我们将超过指定时间的SQL语句查询称为慢查询
一、慢查询的体现
慢查询主要体现在慢上，通常意义上来讲，只要返回时间大于 >1 sec上的查询都可以称为慢查询。
慢查询会导致CPU，内存消耗过高。数据库服务器压力陡然过大，那么大部分情况来讲，肯定是由某些慢查询导致的。
查看/设置“慢查询”的时间定义
mysql> show variables like "long%";
+-----------------+----------+
| Variable_name | Value |
+-----------------+----------+
| long_query_time | 0.000100 |
+-----------------+----------+
1 row in set (0.00 sec)
如上述语句输出，“慢查询”的时间定义为0.0001秒（方便测试，一般设置为1-10秒）。使用下面语句定义“慢查询”时间
mysql> set long_query_time=0.0001;
Query OK, 0 rows affected (0.00 sec)
开启“慢查询”记录功能
mysql> show variables like "slow%";
+---------------------+------------------------------------+
| Variable_name | Value |
+---------------------+------------------------------------+
| slow_launch_time | 2 |
| slow_query_log | OFF |
| slow_query_log_file | /opt/mysql/data/localhost-slow.log |
+---------------------+------------------------------------+
3 rows in set (0.00 sec)
上述语句查看“慢查询”的配置信息，你可以自定义日志文件的存放，但必须将 slow_query_log 全局变量设置为“ON”状态，执行以下语句
mysql> set global slow_query_log=ON;
Query OK, 0 rows affected (0.01 sec)
结果：
mysql> show variables like "slow%";
+---------------------+------------------------------------+
| Variable_name | Value |
+---------------------+------------------------------------+
| slow_launch_time | 2 |
| slow_query_log | ON |
| slow_query_log_file | /opt/mysql/data/localhost-slow.log |
+---------------------+------------------------------------+
3 rows in set (0.00 sec)
那么哪些条件可以导致慢查询呢？或者说根据何种条件判断，优化慢查询。仅从SQL语句方面阐述慢查询，MySQL系统级别的设置暂不考虑。
二、返回列数太多
- 返回列数太多
EXPLAIN SELECT `happy_ni_nis`.*
FROM `happy_ni_nis`
ORDER BY n_total DESC LIMIT 10\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: happy_ni_nis
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 66493186 <- 返回值太多，坏味道
Extra: Using filesort <- 避免使用排序
1 row in set (0.01 sec)
优化建议： 添加 关于 n_total 的索引
mysql> alter table happy_ni_nis add index `idx_of_n_total` (`n_total`, `id`);
Query OK, 0 rows affected (7 min 48.27 sec)
Records: 0 Duplicates: 0 Warnings: 0
EXPLAIN SELECT `happy_ni_nis`.*
FROM `happy_ni_nis`
ORDER BY n_total DESC LIMIT 10\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: happy_ni_nis
type: index
possible_keys: NULL
key: idx_of_n_total
key_len: 8
ref: NULL
rows: 10
Extra:
1 row in set (0.01 sec)
- 但是某些情况下，返回列数比较多，也不代表是慢查询。
SELECT `cd_happys`.*
FROM `cd_happys`
WHERE `cd_happys`.`p_status` = 4
AND `cd_happys`.`status` IN (0,
1,
2,
3,
4)
AND (c_time <= '2015-05-15 23:30:39'
AND update_time <= '2015-05-15 23:30:39')
ORDER BY `cd_happys`.`id` ASC LIMIT 1000
+----+-------------+-----------------+-------+---------------------------------------+---------+---------+-----+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-----------------+-------+---------------------------------------+---------+---------+-----+------+-------------+
| 1 | SIMPLE | cd_happys | index | idx_uptime_seneditor,idx_c_time | PRIMARY | 4 | | 2000 | Using where |
+----+-------------+-----------------+-------+---------------------------------------+---------+---------+-----+------+-------------+
平均查询时间：6 sec
添加一个 ``idx_of_p_status_status_c_time(p_status,status,c_time,id) 索引
mysql> explain SELECT SQL_NO_CACHE `cd_happys`.* FROM `cd_happys` WHERE `cd_happys`.`p_status` = 4 AND `cd_happys`.`status` IN (0, 1, 2, 3, 4) AND (c_time <= '2015-05-15 23:30:39' and update_time <= '2015-05-15 23:30:39') LIMIT 1000\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: cd_happys
