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MySQL架构总览->查询执行流程->SQL解析顺序

时间：2021-07-01 10:21:17 帮助过：34人阅读

SELECT DISTINCT
    < select_list >
FROM
    < left_table > < join_type >
JOIN < right_table > ON < join_condition >
WHERE
    < where_condition >
GROUP BY
    < group_by_list >
HAVING
    < having_condition >
ORDER BY
    < order_by_condition >
LIMIT < limit_number >

　　然而它的执行顺序是这样的技术分享

 1 FROM <left_table>
 2 ON <join_condition>
 3 <join_type> JOIN <right_table>
 4 WHERE <where_condition>
 5 GROUP BY <group_by_list>
 6 HAVING <having_condition>
 7 SELECT 
 8 DISTINCT <select_list>
 9 ORDER BY <order_by_condition>
10 LIMIT <limit_number>

　　虽然自己没想到是这样的，不过一看还是很自然和谐的，从哪里获取，不断的过滤条件，要选择一样或不一样的，排好序，那才知道要取前几条呢。既然如此了，那就让我们一步步来看看其中的细节吧。 准备工作 　　1.创建测试数据库

create database testQuery

　　2.创建测试表

CREATE TABLE table1
(
    uid VARCHAR(10) NOT NULL,
    name VARCHAR(10) NOT NULL,
    PRIMARY KEY(uid)
)ENGINE=INNODB DEFAULT CHARSET=UTF8;

CREATE TABLE table2
(
    oid INT NOT NULL auto_increment,
    uid VARCHAR(10),
    PRIMARY KEY(oid)
)ENGINE=INNODB DEFAULT CHARSET=UTF8;

　　3.插入数据

INSERT INTO table1(uid,name) VALUES(‘aaa‘,‘mike‘),(‘bbb‘,‘jack‘),(‘ccc‘,‘mike‘),(‘ddd‘,‘mike‘);

INSERT INTO table2(uid) VALUES(‘aaa‘),(‘aaa‘),(‘bbb‘),(‘bbb‘),(‘bbb‘),(‘ccc‘),(NULL);

　　4.最后想要的结果

SELECT
    a.uid,
    count(b.oid) AS total
FROM
    table1 AS a
LEFT JOIN table2 AS b ON a.uid = b.uid
WHERE
    a. NAME = ‘mike‘
GROUP BY
    a.uid
HAVING
    count(b.oid) < 2
ORDER BY
    total DESC
LIMIT 1;

！现在开始SQL解析之旅吧！ 1. FROM 当涉及多个表的时候，左边表的输出会作为右边表的输入，之后会生成一个虚拟表VT1。 (1-J1)笛卡尔积计算两个相关联表的笛卡尔积(CROSS JOIN) ，生成虚拟表VT1-J1。技术分享

mysql> select * from table1,table2;
+-----+------+-----+------+
| uid | name | oid | uid  |
+-----+------+-----+------+
| aaa | mike |   1 | aaa  |
| bbb | jack |   1 | aaa  |
| ccc | mike |   1 | aaa  |
| ddd | mike |   1 | aaa  |
| aaa | mike |   2 | aaa  |
| bbb | jack |   2 | aaa  |
| ccc | mike |   2 | aaa  |
| ddd | mike |   2 | aaa  |
| aaa | mike |   3 | bbb  |
| bbb | jack |   3 | bbb  |
| ccc | mike |   3 | bbb  |
| ddd | mike |   3 | bbb  |
| aaa | mike |   4 | bbb  |
| bbb | jack |   4 | bbb  |
| ccc | mike |   4 | bbb  |
| ddd | mike |   4 | bbb  |
| aaa | mike |   5 | bbb  |
| bbb | jack |   5 | bbb  |
| ccc | mike |   5 | bbb  |
| ddd | mike |   5 | bbb  |
| aaa | mike |   6 | ccc  |
| bbb | jack |   6 | ccc  |
| ccc | mike |   6 | ccc  |
| ddd | mike |   6 | ccc  |
| aaa | mike |   7 | NULL |
| bbb | jack |   7 | NULL |
| ccc | mike |   7 | NULL |
| ddd | mike |   7 | NULL |
+-----+------+-----+------+
28 rows in set (0.00 sec)

