Write a SQL query to rank scores. If there is a tie between two scores, both should have the same ranking. Note that after a tie, the next ranking number should be the next consecutive integer value. In other words, there should be no "holes" between ranks.

+----+-------+
| Id | Score |
+----+-------+
| 1 | 3.50 |
| 2 | 3.65 |
| 3 | 4.00 |
| 4 | 3.85 |
| 5 | 4.00 |
| 6 | 3.65 |
+----+-------+
For example, given the above Scores table, your query should generate the following report (order by highest score): +-------+------+
| Score | Rank |
+-------+------+
| 4.00 | 1 |
| 4.00 | 1 |
| 3.85 | 2 |
| 3.65 | 3 |
| 3.65 | 3 |
| 3.50 | 4 |
+-------+------+

此题,其本质就是赋值行号(需要注意分数相同的情景).

在实践过程中,初版答案如下所示:

# Write your MySQL query statement below
SELECT
a.Score AS Score,
(SELECT COUNT(DISTINCT b.Score) FROM Scores b where b.Score >= a.Score) AS Rank
FROM Scores a ORDER BY a.Score DESC;

此处,使用select count来统计行号,注意使用distinct来区分相同分数.

但是,此解题方案的效率较差,sql运行肯定是越快越好.

因此,在sql中引入变量来赋值行号,以替代耗时的select count操作.

# Write your MySQL query statement below
SELECT
Score,
@row := @row + (@pre <> (@pre := Score)) AS Rank
FROM Scores, (SELECT @row := 0, @pre := -1) t
ORDER BY Score DESC;

此处,查询是在Scores与临时表之间进行cross join.

此外,使用临时变量(@row,@pre)记录行号.

Tips:

  • 通过@pre与当前Score的比较,确定是否+1,需要注意mysql中的true/false0/1);
  • sql中,set/update语句中,=表示赋值;在set/update/select中,:=表示赋值,因此使用:=.

通过以上改进,mysql的运行效率得到了较大的提高.

PS:

如果您觉得我的文章对您有帮助,请关注我的微信公众号,谢谢!

LeetCode——Rank Scores的更多相关文章

  1. [LeetCode] Rank Scores 分数排行

    Write a SQL query to rank scores. If there is a tie between two scores, both should have the same ra ...

  2. [LeetCode] Rank Scores -- 数据库知识(mysql)

    Write a SQL query to rank scores. If there is a tie between two scores, both should have the same ra ...

  3. LeetCode:Rank Scores

    做到这题时卡了不少时间,参考了别人的解法,觉得挺不错的,还挺巧妙. SELECT s2.Score,s1.Rank From ( SELECT S1.Score, COUNT(*) as Rank F ...

  4. LeetCode Database: Rank Scores

    Write a SQL query to rank scores. If there is a tie between two scores, both should have the same ra ...

  5. MySQL中变量的用法——LeetCode 178. Rank Scores

    Write a SQL query to rank scores. If there is a tie between two scores, both should have the same ra ...

  6. [LeetCode#178]Rank Scores

    Write a SQL query to rank scores. If there is a tie between two scores, both should have the same ra ...

  7. [SQL]LeetCode178. 分数排名 | Rank Scores

    Write a SQL query to rank scores. If there is a tie between two scores, both should have the same ra ...

  8. 【SQL】178. Rank Scores

    Write a SQL query to rank scores. If there is a tie between two scores, both should have the same ra ...

  9. sql -leetcode 178. Rank Scores

    Score 很好得到: select Score from Scores order by Score desc; 要得到rank, 可以通过比较比当前Score 大的Score 的个数得到: sel ...

随机推荐

  1. [b0006] Spark 2.0.1 伪分布式搭建练手

    环境: 已经安装好: hadoop 2.6.4  yarn 参考: [b0001] 伪分布式 hadoop 2.6.4 准备: spark-2.0.1-bin-hadoop2.6.tgz 下载地址:  ...

  2. Springboot中定时器的简单使用

    在定时器的类上添加注解: @Component@EnableAsync@EnableScheduling 一.普通的定时器: 每天15:10执行的定时器 @Scheduled(cron="0 ...

  3. Prometheus+Grafana监控MySQL、Redis数据库

    俗话说,没有监控的系统就是在裸奔,好的监控就是运维人员的第三只手,第三只眼.本文将使用prometheus及Grafana搭建一套监控系统来监控主机及数据库(MySQL.Redis). 1.  安装G ...

  4. python3.5.3rc1学习三:文件操作

    ##全局变量与局部变量x = 6 def printFuc(): y = 8 z =9 print(y + z) print(x) printFuc()#print(y)#常见错误##name = & ...

  5. 遗传算法求解旅行商(TSP)问题 -- python

    参考资料: 遗传算法解决TSP旅行商问题(附:Python实现) 遗传算法详解(GA)(个人觉得很形象,很适合初学者) from itertools import permutations impor ...

  6. SOA案例分析浅谈

    SOA是英文 Service-Oriented Architecture 三个首字母单词的缩写,中文译为: 面向服务架构 ( SOA), SOA架构与 B/S . C/S 架构是目前最流行三种 Web ...

  7. 编程中的policy

    policy,译为政策,一般是预设的一种限制条件,举个例子   var policyText = { "expiration": "2019-01-01T12:00:00 ...

  8. kafka_2.12-2.2.1 集群搭建

    一.zookeeper集群搭建 kafka集群依赖于zookeeper的集群,搭建zookeeper集群的步骤参考我之前写过的,Solr集群搭建详细教程(一)中的第二步 二.下载解压 去官网下载htt ...

  9. 大话设计模式Python实现-工厂方法模式

    工厂方法模式(Factory Method Pattern):定义一个用于创建对象的接口,让子类决定实例化哪一个类,工厂方法使一个类的实例化延时到其子类. #!/usr/bin/env python ...

  10. 十、自定义ThreadPoolExecutor线程池

    自定义ThreadPoolExecutor线程池 自定义线程池需要遵循的规则 [1]线程池大小的设置 1.计算密集型: 顾名思义就是应用需要非常多的CPU计算资源,在多核CPU时代,我们要让每一个CP ...