标签：buffer 提高 查看 extra 隐式转换 主键索引 数据量 超过 class
#1.建表时创建
create table test(id int primary key);
create table test(id int,primary key(id));
#2.添加主键索引
alter table test add primary key pri_key(id);
#1.建表时创建
create table test(id int unique key);
#2.添加唯一建索引
alter table test add unique key uni_key(id);
#1.添加普通索引
alter table test add index ljp_key(id);
#1.方式一：
mysql> show index from test10;
#2.方式二：
mysql> desc test10;
+-------+---------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+---------+------+-----+---------+-------+
| id | int(11) | YES | UNI | NULL | |
+-------+---------+------+-----+---------+-------+
1 row in set (0.00 sec)
PRI：主键索引
UNI：唯一建索引
MUL：普通索引
mysql> alter table test drop index index_key;
1.创建索引时会将数据重新进行排序
2.创建索引会占用磁盘空间，所以索引不是越多越好
3.在同一列上避免创建多种索引
4.避免在数据很长的字段上创建索引，如果要创建就创建前缀索引
#根据前四个字符创建前缀索引
mysql> alter table test add index index_key(name(4));
mysql> create database xiangqing;
mysql> create table xiangqin(id int,name varchar(20),gender enum(‘m‘,‘f‘),age tinyint,money int,height int,weight int,looks tinyint);
mysql> insert xiangqin values(1,‘qiudao‘,‘m‘,38,-200000,120,130,‘10‘),(2,‘dilireba‘,‘f‘,18,400000,180,100,‘60‘),(3,‘cxk‘,‘m‘,28,100000,170,120,‘440‘),(4,‘fbb‘,‘f‘,18,1000000,165,85,‘90‘);
#创建联合索引
mysql> alter table xiangqin add index lh_key(money,gender,age,looks);
#联合索引使用三种情况
1.部分走索引 money,gender,age
2.全部走索引 money,gender,age,looks
3.不走索引 gender,age
explain + DQL语句
mysql> explain select * from city where countrycode =‘CHN‘ or countrycode =‘USA‘;
#查询中国和美国的数据
mysql> select * from city where countrycode =‘CHN‘ or countrycode =‘USA‘;
mysql> select * from city where countrycode in (‘CHN‘,‘USA‘);
mysql> select * from city where countrycode = ‘CHN‘ union all select * from city where countrycode = ‘USA‘;
Extra（扩展）
Using temporary 使用group by大概率出现
Using filesort 使用了order by大概率出现
Using join buffer 使用join on大概率出现
#一般与聚合索引一起使用
#建表
mysql> create table jixiao(id int,name varchar(20) charset utf8,jixiao int,product varchar(10) charset utf8);
Query OK, 0 rows affected (0.03 sec)
#插入数据
mysql> insert jixiao values(1,‘qiudao‘,‘1000000‘,‘房地产‘),(2,‘niulei‘,‘10000‘,‘房地产‘),(3,‘lijianpeng‘,‘100000‘,‘汽车‘),(4,‘qiandao‘,‘200000‘,‘ 汽车‘);
#查询不同行业绩效最高的人
mysql> select name,sum(jixiao),product from jixiao group by product;
+------------+-------------+-----------+
| name | sum(jixiao) | product |
+------------+-------------+-----------+
| qiudao | 1010000 | 房地产 |
| lijianpeng | 300000 | 汽车 |
+------------+-------------+-----------+
2 rows in set (0.00 sec)
#查询房地产行业绩效最高的人
mysql> select name,sum(jixiao),product from jixiao group by product having product=‘房地产‘;
+--------+-------------+-----------+
| name | sum(jixiao) | product |
+--------+-------------+-----------+
| qiudao | 1010000 | 房地产 |
+--------+-------------+-----------+
1 row in set (0.00 sec)
#1.什么是全表扫描
查询数据时type类型为ALL
#2.什么情况全表扫描
1）查询数据库所有数据
mysql> explain select * from country
2）没有走索引
没设置索引
索引损坏
1.index #全索引扫描
mysql> explain select Name from city;
2.range #范围查询
mysql> explain select * from city where countrycode =‘CHN‘ or countrycode =‘USA‘;
#有限制查询到的数据在总数据的20%以内，超过则走全文扫描，所以在查询是可以使用limit限制
mysql> explain select * from city where countrycode != ‘CHN‘ limit 500;
3.ref #精确查询
mysql> explain select * from city where countrycode =‘CHN‘;
4.eq_ref #使用join on时偶尔会出现
5.const #查询条件是唯一索引或主键索引
mysql> explain select * from city where id=1;
6.system #查询级别与const一样，当数据很少时为该级别
7.null #不需要读取数据，只需要获取最大值或者最小值
mysql> explain select max(population) from city;
1.能创建唯一索引就创建唯一索引
2.为经常需要排序、分组和联合操作的字段建立索引
3.为常作为查询条件的字段建立索引
如果某个字段经常用来做查询条件，那么该字段的查询速度会影响整个表的查询速度。
因此，为这样的字段建立索引，可以提高整个表的查询速度。
4.尽量使用前缀来索引
如果索引字段的值很长，最好使用值的前缀来索引。
