 | 253 |
| 60128137_2000_1_S060 | 60128137_2000_1 | 108329 | S060 | Completed | 05/13/2020 | 2020-05-13 12:38:00.000 | 2020-05-13 12:57:00.000 | 19 |
| 60128137_2000_1_S050 | 60128137_2000_1 | 108329 | S050 | Completed | 05/14/2020 | 2020-05-14 07:28:39.143 | 2020-05-14 07:30:00.000 | 2 |
| 60128137_2000_1_S040 | 60128137_2000_1 | 108329 | S040 | Completed | 05/13/2020 | 2020-05-13 08:26:00.000 | 2020-05-13 08:58:00.000 | 32 |
| 60128137_2000_1_S035 | 60128137_2000_1 | 108329 | S035 | Completed | 05/12/2020 | 2020-05-12 14:41:00.000 | 2020-05-12 15:02:00.000 | 21 |
| 60128137_2000_1_S030 | 60128137_2000_1 | 108329 | S030 | Completed | 05/13/2020 | 2020-05-13 07:47:00.000 | 2020-05-13 08:21:00.000 | 34 |
| 60128137_4000_1_S080 | 60128137_4000_1 | 108330 | S080 | Completed | 05/18/2020 | 2020-05-18 09:19:00.000 | 2020-05-18 09:29:00.000 | 10 |
| 60128137_4000_1_S070 | 60128137_4000_1 | 108330 | S070 | Completed | 05/18/2020 | 2020-05-18 07:10:00.000 | 2020-05-18 08:51:00.000 | 101 |
| 60128137_4000_1_S060 | 60128137_4000_1 | 108330 | S060 | Completed | 05/13/2020 | 2020-05-13 12:59:00.000 | 2020-05-13 13:17:00.000 | 18 |
| 60128137_4000_1_S050 | 60128137_4000_1 | 108330 | S050 | Planned | 05/19/2020 | NULL | NULL | NULL |
| 60128137_4000_1_S040 | 60128137_4000_1 | 108330 | S040 | Completed | 05/13/2020 | 2020-05-13 09:57:00.000 | 2020-05-13 10:01:00.000 | 4 |
| 60128137_4000_1_S035 | 60128137_4000_1 | 108330 | S035 | Completed | 05/12/2020 | 2020-05-12 14:25:00.000 | 2020-05-12 15:14:00.000 | 49 |
+-----------------------+------------------+-----------------+-------------+-----------+------------+-------------------------+-------------------------+-----------+
我使用这段代码来透视数据：
SELECT *
FROM
(
SELECT master.[Customer],
master.[OrderID],
master.[SalesOrderNo],
master.[LineNo],
master.[OrderQty],
master.[Workstation],
master.[Status],
master.ShipDate
FROM
[dbo].[MES Master Data] as master
WHERE [ParentID] IN
(
SELECT TOP (20) [ParentID]
FROM [MES Master Data]
WHERE EndTime IS NOT NULL AND DATEDIFF(DAY, [EndTime], GETDATE()) < 2
Group By [ParentID]
ORDER BY MAX([Workstation]) DESC, MAX([EndTime]) DESC
)
) AS SourceTable PIVOT(MAX([Status]) FOR [Workstation] IN([S010],
[S020],
[S025],
[S030],
[S035],
[S040],
[S050],
[S060],
[S070],
[S080],
[S090],
[S100],
[S110],
[S120])) AS PivotTable
这个效果比较好。我认为我过滤 table 的逻辑可能会更好。我试图只获取最近两天处理过的订单，并且只查看那些至少有一个站点处于 started 或 completed 状态的订单。
这是我查看视图时数据的样子：
+------------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+----------+---------+-----------+
| OrderID | S010 | S020 | S025 | S030 | S035 | S040 | S050 | S060 | S070 | S080 | S090 | S100 | S110 | S120 |
+------------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+----------+---------+-----------+
| 60128569_5000_1 | Planned | Planned | Started | Completed | Completed | Completed | Planned | Completed | Planned | Inactive | Inactive | Inactive | Planned | Inactive |
| 60129128_2000_1 | Completed | Completed | NULL | Completed | Completed | Completed | Completed | Completed | Planned | Completed | Completed | NULL | Planned | Completed |
