一、索引介绍
1.1、索引作用
提供了类似于书中目录的作用,目的是为了优化查询
1.2、索引算法上分类
大的分类：
B树索引 Hash索引 R树 Full text GIS #地图类索引 ------------------------------- #B树基于不同的查找算法分类： B-tree 以下两种类型在范围查询方面提供了更好的性能(> < >= <=) B+Tree B*Tree
1.3、索引功能上的分类
1.3.1、辅助索引
1）辅助索引(S)怎么构建B树结构的?
- (1)索引是基于表中列(索引键)的值生成的B树结构
- (2)首先提取此列所有的值,进行自动排序
- (3)将排好序的值,均匀的分布到索引树的叶子节点中(16K)
- (4)然后生成此索引键值所对应得后端数据页的指针
- (5)生成枝节点和根节点,根据数据量级和索引键长度,生成合适的索引树高度
2）辅助索引细分
- 1）普通的单列辅助索引（普通索引）
- 2）覆盖索引(联合索引)：多个列作为索引条件,生成索引树,理论上设计的好的,可以减少大量的回表查询
- 3）唯一索引:索引列的值都是唯一的.
1.3.2、聚集索引
1）前提
- (1)表中设置了主键,主键列就会自动被作为聚集索引.
- (2)如果没有主键,会选择唯一键作为聚集索引.
- (3)聚集索引必须在建表时才有意义,一般是表的无关列(ID)
2）聚集索引(C)怎么构建B树结构的?
- (1) 在建表时,设置了主键列(ID)
- (2) 在将来录入数据时,就会按照ID列的顺序存储到磁盘上.(我们又称之为聚集索引组织表)
- (3) 将排好序的整行数据,生成叶子节点.可以理解为,磁盘的数据页就是叶子节点
1.3.3、索引高度影响因数
1）数据量级, 解决方法:分表,分库,分布式
2）索引列值过长 , 解决方法:前缀索引
3）数据类型:
变长长度字符串,使用了char,解决方案:变长字符串使用varchar
enum类型的使用enum ('山东','河北','黑龙江','吉林','辽宁','陕西'......)
1.3.4、B树查找算法
二、索引基本管理
2.1、查看索引
mysql> desc city; +-------------+----------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-------------+----------+------+-----+---------+----------------+ | ID | int(11) | NO | PRI | NULL | auto_increment | | Name | char(35) | NO | | | | | CountryCode | char(3) | NO | MUL | | | | District | char(20) | NO | | | | | Population | int(11) | NO | | 0 | | +-------------+----------+------+-----+---------+----------------+ Field :列名字 key :有没有索引,索引类型 PRI: 主键索引 UNI: 唯一索引 MUL: 辅助索引(单列,联和,前缀) mysql> show index from city; +-------+------------+-------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ | Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | +-------+------------+-------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ | city | 0 | PRIMARY | 1 | ID | A | 4188 | NULL | NULL | | BTREE | | | | city | 1 | CountryCode | 1 | CountryCode | A | 4188 | NULL | NULL | | BTREE | | | +-------+------------+-------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
2.2、索引创建修改删除
1）创建索引
alter table city add index idx_name(name); #方法一 create index idx_name1 on city(name); #方法二 show index from city;
2）删除索引
alter table city drop index idx_name1; #直接删除索引名称即可
3）覆盖索引(联合索引)
alter table city add key idx_co_po(countrycode,population); #多个字段上建立索引 alter table city add index idx_co_po(countrycode,population); #多个字段上建立索引
4）前缀索引
alter table city add index idx_di(district(5)); #在前5个字符上建立索引
5）唯一索引
alter table city add unique index idx_uni1(name); ERROR 1062 (23000): Duplicate entry 'San Jose' for key 'idx_uni1' #唯一键冲突
三、执行计划
3.1、执行计划介绍
获取到的是优化器选择完成的,他认为代价最小的执行计划.
作用: 语句执行前,先看执行计划信息,可以有效的防止性能较差的语句带来的性能问题.
