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一、插入数据优化　　1.1 批量插入

如果有多条数据需要同时插入，不要每次插入一条，然后分多次插入，因为每执行一次插入的操作，都要进行数据库的连接，多个操作就会连接多次，而一次批量操作只需要连接1次

1.2 手动提交事务

因为Mysql默认每执行一次操作，就会提交一次事务，这样就会涉及到频繁的事务的开启与关闭

start transaction;　　insert into 表名 values(),(),();　　insert into 表名 values(),(),();　　insert into 表名 values(),(),();commit;

1.3 主键顺序插入

主键一般是默认自增的，但是也可以手动增加，这里不建议手动乱序增加，而是使用默认的顺序增加，原因会在后面解释。

(资料图片仅供参考)

1.4 大批量插入数据

如果一次性需要插入大批量数据，使用insert语句插入性能较低，此时可以使用Mysql数据库提供的load指令进行插入，

首先在连接数据库的时候需要加上 --local-infile 参数

mysql --local-infile -u root -p

在使用本地文件加载功能的时候，需要先查看本地加载文件选项是否开启的

mysql> select @@local_infile;+----------------+| @@local_infile |+----------------+|              0 |+----------------+1 row in set (0.00 sec)

说明1：0表示本地加载文件并未开启

开启本地加载文件的语句

mysql> set global local_infile = 1;Query OK, 0 rows affected (0.01 sec)mysql> select @@local_infile;+----------------+| @@local_infile |+----------------+|              1 |+----------------+1 row in set (0.00 sec)

创建一个空表tb_user，其表结构如下

mysql> desc tb_user;+----------+-------------+------+-----+---------+----------------+| Field    | Type        | Null | Key | Default | Extra          |+----------+-------------+------+-----+---------+----------------+| id       | int         | NO   | PRI | NULL    | auto_increment || username | varchar(50) | NO   | UNI | NULL    |                || password | varchar(50) | NO   |     | NULL    |                || name     | varchar(20) | NO   |     | NULL    |                || birthday | date        | YES  |     | NULL    |                || sex      | char(1)     | YES  |     | NULL    |                |+----------+-------------+------+-----+---------+----------------+6 rows in set (0.01 sec)

使用load加载本地文件 "tb_user_data.sql" 内容到新创建的表中,其中tb_user_data.sql中的测试数据如下

houlei@houleideMacBook-Pro Desktop %cat tb_user_data.sql1,a,aa,aaa,2023-07-01,12,b,bb,bbb,2023-07-02,03,c,cc,ccc,2023-07-03,14,d,dd,ddd,2023-07-04,05,e,ee,eee,2023-07-05,16,f,ff,fff,2023-07-06,07,g,gg,ggg,2023-07-07,1houlei@houleideMacBook-Pro Desktop % 

使用load加载本地文件 "tb_user_data.sql" 内容到新创建的表中　　

mysql> load data local infile "/Users/houlei/Desktop/tb_user_data.sql" into table tb_user fields terminated by "," lines terminated by "\n";Query OK, 7 rows affected (0.01 sec)Records: 7  Deleted: 0  Skipped: 0  Warnings: 0