例如，TEXT和BLOG类型的字段，进行全文检索，会很浪费时间。如果只检索字段的前面的若干个字符，这样可以提高检索速度。
5.限制索引的数目
索引的数目不是越多越好。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。
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。
6.删除不再使用或者很少使用的索引
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。
#没有查询条件
mysql> explain select * from city;
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
| 1 | SIMPLE | city | ALL | NULL | NULL | NULL | NULL | 4188 | NULL |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
1 row in set (0.00 sec)
#查询条件没有索引
mysql> explain select District from city;
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
| 1 | SIMPLE | city | ALL | NULL | NULL | NULL | NULL | 4188 | NULL |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
1 row in set (0.00 sec)
#占总数据的18%，没走索引
mysql> explain select * from city where population > 400000;
#占总数据的15%，走了索引
mysql> explain select * from city where population > 450000;
#如果数据量查询就是表中大部分数据，可以用limit做限制
mysql> explain select * from city where population > 400000 limit 100;
#在=号左侧有特殊符号，不走索引
mysql> explain select * from city where id-1=1;
#在=号右侧有特殊符号，走索引
mysql> explain select * from city where id=3-1;
#建表
mysql> create table test (id int ,name varchar(20),telnum varchar(10));
Query OK, 0 rows affected (0.04 sec)
#插入数据
mysql> insert into test values(1,‘zs‘,‘110‘),(2,‘l4‘,120),(3,‘w5‘,119),(4,‘z4‘,112);
Query OK, 4 rows affected (0.00 sec)
Records: 4 Duplicates: 0 Warnings: 0
#建立索引
mysql> desc phonenum;
+-------+-------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+-------------+------+-----+---------+-------+
| id | int(11) | YES | | NULL | |
| name | varchar(10) | YES | | NULL | |
| phone | varchar(10) | YES | UNI | NULL | |
+-------+-------------+------+-----+---------+-------+
3 rows in set (0.00 sec)
#查询语句级别全文扫描
mysql> explain select * from phonenum where phone=6666666;
+----+-------------+----------+------+---------------+------+---------+------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+----------+------+---------------+------+---------+------+------+-------------+
| 1 | SIMPLE | phonenum | ALL | uni_key | NULL | NULL | NULL | 3 | Using where |
+----+-------------+----------+------+---------------+------+---------+------+------+-------------+
1 row in set (0.00 sec)
#当给字符加上引号，查询为索引扫描
mysql> explain select * from phonenum where phone=‘6666666‘;
+----+-------------+----------+-------+---------------+---------+---------+-------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+----------+-------+---------------+---------+---------+-------+------+-------+
| 1 | SIMPLE | phonenum | const | uni_key | uni_key | 13 | const | 1 | NULL |
+----+-------------+----------+-------+---------------+---------+---------+-------+------+-------+
1 row in set (0.00 sec)
#走range索引扫描
EXPLAIN SELECT * FROM teltab WHERE telnum LIKE ‘31%‘;
#不走索引
EXPLAIN SELECT * FROM teltab WHERE telnum LIKE ‘%110‘;
%linux%类的搜索需求，可以使用Elasticsearch -------> ELK
单独引用联合索引里非第一位置的索引列
CREATE TABLE t1 (id INT,NAME VARCHAR(20),age INT ,sex ENUM(‘m‘,‘f‘),money INT);
ALTER TABLE t1 ADD INDEX t1_idx(money,age,sex);
DESC t1
SHOW INDEX FROM t1
#走索引的情况测试
EXPLAIN SELECT NAME,age,sex,money FROM t1 WHERE money=30 AND age=30 AND sex=‘m‘;
#部分走索引
EXPLAIN SELECT NAME,age,sex,money FROM t1 WHERE money=30 AND age=30;
EXPLAIN SELECT NAME,age,sex,money FROM t1 WHERE money=30 AND sex=‘m‘;
#不走索引
EXPLAIN SELECT NAME,age,sex,money FROM t1 WHERE age=20
EXPLAIN SELECT NAME,age,sex,money FROM t1 WHERE age=30 AND sex=‘m‘;
EXPLAIN SELECT NAME,age,sex,money FROM t1 WHERE sex=‘m‘;
标签：buffer 提高 查看 extra 隐式转换 主键索引 数据量 超过 class
原文地址：https://www.cnblogs.com/zabcd/p/13330076.html