3.2、select 获取数据的方法
1. 全表扫描(应当尽量避免,因为性能低)
2. 索引扫描
3. 获取不到数据
3.3、执行计划获取及分析
获取优化器选择后的执行计划：explain或者desc
explain select SQL_NO_CACHE * from test where name='AAA'G #SQL_NO_CACHE的作用是禁止缓存查询结果。
mysql> desc select * from city where countrycode='CHN'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: city
partitions: NULL
type: ref
possible_keys: CountryCode
key: CountryCode
key_len: 3
ref: const
rows: 363
filtered: 100.00
Extra: NULL
---------------------------------------------------------------
#执行计划相关信息分析：
table: city #查询操作的表
possible_keys: CountryCode,idx_co_po #可能会走的索引
key: CountryCode #真正走的索引
type: ref #索引类型
Extra: Using index condition #额外信息 四、索引类型详解 *****
如下为索引类型，从左到右性能依次变好.
ALL #全表扫描 index #全索引扫描 range #索引范围查询 ref #辅助索引的等值查询 eq_ref #多表连接的表,On的条件是主键或唯一键 system(const) #主键或唯一键的等值查询 NULL #索引中扫描不到这个数据
在索引扫描类型方面，至少保证在range以上级别。
4.1、all: 全表扫描
desc select * from city;
desc select * from city where name like '%C%';
desc select * from city where name != 'CHN'; #或者<>
desc select * from city where countrycode not in ('CHN','USA');
#注意：生产中几乎是没有这种需求的。尽量避免
4.2、index: 全索引扫描
需要扫描整个索引树,获取到想要数据,比ALL性能好,顺序IO,可以减少回表查询
mysql> desc city; +-------------+----------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-------------+----------+------+-----+---------+----------------+ | ID | int(11) | NO | PRI | NULL | auto_increment | | Name | char(35) | NO | | | | | CountryCode | char(3) | NO | MUL | | | | District | char(20) | NO | | | | | Population | int(11) | NO | | 0 | | +-------------+----------+------+-----+---------+----------------+ mysql> desc select CountryCode from city; +----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-------------+ | 1 | SIMPLE | city | NULL | index | NULL | CountryCode | 3 | NULL | 4188 | 100.00 | Using index | +----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-------------+
4.3、 range : 索引范围查询
4.3.1、情况种类
> < >= <= in or like 'CH%' between and --------------------------------------------------- 注意： B+树额外优化了 > < >= <= between and like 'CH%' in or无法享受B+树的额外优化,可以用union all来替代
4.3.2、示例
mysql> desc select * from city where id<10;
+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+
| 1 | SIMPLE | city | NULL | range | PRIMARY | PRIMARY | 4 | NULL | 9 | 100.00 | Using where |
+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+
mysql> desc select * from city where countrycode in ('CHN','USA');
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-----------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-----------------------+
| 1 | SIMPLE | city | NULL | range | CountryCode | CountryCode | 3 | NULL | 637 | 100.00 | Using index condition |
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-----------------------+
mysql> desc select * from city where countrycode like 'CH%';
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-----------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-----------------------+
| 1 | SIMPLE | city | NULL | range | CountryCode | CountryCode | 3 | NULL | 397 | 100.00 | Using index condition |
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-----------------------+
4.3.3、优化案例：in=>union all
mysql> desc select * from city where countrycode in ('CHN','USA');
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-----------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-----------------------+
| 1 | SIMPLE | city | NULL | range | CountryCode | CountryCode | 3 | NULL | 637 | 100.00 | Using index condition |
+----+-------------+-------+------------+-------+---------------+-------------+---------+------+------+----------+-----------------------+