说明1： load data local infile 是加载本地文件的意思，

说明2："/Users/houlei/Desktop/tb_user_data.sql"是文件路径

说明3：into table tb_user 是将文件中的数据，插入到tb_user表中

说明4：fields terminated by "," 是说每个字段之间的数据是使用","分割的

说明5：lines terminated by "\n" 是说每一行之间的数据使用的是‘\n’分割的

说明6：本方法只是举例，在实际运用大数据量插入时100万条数据的插入至少要数分钟，如果使用load方法只需要十几秒

二、主键优化　　2.1 数据组织方式

在InnoDB储存引擎中，表数据都是根据主键顺序组织存放的，这种存储方式的表称为索引组织表(index organized table）IOT

说明1：在索引的B+数中所有的数据保存在叶子节点上，非叶子节点只保存主键key的值

说明2：索引中的各个节点都是保存在逻辑结构页上面的，一页默认大小16K

2.2 页分裂

页可以为空，也可以填充一半，也可以填充100%，每个页包含了2至N行数据，根据主键排列

情况1：主键顺序插入

说明1：row是行数据，每一页上可以存放多个行数据。　　　　

情况2：主键乱序插入

说明1：当我们想要在插入一个id=50的数据时，会发生页分裂

说明2：这时会将 1#page页里面的数据超过 50%的数据，移动到新开辟的 3#page页中

说明3：然后将 id=50的数据也拼接到 3#page页中

说明4：这时就会出现一个问题，3#page中的索引比 2#page页中的索引小，所以还需要将 3#page页前置，这就叫页分裂

2.3 页合并

当删除一行记录时，实际上记录并没有被物理删除，只是记录被标记(flaged)为删除并且它的空间变得允许被其他记录声明使用

当页中删除的记录达到 merge_threshold(默认为页的50%)，InnoDB 会开始寻找最靠近的页（前或者后）看看是否可以合并以优化空间使用

说明1：这时在 2#page删除了13,14,15,16数据后，该页空余空间超过50%时就会寻找前一页或者后一页，是否同样有不满足50%,可以合并的

说明2：这时 1#page页是满的，不能合并，3#page页不满可以合并，所以 3#page页迁移到 2#page页中

说明3：这时如果在有数据20插入就可以直接插入到3#page页上了，这就是页合并。

2.4 主键设计原则满足业务需求的情况下，尽量减低主键的长度。插入数据时，尽量选择顺序插入，选择使用auto_incerment自增主键，尽量不要用uuid作主键或者其他自然主键如身份证号，因为这个值是无需的，会存在页分裂情况。三、order by优化　　3.1 Using filesort

通过表的索引或者全表扫描，读取满足条件的数据行，然后在排序缓冲区sort buffer 中完成排序操作，所有不是通过索引直接返回排序结果的排序都叫FileSort排序

3.2 Using index

通过有序索引顺序扫描直接返回有序数据，这种情况即为using index，不需要额外的排序，操作效率高，即排序的列表字段符合覆盖索引。

3.3 案例

emp表结构：

mysql> desc emp;+-----------+-------------+------+-----+---------+----------------+| Field     | Type        | Null | Key | Default | Extra          |+-----------+-------------+------+-----+---------+----------------+| id        | int         | NO   | PRI | NULL    | auto_increment || name      | varchar(20) | YES  |     | NULL    |                || age       | int         | YES  |     | NULL    |                || job       | varchar(20) | YES  |     | NULL    |                || salary    | int         | YES  |     | NULL    |                || entrydate | date        | YES  |     | NULL    |                || managerid | int         | YES  |     | NULL    |                || dept_id   | int         | YES  | MUL | NULL    |                |+-----------+-------------+------+-----+---------+----------------+8 rows in set (0.01 sec)

emp表中索引情况

mysql>show index from emp;+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | Visible | Expression |+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| emp   |          0 | PRIMARY  |            1 | id          | A         |           7 |     NULL |   NULL |      | BTREE      |         |               | YES     | NULL       || emp   |          1 | fk_dept  |            1 | dept_id     | A         |           3 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL       |+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+

案例1：对查询结果进行按 salary 和 age 都进行升序排序

mysql> explain select salary,age from emp order by salary, age;+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+----------------+| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra          |+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+----------------+|  1 | SIMPLE      | emp   | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    7 |   100.00 |Using filesort|+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+----------------+1 row in set, 1 warning (0.00 sec)

说明1：Extra 中值为 Using filesort说明是先查出来需要的数据，然后再排序的,效率不高。

说明2：为什么会出现Using filesort呢？因为查询的这些字段在查询之前是无须的，索引需要先将数据查询出来，然后再做排序，这样才能得到想要的排序好的数据。

