join 用於多表中字段之間的聯系,語法如下:
... FROM table1 INNER|LEFT|RIGHT JOIN table2 ON conditiona
table1:左表;table2:右表。
JOIN 按照功能大致分為如下三類:
INNER JOIN(內連接,或等值連接):取得兩個表中存在連接匹配關系的記錄。
LEFT JOIN(左連接):取得左表(table1)完全記錄,即是右表(table2)並無對應匹配記錄。
RIGHT JOIN(右連接):與 LEFT JOIN 相反,取得右表(table2)完全記錄,即是左表(table1)並無匹配對應記錄。
注意:mysql不支持Full join,不過可以通過UNION 關鍵字來合並 LEFT JOIN 與 RIGHT JOIN來模擬FULL join.
接下來給出一個列子用於解釋下面幾種分類。如下兩個表(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)
內連接,也叫等值連接,inner join產生同時符合A和B的一組數據。
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中兩者等價,推薦使用left join.)左連接從左表(A)產生一套完整的記錄,與匹配的記錄(右表(B)) .如果沒有匹配,右側將包含null。
如果想只從左表(A)中產生一套記錄,但不包含右表(B)的記錄,可以通過設置where語句來執行,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,還可以模擬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:
根據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;
# 結果
+------+-----------+------+-------------+
| 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:交叉連接,得到的結果是兩個表的乘積,即笛卡爾積
笛卡爾(Descartes)乘積又叫直積。假設集合A={a,b},集合B={0,1,2},則兩個集合的笛卡爾積為{(a,0),(a,1),(a,2),(b,0),(b,1), (b,2)}。可以擴展到多個集合的情況。類似的例子有,如果A表示某學校學生的集合,B表示該學校所有課程的集合,則A與B的笛卡爾積表示所有可能的選課情況。
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)
#再執行:mysql> select * from A inner join B; 試一試
#在執行mysql> select * from A cross join B on A.name = B.name; 試一試
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實際上,在 MySQL 中(僅限於 MySQL) CROSS JOIN 與 INNER JOIN 的表現是一樣的,在不指定 ON 條件得到的結果都是笛卡爾積,反之取得兩個表完全匹配的結果。 INNER JOIN 與 CROSS JOIN 可以省略 INNER 或 CROSS 關鍵字,因此下面的 SQL 效果是一樣的:
... 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)
全連接產生的所有記錄(雙方匹配記錄)在表A和表B。如果沒有匹配,則對面將包含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;
我在數據庫中比較(10w數據)得之,它們用時幾乎相同,第一個是顯示的inner join,後一個是隱式的inner join。
參照:Explicit vs implicit SQL joins
盡量用inner join.避免 LEFT JOIN 和 NULL.
在使用left join(或right join)時,應該清楚的知道以下幾點:
ON 條件(“A LEFT JOIN B ON 條件表達式”中的ON)用來決定如何從 B 表中檢索數據行。如果 B 表中沒有任何一行數據匹配 ON 的條件,將會額外生成一行所有列為 NULL 的數據,在匹配階段 WHERE 子句的條件都不會被使用。僅在匹配階段完成以後,WHERE 子句條件才會被使用。它將從匹配階段產生的數據中檢索過濾。
所以我們要注意:在使用Left (right) join的時候,一定要在先給出盡可能多的匹配滿足條件,減少Where的執行。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
從上面例子可以看出,盡可能滿足ON的條件,而少用Where的條件。從執行性能來看第二個顯然更加省時。
如作者舉了一個列子:
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)
從上可知,第一條查詢使用 ON 條件決定了從 LEFT JOIN的 product_details表中檢索符合的所有數據行。第二條查詢做了簡單的LEFT JOIN,然後使用 WHERE 子句從 LEFT JOIN的數據中過濾掉不符合條件的數據行。
往往性能這玩意兒,更多時候體現在數據量比較大的時候,此時,我們應該避免復雜的子查詢。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;
這個可以參考mysql的exists與inner join 和 not exists與 left join 性能差別驚人
原文:http://www.codesocang.com/jiaocheng/mysql/8068.html