mysql> desc select * from city where countrycode='CHN' union all select * from city where countrycode='USA';
+----+-------------+-------+------------+------+---------------+-------------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+------+---------------+-------------+---------+-------+------+----------+-------+
| 1 | PRIMARY | city | NULL | ref | CountryCode | CountryCode | 3 | const | 363 | 100.00 | NULL |
| 2 | UNION | city | NULL | ref | CountryCode | CountryCode | 3 | const | 274 | 100.00 | NULL |
+----+-------------+-------+------------+------+---------------+-------------+---------+-------+------+----------+-------+4.4、 ref: 辅助索引的等值查询
mysql> desc select * from city where countrycode = 'CHN'; +----+-------------+-------+------------+------+---------------+-------------+---------+-------+------+----------+-------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------------+------+---------------+-------------+---------+-------+------+----------+-------+ | 1 | SIMPLE | city | NULL | ref | CountryCode | CountryCode | 3 | const | 363 | 100.00 | NULL | +----+-------------+-------+------------+------+---------------+-------------+---------+-------+------+----------+-------+
4.5、eq_ref
多表连接的表,On的条件是主键或唯一键
4.6、system 或 const
主键或唯一键的等值查询
mysql> desc select * from city where id=10; +----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+ | 1 | SIMPLE | city | NULL | const | PRIMARY | PRIMARY | 4 | const | 1 | 100.00 | NULL | +----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
4.7、NULL
索引中扫描不到这个数据
mysql> desc select * from city where id=5000; #id=5000不存在 +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+--------------------------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+--------------------------------+ | 1 | SIMPLE | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | no matching row in const table | +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+--------------------------------+
4.8、Extra字段：Using filesort问题
Extra字段：Using filesort #出现说明有问题，要优化 desc select * from city where countrycode='CHN' order by population desc limit 10; #contrycode上有索引，但population上是没有索引的 mysql> desc select * from city where countrycode='CHN' order by population desc limit 10; +----+-------------+-------+------------+------+---------------+-------------+---------+-------+------+----------+---------------------------------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------------+------+---------------+-------------+---------+-------+------+----------+---------------------------------------+ | 1 | SIMPLE | city | NULL | ref | CountryCode | CountryCode | 3 | const | 363 | 100.00 | Using index condition; Using filesort | +----+-------------+-------+------------+------+---------------+-------------+---------+-------+------+----------+---------------------------------------+ #解决思路： 索引可以减少排序,可以很大程度减少CPU时间 辅助索引 应用顺序(优化器选择的) 如果查询条件:符合覆盖索引的顺序时,优先选择覆盖索引 不符合顺序,优先会走where条件的索引 #解决方法：可以在countrycode和population上建立联合索引 mysql> alter table city add index idx_po(countrycode,population); mysql> desc select * from city where countrycode='CHN' order by population limit 10; +----+-------------+-------+------------+------+--------------------+--------+---------+-------+------+----------+-----------------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------------+------+--------------------+--------+---------+-------+------+----------+-----------------------+ | 1 | SIMPLE | city | NULL | ref | CountryCode,idx_po | idx_po | 3 | const | 363 | 100.00 | Using index condition | +----+-------------+-------+------------+------+--------------------+--------+---------+-------+------+----------+-----------------------+
