一、通过索引进行优化

数据结构

Data Structure Visualizations    数据可视化效果展示

Binary Search Tree

插入数据可视化效果展示

 AVL Tree

 Red/Black Tree

--MYISAM存储引擎数据和引用分开存储
DROP TABLE IF EXISTS `t_test`;
CREATE TABLE `t_test` (
  `id` int(11) NOT NULL,
 `test` varchar(9) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=MYISAM;

--InnoDB
DROP TABLE IF EXISTS `t_test2`;
CREATE TABLE `t_test2` (
  `id` int(11) NOT NULL,
 `test` varchar(9) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB;

--查看数据存储路径
show variables like '%datadir%';
mysql> show variables like '%datadir%';
+---------------+---------------------------------------------+
| Variable_name | Value                                       |
+---------------+---------------------------------------------+
| datadir       | C:\ProgramData\MySQL\MySQL Server 8.0\Data\ |
+---------------+---------------------------------------------+
1 row in set, 1 warning (0.00 sec)

--MYISAM存储引擎有如下2个文件
t_test.MYD
t_test.MYI

--InnoDB存储引擎有如下1个文件
t_test2.ibd

1、索引基本知识

索引的优点

1、大大减少了服务器需要扫描的数据量
2、帮助服务器避免排序和临时表
3、将随机io变成顺序io

索引的用处

1、快速查找匹配WHERE子句的行
2、从consideration中消除行,如果可以在多个索引之间进行选择，mysql通常会使用找到最少行的索引
3、如果表具有多列索引，则优化器可以使用索引的任何最左前缀来查找行
4、当有表连接的时候，从其他表检索行数据
5、查找特定索引列的min或max值
6、如果排序或分组时在可用索引的最左前缀上完成的，则对表进行排序和分组
7、在某些情况下，可以优化查询以检索值而无需查询数据行

索引的分类

主键索引
唯一索引
普通索引
全文索引
组合索引

技术名词

回表
覆盖索引
最左匹配
索引下推

索引采用的数据结构

哈希表
B+树

索引匹配方式

CREATE TABLE staffs (
	id INT PRIMARY KEY auto_increment,
	NAME VARCHAR ( 24 ) NOT NULL DEFAULT '' COMMENT '姓名',
	age INT NOT NULL DEFAULT 0 COMMENT '年龄',
	pos VARCHAR ( 20 ) NOT NULL DEFAULT '' COMMENT '职位',
	add_time TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '入职时间' 
) charset utf8 COMMENT '员工记录表';

ALTER TABLE staffs ADD INDEX idx_nap ( NAME, age, pos );

INSERT INTO staffs VALUES ('1', 'zhangsan', 30,'dev',now());
INSERT INTO staffs VALUES ('2', 'lisi', 36,'dev',now());
INSERT INTO staffs VALUES ('3', 'July', 23,'dev',now());
INSERT INTO staffs VALUES ('4', 'Mary', 30,'dev',now());
INSERT INTO staffs VALUES ('6', 'Maryz', 30,'dev',now());
INSERT INTO staffs VALUES ('7', 'July', 25,'dev',now());
INSERT INTO staffs VALUES ('8', 'July', 30,'dev',now());

mysql> show index from staffs;
+--------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+
| Table  | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | Visible | Expression |
+--------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+
| staffs |          0 | PRIMARY  |            1 | id          | A         |           7 |     NULL |   NULL |      | BTREE      |         |               | YES     | NULL       |
| staffs |          1 | idx_nap  |            1 | NAME        | A         |           5 |     NULL |   NULL |      | BTREE      |         |               | YES     | NULL       |
| staffs |          1 | idx_nap  |            2 | age         | A         |           7 |     NULL |   NULL |      | BTREE      |         |               | YES     | NULL       |
| staffs |          1 | idx_nap  |            3 | pos         | A         |           7 |     NULL |   NULL |      | BTREE      |         |               | YES     | NULL       |
+--------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+
4 rows in set (0.02 sec)