案例2：给 salary 和 age 添加一个联合排序

mysql> create index salary_age_idx onemp(salary,age);Query OK, 0 rows affected (0.07 sec)Records: 0  Duplicates: 0  Warnings: 0mysql> show index from emp;+-------+------------+----------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| Table | Non_unique | Key_name       | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | Visible | Expression |+-------+------------+----------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| emp   |          0 | PRIMARY        |            1 | id          | A         |           7 |     NULL |   NULL |      | BTREE      |         |               | YES     | NULL       || emp   |          1 | fk_dept        |            1 | dept_id     | A         |           3 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL       || emp   |          1 | salary_age_idx |            1 | salary      | A         |           7 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL ||emp   |          1 | salary_age_idx |            2 | age         | A         |           7 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL |+-------+------------+----------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+4 rows in set (0.00 sec)

说明1：联合索引salary_age_idx中 salary 是第一索引字段，age 是第二索引字段

说明2：Collation 中A 代表升序，D 代表降序　　　　

案例3：再次使用 order by 对 salary 和 age 进行升序排序

mysql> explain select salary,age from emp order by salary,age;+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+-------------+| id | select_type | table | partitions | type  | possible_keys | key            | key_len | ref  | rows | filtered | Extra       |+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+-------------+|  1 | SIMPLE      | emp   | NULL       | index | NULL          | salary_age_idx | 10      | NULL |    7 |   100.00 | Using index |+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+-------------+1 row in set, 1 warning (0.00 sec)mysql> explain select salary,age from emp order by salary;+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+-------------+| id | select_type | table | partitions | type  | possible_keys | key            | key_len | ref  | rows | filtered | Extra       |+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+-------------+|  1 | SIMPLE      | emp   | NULL       | index | NULL          | salary_age_idx | 10      | NULL |    7 |   100.00 | Using index |+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+-------------+1 row in set, 1 warning (0.00 sec)

说明1：在做升序排列时，无论 order by 后面是组合索引的全部字段，还是只有部分字段，这时 Extra 的值都是Usind index，所以其查询的结果直接就是排序好的结果

说明2：为什么呢？因为这个时候 salary和age是一个联合索引，索引在文件中是一个带顺序的b+数结构，所以将这个字段建立一个联合索引，就意味着使用索引查询的时候，就已经是带着顺序的数据了，所以这个时候就不需要在将数据从新在排序了，这样的查询效率就会更高。

案例4: order by 中的字段顺序和索引顺序不一致的情况

mysql> explain select salary,age from emp order by age,  salary;+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+-----------------------------+| id | select_type | table | partitions | type  | possible_keys | key            | key_len | ref  | rows | filtered | Extra                       |+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+-----------------------------+|  1 | SIMPLE      | emp   | NULL       | index | NULL          | salary_age_idx | 10      | NULL |    7 |   100.00 | Using index; Using filesort|+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+-----------------------------+1 row in set, 1 warning (0.00 sec)

说明1：这个时候order by 是age在前，salary在后，和索引的顺序不一致，仍然会触发索引，使用Using index，但是也会使用Using filesort,所以推荐大家使用正确的索引顺序的字段来进行排序

案例5：对salary和age做降序查询

mysql> explain select salary,age from emp order by salary desc, age desc;+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+----------------------------------+| id | select_type | table | partitions | type  | possible_keys | key            | key_len | ref  | rows | filtered | Extra                            |+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+----------------------------------+|  1 | SIMPLE      | emp   | NULL       | index | NULL          | salary_age_idx | 10      | NULL |    7 |   100.00 | Backward index scan; Using index|+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+----------------------------------+1 row in set, 1 warning (0.00 sec)

mysql> explain select id,salary,age from emp order by salary desc;+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+----------------------------------+| id | select_type | table | partitions | type  | possible_keys | key            | key_len | ref  | rows | filtered | Extra                            |+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+----------------------------------+|  1 | SIMPLE      | emp   | NULL       | index | NULL          | salary_age_idx | 10      | NULL |    7 |   100.00 | Backward index scan; Using index|+----+-------------+-------+------------+-------+---------------+----------------+---------+------+------+----------+----------------------------------+1 row in set, 1 warning (0.00 sec)