type: range
possible_keys: idx_uptime_seneditor,idx_c_time,idx_of_p_status_sanzu_check_status_signup_status,idx_of_p_status_status_c_time
key: idx_of_p_status_status_c_time
key_len: 16
ref: NULL
rows: 3782
Extra: Using where
1 row in set (0.01 sec)
平均查询时间：0.4 sec
三、分页条件，过大的offset
EXPLAIN SELECT `happys`.*
FROM `happys`
INNER JOIN `happy_infos` ON `happy_infos`.`happy_id` = `happys`.`id`
WHERE
(happys.end_time > '2015-08-13 14:08:10')
AND (happys.j_tag_id > 0)
AND (happy_infos.my_image_url = '')
ORDER BY happys.updated_at DESC LIMIT 100
OFFSET 28900\G;
+----+-------------+------------+--------+------------------------------------------------------------+---------------+---------+-----------------+--------+-----------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+--------+------------------------------------------------------------+---------------+---------+-----------------+--------+-----------------------------+
| 1 | SIMPLE | happys | range | PRIMARY,idx_end_time,idx_bg_tag_pub_beg,idx_bg_tag_pub_end | idx_end_time | 8 | | 219114 | Using where; Using filesort |
+----+-------------+------------+--------+------------------------------------------------------------+---------------+---------+-----------------+--------+-----------------------------+
| 1 | SIMPLE | happy_infos | eq_ref | happy_id_index | happy_id_index | 4 | tao800.happys.id | 1 | Using where |
+----+-------------+------------+--------+------------------------------------------------------------+---------------+---------+-----------------+--------+-----------------------------+
平均查询时间：
Empty set (9.78 sec)
优化建议：
1、MySQL里对LIMIT OFFSET的处理方式是，取出OFFSET+LIMIT的所有数据，然后去掉OFFSET，返回底部的LIMIT
使用子查询，使用覆盖索引进行优化。
2、这种方式在offset很高的情况下，
如：limit 100000,20，这样系统会查询100020条，然后把前面的100000条都扔掉，这是开销很大的操作，导致慢查询很慢。
3、使用覆盖索引(convering index) 查询，然后再跟全行做join操作。这样可以直接使用index 得到数据，而不是去查询表，
当找到需要的数据之后，再与全表join获得其他列。
EXPLAIN SELECT SQL_NO_CACHE `happys`.*
FROM `happys`
INNER JOIN
(
SELECT happys.id
FROM happys
INNER JOIN `happy_infos` ON `happy_infos`.`happy_id` = `happys`.`id`
WHERE happys.end_time > '2015-08-13 14:08:10'
AND happys.j_tag_id > 0
AND happy_infos.my_image_url = ''
LIMIT 100 OFFSET 28900
) AS lim ON lim.id = happys.id
ORDER BY happys.updated_at DESC \G;
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: NULL
type: NULL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: NULL
Extra: Impossible WHERE noticed after reading const tables
*************************** 2. row ***************************
id: 2
select_type: DERIVED
table: happys
type: range
possible_keys: PRIMARY,idx_end_time,idx_bg_tag_pub_beg,idx_bg_tag_pub_end
key: idx_bg_tag_pub_end
key_len: 4
ref: NULL
rows: 425143
Extra: Using where; Using index
*************************** 3. row ***************************
id: 2
select_type: DERIVED
table: happy_infos
type: eq_ref
possible_keys: happy_id_index
key: happy_id_index
key_len: 4
ref: tao800.happys.id
rows: 1
Extra: Using where
3 rows in set (0.67 sec)
平均查询时间： 0.67 sec
http://www.jb51.net/article/27504.htm
http://www.jb51.net/article/33777.htm
http://chinahnzhou.iteye.com/blog/1567537
http://dataunion.org/14895.html
http://blog.idaohang123.com/archives/399
http://www.jbxue.com/db/22798.html
http://www.admin10000.com/document/4797.html
http://www.fienda.com/archives/110
http://stackoverflow.com/questions/4481388/why-does-mysql-higher-limit-offset-slow-the-query-down