4.9、explain使用场景
面试：我们公司业务慢,请你从数据库的角度分析原因？ mysql出现性能问题,总结有两种情况: （1）应急性的慢：突然夯住 应急情况:数据库hang(卡了,资源耗尽) 处理过程: (1)show processlist; #获取到导致数据库hang住的语句 (2)explain #分析SQL的执行计划,有没有走索引,索引的类型情况 (3)建索引,改语句 （2）一段时间慢(持续性的): (1)记录慢日志slowlog,分析slowlog (2)explain 分析SQL的执行计划,有没有走索引,索引的类型情况 (3)建索引,改语句
五、索引压力测试
5.1、mysqlslap测试示例
mysqlslap工具介绍
mysqlslap来自于mariadb包，测试的过程默认生成一个mysqlslap的schema,生成测试表t1，查询和插入测试数据，mysqlslap库自动生成，如果已经存在则先删除。用--only-print来打印实际的测试过程，整个测试完成后不会在数据库中留下痕迹。
常用选项：
--auto-generate-sql, -a 自动生成测试表和数据，表示用mysqlslap工具自己生成的SQL脚本来测试并发压力
--auto-generate-sql-load-type=type 测试语句的类型。代表要测试的环境是读操作还是写操作还是两者混合的。取值包括：read，key，write，update和mixed(默认)
--auto-generate-sql-add-auto-increment 代表对生成的表自动添加auto_increment列，从5.1.18版本开始支持
--number-char-cols=N, -x N 自动生成的测试表中包含多少个字符类型的列，默认1
--number-int-cols=N, -y N 自动生成的测试表中包含多少个数字类型的列，默认1
--number-of-queries=N 总的测试查询次数(并发客户数×每客户查询次数)
--query=name,-q 使用自定义脚本执行测试，例如可以调用自定义的存储过程或者sql语句来执行测试
--create-schema 代表自定义的测试库名称，测试的schema，MySQL中schema也就是database
--commint=N 多少条DML后提交一次
--compress, -C 如服务器和客户端都支持压缩，则压缩信息
--concurrency=N, -c N 表示并发量，即模拟多少个客户端同时执行select；可指定多个值，以逗号或者--delimiter参数指定值做为分隔符
--engine=engine_name, -e engine_name 代表要测试的引擎，可以有多个，用分隔符隔开
--iterations=N, -i N 测试执行的迭代次数，代表要在不同并发环境下，各自运行测试多少次
--only-print 只打印测试语句而不实际执行
--detach=N 执行N条语句后断开重连
--debug-info, -T 打印内存和CPU的相关信息
测试示例：
1）单线程测试
[root@centos7 ~]# mysqlslap -a -uroot -p
Enter password:
Benchmark
Average number of seconds to run all queries: 0.004 seconds
Minimum number of seconds to run all queries: 0.004 seconds
Maximum number of seconds to run all queries: 0.004 seconds
Number of clients running queries: 1
Average number of queries per client: 0
2）多线程测试，使用--concurrency来模拟并发连接
[root@centos7 ~]# mysqlslap -uroot -p -a -c 500
Enter password:
Benchmark
Average number of seconds to run all queries: 3.384 seconds
Minimum number of seconds to run all queries: 3.384 seconds
Maximum number of seconds to run all queries: 3.384 seconds
Number of clients running queries: 500
Average number of queries per client: 0
3）同时测试不同的存储引擎的性能进行对比
[root@centos7 ~]# mysqlslap -uroot -p -a --concurrency=500 --number-of-queries 1000 --iterations=5 --engine=myisam,innodb --debug-info
Enter password:
Benchmark
Running for engine myisam
Average number of seconds to run all queries: 0.192 seconds
Minimum number of seconds to run all queries: 0.187 seconds
Maximum number of seconds to run all queries: 0.202 seconds
Number of clients running queries: 500
Average number of queries per client: 2
Benchmark
Running for engine innodb
Average number of seconds to run all queries: 0.355 seconds
Minimum number of seconds to run all queries: 0.350 seconds
Maximum number of seconds to run all queries: 0.364 seconds
Number of clients running queries: 500
Average number of queries per client: 2
User time 0.33, System time 0.58
Maximum resident set size 22892, Integral resident set size 0
Non-physical pagefaults 46012, Physical pagefaults 0, Swaps 0
Blocks in 0 out 0, Messages in 0 out 0, Signals 0
Voluntary context switches 31896, Involuntary context switches 0
4）执行一次测试，分别500和1000个并发，执行5000次总查询
[root@centos7 ~]# mysqlslap -uroot -p -a --concurrency=500,1000 --number-of-queries 5000 --debug-info
Enter password:
Benchmark
Average number of seconds to run all queries: 3.378 seconds
Minimum number of seconds to run all queries: 3.378 seconds
Maximum number of seconds to run all queries: 3.378 seconds
Number of clients running queries: 500
Average number of queries per client: 10
Benchmark
