join 用于多表中字段之间的联系,语法如下:
... FROM table1 INNER|LEFT|RIGHT JOIN table2 ON conditiona
table1:左表;table2:右表。
JOIN 按照功能大致分为如下三类:
INNER JOIN(内连接,或等值连接):取得两个表中存在连接匹配关系的记录。
LEFT JOIN(左连接):取得左表(table1)完全记录,即是右表(table2)并无对应匹配记录。
RIGHT JOIN(右连接):与 LEFT JOIN 相反,取得右表(table2)完全记录,即是左表(table1)并无匹配对应记录。
注意:mysql不支持Full join,不过可以通过UNION 关键字来合并 LEFT JOIN 与 RIGHT JOIN来模拟FULL join.
接下来给出一个列子用于解释下面几种分类。如下两个表(A,B)
mysql> select A.id,A.name,B.name from A,B where A.id=B.id;
+----+-----------+-------------+
| id | name | name |
+----+-----------+-------------+
| 1 | Pirate | Rutabaga |
| 2 | Monkey | Pirate |
| 3 | Ninja | Darth Vader |
| 4 | Spaghetti | Ninja |
+----+-----------+-------------+
4 rows in set (0.00 sec)
内连接,也叫等值连接,inner join产生同时符合A和B的一组数据。
mysql> select * from A inner join B on A.name = B.name;
+----+--------+----+--------+
| id | name | id | name |
+----+--------+----+--------+
| 1 | Pirate | 2 | Pirate |
| 3 | Ninja | 4 | Ninja |
+----+--------+----+--------+
mysql> select * from A left join B on A.name = B.name;
#或者:select * from A left outer join B on A.name = B.name;
+----+-----------+------+--------+
| id | name | id | name |
+----+-----------+------+--------+
| 1 | Pirate | 2 | Pirate |
| 2 | Monkey | NULL | NULL |
| 3 | Ninja | 4 | Ninja |
| 4 | Spaghetti | NULL | NULL |
+----+-----------+------+--------+
4 rows in set (0.00 sec)
left join,(或left outer join:在Mysql中两者等价,推荐使用left join.)左连接从左表(A)产生一套完整的记录,与匹配的记录(右表(B)) .如果没有匹配,右侧将包含null。
如果想只从左表(A)中产生一套记录,但不包含右表(B)的记录,可以通过设置where语句来执行,如下:
mysql> select * from A left join B on A.name=B.name where A.id is null or B.id is null;
+----+-----------+------+------+
| id | name | id | name |
+----+-----------+------+------+
| 2 | Monkey | NULL | NULL |
| 4 | Spaghetti | NULL | NULL |
+----+-----------+------+------+
2 rows in set (0.00 sec)
同理,还可以模拟inner join. 如下:
mysql> select * from A left join B on A.name=B.name where A.id is not null and B.id is not null;
+----+--------+------+--------+
| id | name | id | name |
+----+--------+------+--------+
| 1 | Pirate | 2 | Pirate |
| 3 | Ninja | 4 | Ninja |
+----+--------+------+--------+
2 rows in set (0.00 sec)
求差集:
根据上面的例子可以求差集,如下:
SELECT * FROM A LEFT JOIN B ON A.name = B.name
WHERE B.id IS NULL
union
SELECT * FROM A right JOIN B ON A.name = B.name
WHERE A.id IS NULL;
# 结果
+------+-----------+------+-------------+
| id | name | id | name |
+------+-----------+------+-------------+
| 2 | Monkey | NULL | NULL |
| 4 | Spaghetti | NULL | NULL |
| NULL | NULL | 1 | Rutabaga |
| NULL | NULL | 3 | Darth Vader |
+------+-----------+------+-------------+
mysql> select * from A right join B on A.name = B.name;
+------+--------+----+-------------+
| id | name | id | name |
+------+--------+----+-------------+
| NULL | NULL | 1 | Rutabaga |
| 1 | Pirate | 2 | Pirate |
| NULL | NULL | 3 | Darth Vader |
| 3 | Ninja | 4 | Ninja |
+------+--------+----+-------------+
4 rows in set (0.00 sec)
同left join。
cross join:交叉连接,得到的结果是两个表的乘积,即笛卡尔积
笛卡尔(Descartes)乘积又叫直积。假设集合A={a,b},集合B={0,1,2},则两个集合的笛卡尔积为{(a,0),(a,1),(a,2),(b,0),(b,1), (b,2)}。可以扩展到多个集合的情况。类似的例子有,如果A表示某学校学生的集合,B表示该学校所有课程的集合,则A与B的笛卡尔积表示所有可能的选课情况。
mysql> select * from A cross join B;
+----+-----------+----+-------------+
| id | name | id | name |
+----+-----------+----+-------------+
| 1 | Pirate | 1 | Rutabaga |
| 2 | Monkey | 1 | Rutabaga |
| 3 | Ninja | 1 | Rutabaga |
| 4 | Spaghetti | 1 | Rutabaga |
| 1 | Pirate | 2 | Pirate |
| 2 | Monkey | 2 | Pirate |