| 60129128_2000_2 | Completed | Completed | NULL | Completed | Completed | Completed | Planned | Completed | Completed | Completed | Completed | NULL | Planned | Completed |
| 60129438_2000_1 | Planned | Started | Completed | Completed | Completed | Completed | Completed | Completed | Planned | Completed | Completed | Inactive | Planned | Started |
| 60129438_2000_2 | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Planned | Started | Inactive | Planned | Inactive |
| 60129428_12000_1 | Planned | Completed | NULL | Completed | Completed | Completed | Completed | Completed | Planned | Completed | Completed | NULL | Planned | Completed |
| 60129428_13000_1 | Completed | Completed | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60129428_5000_1 | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60129428_8000_1 | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Started | Completed | Completed | Inactive | Planned | Started |
| 60128369_1000_1 | Planned | Completed | Completed | Planned | Planned | Completed | Completed | Completed | Planned | Completed | Completed | Planned | Planned | Completed |
| 60128369_1000_2 | Completed | Completed | Completed | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60128369_1000_3 | Inactive | Completed | Completed | Planned | Completed | Planned | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60128369_2000_1 | Planned | Completed | Completed | Completed | Completed | Completed | Planned | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60128137_11000_1 | Completed | Completed | NULL | Completed | Completed | Completed | Planned | Completed | Planned | Completed | Completed | NULL | Planned | Completed |
| 60128137_4000_1 | Planned | Completed | NULL | Completed | Completed | Completed | Planned | Completed | Completed | Completed | Completed | NULL | Planned | Completed |
| 60129588_1000_1 | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60128174_1000_1 | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60128174_2000_1 | Planned | Started | Completed | Planned | Completed | Completed | Completed | Completed | Completed | Completed | Completed | Inactive | Planned | Completed |
| 60129024_28000_1 | Planned | Suspended | Completed | Completed | Completed | Completed | Started | Completed | Planned | Inactive | Inactive | Inactive | Planned | Inactive |
| 60129614_4000_1 | Planned | Completed | NULL | Completed | Completed | Completed | Started | Completed | Started | Inactive | Inactive | NULL | Planned | Inactive |
| 60129614_4000_2 | Completed | Completed | NULL | Completed | Completed | Completed | Started | Completed | Planned | Inactive | Inactive | NULL | Planned | Inactive |
| 60129614_4000_3 | Completed | Suspended | NULL | Completed | Completed | Completed | Started | Completed | Planned | Inactive | Inactive | NULL | Planned | Inactive |
| 60129614_4000_4 | Inactive | Suspended | NULL | Completed | Completed | Suspended | Inactive | Completed | Planned | Inactive | Inactive | NULL | Planned | Inactive |
| 60128601_1000_1 | Planned | Planned | Planned | Completed | Completed | Completed | Planned | Completed | Planned | Inactive | Inactive | Inactive | Planned | Inactive |
