Index Condition Pushdown (ICP) is an optimization for the case where MySQL retrieves rows from a table using an index. Without ICP, the storage engine traverses the index to locate rows in the base table and returns them to the MySQL server which evaluates the WHERE
condition for the rows. With ICP enabled, and if parts of the WHERE
condition can be evaluated by using only fields from the index, the MySQL server pushes this part of the WHERE
condition down to the storage engine. The storage engine then evaluates the pushed index condition by using the index entry and only if this is satisfied is the row read from the table. ICP can reduce the number of times the storage engine must access the base table and the number of times the MySQL server must access the storage engine.
也就說:利用索引(二級索引)來過濾一部分where條件
導入數據庫
wget https://launchpad.net/test-db/employees-db-1/1.0.6/+download/employees_db-full-1.0.6.tar.bz2 tar jxf employees_db-full-1.0.6.tar.bz2 cd employees_db mysql -uroot -p < employees.sql
表結構
mysql> show create table employees \G *************************** 1. row *************************** Table: employees Create Table: CREATE TABLE `employees` ( `emp_no` int(11) NOT NULL, `birth_date` date NOT NULL, `first_name` varchar(14) NOT NULL, `last_name` varchar(16) NOT NULL, `gender` enum('M','F') NOT NULL, `hire_date` date NOT NULL, PRIMARY KEY (`emp_no`), KEY `index_bh` (`birth_date`,`hire_date`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8 1 row in set (0.00 sec)
一些表數據
mysql> select @@optimizer_switch like '%index_condition_pushdown%' \G *************************** 1. row *************************** @@optimizer_switch like '%index_condition_pushdown%': 1 1 row in set (0.00 sec) mysql> select @@optimizer_switch like '%index_condition_pushdown%' \G *************************** 1. row *************************** @@optimizer_switch like '%index_condition_pushdown%': 1 1 row in set (0.00 sec) mysql> select @@query_cache_type; +--------------------+ | @@query_cache_type | +--------------------+ | OFF | +--------------------+ 1 row in set (0.01 sec) mysql> select count(*) from employees; +----------+ | count(*) | +----------+ | 300024 | +----------+ 1 row in set (0.17 sec) mysql> set profiling=1; Query OK, 0 rows affected, 1 warning (0.00 sec)
建立索引
alter table employees add index index_bh (`birth_date`,`hire_date`);
查詢分析
mysql> explain select * from employees where birth_date between '1955-01-01' and '1955-12-31' and datediff(hire_date,birth_date)>12300 and first_name like 'S%b%'; +----+-------------+-----------+-------+---------------+----------+---------+------+-------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-----------+-------+---------------+----------+---------+------+-------+-------------+ | 1 | SIMPLE | employees | range | index_bh | index_bh | 3 | NULL | 46318 | Using where | +----+-------------+-----------+-------+---------------+----------+---------+------+-------+-------------+ 1 row in set (0.00 sec) mysql> SET optimizer_switch='index_condition_pushdown=on'; Query OK, 0 rows affected (0.00 sec) mysql> explain select * from employees where birth_date between '1955-01-01' and '1955-12-31' and datediff(hire_date,birth_date)>12300 and first_name like 'S%b%'; +----+-------------+-----------+-------+---------------+----------+---------+------+-------+------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-----------+-------+---------------+----------+---------+------+-------+------------------------------------+ | 1 | SIMPLE | employees | range | index_bh | index_bh | 3 | NULL | 46318 | Using index condition; Using where | +----+-------------+-----------+-------+---------------+----------+---------+------+-------+------------------------------------+ 1 row in set (0.01 sec)
執行查詢
mysql> show profiles; +----------+------------+------------------------------------------------------------------------------------------------------------------------------------------------------+ | Query_ID | Duration | Query | +----------+------------+------------------------------------------------------------------------------------------------------------------------------------------------------+ | 1 | 0.00278025 | desc employees | | 2 | 0.00049775 | show create table employees | | 3 | 0.07444550 | select * from employees where birth_date between '1955-01-01' and '1955-12-31' and datediff(hire_date,birth_date)>12300 and first_name like 'S%b%' | | 4 | 0.00027500 | SET optimizer_switch='index_condition_pushdown=off' | | 5 | 0.12347025 | select * from employees where birth_date between '1955-01-01' and '1955-12-31' and datediff(hire_date,birth_date)>12300 and first_name like 'S%b%' | +----------+------------+------------------------------------------------------------------------------------------------------------------------------------------------------+
從結果可以看出來開啟ICP之後確實快不少
啟用ICP之後,可以用索引來篩選 datediff(hire_date,birth_date)>12300 記錄,不需要讀出整條記錄
如下圖所示(圖來自MariaDB)
ICP的使用條件
1、只能用於二級索引(secondary index)
2、explain顯示的執行計劃中type值(join 類型)為range、 ref、 eq_ref或者ref_or_null。且查詢需要訪問表的整行數據,即不能直接通過二級索引的元組數據獲得查詢結果(索引覆蓋)
3、ICP可以用於MyISAM和InnnoDB存儲引擎,不支持分區表(5.7將會解決這個問題)
4、ICP的加速效果取決於在存儲引擎內通過ICP篩選掉的數據的比例
參考文章
https://mariadb.com/kb/en/index-condition-pushdown/
http://dev.mysql.com/doc/refman/5.6/en/index-condition-pushdown-optimization.html
http://blog.codinglabs.org/articles/index-condition-pushdown.html