MySQL中的排名功能

Question

MySQL中的排名功能

我需要找出客户的排名.在这里,我为我的要求添加了相应的ANSI标准SQL查询.请帮我转换为MySQL.

SELECT RANK() OVER (PARTITION BY Gender ORDER BY Age) AS [Partition by Gender], 
  FirstName, 
  Age,
  Gender 
FROM Person

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有没有找到MySQL排名的函数？

Answer 1

Dan*_*llo 256

一种选择是使用排名变量,例如:

SELECT    first_name,
          age,
          gender,
          @curRank := @curRank + 1 AS rank
FROM      person p, (SELECT @curRank := 0) r
ORDER BY  age;

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该(SELECT @curRank := 0)部分允许变量初始化而无需单独的SET命令.

测试用例:

CREATE TABLE person (id int, first_name varchar(20), age int, gender char(1));

INSERT INTO person VALUES (1, 'Bob', 25, 'M');
INSERT INTO person VALUES (2, 'Jane', 20, 'F');
INSERT INTO person VALUES (3, 'Jack', 30, 'M');
INSERT INTO person VALUES (4, 'Bill', 32, 'M');
INSERT INTO person VALUES (5, 'Nick', 22, 'M');
INSERT INTO person VALUES (6, 'Kathy', 18, 'F');
INSERT INTO person VALUES (7, 'Steve', 36, 'M');
INSERT INTO person VALUES (8, 'Anne', 25, 'F');

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结果:

+------------+------+--------+------+
| first_name | age  | gender | rank |
+------------+------+--------+------+
| Kathy      |   18 | F      |    1 |
| Jane       |   20 | F      |    2 |
| Nick       |   22 | M      |    3 |
| Bob        |   25 | M      |    4 |
| Anne       |   25 | F      |    5 |
| Jack       |   30 | M      |    6 |
| Bill       |   32 | M      |    7 |
| Steve      |   36 | M      |    8 |
+------------+------+--------+------+
8 rows in set (0.02 sec)

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对于狡猾的内联初始化+1,这是一个很棒的技巧. (50认同)
他不是要求分区吗？我对分区的理解是,结果集对男性和女性都有不同的排名. (26认同)
如果我想给Anne和Bob两个等级排名怎么办？ (6认同)
这并没有实现问题中的例子,因为它错过了分析函数的"按性别划分"部分(对每个性别的"等级"*"编号"而不是整体结果) (6认同)
@Jesse：如果是这样的话，我最近回答了一个类似的问题：http://stackoverflow.com/questions/3162389/multiple-ranks-in-one-table/ (2认同)

Answer 2

Sal*_*n A 52

这是一个通用的解决方案,它将分区上的密集排名分配给行.它使用用户变量:

CREATE TABLE person (
    id INT NOT NULL PRIMARY KEY,
    firstname VARCHAR(10),
    gender VARCHAR(1),
    age INT
);

INSERT INTO person (id, firstname, gender, age) VALUES
(1,  'Adams',  'M', 33),
(2,  'Matt',   'M', 31),
(3,  'Grace',  'F', 25),
(4,  'Harry',  'M', 20),
(5,  'Scott',  'M', 30),
(6,  'Sarah',  'F', 30),
(7,  'Tony',   'M', 30),
(8,  'Lucy',   'F', 27),
(9,  'Zoe',    'F', 30),
(10, 'Megan',  'F', 26),
(11, 'Emily',  'F', 20),
(12, 'Peter',  'M', 20),
(13, 'John',   'M', 21),
(14, 'Kate',   'F', 35),
(15, 'James',  'M', 32),
(16, 'Cole',   'M', 25),
(17, 'Dennis', 'M', 27),
(18, 'Smith',  'M', 35),
(19, 'Zack',   'M', 35),
(20, 'Jill',   'F', 25);

SELECT person.*, @rank := CASE
    WHEN @partval = gender AND @rankval = age THEN @rank
    WHEN @partval = gender AND (@rankval := age) IS NOT NULL THEN @rank + 1
    WHEN (@partval := gender) IS NOT NULL AND (@rankval := age) IS NOT NULL THEN 1
END AS rnk
FROM person, (SELECT @rank := NULL, @partval := NULL, @rankval := NULL) AS x
ORDER BY gender, age;

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请注意,变量赋值放在CASE表达式中.这(理论上)负责评估问题的顺序.将IS NOT NULL被添加到处理数据类型转换和短路的问题.

