所以我有一个表格如下:
So I have a table as follows:
ID_STUDENT | ID_CLASS | GRADE
-----------------------------
1 | 1 | 90
1 | 2 | 80
2 | 1 | 99
3 | 1 | 80
4 | 1 | 70
5 | 2 | 78
6 | 2 | 90
6 | 3 | 50
7 | 3 | 90
然后我需要对它们进行分组、排序和排序:
I need to then group, sort and order them to give:
ID_STUDENT | ID_CLASS | GRADE | RANK
------------------------------------
2 | 1 | 99 | 1
1 | 1 | 90 | 2
3 | 1 | 80 | 3
4 | 1 | 70 | 4
6 | 2 | 90 | 1
1 | 2 | 80 | 2
5 | 2 | 78 | 3
7 | 3 | 90 | 1
6 | 3 | 50 | 2
现在我知道你可以使用临时变量来进行排名,像这里,但我如何为分组集做这件事?感谢您的任何见解!
Now I know that you can use a temp variable to rank, like here, but how do I do it for a grouped set? Thanks for any insight!
SELECT id_student, id_class, grade,
@student:=CASE WHEN @class <> id_class THEN 0 ELSE @student+1 END AS rn,
@class:=id_class AS clset
FROM
(SELECT @student:= -1) s,
(SELECT @class:= -1) c,
(SELECT *
FROM mytable
ORDER BY id_class, id_student
) t
这很简单:
id_class 先排序,id_student 第二排序.@student 和 @class 被初始化为 -1@class 用于测试是否输入了下一组.如果 id_class 的先前值(存储在 @class 中)不等于当前值(存储在 id_class 中),@student 被归零.否则递增.@class 被赋值为 id_class 的新值,它将在下一行的第 3 步的测试中使用.id_class first, id_student second.@student and @class are initialized to -1@class is used to test if the next set is entered. If the previous value of the id_class (which is stored in @class) is not equal to the current value (which is stored in id_class), the @student is zeroed. Otherwise is is incremented.@class is assigned with the new value of id_class, and it will be used in test on step 3 at the next row.这篇关于如何在 MySQL 中执行分组排名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