MySQL中一些优化straight_join技巧

在oracle中可以指定的表连接的hint有很多：ordered hint 指示oracle按照from关键字后的表顺序来进行连接；leading hint 指示查询优化器使用指定的表作为连接的首表，即驱动表；use_nl hint指示查

在oracle中可以指定的表连接的hint有很多：ordered hint 指示oracle按照from关键字后的表顺序来进行连接；leading hint 指示查询优化器使用指定的表作为连接的首表，即驱动表；use_nl hint指示查询优化器使用nested loops方式连接指定表和其他行源，并且将强制指定表作为inner表。
在mysql中就有之对应的straight_join,由于mysql只支持nested loops的连接方式，所以这里的straight_join类似oracle中的use_nl hint。mysql优化器在处理多表的关联的时候，很有可能会选择错误的驱动表进行关联，导致了关联次数的增加，从而使得sql语句执行变得非常的缓慢，这个时候需要有经验的DBA进行判断，选择正确的驱动表，这个时候straight_join就起了作用了，下面我们来看一看使用straight_join进行优化的案例：

1．用户实例：spxxxxxx的一条sql执行非常的缓慢，sql如下：

73871 | root | 127.0.0.1:49665 | user_app_test | Query | 500 | Sorting result |
SELECT DATE(practicetime) date_time,COUNT(DISTINCT a.userid) people_rows
FROM test_log a,USER b
WHERE a.userid=b.userid AND b.isfree=0 AND LENGTH(b.username)>4
GROUP BY DATE(practicetime)

2.查看执行计划：

mysql> explain SELECT DATE(practicetime) date_time,COUNT(DISTINCT a.userid) people_rows
FROM test_log a,USER b
WHERE a.userid=b.userid AND b.isfree=0 AND LENGTH(b.username)>4
GROUP BY DATE(practicetime);
mysql> explain SELECT DATE(practicetime) date_time,COUNT(DISTINCT a.userid) people_rows
-> FROM test_log a,USER b
-> WHERE a.userid=b.userid AND b.isfree=0 AND LENGTH(b.username)>4
-> GROUP BY DATE(practicetime)\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: a
type: ALL
possible_keys: ix_test_log_userid
key: NULL
key_len: NULL
ref: NULL
rows: 416782
Extra: Using filesort
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: b
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 96
ref: user_app_testnew.a.userid
rows: 1
Extra: Using where
2 rows in set (0.00 sec)

3.查看索引：

mysql> show index from test_log;
+————–+————+————————-+————–+————-+———–+————-+———-++
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+————–+————+————————-+————–+————-+———–+————-+———-++
| test_log | 0 | ix_test_log_unique_ | 1 | unitid | A | 20 | NULL | NULL | | BTREE | |
| test_log | 0 | ix_test_log_unique_ | 2 | paperid | A | 20 | NULL | NULL | | BTREE | |
| test_log | 0 | ix_test_log_unique_ | 3 | qtid | A | 20 | NULL | NULL | | BTREE | |
| test_log | 0 | ix_test_log_unique_ | 4 | userid | A | 400670 | NULL | NULL | | BTREE | |
| test_log | 0 | ix_test_log_unique_ | 5 | serial | A | 400670 | NULL | NULL | | BTREE | |
| test_log | 1 | ix_test_log_unit | 1 | unitid | A | 519 | NULL | NULL | | BTREE | |
| test_log | 1 | ix_test_log_unit | 2 | paperid | A | 2023 | NULL | NULL | | BTREE | |
| test_log | 1 | ix_test_log_unit | 3 | qtid | A | 16694 | NULL | NULL | | BTREE | |
| test_log | 1 | ix_test_log_serial | 1 | serial | A | 133556 | NULL | NULL | | BTREE | |
| test_log | 1 | ix_test_log_userid | 1 | userid | A | 5892 | NULL | NULL | | BTREE | |
+————–+————+————————-+————–+————-+———–+————-+———-+——–+——+——-+

4.调整索引，A表优化采用覆盖索引：

mysql>alter table test_log drop index ix_test_log_userid,add index ix_test_log_userid(userid,practicetime)