Average number of seconds to run all queries: 3.101 seconds
Minimum number of seconds to run all queries: 3.101 seconds
Maximum number of seconds to run all queries: 3.101 seconds
Number of clients running queries: 1000
Average number of queries per client: 5
User time 0.84, System time 0.64
Maximum resident set size 83068, Integral resident set size 0
Non-physical pagefaults 139977, Physical pagefaults 0, Swaps 0
Blocks in 0 out 0, Messages in 0 out 0, Signals 0
Voluntary context switches 31524, Involuntary context switches 3
5）迭代测试
[root@centos7 ~]# mysqlslap -uroot -p -a --concurrency=500 --number-of-queries 5000 --iterations=5 --debug-info
Enter password:
Benchmark
Average number of seconds to run all queries: 3.307 seconds
Minimum number of seconds to run all queries: 3.184 seconds
Maximum number of seconds to run all queries: 3.421 seconds
Number of clients running queries: 500
Average number of queries per client: 10
User time 2.18, System time 1.58
Maximum resident set size 74872, Integral resident set size 0
Non-physical pagefaults 327732, Physical pagefaults 0, Swaps 0
Blocks in 0 out 0, Messages in 0 out 0, Signals 0
Voluntary context switches 73904, Involuntary context switches 3 1）模拟数据库数据
drop database oldboy; create database oldboy charset utf8;
2）创建一个t1的表，然后导入50万行数据
[root@db01 ~]# vim slap.sh
#!/bin/bash
HOSTNAME="localhost"
PORT="3306"
USERNAME="root"
PASSWORD="1"
DBNAME="oldboy"
TABLENAME="t1"
#create database
mysql -h ${HOSTNAME} -P${PORT} -u${USERNAME} -p${PASSWORD} -e "drop database if exists ${DBNAME}"
create_db_sql="create database if not exists ${DBNAME}"
mysql -h ${HOSTNAME} -P${PORT} -u${USERNAME} -p${PASSWORD} -e "${create_db_sql}"
#create table
create_table_sql="create table if not exists ${TABLENAME}(stuid int not null primary key,stuname varchar(20) not null,stusex char(1)
not null,cardid varchar(20) not null,birthday datetime,entertime datetime,address varchar(100)default null)"
mysql -h ${HOSTNAME} -P${PORT} -u${USERNAME} -p${PASSWORD} ${DBNAME} -e "${create_table_sql}"
#insert data to table
i="1"
while [ $i -le 500000 ]
do
insert_sql="insert into ${TABLENAME} values($i,'alexsb_$i','1','110011198809163418','1990-05-16','2017-09-13','oldboyedu')"
mysql -h ${HOSTNAME} -P${PORT} -u${USERNAME} -p${PASSWORD} ${DBNAME} -e "${insert_sql}"
let i++
done
#select data
select_sql="select count(*) from ${TABLENAME}"
mysql -h ${HOSTNAME} -P${PORT} -u${USERNAME} -p${PASSWORD} ${DBNAME} -e "${select_sql}"
执行脚本：
sh slap.sh
或者直接source
drop database oldboy;
source /root/oldboy.sql3）检查数据可用性
mysql -uroot -p select count(*) from oldboy.t1;
4）使用mysqlslap来进行压力测试
mysqlslap --defaults-file=/etc/my.cnf --concurrency=100 --iterations=1 --create-schema='oldboy' --query="select * from oldboy.t1 where stuname='alexsb_100'" engine=innodb --number-of-queries=2000 -uroot -pmysql -verbose
没建立索引之前：
在查询条件列上建立索引：alter table t1 add index idx_name(stuname);
5.2、其他测试工具（待测试）
1）tpcc
2）sysbench
六、索引应用规范
主要根据公司的业务来建立合适的索引
- 产品的功能
- 用户的行为："热"查询语句，"热"数据
6.1、建立索引的原则
为了使索引的使用效率更高，在创建索引时，必须考虑在哪些字段上创建索引和创建什么类型的索引。
1）建表时一定要有主键，一般是个无关列（必须）
2）选择唯一键索引
唯一性索引的值是唯一的，可以更快速的通过该索引来确定某条记录。
#优化方案：
(1) 如果非得使用重复值较多的列作为查询条件(例如:男女),可以将表逻辑拆分
(2) 可以将此列和其他的查询类,做联和索引
#如何判断索引列有多少是唯一值？
select count(*) from world.city;
select count(distinct countrycode) from world.city;
select count(distinct countrycode,population ) from world.city;
3）为经常需要where 、ORDER BY、GROUP BY,join on等操作的字段建立索引，排序操作会浪费很多时间。注：如果经常作为条件的列，重复值特别多，可以建立联合索引
4）使用前缀索引。如果索引字段的值很长，最好使用值的前缀来索引。
5）限制索引的数目
索引的数目不是越多越好。可能会产生的问题: (1) 每个索引都需要占用磁盘空间，索引越多，需要的磁盘空间就越大。 (2) 修改表时，对索引的重构和更新很麻烦。越多的索引，会使更新表变得很浪费时间。 (3) 优化器的负担会很重,有可能会影响到优化器的选择.
