MySQL3 数据查询 SQL语句个人总结

在使用数据库的时候一般都是查询居多

排序 order by

order by 默认是从小到大排, 可以添加 desc 参数,让查询结果从大到小排, 如:

mysql> select * from python order by id ;
+----+---------+--------+
| id | name    | is_del |
+----+---------+--------+
|  1 | pycharm |      1 |
|  2 | bb      |      0 |
|  3 | cc      |      0 |
|  4 | dd      |      0 |
+----+---------+--------+
4 rows in set (0.00 sec)

mysql> select * from python order by id desc;
+----+---------+--------+
| id | name    | is_del |
+----+---------+--------+
|  4 | dd      |      0 |
|  3 | cc      |      0 |
|  2 | bb      |      0 |
|  1 | pycharm |      1 |
+----+---------+--------+
4 rows in set (0.00 sec)

在使用desc参数后我们可以明显发现查询结果的顺序已经是反过来了,也就是说,desc 可以让 order by 排序从大到小进行排序

聚合函数 count avg max min sum

聚合函数一般是用在字段中的,也有是用在整条数据上的,如:count
统计该数据表有多少条数据

mysql> select count(*) from python order by id desc;
+-----------+
| count(*) |
+-----------+
|         4 |
+-----------+
1 row in set (0.10 sec)

求平均值

mysql> select avg(id) from python order by id desc;
+---------+
| avg(id) |
+---------+
|  2.5000 |
+---------+
1 row in set (0.10 sec)

求和:

mysql> select sum(id) from  order by id desc;
+---------+
| sum(id) |
+---------+
|      10 |
+---------+
1 row in set (0.00 sec)

最大,最小:

mysql> select max(id) from python order by id desc;
+---------+
| max(id) |
+---------+
|       4 |
+---------+
1 row in set (0.00 sec)
mysql> select min(id) from python order by id desc;
+---------+
| min(id) |
+---------+
|       1 |
+---------+
1 row in set (0.00 sec)

可以看到,聚合函数是可以和order by 排序 配合使用的

分组 group by

group by 是给字段进行分组的, 如:

mysql> select is_del from python group by is_del;
+--------+
| is_del |
+--------+
|      1 |
|      0 |
+--------+
2 rows in set (0.00 sec)

给 is_del 字段进行分组, 相当与去重,查询该字段的唯一值

group by + group_concat 可以在分组的同时输出其他字段的值, 如:

mysql> select is_del, group_concat(name), group_concat(id) from python group by is_del;
+--------+--------------------+------------------+
| is_del | group_concat(name) | group_concat(id) |
+--------+--------------------+------------------+
|      0 | bb,cc              | 2,3              |
|      1 | pycharm,dd         | 1,4              |
+--------+--------------------+------------------+
2 rows in set (0.00 sec)

group by 也可以配合聚合函数进行所有, 如:

mysql> select is_del, group_concat(name), avg(id) from python group by is_del;
+--------+--------------------+---------+
| is_del | group_concat(name) | avg(id) |
+--------+--------------------+---------+
|      0 | bb,cc              |  2.5000 |
|      1 | pycharm,dd         |  2.5000 |
+--------+--------------------+---------+
2 rows in set (0.00 sec)

分页 limit

在一个数据表中,如果该表中的数据过多的时候我们可以使用limit进行分页,limit 分页使用两个参数,
开始页, 一页有多少个数据, 如:

mysql> select * from python limit 0, 2;
+----+---------+--------+
| id | name    | is_del |
+----+---------+--------+
|  1 | pycharm |      1 |
|  2 | bb      |      0 |
+----+---------+--------+
2 rows in set (0.00 sec)

0 是开始的页数,2 是展示多少条数据

连接查询,一个完整的项目是会有很多数据表的,表与表之间组成关联性数据库

在整表与表之间的查询就是连接查询了,
MySQL中有 三种连接,内连接,左连接,右连接, 也可以称为两种,内连接,外连接

先创建golang数据表

CREATE TABLE `golang`  (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `name` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
  `py_id` int(11) NULL DEFAULT NULL,
  PRIMARY KEY (`id`) USING BTREE,
  INDEX `py_id`(`py_id`) USING BTREE,
  CONSTRAINT `py_id` FOREIGN KEY (`py_id`) REFERENCES `python` (`id`) ON DELETE RESTRICT ON UPDATE RESTRICT
) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;

-- ----------------------------
-- Records of golang
-- ----------------------------
INSERT INTO `golang` VALUES (1, ‘lawang‘, 1);

给golang数据表添加一个数据,关联python中的 id 为 1 的数据
内连接:

mysql> select * from python inner join golang on golang.py_id = python.id;
+----+---------+--------+----+--------+-------+
| id | name    | is_del | id | name   | py_id |
+----+---------+--------+----+--------+-------+
|  1 | pycharm |      1 |  1 | lawang |     1 |
+----+---------+--------+----+--------+-------+
1 row in set (0.00 sec)

左连接:

mysql> select * from python left join golang on golang.py_id = python.id;
+----+---------+--------+------+--------+-------+
| id | name    | is_del | id   | name   | py_id |
+----+---------+--------+------+--------+-------+
|  1 | pycharm |      1 |    1 | lawang |     1 |
|  2 | bb      |      0 | NULL | NULL   |  NULL |
|  3 | cc      |      0 | NULL | NULL   |  NULL |
|  4 | dd      |      1 | NULL | NULL   |  NULL |
+----+---------+--------+------+--------+-------+
4 rows in set (0.00 sec)

右连接:

mysql> select * from python right join golang on golang.py_id = python.id;
+------+---------+--------+----+--------+-------+
| id   | name    | is_del | id | name   | py_id |
+------+---------+--------+----+--------+-------+
|    1 | pycharm |      1 |  1 | lawang |     1 |
+------+---------+--------+----+--------+-------+
1 row in set (0.00 sec)

其实左右连接都差不多的,就是以哪边查询为做,如上面的左连接,已python数据表为主,查询左右边共有的,和左边满足条件的,右连接是以右边的数据库为主,牢记一种就可以了,

自关联

自关联就是在一个数据表中,数据记录之间自己关联自己表中的其他数据,在一种表中完成主键和外键的我们称为自关联, 自己关联自己,这种查询很简单,通过是否有外键值就可以判断该条数据是否是第一级, 拥有外将值得就是非第一级,如,查询所有第一级的数据, 假如python数据表中有 f_k 外键字段:

select * from pyton where f_k (f_k 表示外键字段) is null;

子查询

子查询就是在一个 select 语句中,嵌入了另外一个 select 语句, 这样的SQL语句嵌套就是子查询, 自查询一个是将嵌入的SQL语句的结果当做主查询的条件来使用的, 如:

mysql> select * from python where  id in (select py_id from golang);
+----+---------+--------+
| id | name    | is_del |
+----+---------+--------+
|  1 | pycharm |      1 |
+----+---------+--------+
1 row in set (0.09 sec)

我们可以将子查询的数据当做主查询的条件来进行主查询了使用;

MySQL3 数据查询 SQL语句个人总结

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