(1-J2)ON过滤基于虚拟表VT1-J1这一个虚拟表进行过滤，过滤出所有满足ON 谓词条件的列，生成虚拟表VT1-J2。注意：这里因为语法限制，使用了‘WHERE‘代替，从中读者也可以感受到两者之间微妙的关系；技术分享

mysql> SELECT
    -> *
    -> FROM
    -> table1,
    -> table2
    -> WHERE
    -> table1.uid = table2.uid
    -> ;
+-----+------+-----+------+
| uid | name | oid | uid  |
+-----+------+-----+------+
| aaa | mike |   1 | aaa  |
| aaa | mike |   2 | aaa  |
| bbb | jack |   3 | bbb  |
| bbb | jack |   4 | bbb  |
| bbb | jack |   5 | bbb  |
| ccc | mike |   6 | ccc  |
+-----+------+-----+------+
6 rows in set (0.00 sec)

(1-J3)添加外部列如果使用了外连接(LEFT,RIGHT,FULL)，主表（保留表）中的不符合ON条件的列也会被加入到VT1-J2中，作为外部行，生成虚拟表VT1-J3。技术分享

mysql> SELECT
    -> *
    -> FROM
    -> table1 AS a
    -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid;
+-----+------+------+------+
| uid | name | oid  | uid  |
+-----+------+------+------+
| aaa | mike |    1 | aaa  |
| aaa | mike |    2 | aaa  |
| bbb | jack |    3 | bbb  |
| bbb | jack |    4 | bbb  |
| bbb | jack |    5 | bbb  |
| ccc | mike |    6 | ccc  |
| ddd | mike | NULL | NULL |
+-----+------+------+------+
7 rows in set (0.00 sec)

下面从网上找到一张很形象的关于‘SQL JOINS‘的解释图，如若侵犯了你的权益，请劳烦告知删除，谢谢。技术分享

2. WHERE 对VT1过程中生成的临时表进行过滤，满足WHERE子句的列被插入到VT2表中。注意：此时因为分组，不能使用聚合运算；也不能使用SELECT中创建的别名；与ON的区别：如果有外部列，ON针对过滤的是关联表，主表（保留表）会返回所有的列；如果没有添加外部列，两者的效果是一样的；应用：对主表的过滤应该放在WHERE；对于关联表，先条件查询后连接则用ON，先连接后条件查询则用WHERE；技术分享

mysql> SELECT
    -> *
    -> FROM
    -> table1 AS a
    -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid
    -> WHERE
    -> a. NAME = ‘mike‘;
+-----+------+------+------+
| uid | name | oid  | uid  |
+-----+------+------+------+
| aaa | mike |    1 | aaa  |
| aaa | mike |    2 | aaa  |
| ccc | mike |    6 | ccc  |
| ddd | mike | NULL | NULL |
+-----+------+------+------+
4 rows in set (0.00 sec)

3. GROUP BY 这个子句会把VT2中生成的表按照GROUP BY中的列进行分组。生成VT3表。注意：其后处理过程的语句，如SELECT,HAVING，所用到的列必须包含在GROUP BY中，对于没有出现的，得用聚合函数；原因： GROUP BY改变了对表的引用，将其转换为新的引用方式，能够对其进行下一级逻辑操作的列会减少；我的理解是：根据分组字段，将具有相同分组字段的记录归并成一条记录，因为每一个分组只能返回一条记录，除非是被过滤掉了，而不在分组字段里面的字段可能会有多个值，多个值是无法放进一条记录的，所以必须通过聚合函数将这些具有多值的列转换成单值；技术分享

mysql> SELECT
    -> *
    -> FROM
    -> table1 AS a
    -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid
    -> WHERE
    -> a. NAME = ‘mike‘
    -> GROUP BY
    -> a.uid;
+-----+------+------+------+
| uid | name | oid  | uid  |
+-----+------+------+------+
| aaa | mike |    1 | aaa  |
| ccc | mike |    6 | ccc  |
| ddd | mike | NULL | NULL |
+-----+------+------+------+
3 rows in set (0.00 sec)