PS:通过删除检查绑定的所有条件,可以轻松地将其转换为分区上的行号.

| id | firstname | gender | age | rank |
|----|-----------|--------|-----|------|
| 11 | Emily     | F      | 20  | 1    |
| 20 | Jill      | F      | 25  | 2    |
| 3  | Grace     | F      | 25  | 2    |
| 10 | Megan     | F      | 26  | 3    |
| 8  | Lucy      | F      | 27  | 4    |
| 6  | Sarah     | F      | 30  | 5    |
| 9  | Zoe       | F      | 30  | 5    |
| 14 | Kate      | F      | 35  | 6    |
| 4  | Harry     | M      | 20  | 1    |
| 12 | Peter     | M      | 20  | 1    |
| 13 | John      | M      | 21  | 2    |
| 16 | Cole      | M      | 25  | 3    |
| 17 | Dennis    | M      | 27  | 4    |
| 7  | Tony      | M      | 30  | 5    |
| 5  | Scott     | M      | 30  | 5    |
| 2  | Matt      | M      | 31  | 6    |
| 15 | James     | M      | 32  | 7    |
| 1  | Adams     | M      | 33  | 8    |
| 18 | Smith     | M      | 35  | 9    |
| 19 | Zack      | M      | 35  | 9    |

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演示db <>小提琴

这个解决方案，或 Mukesh 的解决方案，应该是正确的解决方案。尽管从技术上讲，我相信你们两个的解决方案都代表了 [密集排名](http://msdn.microsoft.com/en-us/library/ms173825.aspx) 而不是常规排名。这是对差异的一个很好的解释：http://www.sqlservercurry.com/2009/04/rank-vs-denserank-with-example-using.html。 (2认同)

Answer 3

Rah*_*wal 47

虽然最受欢迎的答案排名,但它没有分区,你可以自己加入以获得整个分区的东西:

SELECT    a.first_name,
      a.age,
      a.gender,
        count(b.age)+1 as rank
FROM  person a left join person b on a.age>b.age and a.gender=b.gender 
group by  a.first_name,
      a.age,
      a.gender

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用例

CREATE TABLE person (id int, first_name varchar(20), age int, gender char(1));

INSERT INTO person VALUES (1, 'Bob', 25, 'M');
INSERT INTO person VALUES (2, 'Jane', 20, 'F');
INSERT INTO person VALUES (3, 'Jack', 30, 'M');
INSERT INTO person VALUES (4, 'Bill', 32, 'M');
INSERT INTO person VALUES (5, 'Nick', 22, 'M');
INSERT INTO person VALUES (6, 'Kathy', 18, 'F');
INSERT INTO person VALUES (7, 'Steve', 36, 'M');
INSERT INTO person VALUES (8, 'Anne', 25, 'F');

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答案:

Bill    32  M   4
Bob     25  M   2
Jack    30  M   3
Nick    22  M   1
Steve   36  M   5
Anne    25  F   3
Jane    20  F   2
Kathy   18  F   1

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Answer 4

Muk*_*oni 24

丹尼尔版本的调整,以计算百分位数和排名.另外两个具有相同标记的人将获得相同的排名.

set @totalStudents = 0;
select count(*) into @totalStudents from marksheets;
SELECT id, score, @curRank := IF(@prevVal=score, @curRank, @studentNumber) AS rank, 
@percentile := IF(@prevVal=score, @percentile, (@totalStudents - @studentNumber + 1)/(@totalStudents)*100),
@studentNumber := @studentNumber + 1 as studentNumber, 
@prevVal:=score
FROM marksheets, (
SELECT @curRank :=0, @prevVal:=null, @studentNumber:=1, @percentile:=100
) r
ORDER BY score DESC

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查询样本数据的结果 -

+----+-------+------+---------------+---------------+-----------------+
| id | score | rank | percentile    | studentNumber | @prevVal:=score |
+----+-------+------+---------------+---------------+-----------------+
| 10 |    98 |    1 | 100.000000000 |             2 |              98 |
|  5 |    95 |    2 |  90.000000000 |             3 |              95 |
|  6 |    91 |    3 |  80.000000000 |             4 |              91 |
|  2 |    91 |    3 |  80.000000000 |             5 |              91 |
|  8 |    90 |    5 |  60.000000000 |             6 |              90 |
|  1 |    90 |    5 |  60.000000000 |             7 |              90 |
|  9 |    84 |    7 |  40.000000000 |             8 |              84 |
|  3 |    83 |    8 |  30.000000000 |             9 |              83 |
|  4 |    72 |    9 |  20.000000000 |            10 |              72 |
|  7 |    60 |   10 |  10.000000000 |            11 |              60 |
+----+-------+------+---------------+---------------+-----------------+

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Answer 5

era*_*dac 18

丹尼尔和萨尔曼的答案相结合.然而,等级不会给出存在关系的连续序列.相反,它会将排名跳到下一个.所以最大值总是达到行数.

