此时我可能看的不是很清楚,但我在 MySQL 中有一个表,如下所示:
I'm probably not seeing things very clear at this moment, but I have a table in MySQL which looks like this:
ID | a | b | c
1 | a1 | b1 | c1
2 | a2 | b2 | c2
出于某种原因(实际上是另一个表上的连接 - 基于 ID,但我认为如果有人可以帮助我完成这部分,我可以自己完成其余部分),我需要这些行改为这样:
For some reason (actually a join on another table - based on ID, but I think if someone can help me out with this part, I can do the rest myself), I needed those rows to be like this instead:
1 | a1 | a
1 | b1 | b
1 | c1 | c
2 | a2 | a
2 | b2 | b
2 | c2 | c
所以基本上,我需要查看如下行:ID、columntitle、value有什么方法可以轻松做到这一点吗?
So basically, I need to view the rows like: ID, columntitle, value
Is there any way to do this easily?
您正在尝试反透视数据.MySQL 没有 unpivot 功能,因此您必须使用 UNION ALL 查询将列转换为行:
You are trying to unpivot the data. MySQL does not have an unpivot function, so you will have to use a UNION ALL query to convert the columns into rows:
select id, 'a' col, a value
from yourtable
union all
select id, 'b' col, b value
from yourtable
union all
select id, 'c' col, c value
from yourtable
参见SQL Fiddle with Demo.
这也可以使用 CROSS JOIN 来完成:
This can also be done using a CROSS JOIN:
select t.id,
c.col,
case c.col
when 'a' then a
when 'b' then b
when 'c' then c
end as data
from yourtable t
cross join
(
select 'a' as col
union all select 'b'
union all select 'c'
) c
参见SQL Fiddle with Demo
这篇关于MySQL - 如何将列反透视为行?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持html5模板网!
如何有效地使用窗口函数根据 N 个先前值来决定How to use windowing functions efficiently to decide next N number of rows based on N number of previous values(如何有效地使用窗口函数根据
在“GROUP BY"中重用选择表达式的结果;条款reuse the result of a select expression in the quot;GROUP BYquot; clause?(在“GROUP BY中重用选择表达式的结果;条款?)
Pyspark DataFrameWriter jdbc 函数的 ignore 选项是忽略整Does ignore option of Pyspark DataFrameWriter jdbc function ignore entire transaction or just offending rows?(Pyspark DataFrameWriter jdbc 函数的 ig
使用 INSERT INTO table ON DUPLICATE KEY 时出错,使用 Error while using INSERT INTO table ON DUPLICATE KEY, using a for loop array(使用 INSERT INTO table ON DUPLICATE KEY 时出错,使用 for 循环数组
pyspark mysql jdbc load 调用 o23.load 时发生错误 没有合pyspark mysql jdbc load An error occurred while calling o23.load No suitable driver(pyspark mysql jdbc load 调用 o23.load 时发生错误 没有合适的
如何将 Apache Spark 与 MySQL 集成以将数据库表作为How to integrate Apache Spark with MySQL for reading database tables as a spark dataframe?(如何将 Apache Spark 与 MySQL 集成以将数据库表作为