4. HAVING 这个子句对VT3表中的不同的组进行过滤，只作用于分组后的数据，满足HAVING条件的子句被加入到VT4表中。技术分享

mysql> SELECT
    -> *
    -> FROM
    -> table1 AS a
    -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid
    -> WHERE
    -> a. NAME = ‘mike‘
    -> GROUP BY
    -> a.uid
    -> HAVING
    -> count(b.oid) < 2;
+-----+------+------+------+
| uid | name | oid  | uid  |
+-----+------+------+------+
| ccc | mike |    6 | ccc  |
| ddd | mike | NULL | NULL |
+-----+------+------+------+
2 rows in set (0.00 sec)

5. SELECT 这个子句对SELECT子句中的元素进行处理，生成VT5表。 (5-J1)计算表达式计算SELECT 子句中的表达式，生成VT5-J1 (5-J2)DISTINCT 寻找VT5-1中的重复列，并删掉，生成VT5-J2 如果在查询中指定了DISTINCT子句，则会创建一张内存临时表（如果内存放不下，就需要存放在硬盘了）。这张临时表的表结构和上一步产生的虚拟表VT5是一样的，不同的是对进行DISTINCT操作的列增加了一个唯一索引，以此来除重复数据。技术分享

mysql> SELECT
    -> a.uid,
    -> count(b.oid) AS total
    -> FROM
    -> table1 AS a
    -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid
    -> WHERE
    -> a. NAME = ‘mike‘
    -> GROUP BY
    -> a.uid
    -> HAVING
    -> count(b.oid) < 2;
+-----+-------+
| uid | total |
+-----+-------+
| ccc |     1 |
| ddd |     0 |
+-----+-------+
2 rows in set (0.00 sec)

6.ORDER BY 从VT5-J2中的表中，根据ORDER BY 子句的条件对结果进行排序，生成VT6表。注意：唯一可使用SELECT中别名的地方；技术分享

mysql> SELECT
    -> a.uid,
    -> count(b.oid) AS total
    -> FROM
    -> table1 AS a
    -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid
    -> WHERE
    -> a. NAME = ‘mike‘
    -> GROUP BY
    -> a.uid
    -> HAVING
    -> count(b.oid) < 2
    -> ORDER BY
    -> total DESC;
+-----+-------+
| uid | total |
+-----+-------+
| ccc |     1 |
| ddd |     0 |
+-----+-------+
2 rows in set (0.00 sec)

7.LIMIT LIMIT子句从上一步得到的VT6虚拟表中选出从指定位置开始的指定行数据。注意： offset和rows的正负带来的影响；当偏移量很大时效率是很低的，可以这么做：采用子查询的方式优化，在子查询里先从索引获取到最大id，然后倒序排，再取N行结果集采用INNER JOIN优化，JOIN子句里也优先从索引获取ID列表，然后直接关联查询获得最终结果技术分享

mysql> SELECT
    -> a.uid,
    -> count(b.oid) AS total
    -> FROM
    -> table1 AS a
    -> LEFT JOIN table2 AS b ON a.uid = b.uid
    -> WHERE
    -> a. NAME = ‘mike‘
    -> GROUP BY
    -> a.uid
    -> HAVING
    -> count(b.oid) < 2
    -> ORDER BY
    -> total DESC
    -> LIMIT 1;
+-----+-------+
| uid | total |
+-----+-------+
| ccc |     1 |
+-----+-------+
1 row in set (0.00 sec)

至此SQL的解析之旅就结束了，上图总结一下：技术分享

参考书籍： 《MySQL性能调优与架构实践》《MySQL技术内幕：SQL编程》

MySQL架构总览->查询执行流程->SQL解析顺序

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MySQL架构总览->查询执行流程->SQL解析顺序

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