    SELECT    first_name,
              age,
              gender,
              IF(age=@_last_age,@curRank:=@curRank,@curRank:=@_sequence) AS rank,
              @_sequence:=@_sequence+1,@_last_age:=age
    FROM      person p, (SELECT @curRank := 1, @_sequence:=1, @_last_age:=0) r
    ORDER BY  age;

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架构和测试用例:

CREATE TABLE person (id int, first_name varchar(20), age int, gender char(1));

INSERT INTO person VALUES (1, 'Bob', 25, 'M');
INSERT INTO person VALUES (2, 'Jane', 20, 'F');
INSERT INTO person VALUES (3, 'Jack', 30, 'M');
INSERT INTO person VALUES (4, 'Bill', 32, 'M');
INSERT INTO person VALUES (5, 'Nick', 22, 'M');
INSERT INTO person VALUES (6, 'Kathy', 18, 'F');
INSERT INTO person VALUES (7, 'Steve', 36, 'M');
INSERT INTO person VALUES (8, 'Anne', 25, 'F');
INSERT INTO person VALUES (9, 'Kamal', 25, 'M');
INSERT INTO person VALUES (10, 'Saman', 32, 'M');

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输出:

+------------+------+--------+------+--------------------------+-----------------+
| first_name | age  | gender | rank | @_sequence:=@_sequence+1 | @_last_age:=age |
+------------+------+--------+------+--------------------------+-----------------+
| Kathy      |   18 | F      |    1 |                        2 |              18 |
| Jane       |   20 | F      |    2 |                        3 |              20 |
| Nick       |   22 | M      |    3 |                        4 |              22 |
| Kamal      |   25 | M      |    4 |                        5 |              25 |
| Anne       |   25 | F      |    4 |                        6 |              25 |
| Bob        |   25 | M      |    4 |                        7 |              25 |
| Jack       |   30 | M      |    7 |                        8 |              30 |
| Bill       |   32 | M      |    8 |                        9 |              32 |
| Saman      |   32 | M      |    8 |                       10 |              32 |
| Steve      |   36 | M      |   10 |                       11 |              36 |
+------------+------+--------+------+--------------------------+-----------------+

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Answer 6

Luk*_*der 11

从MySQL 8开始，您最终还可以在MySQL中使用窗口函数：https : //dev.mysql.com/doc/refman/8.0/en/window-functions.html

您的查询可以完全相同的方式编写：

SELECT RANK() OVER (PARTITION BY Gender ORDER BY Age) AS `Partition by Gender`, 
  FirstName, 
  Age,
  Gender 
FROM Person

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@ brand-it对于MySQL 8+上的用户，此答案很重要，因为它使我们知道Rank现在可用。如果我没有向下滚动那么远，我会认为较早的答案是唯一的解决方案。 (2认同)

Answer 7

Dav*_*ian 5

@Sam,你的观点非常出色,但我认为你误解了MySQL文档在引用的页面上说的内容 - 或者我误解了:-) - 我只想添加这个,以便如果有人对@感到不舒服丹尼尔回答他们会更放心,或者至少深入挖掘一下.

您在SELECT中看到"@curRank:= @curRank + 1 AS等级"不是"一个语句",它是语句的一个"原子"部分,因此它应该是安全的.

您引用的文档继续显示在语句的2(原子)部分中相同的用户定义变量的示例,例如,"SELECT @curRank,@curRank:= @curRank + 1 AS rank".

有人可能会说@curRank在@ Daniel的回答中使用了两次:(1)"@curRank:= @curRank + 1 AS等级"和(2)"(SELECT @curRank:= 0)r"但是从第二次开始用法是FROM子句的一部分,我很确定它可以保证首先被评估; 基本上使它成为第二个和前面的声明.

事实上,在您引用的同一个MySQL文档页面上,您将在评论中看到相同的解决方案 - 它可能是@Daniel从中得到的; 是的,我知道这是评论,但它是官方文档页面上的评论,并确实带来了一些重量.