说明1：无论是对salary和age同时做降序还是对其中一个字段做降序排列，都会出现Backward index scan; Using index，其中 Backward index scan 是反向扫描索引

说明2：这是因为索引中默认的顺序是升序的，而做降序排列，就需要反向扫描索引了

案例7：创建一个 salary 和 age 都是降序的索引

create index salary_age_desc_idx on emp(salary desc, age desc);Query OK, 0 rows affected (0.02 sec)Records: 0  Duplicates: 0  Warnings: 0

查询目前所有的索引

mysql> show index from emp;+-------+------------+---------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| Table | Non_unique | Key_name            | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | Visible | Expression |+-------+------------+---------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| emp   |          0 | PRIMARY             |            1 | id          | A         |           7 |     NULL |   NULL |      | BTREE      |         |               | YES     | NULL       || emp   |          1 | fk_dept             |            1 | dept_id     | A         |           3 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL       || emp   |          1 | salary_age_desc_idx |            1 | salary      | D         |           7 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL || emp   |          1 | salary_age_desc_idx |            2 | age         | D         |           7 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL || emp   |          1 | salary_age_idx      |            1 | salary      | A         |           7 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL       || emp   |          1 | salary_age_idx      |            2 | age         | A         |           7 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL       |+-------+------------+---------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+6 rows in set (0.01 sec)

说明1：这里 salary_age_desc_idx 就是根据 salary 和 age 做的降序索引，其Collation中的D即降序的意思

案例8：使用salary_age_desc_idx索引然后在使用order by降序查询

mysql> explain select salary,age from emp use index(salary_age_desc_idx) order by salary desc, age desc;+----+-------------+-------+------------+-------+---------------+---------------------+---------+------+------+----------+-------------+| id | select_type | table | partitions | type  | possible_keys | key                 | key_len | ref  | rows | filtered | Extra       |+----+-------------+-------+------------+-------+---------------+---------------------+---------+------+------+----------+-------------+|  1 | SIMPLE      | emp   | NULL       | index | NULL          | salary_age_desc_idx | 10      | NULL |    7 |   100.00 | Using index |+----+-------------+-------+------------+-------+---------------+---------------------+---------+------+------+----------+-------------+1 row in set, 1 warning (0.01 sec)

说明1：这个时候的Extra 中显示的 Using index，效率就会比较高了

说明2：这是因为salary_age_desc_idx索引的顺序就是降序排列的，所以使用该索引做降序排列的时候，就不需要在做反向扫描

说明3：在实际的业务中，我们可以根据自己的查询需要，创建升序或者降序的索引。

3.4 order by总结根据排序字段建立合适的索引，多字段排序是，也遵循最左前缀法则尽量使用覆盖索引多字段排序，如果有升序有降序，此时需要注意联合索引在创建时的规则，也应该有对应的升序和降序如果不可避免的出现filesort,大数据量排序的时候，可以适当增大排序缓冲区的大小，sort_buffer_size（默认256K）四、group by优化

为了测试数据的准确性，这是我先把除了主键以外的索引都删除了，然后根据需要在重新创建

mysql> show index from emp;+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | Visible | Expression |+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| emp   |          0 | PRIMARY  |            1 | id          | A         |           7 |     NULL |   NULL |      | BTREE      |         |               | YES     | NULL       |+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+2 rows in set (0.01 sec)

