MySQL 8.x之——窗口函数

窗口：记录集合
窗口函数：在满足某些条件的记录集合上执行的特殊函数，对于每条记录都要在此窗口内执行函数。有的函数随着记录的不同，窗口大小都是固定的，称为静态窗口；有的函数则相反，不同的记录对应着不同的窗口，称为滑动窗口。

1. 窗口函数和普通聚合函数的区别：

①聚合函数是将多条记录聚合为一条；窗口函数是每条记录都会执行，有几条记录执行完还是几条。
②聚合函数也可以用于窗口函数。

2. 窗口函数的基本用法：

函数名 OVER 子句

over关键字用来指定函数执行的窗口范围，若后面括号中什么都不写，则意味着窗口包含满足WHERE条件的所有行，窗口函数基于所有行进行计算；如果不为空，则支持以下4中语法来设置窗口。
①window_name：给窗口指定一个别名。如果SQL中涉及的窗口较多，采用别名可以看起来更清晰易读；
②PARTITION BY 子句：窗口按照哪些字段进行分组，窗口函数在不同的分组上分别执行；
③ORDER BY子句：按照哪些字段进行排序，窗口函数将按照排序后的记录顺序进行编号；
④FRAME子句：FRAME是当前分区的一个子集，子句用来定义子集的规则，通常用来作为滑动窗口使用。

3. 按功能划分可将MySQL支持的窗口函数分为如下几类：

①序号函数：ROW_NUMBER()、RANK()、DENSE_RANK()

用途：显示分区中的当前行号
应用场景：查询每个学生的分数最高的前3门课程

ROW_NUMBER() OVER (PARTITION BY stu_id ORDER BY score)

mysql> SELECT *
    -> FROM(
    ->     SELECT stu_id,
    ->     ROW_NUMBER() OVER (PARTITION BY stu_id ORDER BY score DESC) AS score_
order,
    ->     lesson_id, score
    ->     FROM t_score) t
    -> WHERE score_order <= 3
    -> ;
+--------+-------------+-----------+-------+
| stu_id | score_order | lesson_id | score |
+--------+-------------+-----------+-------+
|      1 |           1 | L005      |    98 |
|      1 |           2 | L001      |    98 |
|      1 |           3 | L004      |    88 |
|      2 |           1 | L002      |    90 |
|      2 |           2 | L003      |    86 |
|      2 |           3 | L001      |    84 |
|      3 |           1 | L001      |   100 |
|      3 |           2 | L002      |    91 |
|      3 |           3 | L003      |    85 |
|      4 |           1 | L001      |    99 |
|      4 |           2 | L005      |    98 |
|      4 |           3 | L002      |    88 |
+--------+-------------+-----------+-------+

对于stu_id=1的同学，有两门课程的成绩均为98，序号随机排了1和2。但很多情况下二者应该是并列第一，则他的成绩为88的这门课的序号可能是第2名，也可能为第3名。
这时候，ROW_NUMBER()就不能满足需求，需要RANK()和DENSE_RANK()出场，它们和ROW_NUMBER()非常类似，只是在出现重复值时处理逻辑有所不同。

mysql> SELECT *
    -> FROM(
    ->     SELECT
    ->     ROW_NUMBER() OVER (PARTITION BY stu_id ORDER BY score DESC) AS score_order1,
    ->     RANK() OVER (PARTITION BY stu_id ORDER BY score DESC) AS score_order2,
    ->     DENSE_RANK() OVER (PARTITION BY stu_id ORDER BY score DESC) AS score_order3,
    ->     stu_id, lesson_id, score
    ->     FROM t_score) t
    -> WHERE stu_id = 1 AND score_order1 <= 3 AND score_order2 <= 3 AND score_order3 <= 3
    -> ;
+--------------+--------------+--------------+--------+-----------+-------+
| score_order1 | score_order2 | score_order3 | stu_id | lesson_id | score |
+--------------+--------------+--------------+--------+-----------+-------+
|            1 |            1 |            1 |      1 | L005      |    98 |
|            2 |            1 |            1 |      1 | L001      |    98 |
|            3 |            3 |            2 |      1 | L004      |    88 |
+--------------+--------------+--------------+--------+-----------+-------+

ROW_NUMBER()：顺序排序——1、2、3
RANK()：并列排序，跳过重复序号——1、1、3
DENSE_RANK()：并列排序，不跳过重复序号——1、1、2

②分布函数：PERCENT_RANK()、CUME_DIST()

PERCENT_RANK()