四、驱动表，临时表，排序
mysql> EXPLAIN SELECT `happy_d_sales`.`happy_id`
-> FROM `happy_d_sales`
-> INNER JOIN happys ON happys.id = happy_d_sales.happy_id
-> AND happys.j_tag_id = happy_d_sales.tag_id
-> WHERE (status = 1
-> AND date = '2015-08-12')
-> ORDER BY sales DESC LIMIT 300\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: happys
type: index
possible_keys: PRIMARY,idx_bg_tag_pub_beg,idx_bg_tag_pub_end
key: idx_bg_tag_pub_beg
key_len: 20
ref: NULL
rows: 850279 <- 返回数据太多，坏味道
Extra: Using index; Using temporary; Using filesort
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: happy_d_sales
type: eq_ref
possible_keys: happy_id_date_tag_idx,tag_id_date
key: happy_id_date_tag_idx
key_len: 11
ref: tao800.happys.id,const,tao800.happys.j_tag_id
rows: 1
Extra: Using where
2 rows in set (0.00 sec)
ERROR:
No query specified
平均查询时间 Empty set (3.90 sec)
EXPLAIN 返回的第一列的表，就是驱动表，在驱动表上排序，非常快。但是如果在非驱动表上，排序，就很慢。
默认情况下，记录就是按照顺序排列好的，不需要进行排序。但是上述结果，从happys 表中取出一些数据，建立临时表，并且还在临时表上进行排序。
所以就会出现 Using temporary; Using filesort 这种情况。
优化建议：
1、减少返回值rows
2、指定正确的驱动表
mysql> ALTER table `happy_d_sales` ADD INDEX `idx_of_date_and_status` (`date`, `status`, `sales`, `id`);
Query OK, 0 rows affected (19.45 sec)
Records: 0 Duplicates: 0 Warnings: 0
mysql> EXPLAIN SELECT `happy_d_sales`.`happy_id`
-> FROM `happy_d_sales`
-> STRAIGHT_JOIN happys ON happys.id = happy_d_sales.happy_id
-> AND happys.j_tag_id = happy_d_sales.tag_id
-> WHERE date = '2015-08-12' AND status = 1
-> ORDER BY `happy_d_sales`.sales DESC LIMIT 300\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: happy_d_sales <-- 正确的驱动表
type: ref
possible_keys: happy_id_date_tag_idx,tag_id_date,idx_of_date_and_status
key: idx_of_date_and_status
key_len: 7
ref: const,const
rows: 1
Extra: Using where
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: happys
type: eq_ref
possible_keys: PRIMARY,idx_bg_tag_pub_beg,idx_bg_tag_pub_end
key: PRIMARY
key_len: 4
ref: tao800.happy_d_sales.happy_id
rows: 1
Extra: Using where
2 rows in set (0.01 sec)
ERROR:
No query specified
平均查询时间：0.03 sec
五、不合适的group by 分组条件
大表上的group by
CREATE TABLE `p_acc_logs` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`account_id` int(11) NOT NULL DEFAULT '0' ,
`b_amount` int(11) NOT NULL DEFAULT '0' ,
`r_amount` int(11) NOT NULL DEFAULT '0' ,
`amount` int(11) NOT NULL DEFAULT '0' ,
`l_type` int(11) NOT NULL DEFAULT '0',
`created_at` datetime NOT NULL,
`updated_at` datetime NOT NULL,
PRIMARY KEY (`id`),
KEY `idx_created_at` (`created_at`,`id`),
KEY `idx_account_type` (`account_id`,`l_type`,`id`)
) ENGINE=InnoDB AUTO_INCREMENT=3212639 DEFAULT CHARSET=utf8;
该表上有百万条的数据，也有 关于 account_id 的索引，但是使用 group by 查询时，确实很慢。
SELECT MAX(id) max_id FROM `p_acc_logs` WHERE (created_at <= '2015-08-14 00:00:00') GROUP BY account_id
平均查询时间 10sec
六、不合适的order by
EXPLAIN SELECT SQL_NO_CACHE id,
u_id,
amount
FROM `t_orders`
WHERE (settlement_time >= '2015-07-01 00:00:00'
AND settlement_time <= '2015-09-30 23:59:59')
ORDER BY `t_orders`.`id` ASC LIMIT 3000;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: t_orders
type: index
possible_keys: idx_settlement_time
key: PRIMARY <--- 注意这里
key_len: 4
ref: NULL
rows: 6705 <---- 注意这里
Extra: Using where
1 row in set (0.09 sec)
ERROR:
No query specified
平均查询时间：40 sec
CREATE TABLE `t_orders` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`u_id` int(11) NOT NULL DEFAULT '0' ,