全值匹配

--全值匹配指的是和索引中的所有列进行匹配
explain select * from staffs where name = 'July' and age = '23' and pos = 'dev';
mysql> explain select * from staffs where name = 'July' and age = '23' and pos = 'dev';
+----+-------------+--------+------------+------+---------------+---------+---------+-------------------+------+----------+-------+
| id | select_type | table  | partitions | type | possible_keys | key     | key_len | ref               | rows | filtered | Extra |
+----+-------------+--------+------------+------+---------------+---------+---------+-------------------+------+----------+-------+
|  1 | SIMPLE      | staffs | NULL       | ref  | idx_nap       | idx_nap | 140     | const,const,const |    1 |   100.00 | NULL  |
+----+-------------+--------+------------+------+---------------+---------+---------+-------------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

匹配最左前缀

--只匹配前面的几列
explain select * from staffs where name = 'July' and age = '23';
explain select * from staffs where name = 'July';
mysql> explain select * from staffs where name = 'July' and age = '23';
+----+-------------+--------+------------+------+---------------+---------+---------+-------------+------+----------+-------+
| id | select_type | table  | partitions | type | possible_keys | key     | key_len | ref         | rows | filtered | Extra |
+----+-------------+--------+------------+------+---------------+---------+---------+-------------+------+----------+-------+
|  1 | SIMPLE      | staffs | NULL       | ref  | idx_nap       | idx_nap | 78      | const,const |    1 |   100.00 | NULL  |
+----+-------------+--------+------------+------+---------------+---------+---------+-------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

mysql> explain select * from staffs where name = 'July';
+----+-------------+--------+------------+------+---------------+---------+---------+-------+------+----------+-------+
| id | select_type | table  | partitions | type | possible_keys | key     | key_len | ref   | rows | filtered | Extra |
+----+-------------+--------+------------+------+---------------+---------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | staffs | NULL       | ref  | idx_nap       | idx_nap | 74      | const |    3 |   100.00 | NULL  |
+----+-------------+--------+------------+------+---------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

匹配列前缀

--可以匹配某一列的值的开头部分
explain select * from staffs where name like 'J%';
explain select * from staffs where name like '%y';

mysql> explain select * from staffs where name like 'J%';
+----+-------------+--------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
| id | select_type | table  | partitions | type  | possible_keys | key     | key_len | ref  | rows | filtered | Extra                 |
+----+-------------+--------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
|  1 | SIMPLE      | staffs | NULL       | range | idx_nap       | idx_nap | 74      | NULL |    3 |   100.00 | Using index condition |
+----+-------------+--------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)

mysql> explain select * from staffs where name like '%y';
+----+-------------+--------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table  | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+--------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | staffs | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    7 |    14.29 | Using where |
+----+-------------+--------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

匹配范围值

--可以查找某一个范围的数据
explain select * from staffs where name > 'Mary';
mysql> explain select * from staffs where name > 'Mary';
+----+-------------+--------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
| id | select_type | table  | partitions | type  | possible_keys | key     | key_len | ref  | rows | filtered | Extra                 |
+----+-------------+--------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
|  1 | SIMPLE      | staffs | NULL       | range | idx_nap       | idx_nap | 74      | NULL |    2 |   100.00 | Using index condition |
+----+-------------+--------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)

精确匹配某一列并范围匹配另外一列

--可以查询第一列的全部和第二列的部分
explain select * from staffs where name = 'July' and age > 25;
mysql> explain select * from staffs where name = 'July' and age > 25;
+----+-------------+--------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
| id | select_type | table  | partitions | type  | possible_keys | key     | key_len | ref  | rows | filtered | Extra                 |
+----+-------------+--------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
|  1 | SIMPLE      | staffs | NULL       | range | idx_nap       | idx_nap | 78      | NULL |    1 |   100.00 | Using index condition |
+----+-------------+--------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)

