表结构

    学生表如下:

    CREATE TABLE `t_student` (
      `id` int NOT NULL AUTO_INCREMENT,
      `t_id` int DEFAULT NULL COMMENT '学科id',
      `score` int DEFAULT NULL COMMENT '分数',
      PRIMARY KEY (`id`)
    );
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    数据如下:

    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    题目一:获取每个科目下前五成绩排名(允许并列)

    允许并列情况可能存在如4、5名成绩并列情况,会导致取前4名得出5条数据,取前5名也是5条数据。

    SELECT
    	s1.* 
    FROM
    	student s1
    	LEFT JOIN student s2 ON s1.t_id = s2.t_id 
    	AND s1.score < s2.score 
    GROUP BY
    	s1.id
    HAVING
    	COUNT( s2.id ) < 5 
    ORDER BY
    	s1.t_id,
    	s1.score DESC
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    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    ps:取前4名时

    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    分析:

    1.自身左外连接,得到所有的左边值小于右边值的集合。以t_id=1时举例,24有5个成绩大于他的(74、64、54、44、34),是第6名,34只有4个成绩大于他的,是第5名......74没有大于他的,是第一名。

    SELECT
    	* 
    FROM
    	student s1
    	LEFT JOIN student s2 ON s1.t_id = s2.t_id 
    	AND s1.score < s2.score
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    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    2. 把总结的规律转换成SQL表示出来,就是group by 每个student 的 id(s1.id),Having统计这个id下面有多少个比他大的值(s2.id)

    SELECT
    	s1.* 
    FROM
    	student s1
    	LEFT JOIN student s2 ON s1.t_id = s2.t_id 
    	AND s1.score < s2.score 
    GROUP BY
    	s1.id
    HAVING
    	COUNT( s2.id ) < 5
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    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    3. 最后根据 t_id 分类,score 倒序排序即可。

    题目二:获取每个科目下最后两名学生的成绩平均值

    取最后两名成绩

    SELECT
    	s1.* 
    FROM
    	student s1
    	LEFT JOIN student s2 ON s1.t_id = s2.t_id 
    	AND s1.score > s2.score 
    GROUP BY
    	s1.id 
    HAVING
    	COUNT( s1.id )< 2 
    ORDER BY
    	s1.t_id,
    	s1.score
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    并列存在情况下可能导致筛选出的同一t_id 下结果条数大于2条,但题目要求是取最后两名的平均值,多条平均后还是本身,故不必再对其处理,可以满足题目要求。

    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    分组求平均值:

    SELECT
    	t_id,AVG(score)
    FROM
    	(
    	SELECT
    		s1.*
    	FROM
    		student s1
    		LEFT JOIN student s2 ON s1.t_id = s2.t_id 
    		AND s1.score > s2.score
    	GROUP BY
    		s1.id 
    	HAVING
    		COUNT( s1.id )< 2 
    	ORDER BY
    		s1.t_id,
    		s1.score 
    	) tt 
    GROUP BY
    	t_id
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    结果:

    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    分析:

    1. 查询出所有t1.score>t2.score 的记录

    SELECT
    		s1.*,s2.*
    	FROM
    		student s1
    		LEFT JOIN student s2 ON s1.t_id = s2.t_id 
    		AND s1.score > s2.score
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    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    2. group by s.id 去重,having 计数取2条

    3. group by t_id 分别取各自学科的然后avg取均值

    题目三:获取每个科目下前五成绩排名(不允许并列)

    SELECT
    	* 
    FROM
    	(
    	SELECT
    		s1.*,
    		@rownum := @rownum + 1 AS num_tmp,
    		@incrnum :=
    	CASE
    			
    			WHEN @rowtotal = s1.score THEN
    			@incrnum 
    			WHEN @rowtotal := s1.score THEN
    			@rownum 
    		END AS rownum 
    	FROM
    		student s1
    		LEFT JOIN student s2 ON s1.t_id = s2.t_id 
    		AND s1.score > s2.score,
    		( SELECT @rownum := 0, @rowtotal := NULL, @incrnum := 0 ) AS it 
    	GROUP BY
    		s1.id 
    	ORDER BY
    		s1.t_id,
    		s1.score DESC 
    	) tt 
    GROUP BY
    	t_id,
    	score,
    	rownum 
    HAVING
    	COUNT( rownum )< 5
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    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    分析:

    1.引入辅助参数

    SELECT
    	s1.*,
    	@rownum := @rownum + 1 AS num_tmp,
    	@incrnum :=
    CASE
    		
    		WHEN @rowtotal = s1.score THEN
    		@incrnum 
    		WHEN @rowtotal := s1.score THEN
    		@rownum 
    	END AS rownum 
    FROM
    	student s1
    	LEFT JOIN student s2 ON s1.t_id = s2.t_id 
    	AND s1.score > s2.score,
    	( SELECT @rownum := 0, @rowtotal := NULL, @incrnum := 0 ) AS it
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    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    2.去除重复s1.id,分组排序

    SELECT
    		s1.*,
    		@rownum := @rownum + 1 AS num_tmp,
    		@incrnum :=
    	CASE
    			
    			WHEN @rowtotal = s1.score THEN
    			@incrnum 
    			WHEN @rowtotal := s1.score THEN
    			@rownum 
    		END AS rownum 
    	FROM
    		student s1
    		LEFT JOIN student s2 ON s1.t_id = s2.t_id 
    		AND s1.score > s2.score,
    		( SELECT @rownum := 0, @rowtotal := NULL, @incrnum := 0 ) AS it 
    	GROUP BY
    		s1.id 
    	ORDER BY
    		s1.t_id,
    		s1.score DESC
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    MySQL中分类排名和分组TOP N的示例分析-LMLPHP

    3.GROUP BY t_id, score, rownum 然后 HAVING 取前5条不重复的

    以上就是MySQL中分类排名和分组TOP N的示例分析的详细内容,更多请关注Work网其它相关文章!

    09-17 20:45