重新格式化部门表Java
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# 题目
部门表 Department:
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| id | int |
| revenue | int |
| month | varchar |
+---------------+---------+
(id, month) 是表的联合主键。
这个表格有关于每个部门每月收入的信息。
月份(month)可以取下列值 ["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"]。
编写一个 SQL 查询来重新格式化表,使得新的表中有一个部门 id 列和一些对应 每个月 的收入(revenue)列。
查询结果格式如下面的示例所示:
Department 表:
+------+---------+-------+
| id | revenue | month |
+------+---------+-------+
| 1 | 8000 | Jan |
| 2 | 9000 | Jan |
| 3 | 10000 | Feb |
| 1 | 7000 | Feb |
| 1 | 6000 | Mar |
+------+---------+-------+
查询得到的结果表:
+------+-------------+-------------+-------------+-----+-------------+
| id | Jan_Revenue | Feb_Revenue | Mar_Revenue | ... | Dec_Revenue |
+------+-------------+-------------+-------------+-----+-------------+
| 1 | 8000 | 7000 | 6000 | ... | null |
| 2 | 9000 | null | null | ... | null |
| 3 | null | 10000 | null | ... | null |
+------+-------------+-------------+-------------+-----+-------------+
注意,结果表有 13 列 (1个部门 id 列 + 12个月份的收入列)。
# 思路
# 解法
# Write your MySQL query statement below
SELECT
`id`,
SUM(CASE `month` WHEN 'Jan' THEN `revenue` ELSE NULL END) AS `Jan_Revenue`,
SUM(CASE `month` WHEN 'Feb' THEN `revenue` ELSE NULL END) AS `Feb_Revenue`,
SUM(CASE `month` WHEN 'Mar' THEN `revenue` ELSE NULL END) AS `Mar_Revenue`,
SUM(CASE `month` WHEN 'Apr' THEN `revenue` ELSE NULL END) AS `Apr_Revenue`,
SUM(CASE `month` WHEN 'May' THEN `revenue` ELSE NULL END) AS `May_Revenue`,
SUM(CASE `month` WHEN 'Jun' THEN `revenue` ELSE NULL END) AS `Jun_Revenue`,
SUM(CASE `month` WHEN 'Jul' THEN `revenue` ELSE NULL END) AS `Jul_Revenue`,
SUM(CASE `month` WHEN 'Aug' THEN `revenue` ELSE NULL END) AS `Aug_Revenue`,
SUM(CASE `month` WHEN 'Sep' THEN `revenue` ELSE NULL END) AS `Sep_Revenue`,
SUM(CASE `month` WHEN 'Oct' THEN `revenue` ELSE NULL END) AS `Oct_Revenue`,
SUM(CASE `month` WHEN 'Nov' THEN `revenue` ELSE NULL END) AS `Nov_Revenue`,
SUM(CASE `month` WHEN 'Dec' THEN `revenue` ELSE NULL END) AS `Dec_Revenue`
FROM
`Department`
GROUP BY `id`
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# 总结
- 分析出几种情况,然后分别对各个情况实现


