How to create an index

How to create an index ？
There are three ways to create an index .

In execution CREATE TABLE Create index

CREATE TABLE user_index2 (
id INT auto_increment PRIMARY KEY,
first_name VARCHAR (16),
last_name VARCHAR (16),
id_card VARCHAR (18),
information text,
KEY name (first_name, last_name),
FULLTEXT KEY (information),
UNIQUE KEY (id_card)
);

Use ALTER TABLE Command to add index .

ALTER TABLE table_name ADD INDEX index_name (column_list);
ALTER TABLE To create a normal index 、UNIQUE Index or PRIMARY KEY Indexes .

among table_name Is the name of the table to be indexed ,column_list Indicate which columns are indexed , Multiple columns are separated by commas .

Index name index_name You can name it yourself , By default ,MySQL A name will be assigned to the first index column . in addition ,ALTER TABLE Allow multiple tables to be changed in a single statement , So you can create multiple indexes at the same time .
Use CREATE INDEX Command to create .

CREATE INDEX index_name ON table_name (column_list);
What to pay attention to when creating indexes ？
Non empty field ： Column should be specified as NOT NULL, Unless you want to store NULL. stay mysql in , Columns with null values are difficult to optimize , Because they make indexes 、 Index statistics and comparison operations are more complex . You should use 0、 A special value or an empty string instead of a null value ;
Take discrete large fields ：（ The degree of difference between the values of variables ） The columns of are placed in front of the union index , Can pass count() Function to view the difference value of a field , The larger the return value, the more unique the value of the field, the higher the discreteness of the field ;
The smaller the index field, the better ： The data storage of the database takes the page as the unit, the more data a page stores IO The greater the data obtained by the operation, the higher the efficiency .
What are the principles of indexing ？
1、 Leftmost prefix matching principle , Very important principle ,mysql It will keep matching to the right until it encounters a range query (>、<、between、like) Just stop matching , such as a = 1 and b = 2 and c > 3 and d = 4 If set up (a,b,c,d) Index of order ,d There is no index , If set up (a,b,d,c) The index of can be used ,a,b,d The order of can be adjusted at will .

2、= and in You can order , such as a = 1 and b = 2 and c = 3 establish (a,b,c) Indexes can be in any order ,mysql The query optimizer will help you optimize it into a form that the index can recognize .

3、 Try to select highly differentiated columns as indexes , The formula of discrimination is count(distinct col)/count(*), Indicates the proportion of fields that do not repeat , The larger the ratio, the fewer records we scan , The only key differentiator is 1, And some states 、 Gender fields may be differentiated in front of big data 0, Then someone might ask , What is the experience value of this ratio ？ Different scenarios , It's also hard to determine , Generally need join We all need to 0.1 above , On average 1 Bar scan 10 Bar record .

4、 The index column cannot participate in the calculation , Keep the column “ clean ”, such as from_unixtime(create_time) = ’2014-05-29’ You can't use indexes , The reason is simple ,b+ All the data stored in the tree are the field values in the data table , But when searching , You need to apply functions to all elements to compare , Obviously it costs too much . So the sentence should be written as create_time = unix_timestamp(’2014-05-29’).

5、 Expand the index as much as possible , Don't create a new index . Let's say it's already in the table a The index of , Now want to add (a,b) The index of , All you need to do is change the original index .

Can index query improve query performance ？
It is usually faster to query data through index than to scan the whole table . But we also have to pay attention to the cost .

Indexes need space to store , It also needs regular maintenance , Whenever a record is added or deleted in a table or an index column is modified , The index itself will also be modified . This means that every recorded I* NSERT,DELETE,UPDATE Will pay more for this 4,5 Secondary disk I/O. Because indexes need extra storage and processing , Those unnecessary indexes will slow down the response time of queries . Using index queries does not necessarily improve query performance , Index range query (INDEX RANGE SCAN) It can be used in two cases :

Search based on a range , In general, the result set returned by a query is less than the number of records in the table 30%.
Search based on non unique index .
When not to index （ Index failure ）？
1、 Use != perhaps <> Cause index to fail
2、 Index invalidation due to type inconsistency
3、 Index invalidation caused by function
Such as ：

SELECT * FROM user WHERE DATE(create_time) = ‘2020-09-03’;
If you use a function in the index column , This is not indexed .

4、 Index invalidation caused by operator
SELECT * FROM user WHERE age - 1 = 20;
If you do a column （+,-,*,/,!）, Then they won't be indexed .

5、OR Index invalidation caused by
SELECT * FROM user WHERE name = ‘ Zhang San ’ OR height = ‘175’;
OR Causes the index to be in a specific situation , Not all OR It's all about invalidating the index , If OR It's connected to the same field , Then the index will not fail , On the contrary, the index is invalid .

6、 Index invalidation caused by fuzzy search
SELECT * FROM user WHERE name LIKE ‘% ice ’;
When % You don't index before matching fields , Put it in the back to go .