用途：每行按照公式(rank-1) / (rows-1)进行计算。其中，rank为RANK()函数产生的序号，rows为当前窗口的记录总行数
应用场景：不常用

给窗口指定别名：WINDOW w AS (PARTITION BY stu_id ORDER BY score)
rows = 5

mysql> SELECT
    -> RANK() OVER w AS rk,
    -> PERCENT_RANK() OVER w AS prk,
    -> stu_id, lesson_id, score
    -> FROM t_score
    -> WHERE stu_id = 1
    -> WINDOW w AS (PARTITION BY stu_id ORDER BY score)
    -> ;
+----+------+--------+-----------+-------+
| rk | prk  | stu_id | lesson_id | score |
+----+------+--------+-----------+-------+
|  1 |    0 |      1 | L003      |    79 |
|  2 | 0.25 |      1 | L002      |    86 |
|  3 |  0.5 |      1 | L004      |    88 |
|  4 | 0.75 |      1 | L005      |    98 |
|  4 | 0.75 |      1 | L001      |    98 |
+----+------+--------+-----------+-------+

CUME_DIST()

用途：分组内小于、等于当前rank值的行数 / 分组内总行数
应用场景：查询小于等于当前成绩（score）的比例

cd1：没有分区，则所有数据均为一组，总行数为8
cd2：按照lesson_id分成了两组，行数各为4

mysql> SELECT stu_id, lesson_id, score,
    -> CUME_DIST() OVER (ORDER BY score) AS cd1,
    -> CUME_DIST() OVER (PARTITION BY lesson_id ORDER BY score) AS cd2
    -> FROM t_score
    -> WHERE lesson_id IN ('L001','L002')
    -> ;
+--------+-----------+-------+-------+------+
| stu_id | lesson_id | score | cd1   | cd2  |
+--------+-----------+-------+-------+------+
|      2 | L001      |    84 | 0.125 | 0.25 |
|      1 | L001      |    98 |  0.75 |  0.5 |
|      4 | L001      |    99 | 0.875 | 0.75 |
|      3 | L001      |   100 |     1 |    1 |
|      1 | L002      |    86 |  0.25 | 0.25 |
|      4 | L002      |    88 | 0.375 |  0.5 |
|      2 | L002      |    90 |   0.5 | 0.75 |
|      3 | L002      |    91 | 0.625 |    1 |
+--------+-----------+-------+-------+------+

③前后函数：LAG(expr,n)、LEAD(expr,n)

用途：返回位于当前行的前n行（LAG(expr,n)）或后n行（LEAD(expr,n)）的expr的值
应用场景：查询前1名同学的成绩和当前同学成绩的差值

内层SQL先通过LAG()函数得到前1名同学的成绩，外层SQL再将当前同学和前1名同学的成绩做差得到成绩差值diff

mysql> SELECT stu_id, lesson_id, score, pre_score,
    -> score-pre_score AS diff
    -> FROM(
    ->     SELECT stu_id, lesson_id, score,
    ->     LAG(score,1) OVER w AS pre_score
    ->     FROM t_score
    ->     WHERE lesson_id IN ('L001','L002')
    ->     WINDOW w AS (PARTITION BY lesson_id ORDER BY score)) t
    -> ;
+--------+-----------+-------+-----------+------+
| stu_id | lesson_id | score | pre_score | diff |
+--------+-----------+-------+-----------+------+
|      2 | L001      |    84 |      NULL | NULL |
|      1 | L001      |    98 |        84 |   14 |
|      4 | L001      |    99 |        98 |    1 |
|      3 | L001      |   100 |        99 |    1 |
|      1 | L002      |    86 |      NULL | NULL |
|      4 | L002      |    88 |        86 |    2 |
|      2 | L002      |    90 |        88 |    2 |
|      3 | L002      |    91 |        90 |    1 |
+--------+-----------+-------+-----------+------+

④头尾函数：FIRST_VALUE(expr)、LAST_VALUE(expr)

用途：返回第一个（FIRST_VALUE(expr)）或最后一个（LAST_VALUE(expr)）expr的值
应用场景：截止到当前成绩，按照日期排序查询第1个和最后1个同学的分数

添加新列：mysql> ALTER TABLE t_score ADD create_time DATE;

mysql> SELECT stu_id, lesson_id, score, create_time,
    -> FIRST_VALUE(score) OVER w AS first_score,
    -> LAST_VALUE(score) OVER w AS last_score
    -> FROM t_score
    -> WHERE lesson_id IN ('L001','L002')
    -> WINDOW w AS (PARTITION BY lesson_id ORDER BY create_time)
    -> ;
+--------+-----------+-------+-------------+-------------+------------+
| stu_id | lesson_id | score | create_time | first_score | last_score |
+--------+-----------+-------+-------------+-------------+------------+
|      3 | L001      |   100 | 2018-08-07  |         100 |        100 |
|      1 | L001      |    98 | 2018-08-08  |         100 |         98 |
|      2 | L001      |    84 | 2018-08-09  |         100 |         99 |
|      4 | L001      |    99 | 2018-08-09  |         100 |         99 |
|      3 | L002      |    91 | 2018-08-07  |          91 |         91 |
|      1 | L002      |    86 | 2018-08-08  |          91 |         86 |
|      2 | L002      |    90 | 2018-08-09  |          91 |         90 |
|      4 | L002      |    88 | 2018-08-10  |          91 |         88 |
+--------+-----------+-------+-------------+-------------+------------+

