我正在尝试运行查询一段时间,但这比我想象的要困难。 我有以下3个表:
Stores:
+--+-------+--------------+-------+---------+---------+----+---------------+---+------+
|ID|Company|Address |PostCod|Latitude |Longitude|Stat| Division |Gro| When |
+--+-------+--------------+-------+---------+---------+----+---------------+---+------+
|17|Company|Site Address 3|WF1 5NT|53.666340|-1.487857|OPEN|Test Division 2|arl|2014-01-31 14:36:04
|18|Company|Site Address 3|WF1 5NT|53.666340|-1.487857|OPEN|Test Division 2|arl|2014-01-31 14:36:04
|19|Company|Site Address 3|WF1 5NT|53.666340|-1.487857|OPEN|Test Division 2|arl|2014-01-31 14:36:04
|20|Company|Site Address 3|WF1 5NT|53.666340|-1.487857|OPEN|Test Division 2|arl|2014-01-31 14:36:04
+--+-------+--------------+-------+---------+---------+----+---------------+---+------+
Jobs:
+--------+-------------------------------------------+-------+------------+------+--------+
| client | description | freq | from | till |job_id |
+--------+-------------------------------------------+-------+------------+------+--------+
| 17 | Weekly external and internal window clean | 7 | 2013-10-01 | NULL | 17 |
| 18 | Weekly external and internal window clean | 7 | 2013-10-01 | NULL | 18 |
| 19 | Weekly external and internal window clean | 7 | 2013-10-01 | NULL | 19 |
| 20 | Weekly external and internal window clean | 7 | 2013-10-01 | NULL | 20 |
| 17 | 4 weekly fascia and upper floor windows | 28 | 2013-10-01 | NULL | 645 |
| 18 | 4 weekly fascia and upper floor windows | 28 | 2013-10-01 | NULL | 646 |
| 19 | 4 weekly fascia and upper floor windows | 28 | 2013-10-01 | NULL | 647 |
| 20 | 4 weekly fascia and upper floor windows | 28 | 2013-10-01 | NULL | 648 |
+--------+-------------------------------------------+-------+------------+------+--------+
Job_hist
+------+-------------------+-----------------+---------+------+--------------+-----------------------------------------+-------------------------------+------+-----+-----------------------+------+
|Job_id| last | user | Company | LINK | Signedy_by | Job Description | Address | Accu |Days | Possition |Uniqid|
+------+-------------------+-----------------+---------+------+--------------+-----------------------------------------+-------------------------------+------+-----+-----------------------+------+
|17 |2013-10-01 09:35:37|ARL_Operative_013|Santander| LINK |tony moore |Weekly external window clean | AN WELLING 14 BR (DA16 3PP) |739.00|10 |Branch Manager |132 |
|20 |2013-10-02 12:27:51|ARL_Operative_013|Santander| LINK |alex goodman |Weekly external window clean | AN HAROLD HILL 69 FR (RM3 8XA)|55.00 |6 |Store Assistant Manager|268 |
|19 |2013-10-03 09:14:19|ARL_Operative_013|Santander| LINK |darren pickett|Weekly external window clean | AN WOOLWICH 41 PS (SE18 6JD) |50.00 |5 |Other |332 |
|18 |2013-10-03 09:54:49|ARL_Operative_013|Santander| LINK |james lawrence|Weekly external window clean | AN ELTHAM 73 EHS (SE9 1UW) |49.00 |7 |Other |346 |
|17 |2013-10-08 09:05:16|ARL_Operative_013|Santander| LINK |tony moore |Weekly external and internal window clean| AN WELLING 14 BR (DA16 3PP) |67.00 |6 |Branch Manager |697 |
+------+-------------------+-----------------+---------+------+--------------+-----------------------------------------+-------------------------------+------+-----+-----------------------+------+
我需要编写一个查询,根据分区进行一些性能计算。
目标是:
1)计算在给定时间范围内安排的清洁次数,(简单版本)采取开始日期和结束日期,计算天数并除以stores
。freq
2)在此期间,有多少计划清洁按时完成。我们从job_hist获取这些数据(其中job_hist.jod_id = jobs.job_id和job_hist.last属于这个区间,而job_hist.days< = freq
3)按时完成清洁的百分比
4)多少次清理工作的时间较晚(与第2点相同的逻辑只是job_hist> freq)
5)已完成的清洁工作的百分比
6)错过了多少人(预定 - 按时完成 - 迟到)
7)错过的百分比
所有这些都应按分组进行分组,因此结果应如下所示:
+------------------------------+---------+------+-----------------+---------+--------------------+------+-----------------+
|division |scheduled|ontime|ontime_percentage|completed|completed_percentage|missed|missed_percentage
+------------------------------+---------+------+-----------------+---------+--------------------+------+-----------------+
|fsdfoihsdfljksdlgjdfsligsgfsfd|16282 |10404 |63.90% |10825 |66.48% |5457 |33.52%
|Test Division 2 |259 |129 |49.81% |133 |51.35% |126 |48.65%
|Test Division 3 |30 |15 |50.00% |15 |50.00% |15 |50.00%
+------------------------------+---------+------+-----------------+---------+--------------------+------+-----------------+
现在我对SQL查询不太满意,但我已经设法将以下查询放在一起:
SELECT `stores`.`division`,
SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) as `scheduled`,
count(`name`) as `ontime`,
concat(round(( count(`name`)/SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) * 100 ),2),'%') AS ontime_percentage,
count(`user`) as `completed`,
concat(round(( count(`user`)/SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) * 100 ),2),'%') AS completed_percentage,
(SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`)-count(`user`)) as `missed`,
concat(round(( (SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`)-count(`user`)) /SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) * 100 ),2),'%') AS missed_percentage
from `stores` left join `jobs` on `stores`.`id`=`jobs`.`client`
left join (select `user`,`job_id` from `job_hist` where `job_hist`.`last`>='$from' and `job_hist`.`last`<='$till') as `myquery` on `myquery`.`job_id`=`jobs`.`job_id`
left join (select `name`,`job_hist`.`job_id` from `job_hist` left join `jobs` on `jobs`.`job_id`=`job_hist`.`job_id` where `job_hist`.`last`>='$from' and `job_hist`.`last`<='$till' and `job_hist`.`days`<=`jobs`.`freq`) as `myquery2` on `myquery2`.`job_id`=`jobs`.`job_id`
where `stores`.`owner`='$group'
group by `division`
$ till,$ from,$ group是一些PHP变量,$ until和$ from是字符串格式的日期,$ group是字符串。
现在查询运行得很好,但是(总是有一个但是),Scheduled字段正在总结不同的值,我的意思是有时它会使值加倍,有时候它会增加三倍。
我已阅读THIS,但我仍然无法理解它。我或多或少地明白我的一些结果是加倍的,但仍然无法弄清楚我需要改变什么。
在任何人建议加入stores
。division
和job_hist
。division
之间的划分之前,这是不可行的,因为划分可以及时更改,并且会更新在stores
但不在job_hist
中。job_hist
不应随时修改,只包含历史数据。
感谢您的帮助。
更新
好的,所以在将我的头撞在砖墙上另外2个小时后,我设法调整了我的查询,直到现在它看起来我得到了正确的数据,但我需要运行更多测试以确保在发布之前我自己的答案。无论如何这里是我更新的查询:
SELECT `stores`.`division`,
SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) as `scheduled`,
sum(`ontime`),
concat(round(( sum(`ontime`)/SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) * 100 ),2),'%') AS ontime_percentage,
sum(`completed`-`ontime`),
concat(round(( sum(`completed`-`ontime`)/SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) * 100 ),2),'%') AS completed_percentage,
(SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`)-sum(`completed`)) as `missed`,
concat(round(( (SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`)-sum(`completed`)) /SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) * 100 ),2),'%') AS missed_percentage from `stores`
left join `jobs` on `stores`.`id`=`jobs`.`client`
left join (select count(`user`) as `completed`,`job_id` from `job_hist` where `job_hist`.`last`>='$from' and `job_hist`.`last`<='$till' group by `job_id`) as `myquery` on `myquery`.`job_id`=`jobs`.`job_id`
left join (select count(`name`) as `ontime`,`job_hist`.`job_id` from `job_hist` left join `jobs` on `jobs`.`job_id`=`job_hist`.`job_id` where `job_hist`.`last`>='$from' and `job_hist`.`last`<='$till' and `job_hist`.`days`<=`jobs`.`freq` group by `job_id`) as `myquery2` on `myquery2`.`job_id`=`jobs`.`job_id`
where `stores`.`owner`='$group'
group by `stores`.`division`
如果有人能提出更好的方法,我会非常感激。
再次感谢。
答案 0 :(得分:0)
确定。
问题在于分组,所以这里是正确返回数据的查询:
SELECT `stores`.`division`,
SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) as `scheduled`,
sum(`ontime`),
concat(round(( sum(`ontime`)/SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) * 100 ),2),'%') AS ontime_percentage,
sum(`completed`)-sum(`ontime`),
concat(round(( (sum(`completed`)-sum(`ontime`))/SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) * 100 ),2),'%') AS completed_percentage,
(SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`)-sum(`completed`)) as `missed`,
concat(round(( (SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`)-sum(`completed`)) /SUM(DATEDIFF(LEAST(IFNULL(`till`,CURDATE()),'$till'),GREATEST(`from`,'$from')) DIV `freq`) * 100 ),2),'%') AS missed_percentage from `stores`
left join `jobs` on `stores`.`id`=`jobs`.`client`
left join (select count(`user`) as `completed`,`job_id` from `job_hist` where `job_hist`.`last`>='$from' and `job_hist`.`last`<='$till' group by `job_id`) as `myquery` on `myquery`.`job_id`=`jobs`.`job_id`
left join (select count(`name`) as `ontime`,`job_hist`.`job_id` from `job_hist` left join `jobs` on `jobs`.`job_id`=`job_hist`.`job_id` where `job_hist`.`last`>='$from' and `job_hist`.`last`<='$till' and `job_hist`.`days`<=`jobs`.`freq` group by `job_id`) as `myquery2` on `myquery2`.`job_id`=`jobs`.`job_id`
where `stores`.`owner`='$group'
group by `stores`.`division`
如果有人有更好的解决方案,请发布。
谢谢。