Index of MySQL

Introduce ：
The index is through some algorithm , Build a data model , Used to quickly find rows with a specific value in a column , No index ,MySQL You must read the entire table from the first entry , Until you find the relevant row , The bigger the watch , The more time it takes to query the data , If the queried column in the table has an index ,MySQL Can quickly reach a location to search data files , Instead of looking at all the data , That would save a lot of time .

classification

An index is a data structure used by a storage engine to quickly find records , According to the way of implementation, it is divided into , There are mainly HASH Index and B+TREE Indexes

Create index

Single index ： An index contains only a single column , But you can have multiple single-column indexes in a table
General index ：MySQL Basic index type , There are no restrictions , Allows you to insert duplicate values and controls into columns that define indexes , Just to query data faster .

Single index

General index

Create operation
for example ：

CREATE DATABASE mydb5;
USE mydb5;

--  Mode one  - When creating a table, specify 
CREATE TABLE student(
	sid INT PRIMARY KEY,
	card_id VARCHAR(50),
	name VARCHAR(50),
	gender VARCHAR(20),
	age INT,
	birth DATE,
	phone_num VARCHAR(20),
	score DOUBLE,
	INDEX index_name(name) --  to name Column creation index 
);
SELECT * FROM student WHERE name=' Zhang San ';

--  The second way  -  Create directly 
CREATE INDEX index_gender ON student(gender);

--  The third way  -  Modify table structure （ Add index ）
ALTER TABLE student ADD INDEX index_age(age);

Check operation
for example ：

-- 1. View all indexes of the database 
SELECT * FROM mysql.innodb_index_stats a WHERE a.database_name='mydb5';

-- 2. View all indexes in the table 
SELECT * FROM mysql.innodb_index_stats a WHERE a.database_name = 'mydb5' AND a.table_name LIKE '%student%';

-- 3. View all indexes in the table 
SHOW INDEX FROM student;

Delete index
Method ：
DROP INDEX Index name ON Table name
or
ALTER TABLE Table name DROP INDEX Index name

for example ：

--  Delete index 
DROP INDEX index_gender ON student;

ALTER TABLE student DROP INDEX index_age;

unique index

Concept ： The unique index is similar to the previous ordinary index , The difference is that ： The value of the index column must be unique , But you can have an empty value . If it's a composite index , The combination of column values must be unique .
Add index
for example ：

--  Mode one  - When creating a table, specify 
CREATE TABLE student2(
	sid INT PRIMARY KEY,
	card_id VARCHAR(50),
	name VARCHAR(50),
	gender VARCHAR(20),
	age INT,
	birth DATE,
	phone_num VARCHAR(20),
	score DOUBLE,
	UNIQUE index_card_id(card_id) --  to card_id Column creation index 
);

--  The second way  -  Create directly 
CREATE UNIQUE INDEX index_gender ON student2(gender);

--  The third way  -  Modify table structure （ Add index ）
ALTER TABLE student ADD UNIQUE INDEX index_age(age);

Delete index
Method ：
DROP INDEX Index name ON Table name
or
ALTER TABLE Table name DROP INDEX Index name

for example ：

--  Delete index 
DROP INDEX index_gender ON student2;

ALTER TABLE student2 DROP INDEX index_age;

primary key

Concept ： Each table usually has its own primary key , When we create a table MySQL Will automatically create an index on the primary key column , This is the primary key index . The primary key is unique and cannot be NULL, So it's a special kind of unique index .

for example ：

--  primary key 
SHOW INDEX FROM student2;
--  At this point, you can see the primary key index , But it cannot be seen in the visual interface , And for automatic creation 

Composite index

Concept ：

• Composite index is also called composite index , It means that we use multiple fields when building the index , For example, use both ID card and mobile phone number to establish index , Similarly, it is also necessary to establish a common index or a unique index .
• The leftmost principle of composite index

Method ：
CREATE INDEX indexname ON table_name (column1(length),column2(length));

for example ：

--  Create a normal index 
CREATE INDEX index_phone_name ON student(phone_num,name);

--  Delete index 
DROP INDEX index_phone_name ON student;

--  Create unique index 
CREATE UNIQUE INDEX index_phone_name ON student(phone_num,name);

Full-text index

Concept ：

• The keyword of full-text index is fulltext

• Full text index is mainly used to find keywords in text , Rather than directly comparing the values in the index , It's more like a search engine , Similarity based query is not simple where The parameters of the statement match .

• use like+% Then we can achieve fuzzy matching , But this method is suitable when there is less data , For a large number of text data retrieval , You can't . Full text search in a large amount of data , Than like+% It's much faster , But there is a precision problem in full-text retrieval

• MySQL5.6 Before , Only MyISAM The storage engine supports full-text indexing

• MySQL5.6 after ,MyISAM and InnoDB Storage engines support full-text indexing

• Only the data type of the field is char、varchar、text And its series

• When the data is large , First put the data into a table without a global index , And then use craete index establish fulltext Indexes , It's better than building a table first fulltext Then the speed of data writing is much faster

• When testing or using full-text indexing , Look at your own first MySQL edition 、 Whether the storage engine and data type support full-text indexing .