`order_id` varchar(20) NOT NULL DEFAULT '' ,
`amount` int(11) NOT NULL DEFAULT '0' ,
`settlement_time` datetime NOT NULL DEFAULT '1970-01-01 00:00:00' ,
`d_s_time` datetime DEFAULT '1970-01-01 00:00:00' ,
`serial_number` bigint(20) unsigned DEFAULT NULL ,
`order_type` int(11) DEFAULT NULL ,
`created_at` datetime NOT NULL,
`updated_at` datetime NOT NULL,
PRIMARY KEY (`id`),
KEY `index_t_orders_on_u_id_and_settlement_time_and_id` (`u_id`,`settlement_time`,`id`),
KEY `index_t_orders_on_order_id_and_order_type_and_id` (`order_id`,`order_type`,`id`),
KEY `index_t_orders_on_serial_number_and_order_type_and_id` (`serial_number`,`order_type`,`id`),
KEY `idx_settlement_time` (`settlement_time`,`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
优化建议：
1、去除错误的order by 查询，记录集默认就是按照id升序排列的。
2、使查询语句能够按照正确的方式查询
EXPLAIN SELECT SQL_NO_CACHE id,
u_id,
amount
FROM `t_orders`
WHERE (settlement_time >= '2015-07-01 00:00:00'
AND settlement_time <= '2015-09-30 23:59:59')
LIMIT 3000;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: t_orders
type: range
possible_keys: idx_settlement_time
key: idx_settlement_time <-- 注意这里
key_len: 8
ref: NULL
rows: 12784434 <-- 注意这里
Extra: Using where
1 row in set (0.00 sec)
ERROR:
No query specified
平均查询时间：0.16 sec
七、模糊查询
EXPLAIN SELECT `p_d_logs`.*
FROM `p_d_logs`
WHERE (details LIKE '%waiting%'
AND created_at < '2015-08-09 03:40:35')
AND (`p_d_logs`.`id` > 297273949)
ORDER BY `p_d_logs`.`id` ASC LIMIT 10000\G
+----+-------------+-------------------+-------+---------------+---------+---------+-----+---------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------------------+-------+---------------+---------+---------+-----+---------+-------------+
| 1 | SIMPLE | p_d_logs | range | PRIMARY | PRIMARY | 4 | | 3340552 | Using where |
+----+-------------+-------------------+-------+---------------+---------+---------+-----+---------+-------------+
平均查询时间：7.5889787673950195 sec
EXPLAIN SELECT `e_logs`.`loggable_id`
FROM `e_logs`
WHERE (user_name LIKE '%王大傻%'
AND action_type_id = 0
AND loggable_type = 'HappyBase') \G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: e_logs
type: ref
possible_keys: by_loggable_type
key: by_loggable_type
key_len: 92
ref: const
rows: 684252
Extra: Using where
1 row in set (10.61 sec)
15738 rows in set (3 min 45.75 sec)
CREATE TABLE `e_logs` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`loggable_type` varchar(30) NOT NULL DEFAULT '' ,
`loggable_id` int(11) NOT NULL DEFAULT '0' ,
`u_id` int(11) NOT NULL DEFAULT '0' ,
`user_name` varchar(24) NOT NULL DEFAULT '' ,
`create_time` datetime NOT NULL DEFAULT '1970-01-01 00:00:00' ,
`execution_type_id` tinyint(4) NOT NULL DEFAULT '0' ,
`action_type_id` tinyint(4) NOT NULL DEFAULT '0' ,
`from_url` varchar(200) NOT NULL DEFAULT '' ,
`updated_changes` longtext ,
`t_s_id` int(11) NOT NULL DEFAULT '0' ,
PRIMARY KEY (`id`),
KEY `index_e_logs_on_loggable_id_and_loggable_type` (`loggable_id`,`loggable_type`),
KEY `idx_user_name` (`user_name`,`action_type_id`,`id`),
KEY `index_e_logs_on_create_time` (`create_time`),
KEY `by_t_s_id` (`t_s_id`,`id`),
KEY `by_loggable_type` (`loggable_type`,`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8
优化建议：
1、调整查询语句顺序
2、添加合适的索引。删除旧的索引。
alter table e_logs drop index `by_loggable_type`;
Query OK, 0 rows affected (3 min 12.71 sec)