案例1：根据job做聚合查询

mysql> select job, count(*) from emp group by job;;+--------------+----------+| job          | count(*) |+--------------+----------+| 董事长       |        1 || 项目经理     |        1 || 开发         |        3 || 财务         |        1 || 出纳         |        1 || 人事         |        1 |+--------------+----------+6 rows in set (0.00 sec)

我们使用explain查看一下执行计划

mysql> explain select job, count(*) from emp group by job;+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-----------------+| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra           |+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-----------------+|  1 | SIMPLE      | emp   | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    7 |   100.00 | Using temporary |+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-----------------+1 row in set, 1 warning (0.00 sec)

说明1：通过Extra字段：Using temporary,说明在这次的查询中创建了一张临时表，这是无论是空间上还是速度上都会影响到查询效率的。

这时我们给 job 创建一个索引，再次使用explain查看一下执行计划

mysql> create index job_idx onemp(job);Query OK, 0 rows affected (0.02 sec)Records: 0  Duplicates: 0  Warnings: 0mysql> show index from emp;+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | Visible | Expression |+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| emp   |          0 | PRIMARY  |            1 | id          | A         |           7 |     NULL |   NULL |      | BTREE      |         |               | YES     | NULL       || emp   |          1 | job_idx  |            1 | job         | A         |           6 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL       |+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+

mysql> explain select job, count(*) from emp group by job;+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+| id | select_type | table | partitions | type  | possible_keys | key     | key_len | ref  | rows | filtered | Extra       |+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+|  1 | SIMPLE      | emp   | NULL       | index | job_idx       | job_idx | 83      | NULL |    7 |   100.00 | Using index|+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+1 row in set, 1 warning (0.00 sec)

说明2：这是查询中就使用到了索引查询，而没有建立临时表

这时我们在对 job 和 age 同时做分组查询

mysql> explain select job,age, count(*) from emp group by job,age;+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-----------------+| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra           |+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-----------------+|  1 | SIMPLE      | emp   | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    7 |   100.00 | Using temporary|+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-----------------+1 row in set, 1 warning (0.00 sec)

说明3：这时Extra字段的值，仍然是Using temporary，那是因为没有一个与之对应的联合索引。

我们继续创建一个 job 和 age 的联合索引，然后再看一下 explain 的执行计划

mysql> create index job_age_idx onemp(job,age);Query OK, 0 rows affected (0.05 sec)Records: 0  Duplicates: 0  Warnings: 0mysql> show index from emp;+-------+------------+-------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| Table | Non_unique | Key_name    | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | Visible | Expression |+-------+------------+-------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+| emp   |          0 | PRIMARY     |            1 | id          | A         |           7 |     NULL |   NULL |      | BTREE      |         |               | YES     | NULL       || emp   |          1 | job_idx     |            1 | job         | A         |           6 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL       || emp   |          1 | job_age_idx |            1 | job         | A         |           6 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL || emp   |          1 | job_age_idx |            2 | age         | A         |           6 |     NULL |   NULL | YES  | BTREE      |         |               | YES     | NULL|+-------+------------+-------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+5 rows in set (0.00 sec)

mysql> select job,age,count(*) from emp group by job,age;+--------------+------+----------+| job          | age  | count(*) |+--------------+------+----------+| 人事         |   27 |        1 || 出纳         |   25 |        1 || 开发         |   22 |        2 || 开发         |   24 |        1 || 董事长       |   43 |        1 || 财务         |   25 |        1 || 项目经理     |   38 |        1 |+--------------+------+----------+7 rows in set (0.00 sec)mysql> explain select job,age,count(*) from emp group by job,age;+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-------------+| id | select_type | table | partitions | type  | possible_keys | key         | key_len | ref  | rows | filtered | Extra       |+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-------------+|  1 | SIMPLE      | emp   | NULL       | index | job_age_idx   | job_age_idx | 88      | NULL |    7 |   100.00 | Using index|+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-------------+1 row in set, 1 warning (0.00 sec)

