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【原创】MySQL 以及 Python 实现排名窗口函数

程序员文章站 2022-06-09 08:09:42
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大部分数据库都提供了窗口函数,比如RANK,ROW_NUMBER等等。MySQL这方面没有直接提供,但是可以变相的实现,我以前写了row_number的实现,今天有时间把rank的实现

大部分数据库都提供了窗口函数,比如RANK,ROW_NUMBER等等。 MySQL 这方面没有直接提供,但是可以变相的实现,我以前写了row_number 的实现,今天有时间把 rank 的实现贴出来。


这里,我用MySQL 以及Python 分别实现了rank 窗口函数。

原始表信息:

t_girl=# \d group_concat; Table "ytt.group_concat" Column | Type | Modifiers ----------+-----------------------+----------- rank | integer | username | character varying(20) |

表数据

t_girl=# select * from group_concat; rank | username ------+---------- 100 | Lucy 127 | Lucy 146 | Lucy 137 | Lucy 104 | Lucy 121 | Lucy 136 | Lily 100 | Lily 100 | Lily 105 | Lily 136 | Lily 149 | ytt 116 | ytt 116 | ytt 149 | ytt 106 | ytt 117 | ytt (17 rows) Time: 0.638 ms

PostgreSQL 的rank 窗口函数示例:

t_girl=# select username,rank,rank() over(partition by username order by rank desc) as rank_cnt from group_concat; username | rank | rank_cnt ----------+------+---------- Lily | 136 | 1 Lily | 136 | 1 Lily | 105 | 3 Lily | 100 | 4 Lily | 100 | 4 Lucy | 146 | 1 Lucy | 137 | 2 Lucy | 127 | 3 Lucy | 121 | 4 Lucy | 104 | 5 Lucy | 100 | 6 ytt | 149 | 1 ytt | 149 | 1 ytt | 117 | 3 ytt | 116 | 4 ytt | 116 | 4 ytt | 106 | 6 (17 rows) Time: 131.150 ms



MySQL 提供了group_concat 聚合函数可以变相的实现:

mysql> select a.username, a.rank, find_in_set(a.rank,b.rank_gp) as rank_cnt from group_concat as a , (select username,group_concat(rank order by rank desc separator ',') as rank_gp from group_concat group by username ) b where a.username = b.username order by a.username asc,a.rank desc; +----------+------+----------+ | username | rank | rank_cnt | +----------+------+----------+ | Lily | 136 | 1 | | Lily | 136 | 1 | | Lily | 105 | 3 | | Lily | 100 | 4 | | Lily | 100 | 4 | | Lucy | 146 | 1 | | Lucy | 137 | 2 | | Lucy | 127 | 3 | | Lucy | 121 | 4 | | Lucy | 104 | 5 | | Lucy | 100 | 6 | | ytt | 149 | 1 | | ytt | 149 | 1 | | ytt | 117 | 3 | | ytt | 116 | 4 | | ytt | 116 | 4 | | ytt | 106 | 6 | +----------+------+----------+ 17 rows in set (0.02 sec)

当然了,如果MySQL SQL不太熟悉,,可以用程序来处理,比如我下面用python 实现了rank 函数,执行结果如下:(脚本源代码最后)


>>> ================================ RESTART ================================ >>> username | rank | rank_cnt -------------------------------- ytt |149 |1 ytt |149 |1 ytt |117 |3 ytt |116 |4 ytt |116 |4 ytt |106 |6 Lucy |146 |1 Lucy |137 |2 Lucy |127 |3 Lucy |121 |4 Lucy |104 |5 Lucy |100 |6 Lily |136 |1 Lily |136 |2 Lily |105 |3 Lily |100 |4 Lily |100 |4 (17 Rows.) Time: 0.162 Seconds.


附上脚本代码:

from __future__ import print_function from datetime import date, datetime, timedelta import mysql.connector import time # Created by ytt 2014/5/14. # Rank function implement. def db_connect(is_true): cnx = mysql.connector.connect(host='192.168.1.131',port='3306',user='python_user', password='python_user',database='t_girl',autocommit=is_true) return cnx def db_rs_rank(c1 ='username desc' ,c2 = ' rank desc'): # c1: partition column. # c2: sort column. time_start = time.time() cnx = db_connect(True) rs = cnx.cursor() query0 = "select username,rank from group_concat order by " + c1 + ", " + c2 rs.execute(query0,multi=False) if rs.with_rows: rows = rs.fetchall() else: return "No rows affected." i = 0 j = 0 k = 1 result = [] field1_compare = rows[0][0] field2_compare = rows[0][1] while i


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