6）删除不再使用或者很少使用的索引(使用percona toolkit)
表中的数据被大量更新，或者数据的使用方式被改变后，原有的一些索引可能不再需要。数据库管理 员应当定期找出这些索引，将它们删除，从而减少索引对更新操作的影响。
7）大表加索引,要在业务不繁忙期间操作
8）尽量少在经常更新值的列上建索引
建立索引原则总结：
(1) 必须要有主键,如果没有可以做为主键条件的列,创建无关列 (2) 经常做为where条件列 order by group by join on, distinct 的条件(业务:产品功能+用户行为) (3) 最好使用唯一值多的列作为索引,如果索引列重复值较多,可以考虑使用联合索引 (4) 列值长度较长的索引列,我们建议使用前缀索引. (5) 降低索引条目,一方面不要创建没用索引,不常使用的索引清理,使用percona toolkit工具 (6) 索引维护要避开业务繁忙期
6.2、 不走索引的情况
1）没有查询条件，或者查询条件没有建立索引
select * from tab; #全表扫描 select * from tab where 1=1;
在业务数据库中，特别是数据量比较大的表，是没有全表扫描这种需求。
- 对用户查看是非常痛苦的。
- 对服务器来讲毁灭性的。
（1）select * from tab; SQL改写成以下语句： selec * from tab order by price limit 10 ; #需要在price列上建立索引 （2）select * from tab where name='zhangsan' #name列没有索引 改成如下语句： 1、换成有索引的列作为查询条件 2、将name列建立索引
2）查询的结果集，超过了总数行数25%，优化器默认没有必要走索引
解决方法： 1、如果业务允许，可以使用limit控制。 2、尽量不要在mysql存放这个数据了，可以放到redis里面
3）索引本身失效，统计数据不真实
索引有自我维护的能力。对于表内容变化比较频繁的情况下，有可能会出现索引失效。一般是删除重建
4）查询条件使用函数在索引列上，或者对索引列进行运算，运算包括(+，-，*，/，! 等)
错误的例子：select * from test where id-1=9; 正确的例子：select * from test where id=10; 在索引列上使用算术运算，函数运算，子查询时，可能不会走索引
5）隐式转换导致索引失效
mysql> alter table tab add index inx_tel(telnum); mysql> desc tab; +--------+-------------+------+-----+---------+-------+ | Field | Type | Null | Key | Default | Extra | +--------+-------------+------+-----+---------+-------+ | id | int(11) | YES | | NULL | | | name | varchar(20) | YES | | NULL | | | telnum | varchar(20) | YES | MUL | NULL | | #字段类型是varchar，同时建立了索引 +--------+-------------+------+-----+---------+-------+ mysql> select * from tab where telnum='1333333'; #查询条件是字符串，走索引 +------+------+---------+ | id | name | telnum | +------+------+---------+ | 1 | a | 1333333 | +------+------+---------+ mysql> select * from tab where telnum=1333333; #查询条件是数字，隐式转换为字符串 +------+------+---------+ | id | name | telnum | +------+------+---------+ | 1 | a | 1333333 | +------+------+---------+ mysql> explain select * from tab where telnum='1333333'; +----+-------------+-------+------+---------------+---------+---------+-------+------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+------+---------------+---------+---------+-------+------+-----------------------+ | 1 | SIMPLE | tab | ref | inx_tel | inx_tel | 63 | const | 1 | Using index condition | +----+-------------+-------+------+---------------+---------+---------+-------+------+-----------------------+ mysql> explain select * from tab where telnum=1333333; +----+-------------+-------+------+---------------+------+---------+------+------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+------+---------------+------+---------+------+------+-------------+ | 1 | SIMPLE | tab | ALL | inx_tel | NULL | NULL | NULL | 2 | Using where | +----+-------------+-------+------+---------------+------+---------+------+------+-------------+
6）<> ，not in 不走索引
EXPLAIN SELECT * FROM teltab WHERE telnum <> '110';
EXPLAIN SELECT * FROM teltab WHERE telnum NOT IN ('110','119');
注意：
1. 单独的>,<,in 有可能走，也有可能不走，和结果集有关，尽量结合业务添加limit
2. or或in 尽量改成union
EXPLAIN SELECT * FROM teltab WHERE telnum IN ('110','119');
改写成：
EXPLAIN SELECT * FROM teltab WHERE telnum='110'
UNION ALL
SELECT * FROM teltab WHERE telnum='119'
7）like "%_" 百分号在最前面不走
EXPLAIN SELECT * FROM teltab WHERE telnum LIKE '31%' #走range索引扫描 EXPLAIN SELECT * FROM teltab WHERE telnum LIKE '%110' #不走索引 %linux%类的搜索需求，可以使用elasticsearch+mongodb 专门做搜索服务的数据库产品
8）单独引用联合索引里非第一位置的索引列.作为条件查询时不走索引
idx_a_b_c(a,b,c) #建立的联合索引 走索引的情况： where a b c where a b where a ============ 部分走索引 where a c where a c b ============ 不走索引 where c where b where bc where cb where ca where cba