| 60128603_2000_1 | Planned | Planned | NULL | Completed | Planned | Completed | Planned | Completed | Planned | Inactive | Inactive | NULL | Planned | Inactive |
| 60128603_3000_1 | Planned | Planned | Planned | Completed | Planned | Completed | Planned | Planned | Inactive | Inactive | Inactive | Inactive | Planned | Inactive |
| 60128603_7000_1 | Inactive | Inactive | Inactive | Completed | Planned | Started | Inactive | Inactive | Inactive | Inactive | Inactive | Inactive | Planned | Inactive |
+------------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+----------+---------+-----------+
以下是我想改进的地方：
- 过滤原始
Master Data，只显示至少有一个站点状态为started或completed的全部订单。通过仅显示最近两天内具有EndTime的那些订单来进一步过滤。 - 添加另一个名为 "LastActiveStation" 的列，它将显示订单处理的最新站点。 （生产流程是线性的，从 S010 -> S120。）
- 添加另一个名为 "LastActiveTime" 的列，它将显示 "LastActiveStation" 中电台的最新
EndTime
我真的在为最后两颗子弹而苦苦挣扎。无论我做什么，我似乎都无法正确聚合。
提前感谢您阅读冗长的 post，如果有任何帮助，我将不胜感激。
诀窍是在透视后将额外的字段合并回去。我喜欢用 Common Table Expressions 将它们分开以使其更具可读性，请参见下面的示例。请注意，第一个（巨大的）cte 只是以可用的形式获取您的示例数据，真正的工作从 cteDateLimit 开始。您不想一遍又一遍地调用 GETDATE 和 DATEADD，定义一次限制并在后续 CTE 中使用它。
;with cteData as (
SELECT * FROM (VALUES ('60127429_1000_1_S120', '60127429_1000_1', '108100', 'S120', 'Completed', '05/12/2020', '2020-05-12 12:44:00.000', '2020-05-12 13:02:00.000', '18')
,('60127429_1000_1_S090', '60127429_1000_1', '108100', 'S090', 'Completed', '05/12/2020', '2020-05-12 12:20:00.000', '2020-05-12 12:44:00.000', '24')
,('60127429_1000_1_S080', '60127429_1000_1', '108100', 'S080', 'Completed', '05/12/2020', '2020-05-12 10:40:00.000', '2020-05-12 10:47:00.000', '7')
,('60127429_1000_1_S035', '60127429_1000_1', '108100', 'S035', 'Completed', '05/13/2020', '2020-05-13 10:39:00.000', '2020-05-13 12:40:00.000', '121')
,('60127527_2000_1_S120', '60127527_2000_1', '883331', 'S120', 'Completed', '05/12/2020', '2020-05-12 12:09:00.000', '2020-05-12 12:28:00.000', '19')
,('60127527_2000_1_S090', '60127527_2000_1', '883331', 'S090', 'Completed', '05/12/2020', '2020-05-12 11:47:00.000', '2020-05-12 12:06:00.000', '19')
,('60127527_2000_1_S080', '60127527_2000_1', '883331', 'S080', 'Completed', '05/12/2020', '2020-05-12 10:31:00.000', '2020-05-12 10:38:00.000', '7')
,('60127527_2000_1_S070', '60127527_2000_1', '883331', 'S070', 'Completed', '05/12/2020', '2020-05-12 09:24:04.400', '2020-05-12 09:24:00.000', '0')
,('60127527_5025_1_S020', '60127527_5000_1', '880051', 'S020', 'Completed', '05/12/2020', '2020-05-12 07:14:04.550', '2020-05-12 07:34:00.000', '20')
,('60127527_5000_1_S120', '60127527_5000_1', '880049', 'S120', 'Completed', '05/12/2020', '2020-05-12 09:57:00.000', '2020-05-12 10:17:00.000', '20')
,('60127527_5000_1_S090', '60127527_5000_1', '880049', 'S090', 'Completed', '05/12/2020', '2020-05-12 09:38:00.000', '2020-05-12 09:53:00.000', '15')
,('60127527_5000_1_S070', '60127527_5000_1', '880049', 'S070', 'Completed', '05/12/2020', '2020-05-12 09:23:00.000', '2020-05-12 10:25:00.000', '62')
,('60128137_11025_1_S020', '60128137_11000_1', '108338', 'S020', 'Completed', '05/14/2020', '2020-05-14 10:04:09.877', '2020-05-14 10:28:00.000', '24')
