标签:临时 添加 ota char 部分 var 的区别 val 行数据
接下来再走一步,让我们看看一条SQL语句的前世今生。首先看一下示例语句:
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:
1 FROM <left_table>
2 ON <join_condition>
3 <join_type> JOIN <right_table> 第二步和第三步会循环执行
4 WHERE <where_condition> 第四步会循环执行,多个条件的执行顺序是从左往右的。
5 GROUP BY <group_by_list>
6 HAVING <having_condition>
7 SELECT 分组之后才会执行SELECT
8 DISTINCT <select_list>
9 ORDER BY <order_by_condition>
10 LIMIT <limit_number>前9步都是SQL92标准语法。limit是MySQL的独有语法。
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。
create database testQuery
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;
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);
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!
对FROM的左边的表和右边的表计算笛卡尔积(CROSS JOIN)。产生虚表VT1
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 |
+-----+------+-----+------+
rows in set (0.00 sec)
对虚表VT1进行ON筛选,只有那些符合 <join-condition> 的行才会被记录在虚表VT2中。
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;
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 |
+-----+------+-----+------+
rows in set (0.00 sec)
如果指定了OUTER JOIN(比如left join、 right join),那么保留表中未匹配的行就会作为外部行添加到虚拟表VT2中,产生虚拟表VT3。
如果FROM子句中包含两个以上的表的话,那么就会对上一个join连接产生的结果VT3和下一个表重复执行步骤1~3这三个步骤,一直到处理完所有的表为止。
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 |
+-----+------+------+------+
rows in set (0.00 sec)
对虚拟表VT3进行WHERE条件过滤。只有符合<where-condition>的记录才会被插入到虚拟表VT4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;
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 |
+-----+------+------+------+
rows in set (0.00 sec)
根据group by子句中的列,对VT4中的记录进行分组操作,产生虚拟表VT5。
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;
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 |
+-----+------+------+------+
rows in set (0.00 sec)
对虚拟表VT5应用having过滤,只有符合<having-condition>的记录才会被 插入到虚拟表VT6中。
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 |
+-----+------+------+------+
rows in set (0.00 sec)
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
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。
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 |
+-----+-------+
rows in set (0.00 sec)
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;
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 |
+-----+-------+
rows in set (0.00 sec)
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
mysql> SELEC
-> 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 |
+-----+-------+
row in set (0.00 sec)
FROM(将最近的两张表,进行笛卡尔积)---VT1
ON(将VT1按照它的条件进行过滤)---VT2
LEFT JOIN(保留左表的记录)---VT3
WHERE(过滤VT3中的记录)--VT4…VTn
GROUP BY(对VT4的记录进行分组)---VT5
HAVING(对VT5中的记录进行过滤)---VT6
SELECT(对VT6中的记录,选取指定的列)--VT7
ORDER BY(对VT7的记录进行排序)--VT8
单表查询:根据WHERE条件过滤表中的记录,形成中间表(这个中间表对用户是不可见的);然后根据SELECT的选择列选择相应的列进行返回最终结果。
两表连接查询:对两表求积(笛卡尔积)并用ON条件和连接连接类型进行过滤形成中间表;然后根据WHERE条件过滤中间表的记录,并根据SELECT指定的列返回查询结果。
笛卡尔积:行相乘、列相加。
多表连接查询:先对第一个和第二个表按照两表连接做查询,然后用查询结果和第三个表做连接查询,以此类推,直到所有的表都连接上为止,最终形成一个中间的结果表,然后根据WHERE条件过滤中间表的记录,并根据SELECT指定的列返回查询结果。
WHERE条件解析顺序
MySQL:从左往右去执行WHERE条件的。
写WHERE条件的时候,优先级高的部分要去编写过滤力度最大的条件语句。
标签:临时 添加 ota char 部分 var 的区别 val 行数据
原文地址:https://blog.51cto.com/14901322/2520820