我想按Name，Year/Month和Total进行细分。到目前为止，我该怎么做？
我的数据如下：
| name | ArtifactID | Name | DateCollected | FileSizeInBytes | WorkspaceArtifactId | TimestampOfLatestRecord |
+---------+------------+---------------------------+-------------------------+-----------------+---------------------+-------------------------+
| Pony | 1265555 | LiteDataPublishedToReview | 2018-12-21 00:00:00.000 | 5474.00 | 2534710 | 2018-12-21 09:26:49.000 |
| Wheels | 1265566 | LiteDataPublishedToReview | 2019-02-26 00:00:00.000 | 50668.00 | 2634282 | 2019-02-26 17:38:39.000 |
| Wheels | 1265567 | LiteDataPublishedToReview | 2019-01-11 00:00:00.000 | 10921638320.00 | 2634282 | 2019-01-11 16:44:04.000 |
| Wheels | 1265568 | LiteDataPublishedToReview | 2019-01-15 00:00:00.000 | 110261521.00 | 2634282 | 2019-01-15 17:43:57.000 |
| Wheels | 1265569 | LiteDataProcessed | 2018-12-13 00:00:00.000 | 123187605031.00 | 2634282 | 2018-12-13 21:50:34.000 |
| Wheels | 1265570 | FullDataProcessed | 2018-12-13 00:00:00.000 | 6810556609.00 | 2634282 | 2018-12-13 21:50:34.000 |
| Wheels | 1265571 | LiteDataProcessed | 2018-12-15 00:00:00.000 | 0.00 | 2634282 | 2018-12-15 14:52:20.000 |
| Wheels | 1265572 | FullDataProcessed | 2018-12-15 00:00:00.000 | 13362690.00 | 2634282 | 2018-12-15 14:52:20.000 |
| Wheels | 1265573 | LiteDataProcessed | 2019-01-09 00:00:00.000 | 1480303616.00 | 2634282 | 2019-01-09 13:52:23.000 |
| Wheels | 1265574 | FullDataProcessed | 2019-01-09 00:00:00.000 | 0.00 | 2634282 | 2019-01-09 13:52:23.000 |
| Wheels | 1265575 | LiteDataProcessed | 2019-02-25 00:00:00.000 | 0.00 | 2634282 | 2019-02-25 10:49:41.000 |
| Wheels | 1265576 | FullDataProcessed | 2019-02-25 00:00:00.000 | 7633201.00 | 2634282 | 2019-02-25 10:49:41.000 |
| Levack | 1265577 | LiteDataProcessed | 2018-12-16 00:00:00.000 | 0.00 | 2636230 | 2018-12-16 10:13:36.000 |
| Levack | 1265578 | FullDataProcessed | 2018-12-16 00:00:00.000 | 59202559.00 | 2636230 | 2018-12-16 10:13:36.000 |
| Van | 1265579 | LiteDataPublishedToReview | 2019-01-11 00:00:00.000 | 2646602711.00 | 2636845 | 2019-01-11 09:50:49.000 |
| Van | 1265580 | LiteDataPublishedToReview | 2019-01-10 00:00:00.000 | 10081222022.00 | 2636845 | 2019-01-10 18:32:03.000 |
| Van | 1265581 | LiteDataPublishedToReview | 2019-01-15 00:00:00.000 | 3009227476.00 | 2636845 | 2019-01-15 10:49:38.000 |
| Van | 1265582 | LiteDataPublishedToReview | 2019-03-26 00:00:00.000 | 87220831.00 | 2636845 | 2019-03-26 10:34:10.000 |
| Van | 1265583 | LiteDataPublishedToReview | 2019-03-28 00:00:00.000 | 688708119.00 | 2636845 | 2019-03-28 14:11:38.000 |
| Van | 1265584 | LiteDataProcessed | 2018-12-18 00:00:00.000 | 5408886887.00 | 2636845 | 2018-12-18 11:29:03.000 |
| Van | 1265585 | FullDataProcessed | 2018-12-18 00:00:00.000 | 0.00 | 2636845 | 2018-12-18 11:29:03.000 |
| Van | 1265586 | LiteDataProcessed | 2018-12-19 00:00:00.000 | 12535359488.00 | 2636845 | 2018-12-19 17:25:10.000 |
| Van | 1265587 | FullDataProcessed | 2018-12-19 00:00:00.000 | 0.00 | 2636845 | 2018-12-19 17:25:10.000 |
| Van | 1265588 | LiteDataProcessed | 2018-12-21 00:00:00.000 | 52599693312.00 | 2636845 | 2018-12-21 09:09:18.000 |
| Van | 1265589 | FullDataProcessed | 2018-12-21 00:00:00.000 | 0.00 | 2636845 | 2018-12-21 09:09:18.000 |
| Van | 1265590 | LiteDataProcessed | 2019-03-25 00:00:00.000 | 3588613120.00 | 2636845 | 2019-03-25 16:41:17.000 |
| Van | 1265591 | FullDataProcessed | 2019-03-25 00:00:00.000 | 0.00 | 2636845 | 2019-03-25 16:41:17.000 |
| Holiday | 1265592 | LiteDataProcessed | 2018-12-28 00:00:00.000 | 0.00 | 2638126 | 2018-12-28 09:15:21.000 |
| Holiday | 1265593 | FullDataProcessed | 2018-12-28 00:00:00.000 | 9219122847.00 | 2638126 | 2018-12-28 09:15:21.000 |
| Holiday | 1265594 | LiteDataProcessed | 2019-01-31 00:00:00.000 | 0.00 | 2638126 | 2019-01-31 14:45:07.000 |