Answer 8

Sal*_*n A 5

确定给定值排名的最直接解决方案是计算该值之前的值的数量。假设我们有以下值：

10 20 30 30 30 40

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所有30值均被视为第三个
所有40值均被视为第六（排名）或第四（密集排名）

现在回到原来的问题。以下是一些示例数据，按照 OP 中的描述进行排序（预期排名添加在右侧）：

+------+-----------+------+--------+    +------+------------+
| id   | firstname | age  | gender |    | rank | dense_rank |
+------+-----------+------+--------+    +------+------------+
|   11 | Emily     |   20 | F      |    |    1 |          1 |
|    3 | Grace     |   25 | F      |    |    2 |          2 |
|   20 | Jill      |   25 | F      |    |    2 |          2 |
|   10 | Megan     |   26 | F      |    |    4 |          3 |
|    8 | Lucy      |   27 | F      |    |    5 |          4 |
|    6 | Sarah     |   30 | F      |    |    6 |          5 |
|    9 | Zoe       |   30 | F      |    |    6 |          5 |
|   14 | Kate      |   35 | F      |    |    8 |          6 |
|    4 | Harry     |   20 | M      |    |    1 |          1 |
|   12 | Peter     |   20 | M      |    |    1 |          1 |
|   13 | John      |   21 | M      |    |    3 |          2 |
|   16 | Cole      |   25 | M      |    |    4 |          3 |
|   17 | Dennis    |   27 | M      |    |    5 |          4 |
|    5 | Scott     |   30 | M      |    |    6 |          5 |
|    7 | Tony      |   30 | M      |    |    6 |          5 |
|    2 | Matt      |   31 | M      |    |    8 |          6 |
|   15 | James     |   32 | M      |    |    9 |          7 |
|    1 | Adams     |   33 | M      |    |   10 |          8 |
|   18 | Smith     |   35 | M      |    |   11 |          9 |
|   19 | Zack      |   35 | M      |    |   11 |          9 |
+------+-----------+------+--------+    +------+------------+

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要计算RANK() OVER (PARTITION BY Gender ORDER BY Age)Sarah ，您可以使用以下查询：

SELECT COUNT(id) + 1 AS rank, COUNT(DISTINCT age) + 1 AS dense_rank
FROM testdata
WHERE gender = (SELECT gender FROM testdata WHERE id = 6)
AND age < (SELECT age FROM testdata WHERE id = 6)

+------+------------+
| rank | dense_rank |
+------+------------+
|    6 |          5 |
+------+------------+

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要计算RANK() OVER (PARTITION BY Gender ORDER BY Age)所有行，您可以使用以下查询：

SELECT testdata.id, COUNT(lesser.id) + 1 AS rank, COUNT(DISTINCT lesser.age) + 1 AS dense_rank
FROM testdata
LEFT JOIN testdata AS lesser ON lesser.age < testdata.age AND lesser.gender = testdata.gender
GROUP BY testdata.id

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这是结果（连接值添加在右侧）：

+------+------+------------+    +-----------+-----+--------+
| id   | rank | dense_rank |    | firstname | age | gender |
+------+------+------------+    +-----------+-----+--------+
|   11 |    1 |          1 |    | Emily     |  20 | F      |
|    3 |    2 |          2 |    | Grace     |  25 | F      |
|   20 |    2 |          2 |    | Jill      |  25 | F      |
|   10 |    4 |          3 |    | Megan     |  26 | F      |
|    8 |    5 |          4 |    | Lucy      |  27 | F      |
|    6 |    6 |          5 |    | Sarah     |  30 | F      |
|    9 |    6 |          5 |    | Zoe       |  30 | F      |
|   14 |    8 |          6 |    | Kate      |  35 | F      |
|    4 |    1 |          1 |    | Harry     |  20 | M      |
|   12 |    1 |          1 |    | Peter     |  20 | M      |
|   13 |    3 |          2 |    | John      |  21 | M      |
|   16 |    4 |          3 |    | Cole      |  25 | M      |
|   17 |    5 |          4 |    | Dennis    |  27 | M      |
|    5 |    6 |          5 |    | Scott     |  30 | M      |
|    7 |    6 |          5 |    | Tony      |  30 | M      |
|    2 |    8 |          6 |    | Matt      |  31 | M      |
|   15 |    9 |          7 |    | James     |  32 | M      |
|    1 |   10 |          8 |    | Adams     |  33 | M      |
|   18 |   11 |          9 |    | Smith     |  35 | M      |
|   19 |   11 |          9 |    | Zack      |  35 | M      |
+------+------+------------+    +-----------+-----+--------+

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