Index Condition Pushdown (ICP)是MySQL 5.6 版本中的新特性,是一种在存储引擎层使用索引过滤数据的一种优化方式。
【Index Condition Pushdown】
当关闭ICP时,index 仅仅是data access 的一种访问方式，存储引擎通过索引回表获取的数据会传递到MySQL Server 层进行where条件过滤。
当打开ICP时,如果部分where条件能使用索引中的字段,MySQL Server 会把这部分下推到引擎层,可以利用index过滤的where条件在存储引擎层进行数据过滤,而非将所有通过index access的结果传递到MySQL server层进行where过滤.
优化效果:ICP能减少引擎层访问基表的次数和MySQL Server 访问存储引擎的次数,减少io次数，提高查询语句性能。
- 实践案例
当开启ICP时
mysql> SET profiling = 1; Query OK, 0 rows affected, 1 warning (0.00 sec) mysql> select * from employees where first_name='Anneke' and last_name like '%sig' ; +--------+------------+------------+-----------+--------+------------+ | emp_no | birth_date | first_name | last_name | gender | hire_date | +--------+------------+------------+-----------+--------+------------+ | 10006 | 1953-04-20 | Anneke | Preusig | F | 1989-06-02 | +--------+------------+------------+-----------+--------+------------+ 1 row in set (0.00 sec) mysql> show profiles; +----------+------------+--------------------------------------------------------------------------------+ | Query_ID | Duration | Query | +----------+------------+--------------------------------------------------------------------------------+ | 1 | 0.00060275 | select * from employees where first_name='Anneke' and last_name like '%sig' | +----------+------------+--------------------------------------------------------------------------------+ 3 rows in set, 1 warning (0.00 sec) mysql> show profile cpu,block io for query 1; +----------------------+----------+----------+------------+--------------+---------------+ | Status | Duration | CPU_user | CPU_system | Block_ops_in | Block_ops_out | +----------------------+----------+----------+------------+--------------+---------------+ | starting | 0.000094 | 0.000000 | 0.000000 | 0 | 0 | | checking permissions | 0.000011 | 0.000000 | 0.000000 | 0 | 0 | | Opening tables | 0.000025 | 0.000000 | 0.000000 | 0 | 0 | | init | 0.000044 | 0.000000 | 0.000000 | 0 | 0 | | System lock | 0.000014 | 0.000000 | 0.000000 | 0 | 0 | | optimizing | 0.000021 | 0.000000 | 0.000000 | 0 | 0 | | statistics | 0.000093 | 0.000000 | 0.000000 | 0 | 0 | | preparing | 0.000024 | 0.000000 | 0.000000 | 0 | 0 | | executing | 0.000006 | 0.000000 | 0.000000 | 0 | 0 | | Sending data | 0.000189 | 0.000000 | 0.000000 | 0 | 0 | | end | 0.000019 | 0.000000 | 0.000000 | 0 | 0 | | query end | 0.000012 | 0.000000 | 0.000000 | 0 | 0 | | closing tables | 0.000013 | 0.000000 | 0.000000 | 0 | 0 | | freeing items | 0.000034 | 0.000000 | 0.000000 | 0 | 0 | | cleaning up | 0.000007 | 0.000000 | 0.000000 | 0 | 0 | +----------------------+----------+----------+------------+--------------+---------------+ 15 rows in set, 1 warning (0.00 sec)
当关闭ICP时
实践案例 mysql> set optimizer_switch='index_condition_pushdown=off'; Query OK, 0 rows affected (0.00 sec) mysql> SET profiling = 1; Query OK, 0 rows affected, 1 warning (0.00 sec) mysql> select * from employees where first_name='Anneke' and last_name like '%sig' ; +--------+------------+------------+-----------+--------+------------+ | emp_no | birth_date | first_name | last_name | gender | hire_date | +--------+------------+------------+-----------+--------+------------+ | 10006 | 1953-04-20 | Anneke | Preusig | F | 1989-06-02 | +--------+------------+------------+-----------+--------+------------+ 1 row in set (0.00 sec) mysql> SET profiling = 0; Query OK, 0 rows affected, 1 warning (0.00 sec) mysql> show profiles; +----------+------------+--------------------------------------------------------------------------------+ | Query_ID | Duration | Query | +----------+------------+--------------------------------------------------------------------------------+ | 2 | 0.00097000 | select * from employees where first_name='Anneke' and last_name like '%sig' | +----------+------------+--------------------------------------------------------------------------------+ 6 rows in set, 1 warning (0.00 sec) mysql> show profile cpu,block io for query 2; +----------------------+----------+----------+------------+--------------+---------------+ | Status | Duration | CPU_user | CPU_system | Block_ops_in | Block_ops_out | +----------------------+----------+----------+------------+--------------+---------------+ | starting | 0.000045 | 0.000000 | 0.000000 | 0 | 0 | | checking permissions | 0.000007 | 0.000000 | 0.000000 | 0 | 0 | | Opening tables | 0.000015 | 0.000000 | 0.000000 | 0 | 0 | | init | 0.000024 | 0.000000 | 0.000000 | 0 | 0 | | System lock | 0.000009 | 0.000000 | 0.000000 | 0 | 0 | | optimizing | 0.000012 | 0.000000 | 0.000000 | 0 | 0 | | statistics | 0.000049 | 0.000000 | 0.000000 | 0 | 0 | | preparing | 0.000016 | 0.000000 | 0.000000 | 0 | 0 | | executing | 0.000005 | 0.000000 | 0.000000 | 0 | 0 | | Sending data | 0.000735 | 0.001000 | 0.000000 | 0 | 0 | | end | 0.000008 | 0.000000 | 0.000000 | 0 | 0 | | query end | 0.000008 | 0.000000 | 0.000000 | 0 | 0 | | closing tables | 0.000009 | 0.000000 | 0.000000 | 0 | 0 | | freeing items | 0.000023 | 0.000000 | 0.000000 | 0 | 0 | | cleaning up | 0.000007 | 0.000000 | 0.000000 | 0 | 0 | +----------------------+----------+----------+------------+--------------+---------------+ 15 rows in set, 1 warning (0.00 sec)
从上面的profile 可以看出ICP 开启时整个sql 执行时间是未开启的2/3，sending data 环节的时间消耗前者仅是后者的1/4。
ICP 开启时的执行计划 含有 Using index condition 标示 ，表示优化器使用了ICP对数据访问进行优化。
mysql> explain select * from employees where first_name='Anneke' and last_name like '%nta' ; +----+-------------+-----------+------+---------------+--------------+---------+-------+------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-----------+------+---------------+--------------+---------+-------+------+-----------------------+ | 1 | SIMPLE | employees | ref | idx_emp_fnln | idx_emp_fnln | 44 | const | 224 | Using index condition | +----+-------------+-----------+------+---------------+--------------+---------+-------+------+-----------------------+ 1 row in set (0.00 sec)
ICP 关闭时的执行计划显示use where
mysql> explain select * from employees where first_name='Anneke' and last_name like '%nta' ; +----+-------------+-----------+------+---------------+--------------+---------+-------+------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-----------+------+---------------+--------------+---------+-------+------+-------------+ | 1 | SIMPLE | employees | ref | idx_emp_fnln | idx_emp_fnln | 44 | const | 224 | Using where | +----+-------------+-----------+------+---------------+--------------+---------+-------+------+-------------+ 1 row in set (0.00 sec)
以上面的查询为例关闭ICP 时,存储引擎通前缀index first_name 访问表中225条first_name 为Anneke的数据,并在MySQL server层根据last_name like '%sig' 进行过滤；开启ICP 时，last_name 的like '%sig'条件可以通过索引字段last_name 进行过滤，在存储引擎内部通过与where条件的对比，直接过滤掉不符合条件的数据。该过程不回表,只访问符合条件的1条记录并返回给MySQL Server ,有效的减少了io访问和各层之间的交互。
- ICP的使用限制
- 当sql需要全表访问时,ICP的优化策略可用于range, ref, eq_ref, ref_or_null 类型的访问数据方法 。
- 支持InnoDB和MyISAM表。
- ICP只能用于二级索引，不能用于主索引。
- 并非全部where条件都可以用ICP筛选。
- 如果where条件的字段不在索引列中,还是要读取整表的记录到server端做where过滤。
- ICP的加速效果取决于在存储引擎内通过ICP筛选掉的数据的比例。
- 5.6 版本的不支持分表的ICP 功能，5.7 版本的开始支持。
- 当sql 使用覆盖索引时，不支持ICP 优化方法。
mysql> explain select * from employees where first_name='Anneke' and last_name='Porenta' ; +----+-------------+-----------+------+---------------+--------------+---------+-------------+------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-----------+------+---------------+--------------+---------+-------------+------+-----------------------+ | 1 | SIMPLE | employees | ref | idx_emp_fnln | idx_emp_fnln | 94 | const,const | 1 | Using index condition | +----+-------------+-----------+------+---------------+--------------+---------+-------------+------+-----------------------+ 1 row in set (0.00 sec) mysql> explain select first_name,last_name from employees where first_name='Anneke' and last_name='Porenta' ; +----+-------------+-----------+------+---------------+--------------+---------+-------------+------+--------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-----------+------+---------------+--------------+---------+-------------+------+--------------------------+ | 1 | SIMPLE | employees | ref | idx_emp_fnln | idx_emp_fnln | 94 | const,const | 1 | Using where; Using index | +----+-------------+-----------+------+---------------+--------------+---------+-------------+------+--------------------------+ 1 row in set (0.00 sec)