5.查看执行计划：

mysql> explain SELECT DATE(practicetime) date_time,COUNT(DISTINCT a.userid) people_rows
FROM test_log a,USER b
WHERE a.userid=b.userid AND b.isfree=0 AND LENGTH(b.username)>4
GROUP BY DATE(practicetime)\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: a
type: index
possible_keys: ix_test_log_userid
key: ix_test_log_userid
key_len: 105
ref: NULL
rows: 388451
Extra: Using index; Using filesort
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: b
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 96
ref: user_app_test.a.userid
rows: 1
Extra: Using where
2 rows in set (0.00 sec)

调整后执行稍有效果，但是还不明显，还没有找到要害：

SELECT DATE(practicetime) date_time,COUNT(DISTINCT a.userid) people_rows
FROM test_log a,USER b
WHERE a.userid=b.userid AND b.isfree=0 AND LENGTH(b.username)>4
GROUP BY DATE(practicetime);
……………….
143 rows in set (1 min 12.62 sec)

6.执行时间仍然需要很长，时间的消耗主要耗费在Using filesort中，参与排序的数据量有38W之多，所以需要转换驱动表；尝试采用user表做驱动表：使用straight_join强制连接顺序：

mysql> explain SELECT DATE(practicetime) date_time,COUNT(DISTINCT a.userid) people_rows
FROM USER b straight_join test_log a
WHERE a.userid=b.userid AND b.isfree=0 AND LENGTH(b.username)>4
GROUP BY DATE(practicetime)\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: b
type: ALL
possible_keys: PRIMARY
key: NULL
key_len: NULL
ref: NULL
rows: 42806
Extra: Using where; Using temporary; Using filesort
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: a
type: ref
possible_keys: ix_test_log_userid
key: ix_test_log_userid
key_len: 96
ref: user_app_test.b.userid
rows: 38
Extra: Using index
2 rows in set (0.00 sec)

执行时间已经有了质的变化，降低到了2.56秒；

mysql>SELECT DATE(practicetime) date_time,COUNT(DISTINCT a.userid) people_rows
FROM USER b straight_join test_log a
WHERE a.userid=b.userid AND b.isfree=0 AND LENGTH(b.username)>4
GROUP BY DATE(practicetime);
……..
143 rows in set (2.56 sec)

7.在分析执行计划的第一步：Using where; Using temporary; Using filesort，user表其实也可以采用覆盖索引来避免using where的出现，所以继续调整索引：

mysql> show index from user;
+——-+————+——————+————–+————-+———–+————-+———-+——–+——+————+———+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+——-+————+——————+————–+————-+———–+————-+———-+——–+——+————+———+
| user | 0 | PRIMARY | 1 | userid | A | 43412 | NULL | NULL | | BTREE | |
| user | 0 | ix_user_email | 1 | email | A | 43412 | NULL | NULL | | BTREE | |
| user | 1 | ix_user_username | 1 | username | A | 202 | NULL | NULL | | BTREE | |
+——-+————+——————+————–+————-+———–+————-+———-+——–+——+————+———+
3 rows in set (0.01 sec)

mysql>alter table user drop index ix_user_username,add index ix_user_username(username,isfree);
Query OK, 42722 rows affected (0.73 sec)
Records: 42722 Duplicates: 0 Warnings: 0

mysql>explain SELECT DATE(practicetime) date_time,COUNT(DISTINCT a.userid) people_rows
FROM USER b straight_join test_log a
WHERE a.userid=b.userid AND b.isfree=0 AND LENGTH(b.username)>4
GROUP BY DATE(practicetime);
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: b
type: index
possible_keys: PRIMARY
key: ix_user_username
key_len: 125
ref: NULL
rows: 42466
Extra: Using where; Using index; Using temporary; Using filesort
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: a
type: ref
possible_keys: ix_test_log_userid
key: ix_test_log_userid
key_len: 96
ref: user_app_test.b.userid
rows: 38
Extra: Using index
2 rows in set (0.00 sec)

8.执行时间降低到了1.43秒：

mysql>SELECT DATE(practicetime) date_time,COUNT(DISTINCT a.userid) people_rows
FROM USER b straight_join test_log a
WHERE a.userid=b.userid AND b.isfree=0 AND LENGTH(b.username)>4
GROUP BY DATE(practicetime);
。。。。。。。
143 rows in set (1.43 sec)