,('60128137_11025_1_S010', '60128137_11000_1', '108338', 'S010', 'Completed', '05/14/2020', '2020-05-14 07:55:00.000', '2020-05-14 08:48:00.000', '53')
,('60128137_11000_1_S120', '60128137_11000_1', '108333', 'S120', 'Completed', '05/18/2020', '2020-05-18 08:24:00.000', '2020-05-18 09:54:00.000', '90')
,('60128137_11000_1_S110', '60128137_11000_1', '108333', 'S110', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_11000_1_S090', '60128137_11000_1', '108333', 'S090', 'Completed', '05/18/2020', '2020-05-18 07:52:00.000', '2020-05-18 08:11:00.000', '19')
,('60128137_11000_1_S080', '60128137_11000_1', '108333', 'S080', 'Completed', '05/18/2020', '2020-05-18 07:21:00.000', '2020-05-18 07:27:00.000', '6')
,('60128137_11000_1_S070', '60128137_11000_1', '108333', 'S070', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_11000_1_S060', '60128137_11000_1', '108333', 'S060', 'Completed', '05/14/2020', '2020-05-14 07:33:00.000', '2020-05-14 08:03:00.000', '30')
,('60128137_11000_1_S050', '60128137_11000_1', '108333', 'S050', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_11000_1_S040', '60128137_11000_1', '108333', 'S040', 'Completed', '05/13/2020', '2020-05-13 10:34:00.000', '2020-05-13 12:15:00.000', '101')
,('60128137_11000_1_S035', '60128137_11000_1', '108333', 'S035', 'Completed', '05/13/2020', '2020-05-13 07:58:00.000', '2020-05-13 08:29:00.000', '31')
,('60128137_11000_1_S030', '60128137_11000_1', '108333', 'S030', 'Completed', '05/13/2020', '2020-05-13 09:46:00.000', '2020-05-13 09:51:00.000', '5')
,('60128137_2025_1_S020', '60128137_2000_1', '108334', 'S020', 'Completed', '05/13/2020', '2020-05-13 14:42:04.890', '2020-05-13 15:06:00.000', '24')
,('60128137_2025_1_S010', '60128137_2000_1', '108334', 'S010', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_2000_1_S120', '60128137_2000_1', '108329', 'S120', 'Completed', '05/14/2020', '2020-05-14 13:13:00.000', '2020-05-14 14:24:00.000', '71')
,('60128137_2000_1_S110', '60128137_2000_1', '108329', 'S110', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_2000_1_S090', '60128137_2000_1', '108329', 'S090', 'Completed', '05/14/2020', '2020-05-14 12:37:00.000', '2020-05-14 13:04:00.000', '27')
,('60128137_2000_1_S080', '60128137_2000_1', '108329', 'S080', 'Completed', '05/14/2020', '2020-05-14 12:03:00.000', '2020-05-14 12:27:00.000', '24')
,('60128137_2000_1_S070', '60128137_2000_1', '108329', 'S070', 'Completed', '05/14/2020', '2020-05-14 07:56:00.000', '2020-05-14 12:09:00.000', '253')
,('60128137_2000_1_S060', '60128137_2000_1', '108329', 'S060', 'Completed', '05/13/2020', '2020-05-13 12:38:00.000', '2020-05-13 12:57:00.000', '19')
,('60128137_2000_1_S050', '60128137_2000_1', '108329', 'S050', 'Completed', '05/14/2020', '2020-05-14 07:28:39.143', '2020-05-14 07:30:00.000', '2')
,('60128137_2000_1_S040', '60128137_2000_1', '108329', 'S040', 'Completed', '05/13/2020', '2020-05-13 08:26:00.000', '2020-05-13 08:58:00.000', '32')
,('60128137_2000_1_S035', '60128137_2000_1', '108329', 'S035', 'Completed', '05/12/2020', '2020-05-12 14:41:00.000', '2020-05-12 15:02:00.000', '21')
,('60128137_2000_1_S030', '60128137_2000_1', '108329', 'S030', 'Completed', '05/13/2020', '2020-05-13 07:47:00.000', '2020-05-13 08:21:00.000', '34')