只访问索引的查询:也叫索引覆盖   Extra:Using index

--查询的时候只需要访问索引，不需要访问数据行，本质上就是覆盖索引
explain select name,age,pos from staffs where name = 'July' and age = 25 and pos = 'dev';
mysql> explain select name,age,pos from staffs where name = 'July' and age = 25 and pos = 'dev';
+----+-------------+--------+------------+------+---------------+---------+---------+-------------------+------+----------+-------------+
| id | select_type | table  | partitions | type | possible_keys | key     | key_len | ref               | rows | filtered | Extra       |
+----+-------------+--------+------------+------+---------------+---------+---------+-------------------+------+----------+-------------+
|  1 | SIMPLE      | staffs | NULL       | ref  | idx_nap       | idx_nap | 140     | const,const,const |    1 |   100.00 | Using index |
+----+-------------+--------+------------+------+---------------+---------+---------+-------------------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

MySQL官网提供数据结构案例

下载sakila database，执行SQL语句

--导入DB结构
mysql> source D:\.m2\sakila-db\sakila-schema.sql
Query OK, 0 rows affected (0.01 sec)
.....

--导入数据
mysql> source D:\.m2\sakila-db\sakila-data.sql
Query OK, 0 rows affected (0.00 sec)

Database changed
Query OK, 0 rows affected (0.00 sec)
...

2、哈希索引

基于哈希表的实现，只有精确匹配索引所有列的查询才有效
在mysql中，只有memory的存储引擎显式支持哈希索引
哈希索引自身只需存储对应的hash值，所以索引的结构十分紧凑，这让哈希索引查找的速度非常快
哈希索引的限制
    1、哈希索引只包含哈希值和行指针，而不存储字段值，索引不能使用索引中的值来避免读取行
    2、哈希索引数据并不是按照索引值顺序存储的，所以无法进行排序
    3、哈希索引不支持部分列匹配查找，哈希索引是使用索引列的全部内容来计算哈希值
    4、哈希索引支持等值比较查询，也不支持任何范围查询
    5、访问哈希索引的数据非常快，除非有很多哈希冲突，当出现哈希冲突的时候，存储引擎必须遍历链表中的所有行指针，逐行进行比较，直到找到所有符合条件的行
    6、哈希冲突比较多的话，维护的代价也会很高

案例

当需要存储大量的URL，并且根据URL进行搜索查找，如果使用B+树，存储的内容就会很大
select id from url where url=""
也可以利用将url使用CRC32做哈希，可以使用以下查询方式：
select id fom url where url="" and url_crc=CRC32("")
此查询性能较高原因是使用体积很小的索引来完成查找

CRC（Cyclic Redundancy Check）校验实用程序库在数据存储和数据通讯领域，为了保证数据的正确，就不得不采用检错的手段。在诸多检错手段中，CRC是最著名的一种。CRC的全称是循环冗余校验。

CRC的本质
是模-2除法的余数，采用的除数不同，CRC的类型也就不一样。通常，CRC的除数用生成多项式来表示。最常用的CRC码的生成多项式如表1所示。最常用的CRC码及生成多项式名称生成多项式
CRC-12

CRC-16

CRC-CCITT

CRC-32

由于CRC在通讯和数据处理软件中经常采用，笔者在实际工作中对其算法进行了研究和比较，总结并编写了一个具有最高效率的CRC通用程序库。该程序采用查表法计算CRC，在速度上优于一般的直接模仿硬件的算法，可以应用于通讯和数据压缩程序。

MySQL Optimization Learning(一)

MySQL Optimization Learning(二)

不断学习才能不断提高！
生如蝼蚁，当立鸿鹄之志，命比纸薄，应有不屈之心。
乾坤未定，你我皆是黑马，若乾坤已定，谁敢说我不能逆转乾坤？
努力吧，机会永远是留给那些有准备的人，否则，机会来了，没有实力，只能眼睁睁地看着机会溜走。