说明4：当我们group by后面的分组字段，存在于某一个联合索引中的时候，group by会使用索引查询，而不会建立临时表

案例2：我们根据job做过滤然后再根据age排序

mysql> select job,age from emp where job="开发" group by age;+--------+------+| job    | age  |+--------+------+| 开发   |   22 || 开发   |   24 |+--------+------+2 rows in set (0.01 sec)mysql> explain select job,age from emp where job="开发" group by age;+----+-------------+-------+------------+------+---------------------+-------------+---------+-------+------+----------+-------------+| id | select_type | table | partitions | type | possible_keys       | key         | key_len | ref   | rows | filtered | Extra       |+----+-------------+-------+------------+------+---------------------+-------------+---------+-------+------+----------+-------------+|  1 | SIMPLE      | emp   | NULL       | ref  | job_idx,job_age_idx | job_age_idx| 83      | const |    3 |   100.00 | Using index|+----+-------------+-------+------------+------+---------------------+-------------+---------+-------+------+----------+-------------+1 row in set, 1 warning (0.00 sec)

说明1：当where后面的条件和group by 后面的条件一起组合成连锁索引，也不会建立临时表，也会直接走连个查询索引的。效率同样比较高

总结：

在分组操作时，可以通过索引来提高效率分组操作时，索引的使用也满足最左前缀法则五、limit优化

account_transaction表数据量展示

mysql> select count(*) from account_transaction;+----------+| count(*) |+----------+|  2261942 |+----------+1 row in set (8.40 sec)

说明1：account_transaction总数据量有226万+

案例1：分别采用分页查询，第一页，第1万页，200万页的数据

mysql> select * from account_transaction limit 1,2;+----+--------------------+--------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+| id | trade_no           | type   | method | time                       | payment       | out_trade_no | amount | balance | trader_staff_id | operator_staff_id | device_id | remark |+----+--------------------+--------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+|  2 | 156384294742000250 | TOP_UP | CASH   | 2019-07-23 00:49:07.072256 | LOCAL_ACCOUNT |              |  10000 |   10000 |             250 |                12 | 6         |        ||  3 | 156384301875000251 | TOP_UP | CASH   | 2019-07-23 00:50:18.059192 | LOCAL_ACCOUNT |              |  10000 |   10000 |             251 |                12 | 6         |        |+----+--------------------+--------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+2 rows in set (0.00 sec)mysql> select * from account_transaction limit 10000,2;+-------+--------------------+---------------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+| id    | trade_no           | type          | method | time                       | payment       | out_trade_no | amount | balance | trader_staff_id | operator_staff_id | device_id | remark |+-------+--------------------+---------------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+| 10054 | 156506391300003827 | CONSUME_LUNCH |        | 2019-08-06 03:58:33.000000 | LOCAL_ACCOUNT |              |    200 |    9800 |            3827 |                 0 | 27        |        || 10055 | 156506391300002816 | CONSUME_LUNCH |        | 2019-08-06 03:58:33.000000 | LOCAL_ACCOUNT |              |    200 |    9800 |            2816 |                 0 | 19        |        |+-------+--------------------+---------------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+2 rows in set (0.02 sec)mysql> select * from account_transaction limit 2000000,2;+---------+--------------------+---------------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+| id      | trade_no           | type          | method | time                       | payment       | out_trade_no | amount | balance | trader_staff_id | operator_staff_id | device_id | remark |+---------+--------------------+---------------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+| 5524352 | 163539315991003043 | CONSUME_LUNCH |        | 2021-10-28 03:52:39.000000 | LOCAL_ACCOUNT |              |    200 |    3800 |            3043 |                 0 | 34        |        || 5524354 | 163539342290003077 | CONSUME_LUNCH |        | 2021-10-28 03:57:02.000000 | LOCAL_ACCOUNT |              |    200 |    1500 |            3077 |                 0 | 19        |        |+---------+--------------------+---------------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+2 rows in set (2.51 sec)