,('60128137_4000_1_S080', '60128137_4000_1', '108330', 'S080', 'Completed', '05/18/2020', '2020-05-18 09:19:00.000', '2020-05-18 09:29:00.000', '10')
,('60128137_4000_1_S070', '60128137_4000_1', '108330', 'S070', 'Completed', '05/18/2020', '2020-05-18 07:10:00.000', '2020-05-18 08:51:00.000', '101')
,('60128137_4000_1_S060', '60128137_4000_1', '108330', 'S060', 'Completed', '05/13/2020', '2020-05-13 12:59:00.000', '2020-05-13 13:17:00.000', '18')
,('60128137_4000_1_S050', '60128137_4000_1', '108330', 'S050', 'Planned', '05/19/2020', NULL, NULL, NULL)
,('60128137_4000_1_S040', '60128137_4000_1', '108330', 'S040', 'Completed', '05/13/2020', '2020-05-13 09:57:00.000', '2020-05-13 10:01:00.000', '4')
,('60128137_4000_1_S035', '60128137_4000_1', '108330', 'S035', 'Completed', '05/12/2020', '2020-05-12 14:25:00.000', '2020-05-12 15:14:00.000', '49')
) as DataIn(ID, OrderID, ProductionOrder, Workstation, WorkStatus, ProcDate, StartTime, EndTime, TotalTime)
),cteDateLimit as ( SELECT DATEADD(DAY, -6, GETDATE()) as DayLimit
), cteFiltOrder as (
SELECT DISTINCT OrderID FROM cteData as D CROSS JOIN cteDateLimit as L
WHERE D.EndTime >= L.DayLimit
AND EXISTS (SELECT * FROM cteData as D2 WHERE D.OrderID = D2.OrderID
AND D2.WorkStatus IN ('Completed', 'Started'))
--NOTE: Your spec as written passes a part with a new EndTime and an older WorkStatus,
--If you want to require the COMPLETED or STARTED to be in the time limit also
-- then replace the whole EXISTS clause with D.WorkStatus IN ('Completed', 'Started')
), cteLastOp as (--Figure out the last operation you did on the part
SELECT D.ID as LastID , D.OrderID as LastOrdID
, ROW_NUMBER () OVER (PARTITION BY D.OrderID ORDER BY ENDTIME DESC) as RowNewness
FROM cteData as D INNER JOIN cteFiltOrder as F on F.OrderID = D.OrderID
), cteExtra as (--Capture details of the last operation to merge back in after pivot
SELECT D.OrderID, D.Workstation as LastActiveStation
, D.EndTime as LastActiveTime
FROM cteData as D INNER JOIN cteLastOp as L on L.LastID = D.ID
WHERE L.RowNewness = 1
), cteFiltered as ( --Get all operations on the Order
SELECT D.*
FROM cteData as D INNER JOIN cteLastOp as L ON L.LastOrdID = D.OrderID
WHERE L.RowNewness = 1
), ctePivot as ( --generate teh pivot, it can only handle 1 non-pivot field
SELECT * FROM (SELECT OrderID, Workstation, WorkStatus FROM cteFiltered) as SourceTable
PIVOT (MAX(WorkStatus) FOR Workstation IN ([S010],[S020]
,[S025],[S030],[S035],[S040],[S050],[S060],[S070]
,[S080],[S090],[S100],[S110],[S120])) AS PivotTable
)SELECT E.LastActiveStation , E.LastActiveTime , P.*
FROM ctePivot as P INNER JOIN cteExtra as E on P.OrderID = E.OrderID
基本流程是首先定义您的日期限制，然后使用它来获取至少有一个操作处于已完成或已启动状态并且在过去 2 天内有一些步骤结束的 OrderID 列表。请注意，我在这里使用了 6 天，因为我得到的时间太少，只需将 -6 更改为 -2 或其他任何内容即可。
下一步是找到每个 OrderID 的最后一个操作，我使用 ROW_NUMBER ordered on EndTime descending 来标识最后一个，如果你只想添加一个排除，例如，排除"Planned" 考虑运营。
您还可以插入更多 CTE，以生成有关 OrderID 的额外信息，例如花费的总时间。当你在 cteExtra 中合并时，只需添加一个新的 CTE 并在最后合并它。
接下来，我将符合日期选择标准的 OrderID 列表加入到整个数据集，因此我只处理将出现在输出中的行，我将其称为 cteFiltered
下一步 PIVOT 并将 OrderID 和旋转的工作站存储在 ctePivot
最后一步是将我们在 cteExtra 中捕获的有关 orderID 的额外信息合并回 Pivot 以获得完整输出。