  MySQL The full-text index in has two variables , Minimum search length and maximum search length . For words whose length is less than the minimum search length and the maximum search length , Will not be indexed . These two default values can be viewed with the following command ：
  SHOW VARIABLES LIKE ‘%ft%’

Operation of full-text index

for example ：

CREATE table t_article(
	id INT PRIMARY KEY AUTO_INCREMENT,
	title VARCHAR(255),
	content VARCHAR(10000),
	writing_date DATE
-- 	FULLTEXT(content)  Create full text index 
);

insert into t_article values(null,"Yesterday Once More","When I was young I listen to the radio",'2021-10-01');
insert into t_article values(null,"Right Here Waiting","Oceans apart, day after day,and I slowly go insane",'2021-10-02'); 
insert into t_article values(null,"My Heart Will Go On","every night in my dreams,i see you, i feel you",'2021-10-03');
insert into t_article values(null,"Everything I Do","eLook into my eyes,You will see what you mean to me",'2021-10-04');
insert into t_article values(null,"Called To Say I Love You","say love you no new year's day, to celebrate",'2021-10-05');
insert into t_article values(null,"Nothing's Gonna Change My Love For You","if i had to live my life without you near me",'2021-10-06');
insert into t_article values(null,"Everybody","We're gonna bring the flavor show U how.",'2021-10-07');

--  Modify table structure to add full-text index 
ALTER TABLE t_article ADD FULLTEXT index_context(content);

--  Add full text index ( Choose one from the above modification )
CREATE FULLTEXT INDEX index_context ON t_article(content);

--  Use full text indexing 
SELECT * FROM t_article WHERE MATCH(content) AGAINST('yo'); --  No results ( The reason is the minimum query value problem )

SELECT * FROM t_article WHERE MATCH(content) AGAINST('you'); --  It turns out 

Spatial index

Concept ：

• MySQL stay 5.7 Then support spatial index , Support OpenGIS Geometric data model
• A spatial index is an index of a field of a spatial data type ,MySQL Spatial data types in 4 Kind of , Namely GEOMETRY、POINT、LINESTRING、POLYGON..
• MySQL Use SPATIAL Keyword expansion , Yes, it can be used to create a regular index type syntax to create a spatial index .
• A column that creates a spatial index , It must be declared as NOT NULL.
• Spatial index is less used , Understanding can

type	meaning	explain
Geometry	Spatial data	Any type of space
Point	spot	Coordinate value
LineString	Line	There are a series of points connected
Polygon	polygon	Composed of multiple lines

for example ：

create table shop_info (
  id  int  primary key auto_increment comment 'id',
  shop_name varchar(64) not null comment ' Store name ',
	geom_point geometry not null comment ' Longitude and latitude ',
  spatial key geom_index(geom_point)
);

internals

Concept ：

• Generally speaking, the index itself is very large , It's impossible to store everything in memory , So indexes are often stored on disk as index files .
• In this case , Disk will be generated during index search I/O Consume , Relative to memory access ,I/O How many orders of magnitude higher is the consumption of access , So the most important index to evaluate a data structure as an index is the disk in the search process I/O Progressive complexity of the number of operations .
• let me put it another way , The structure of index should be organized to minimize the number of disks in the process of searching I/O Access times of .

Hash Algorithm

advantage ： Calculated from the value of the field Hash value , Location data is very fast
shortcoming ： No range lookup , Because the values in the hash table are unordered , Cannot compare sizes .

Binary tree and binary balanced tree

Binary tree
advantage ： It is divided into left subtree 、 Right subtree and root node , The left subtree is smaller than the root node , The right subtree is larger than the root node
shortcoming ： It is possible to produce an unbalanced structure similar to a linked list

Balanced binary trees
advantage ：

1. Its left and right subtrees are balanced binary trees
2. The left subtree is smaller than the middle , The right subtree is larger than the middle value
3. The absolute value of the difference between the depth of the left subtree and that of the right subtree does not exceed 1
   shortcoming ：
4. The insertion operation requires rotation
5. Support range query , However, the efficiency of roundabout query is low , For example, the query is larger than 8 Of , Will swing to the parent node 7、10
6. If you store hundreds of pieces of data , The higher the tree is , The slower the query efficiency

BTREE Tree model

At present, most data systems and file systems use B-TREE Or its variants B+TREE As an index structure ,BTREE Structure can effectively solve the problems encountered by previous related algorithms .

BTREE Trees Index application

MyISAM Engine USES B+TREE As an index structure , Leaf node data The domain stores the address of the data record .

Features of index

advantage

• Greatly speed up the data query speed
• When using grouping and sorting for data query , It can significantly reduce the time of grouping and sorting when querying
• Create unique index , It can ensure the uniqueness of each row of data in the database table
• In terms of reference integrity of real data , Can speed up the connection between tables

shortcoming

• Creating and maintaining indexes takes time , And as the amount of data increases , Time will also increase
• Indexes need to occupy disk space
• When adding, deleting or modifying data in the data table , Indexes should also be maintained dynamically , Reduce the speed of dimension

The principle of index creation

• Columns that update frequently should not be indexed
• Don't use indexes for tables with small amount of data
• Fields with a lot of duplicate data should not be set as indexes
• First of all, we should consider where and order by Index the columns involved