⑤其它函数：NTH_VALUE(expr, n)、NTILE(n)

NTH_VALUE(expr,n)

用途：返回窗口中第n个expr的值。expr可以是表达式，也可以是列名
应用场景：截止到当前成绩，显示每个同学的成绩中排名第2和第3的成绩的分数

mysql> SELECT stu_id, lesson_id, score,
    -> NTH_VALUE(score,2) OVER w AS second_score,
    -> NTH_VALUE(score,3) OVER w AS third_score
    -> FROM t_score
    -> WHERE stu_id IN (1,2)
    -> WINDOW w AS (PARTITION BY stu_id ORDER BY score)
    -> ;
+--------+-----------+-------+--------------+-------------+
| stu_id | lesson_id | score | second_score | third_score |
+--------+-----------+-------+--------------+-------------+
|      1 | L003      |    79 |         NULL |        NULL |
|      1 | L002      |    86 |           86 |        NULL |
|      1 | L004      |    88 |           86 |          88 |
|      1 | L001      |    98 |           86 |          88 |
|      1 | L005      |    98 |           86 |          88 |
|      2 | L004      |    75 |         NULL |        NULL |
|      2 | L005      |    77 |           77 |        NULL |
|      2 | L001      |    84 |           77 |          84 |
|      2 | L003      |    86 |           77 |          84 |
|      2 | L002      |    90 |           77 |          84 |
+--------+-----------+-------+--------------+-------------+

NTILE(n)

用途：将分区中的有序数据分为n个等级，记录等级数
应用场景：将每门课程按照成绩分成3组

mysql> SELECT
    -> NTILE(3) OVER w AS nf,
    -> stu_id, lesson_id, score
    -> FROM t_score
    -> WHERE lesson_id IN ('L001','L002')
    -> WINDOW w AS (PARTITION BY lesson_id ORDER BY score)
    -> ;
+------+--------+-----------+-------+
| nf   | stu_id | lesson_id | score |
+------+--------+-----------+-------+
|    1 |      2 | L001      |    84 |
|    1 |      1 | L001      |    98 |
|    2 |      4 | L001      |    99 |
|    3 |      3 | L001      |   100 |
|    1 |      1 | L002      |    86 |
|    1 |      4 | L002      |    88 |
|    2 |      2 | L002      |    90 |
|    3 |      3 | L002      |    91 |
+------+--------+-----------+-------+

NTILE(n)函数在数据分析中应用较多，比如由于数据量大，需要将数据平均分配到n个并行的进程分别计算，此时就可以用NTILE(n)对数据进行分组（由于记录数不一定被n整除，所以数据不一定完全平均），然后将不同桶号的数据再分配。

4. 聚合函数作为窗口函数：

用途：在窗口中每条记录动态地应用聚合函数（SUM()、AVG()、MAX()、MIN()、COUNT()），可以动态计算在指定的窗口内的各种聚合函数值
应用场景：截止到当前时间，查询stu_id=1的学生的累计分数、分数最高的科目、分数最低的科目

mysql> SELECT stu_id, lesson_id, score, create_time,
    -> SUM(score) OVER w AS score_sum,
    -> MAX(score) OVER w AS score_max,
    -> MIN(score) OVER w AS score_min
    -> FROM t_score
    -> WHERE stu_id = 1
    -> WINDOW w AS (PARTITION BY stu_id ORDER BY create_time)
    -> ;
+--------+-----------+-------+-------------+-----------+-----------+-----------+

| stu_id | lesson_id | score | create_time | score_sum | score_max | score_min |

+--------+-----------+-------+-------------+-----------+-----------+-----------+

|      1 | L001      |    98 | 2018-08-08  |       184 |        98 |        86 |

|      1 | L002      |    86 | 2018-08-08  |       184 |        98 |        86 |

|      1 | L003      |    79 | 2018-08-09  |       263 |        98 |        79 |

|      1 | L004      |    88 | 2018-08-10  |       449 |        98 |        79 |

|      1 | L005      |    98 | 2018-08-10  |       449 |        98 |        79 |

+--------+-----------+-------+-------------+-----------+-----------+-----------+

参考链接：http://www.cnblogs.com/DataArt/p/9961676.html

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