| Holiday | 1265595 | FullDataProcessed | 2019-01-31 00:00:00.000 | 61727744.00 | 2638126 | 2019-01-31 14:45:07.000 |
| Holiday | 1265596 | LiteDataProcessed | 2019-02-05 00:00:00.000 | 0.00 | 2638126 | 2019-02-05 15:23:27.000 |
| Holiday | 1265597 | FullDataProcessed | 2019-02-05 00:00:00.000 | 199454805.00 | 2638126 | 2019-02-05 15:23:27.000 |
| Holiday | 1265598 | LiteDataProcessed | 2019-02-07 00:00:00.000 | 0.00 | 2638126 | 2019-02-07 11:55:55.000 |
| Holiday | 1265599 | FullDataProcessed | 2019-02-07 00:00:00.000 | 17944713.00 | 2638126 | 2019-02-07 11:55:55.000 |
| Holiday | 1265600 | LiteDataProcessed | 2019-02-13 00:00:00.000 | 0.00 | 2638126 | 2019-02-13 15:48:56.000 |
| Holiday | 1265601 | FullDataProcessed | 2019-02-13 00:00:00.000 | 60421568.00 | 2638126 | 2019-02-13 15:48:56.000 |
| Crosbie | 1265604 | LiteDataProcessed | 2019-01-21 00:00:00.000 | 0.00 | 2644032 | 2019-01-21 15:43:43.000 |
| Crosbie | 1265605 | FullDataProcessed | 2019-01-21 00:00:00.000 | 131445.00 | 2644032 | 2019-01-21 15:43:43.000 |
| Stone | 1265606 | LiteDataPublishedToReview | 2019-02-12 00:00:00.000 | 1626943444.00 | 2647518 | 2019-02-12 17:45:25.000 |
| Stone | 1265607 | LiteDataPublishedToReview | 2019-03-05 00:00:00.000 | 2134872671.00 | 2647518 | 2019-03-05 13:00:31.000 |
| Stone | 1265608 | LiteDataProcessed | 2019-02-05 00:00:00.000 | 38828043264.00 | 2647518 | 2019-02-05 09:40:55.000 |
| Stone | 1265609 | FullDataProcessed | 2019-02-05 00:00:00.000 | 0.00 | 2647518 | 2019-02-05 09:40:55.000 |
| Frost | 1265610 | LiteDataPublishedToReview | 2019-03-18 00:00:00.000 | 776025640.00 | 2658542 | 2019-03-18 12:34:10.000 |
| Frost | 1265611 | LiteDataPublishedToReview | 2019-03-05 00:00:00.000 | 3325335118.00 | 2658542 | 2019-03-05 15:02:39.000 |
| Frost | 1265612 | LiteDataPublishedToReview | 2019-03-20 00:00:00.000 | 211927893.00 | 2658542 | 2019-03-20 17:25:30.000 |
| Frost | 1265613 | LiteDataPublishedToReview | 2019-03-06 00:00:00.000 | 466536488.00 | 2658542 | 2019-03-06 11:00:59.000 |
| Frost | 1265614 | LiteDataPublishedToReview | 2019-03-21 00:00:00.000 | 3863850553.00 | 2658542 | 2019-03-21 17:14:27.000 |
| Frost | 1265615 | LiteDataProcessed | 2019-02-28 00:00:00.000 | 94249740012.00 | 2658542 | 2019-02-28 14:13:23.000 |
| Frost | 1265616 | FullDataProcessed | 2019-02-28 00:00:00.000 | 0.00 | 2658542 | 2019-02-28 14:13:23.000 |
| Yellow | 1265617 | LiteDataPublishedToReview | 2019-03-27 00:00:00.000 | 4550540631.00 | 2659077 | 2019-03-27 16:09:41.000 |
| Yellow | 1265618 | LiteDataProcessed | 2019-03-07 00:00:00.000 | 0.00 | 2659077 | 2019-03-07 16:53:16.000 |
| Yellow | 1265619 | FullDataProcessed | 2019-03-07 00:00:00.000 | 96139872.00 | 2659077 | 2019-03-07 16:53:16.000 |
| Yellow | 1265620 | LiteDataProcessed | 2019-03-08 00:00:00.000 | 105357273318.00 | 2659077 | 2019-03-08 16:43:24.000 |
| Yellow | 1265621 | FullDataProcessed | 2019-03-08 00:00:00.000 | 0.00 | 2659077 | 2019-03-08 16:43:24.000 |
+---------+------------+---------------------------+-------------------------+-----------------+---------------------+-------------------------+
这是我的尝试：
SELECT
CAST(YEAR(ps.DateCollected) AS VARCHAR(4)) + '-' + right('00' + CAST(MONTH(ps.DateCollected) AS VARCHAR(2)), 2),
ps.[Name],
c.name,
ceiling(SUM(ps.FileSizeInBytes)/1024/1024/1024.0) [Processed]
FROM EDDSDBO.RPCCProcessingStatistics ps
inner join edds.eddsdbo.[case] c on c.artifactid = ps.workspaceartifactid
where ps.DateCollected >= '2018-12-01'
GROUP BY ps.name, c.name, CAST(YEAR(ps.DateCollected) AS VARCHAR(4)) + '-' + right('00' + CAST(MONTH(ps.DateCollected) AS VARCHAR(2)), 2)
逻辑应该是这样的：
（1）以字节为单位获取2018-12-01之后的所有值
（2）总计
（3）转换为GB
（4）确定结果
当我运行代码并将FullDataProcessed的结果加在一起时，我得到22。但是，当我手动将FullDataProcessed的结果相加时，会得到15.40，当最高值是16时。
我希望代码结果中的FullDataProcessed等于16，而不是22。
答案 0 :(得分：0)
我想您的一个或多个记录在edds.eddsdbo。[case]表中已多次指定其工作区artifactid。案例表上的主键不仅是工件标识符吗？