alter table e_logs add index `idx_of_loggable_type_and_type_id` (`loggable_type`, `action_type_id`, `id`);
Query OK, 0 rows affected (6 min 5.70 sec)
EXPLAIN SELECT SQL_NO_CACHE `e_logs`.`loggable_id`
FROM `e_logs`
WHERE (loggable_type = 'HappyBase' AND action_type_id = 0 AND user_name LIKE '王大傻%') \G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: e_logs
type: range
possible_keys: idx_user_name,idx_of_loggable_type_and_type_id
key: idx_user_name
key_len: 75
ref: NULL
rows: 39546
Extra: Using where
1 row in set (0.01 sec)
平均查询时间： 0.13 sec 效率提升 1700 倍
八、检索条件，没有按照索引列查询
索引，中范围查询什么的，是否能使用到索引，详细演示一下
SELECT happy_id, sum(sales) as all_sales
FROM `happy_d_sales`
WHERE `happy_d_sales`.`status` = 1
AND `happy_d_sales`.`tag_id` IN (xxx,)
GROUP BY happy_id ORDER BY all_sales desc LIMIT 100 OFFSET 0
平均查询时间：20sec
CREATE TABLE `happy_d_sales` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`happy_id` int(11) NOT NULL ,
`tag_id` int(11) NOT NULL ,
`sales` int(11) NOT NULL DEFAULT '0' ,
`status` int(11) NOT NULL DEFAULT '0' ,
`date` date NOT NULL ,
`created_at` datetime NOT NULL,
`updated_at` datetime NOT NULL,
`r_count` int(11) NOT NULL DEFAULT '0' ,
`a_t_s_count` int(11) NOT NULL DEFAULT '0' ,
PRIMARY KEY (`id`),
UNIQUE KEY `happy_id_date_tag_idx` (`happy_id`,`date`,`tag_id`),
KEY `tag_id_date` (`tag_id`,`date`) ,
KEY `idx_of_date_and_status` (`date`,`status`,`sales`,`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 ;
调整下SQL语句的顺序，并且添加合适的索引，瞬间减少查询时间。
explain SELECT SQL_NO_CACHE happy_id, sum(sales) as all_sales
FROM `happy_d_sales`
WHERE `happy_d_sales`.`tag_id` IN (xxxx,xxxx,xxxx)
AND `happy_d_sales`.`status` = 1
GROUP BY happy_id ORDER BY all_sales desc
LIMIT 100 OFFSET 0\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: happy_d_sales
type: range
possible_keys: tag_id_date,idx_of_tag_id_status_happy_id
key: idx_of_tag_id_status_happy_id
key_len: 8
ref: NULL
rows: 94380
Extra: Using where; Using temporary; Using filesort
1 row in set (0.06 sec)
平均查询时间： 100 rows in set (0.43 sec)
九、根本没有索引
explain select t_s_id from guang_happy_outs group by t_s_id;
+----+-------------+-----------------+------+---------------+------+---------+------+----------+---------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-----------------+------+---------------+------+---------+------+----------+---------------------------------+
| 1 | SIMPLE | guang_happy_outs | ALL | NULL | NULL | NULL | NULL | 69008793 | Using temporary; Using filesort |
+----+-------------+-----------------+------+---------------+------+---------+------+----------+---------------------------------+
1 row in set (0.00 sec)
平均查询时间：3 sec
CREATE TABLE `guang_happy_outs` (
`id` int(11) NOT NULL AUTO_INCREMENT ,
`t_s_id` int(11) NOT NULL DEFAULT '0' ,
`happy_id` int(11) NOT NULL DEFAULT '0' ,
`count` int(11) NOT NULL DEFAULT '0' ,
`de_id` int(11) NOT NULL DEFAULT '0' ,
`ad_count` int(11) NOT NULL DEFAULT '0' ,
`st_date` date NOT NULL DEFAULT '1970-01-01' ,
`created_at` datetime DEFAULT NULL,
`updated_at` datetime DEFAULT NULL,
`amount` int(11) NOT NULL DEFAULT '0' ,
PRIMARY KEY (`id`),
KEY `idx_guang_dlout_dlid` (`happy_id`),
KEY `idx_guang_dlout_cat` (`created_at`),
KEY `idx_guang_dlout_stdate` (`st_date`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
优化建议：
1、添加必要的索引
mysql> alter table guang_happy_outs add index `idx_of_t_s_id` (`t_s_id`, `id`);
