你将如何整理这个Mysql逻辑
我用它来显示每日基本数据。 假设一个人每天吃3次早、中、午。所以我像这样输入数据你将如何整理这个Mysql逻辑,mysql,Mysql,我用它来显示每日基本数据。 假设一个人每天吃3次早、中、午。所以我像这样输入数据 Table: table -------------------------------------------------------------------- | manId(AI)(PK) | date | schedules | amount | blah | [....] ------------------------------------------------------------------
Table: table
--------------------------------------------------------------------
| manId(AI)(PK) | date | schedules | amount | blah | [....]
--------------------------------------------------------------------
102 - 01/01/2016 - 0.5 KG (morning time data)
102 - 01/01/2016 - 0.5 KG (noon time data)
102 - 01/01/2016 - 0.5 KG (after_noon time data)
103 - 01/01/2016 - 0.5 KG (morning time data)
102 - 01/01/2016 - 1.5 KG (Sum all schedules)
103 - 02/01/2016 - 1.5 KG (Sum all schedules)
104 - 03/01/2016 - 1.5 KG (Sum all schedules)
当我查询显示morris图表数据时,它会像这样显示每个数据
Table: table
--------------------------------------------------------------------
| manId(AI)(PK) | date | schedules | amount | blah | [....]
--------------------------------------------------------------------
102 - 01/01/2016 - 0.5 KG (morning time data)
102 - 01/01/2016 - 0.5 KG (noon time data)
102 - 01/01/2016 - 0.5 KG (after_noon time data)
103 - 01/01/2016 - 0.5 KG (morning time data)
102 - 01/01/2016 - 1.5 KG (Sum all schedules)
103 - 02/01/2016 - 1.5 KG (Sum all schedules)
104 - 03/01/2016 - 1.5 KG (Sum all schedules)
我想做的是,每天都会像这样展示
Table: table
--------------------------------------------------------------------
| manId(AI)(PK) | date | schedules | amount | blah | [....]
--------------------------------------------------------------------
102 - 01/01/2016 - 0.5 KG (morning time data)
102 - 01/01/2016 - 0.5 KG (noon time data)
102 - 01/01/2016 - 0.5 KG (after_noon time data)
103 - 01/01/2016 - 0.5 KG (morning time data)
102 - 01/01/2016 - 1.5 KG (Sum all schedules)
103 - 02/01/2016 - 1.5 KG (Sum all schedules)
104 - 03/01/2016 - 1.5 KG (Sum all schedules)
使用
date
列上的groupby
和sum
所有值
SELECT id,date,SUM(amount)
FROM table_name
GROUP BY date;