| 3 | Ninja | 2 | Pirate |
| 4 | Spaghetti | 2 | Pirate |
| 1 | Pirate | 3 | Darth Vader |
| 2 | Monkey | 3 | Darth Vader |
| 3 | Ninja | 3 | Darth Vader |
| 4 | Spaghetti | 3 | Darth Vader |
| 1 | Pirate | 4 | Ninja |
| 2 | Monkey | 4 | Ninja |
| 3 | Ninja | 4 | Ninja |
| 4 | Spaghetti | 4 | Ninja |
+----+-----------+----+-------------+
16 rows in set (0.00 sec)
#再执行:mysql> select * from A inner join B; 试一试
#在执行mysql> select * from A cross join B on A.name = B.name; 试一试
实际上,在 MySQL 中(仅限于 MySQL) CROSS JOIN 与 INNER JOIN 的表现是一样的,在不指定 ON 条件得到的结果都是笛卡尔积,反之取得两个表完全匹配的结果。INNER JOIN 与 CROSS JOIN 可以省略 INNER 或 CROSS 关键字,因此下面的 SQL 效果是一样的:
... FROM table1 INNER JOIN table2
... FROM table1 CROSS JOIN table2
... FROM table1 JOIN table2
mysql> select * from A left join B on B.name = A.name
-> union
-> select * from A right join B on B.name = A.name;
+------+-----------+------+-------------+
| id | name | id | name |
+------+-----------+------+-------------+
| 1 | Pirate | 2 | Pirate |
| 2 | Monkey | NULL | NULL |
| 3 | Ninja | 4 | Ninja |
| 4 | Spaghetti | NULL | NULL |
| NULL | NULL | 1 | Rutabaga |
| NULL | NULL | 3 | Darth Vader |
+------+-----------+------+-------------+
6 rows in set (0.00 sec)
全连接产生的所有记录(双方匹配记录)在表A和表B。如果没有匹配,则对面将包含null。
如:
select * from
table a inner join table b
on a.id = b.id;
VS
select a.*, b.*
from table a, table b
where a.id = b.id;
我在数据库中比较(10w数据)得之,它们用时几乎相同,第一个是显示的inner join,后一个是隐式的inner join。
参照:Explicit vs implicit SQL joins
尽量用inner join.避免 LEFT JOIN 和 NULL.
在使用left join(或right join)时,应该清楚的知道以下几点:
ON 条件(“A LEFT JOIN B ON 条件表达式”中的ON)用来决定如何从 B 表中检索数据行。如果 B 表中没有任何一行数据匹配 ON 的条件,将会额外生成一行所有列为 NULL 的数据,在匹配阶段 WHERE 子句的条件都不会被使用。仅在匹配阶段完成以后,WHERE 子句条件才会被使用。它将从匹配阶段产生的数据中检索过滤。
所以我们要注意:在使用Left (right) join的时候,一定要在先给出尽可能多的匹配满足条件,减少Where的执行。如:
PASS
select * from A
inner join B on B.name = A.name
left join C on C.name = B.name
left join D on D.id = C.id
where C.status>1 and D.status=1;
Great
select * from A
inner join B on B.name = A.name
left join C on C.name = B.name and C.status>1
left join D on D.id = C.id and D.status=1
从上面例子可以看出,尽可能满足ON的条件,而少用Where的条件。从执行性能来看第二个显然更加省时。
如作者举了一个列子:
mysql> SELECT * FROM product LEFT JOIN product_details
ON (product.id = product_details.id)
AND product_details.id=2;
+----+--------+------+--------+-------+
| id | amount | id | weight | exist |
+----+--------+------+--------+-------+
| 1 | 100 | NULL | NULL | NULL |
| 2 | 200 | 2 | 22 | 0 |
| 3 | 300 | NULL | NULL | NULL |
| 4 | 400 | NULL | NULL | NULL |
+----+--------+------+--------+-------+
4 rows in set (0.00 sec)
mysql> SELECT * FROM product LEFT JOIN product_details
ON (product.id = product_details.id)
WHERE product_details.id=2;
+----+--------+----+--------+-------+
| id | amount | id | weight | exist |
+----+--------+----+--------+-------+
| 2 | 200 | 2 | 22 | 0 |
+----+--------+----+--------+-------+
1 row in set (0.01 sec)
从上可知,第一条查询使用 ON 条件决定了从 LEFT JOIN的 product_details表中检索符合的所有数据行。第二条查询做了简单的LEFT JOIN,然后使用 WHERE 子句从 LEFT JOIN的数据中过滤掉不符合条件的数据行。
往往性能这玩意儿,更多时候体现在数据量比较大的时候,此时,我们应该避免复杂的子查询。如下:
PASS
insert into t1(a1) select b1 from t2 where not exists(select 1 from t1 where t1.id = t2.r_id);
Great
insert into t1(a1)
select b1 from t2
left join (select distinct t1.id from t1 ) t1 on t1.id = t2.r_id
where t1.id is null;
这个可以参考mysql的exists与inner join 和 not exists与 left join 性能差别惊人
A Visual Explanation of SQL Joins
Mysql Join语法解析与性能分析,布布扣,bubuko.com
原文地址:http://www.cnblogs.com/BeginMan/p/3754322.html