Query OK, 0 rows affected (7 min 41.47 sec)
Records: 0 Duplicates: 0 Warnings: 0
explain select t_s_id from guang_happy_outs group by t_s_id\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: guang_happy_outs
type: range
possible_keys: NULL
key: idx_of_t_s_id
key_len: 4
ref: NULL
rows: 201
Extra: Using index for group-by
1 row in set (0.01 sec)
ERROR:
No query specified
平均查询时间：
4818 rows in set (0.03 sec)
不过针对大表而言，对于一些常用的查询，可以单独建立小表，在关联的小表上进行查询。
十、EXPLAIN 返回type 为 ALL，全表扫描
EXPLAIN SELECT `r_records`.*
FROM `r_records`
WHERE (create_time >= '2015-08-13'
AND create_time < '2015-08-14'
AND device_id !="0")\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: r_records
type: ALL <-- 看这里
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 10753575 <- 看这里
Extra: Using where
1 row in set (0.01 sec)
ERROR:
No query specified
优化建议：
1、添加关于 create_time 和 device_id 的联合索引。
2、最好的方式就是单独单独建立统计表，针对每天的日志情况做统计。避免在大表上进行范围查询。
alter table r_records add index `idx_of_create_time` (`create_time`, `device_id`, `id`);
Query OK, 0 rows affected (4 min 14.59 sec)
EXPLAIN SELECT `r_records`.*
FROM `r_records`
WHERE (create_time >= '2015-08-13'
AND create_time < '2015-08-14'
AND device_id !="0")\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: r_records
type: range
possible_keys: idx_of_create_time <-- 看这里
key: idx_of_create_time
key_len: 777 <-- 看这里
ref: NULL
rows: 1
Extra: Using where
1 row in set (0.00 sec)
另一个例子
EXPLAIN SELECT `happy_ni_nis`.*
FROM `happy_ni_nis`
ORDER BY n_total DESC LIMIT 10\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: happy_ni_nis
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 66493186 <- 返回值太多，坏味道
Extra: Using filesort <- 避免使用排序
1 row in set (0.01 sec)
平均查询时间：13 sec
优化建议：
1、添加 关于 n_total 的索引
mysql> alter table happy_ni_nis add index `idx_of_n_total` (`n_total`, `id`);
Query OK, 0 rows affected (7 min 48.27 sec)
Records: 0 Duplicates: 0 Warnings: 0
EXPLAIN SELECT `happy_ni_nis`.*
FROM `happy_ni_nis`
ORDER BY n_total DESC LIMIT 10\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: happy_ni_nis
type: index
possible_keys: NULL
key: idx_of_n_total
key_len: 8
ref: NULL
rows: 10
Extra:
1 row in set (0.01 sec)
ERROR:
No query specified
平均查询时间：0.01 sec
十一、针对大表的 count(id)
mysql> select SQL_NO_CACHE count(id) from guang_happy_outs;
+-----------+
| count(id) |
+-----------+
| 69008543 |
+-----------+
1 row in set (31.14 sec)
千万表上的 count(id) 操作
无解。
如有同学知道怎么解决，请回复，3Q
在 select count (*) from table_name 为什么没有使用主键索引? 有详细的讨论。
mysql> select SQL_NO_CACHE count(id) from g_d_outs\G;
*************************** 1. row ***************************
count(id): 69008543
1 row in set (10.76 sec)
ERROR:
No query specified
如果你想得到近似的统计值，使用 下面的这个方式 查找 Rows 值，这种方式是非常快的。
mysql> show table status where name = 'g_d_outs'\G;
*************************** 1. row ***************************
Name: g_d_outs
Engine: InnoDB
Version: 10
Row_format: Compact
Rows: 69008796
Avg_row_length: 71
Data_length: 4965007360
Max_data_length: 0
Index_length: 3560964096
Data_free: 5242880
Auto_increment: 138022949
Create_time: 2015-08-14 18:46:13
Update_time: NULL
Check_time: NULL
Collation: utf8_general_ci
Checksum: NULL
Create_options:
Comment: ??????????
1 row in set (0.01 sec)
总结：
1、索引优化，最傻的办法，给查询语句添加覆盖索引。但不是最好的方式。
2、将大表拆成小的汇总表。
3、重在实践，MySQL优化器在很多情况下不能给出，最快的实现方式。
4、避免在大表上的group by，order by，offset 操作，除非你知道如何优化的前提下。
5、SQL WHERE查询条件，尽量按照目前添加的索引顺序来。