说明1：我们对1页，1万页，200万页的数据分别查询，发现随着查询数据量的增加，查询的时间也在增加

说明2：当我们查询limit 2000000,2时，此时需要Mysql排序钱2000002条记录，但是仅仅需要返回200001-20002的记录，前2000000条记录丢弃，查询排序的代价非常大

查询优化

mysql> select a.* from account_transaction as a, (select id from account_transaction order by id limit 2000000,2) as at where a.id = at.id;+---------+--------------------+---------------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+| id      | trade_no           | type          | method | time                       | payment       | out_trade_no | amount | balance | trader_staff_id | operator_staff_id | device_id | remark |+---------+--------------------+---------------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+| 5524352 | 163539315991003043 | CONSUME_LUNCH |        | 2021-10-28 03:52:39.000000 | LOCAL_ACCOUNT |              |    200 |    3800 |            3043 |                 0 | 34        |        || 5524354 | 163539342290003077 | CONSUME_LUNCH |        | 2021-10-28 03:57:02.000000 | LOCAL_ACCOUNT |              |    200 |    1500 |            3077 |                 0 | 19        |        |+---------+--------------------+---------------+--------+----------------------------+---------------+--------------+--------+---------+-----------------+-------------------+-----------+--------+2 rows in set (0.51 sec)

说明3：同样是分页查询2000000页以后的数据，该查询仅好事0.51秒，比直接使用limit分页查询快了几倍

说明4：Mysql官方针对大数据量的分页查询给出的方案是，建议使用覆盖查询加子查询形式进行优化

说明5：该插叙的子查询：select id from account_transaction order by id limit 2000000,2，首先这是根据id查询到需要数据的id，本身根据id查找就是比较快的。

mysql> select id from account_transaction order by id limit 2000000,2;+---------+| id      |+---------+| 5524352 || 5524354 |+---------+2 rows in set (0.45 sec)

说明6：将该子查询的结果当做一张表，与account_trasaction做子查询，这样效率就会比直接使用limit速度快很多。

六、count优化　　6.1 count() 原理

是一个聚合函数，对于返回的结果集，一行一行的判断，如果count函数的参数不为NULL,累计值就+1，否则不加1，最后返回累计值

6.2 count的几种用法

count(*)：

InnoDB引擎并不会把全部的字段取出来，而是专门做了优化，不取值，服务层直接按行进行累加,mysql 对count(*)做了优化。

count(主键)

InnoDB引擎会遍历整张表，把每一行的主键id值都取出来，返回给服务层，服务层那个主键后，直接按行进行累加（主键不可能为空）

count(普通字段)：

没有not null 约束：InnoDB引擎会遍历整张表，把每一行的字段值都取出来，返回给服务层，服务层判断是否为null，不为null,计数+1.

有not null 约束：InnofDB引擎会遍历整张表，把每一行的字段值都取出来，返回给服务层，直接按行累加

count(1）

InnoDB引擎遍历整张表，但不取值，服务层对于返回的每一行，放一个数字“1”进去，直接按行进行累加。

6.3 效率排序

count(*) ≈count(1)>count(id)>count(普通字段)

七、update优化　　7.1案例1：根据索引修改数据，仅仅会触发行锁

说明1：因为左边和右边都是根据id修改的不同数据，这时id是主键索引，所以这里的修改都只会触发行锁，不会影响其他行的修改。

7.2案例2：根据非索引字段同时修改记录数据

说明1：update的时候，如果条件是索引字段，则只会触发行索引

说明2：updae的时候，如果条件是非索引字段，则会触发表索引，即在update的时候，整张表处于锁住的状态。

说明3：主需要对update的字段创建一个索引值，就可以在update的时候将表锁降低为行锁。

7.3 总结：

InnoDB的行锁是针对索引加的锁，不是针对记录加的锁，并且该索引不能失效，否则会从行锁升级为表锁。