Mysql database index study notes

Preface

The author has been studying database indexing recently , So I want to write a blog to record my learning , If there is a mistake , Please point out .

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One 、 Index introduction

1.1 What is the index

The index is a separate 、 Database structure stored on disk , Contains a reference pointer to all records in the data table . Using an index, you can quickly find rows with a specific value in one or more columns , all MySQL All column types can be indexed , Using indexes on related columns is the best way to improve the speed of query operation .

1.2 Advantages and disadvantages of index

advantage ：

• Can improve the efficiency of data retrieval , Reduce the IO cost
• Sort data through index columns , To reduce the CPU Consumption of

Inferiority :

• Take up disk space
• When adding data in the table 、 When deleting and modifying , Index should also be maintained dynamically , This reduces the speed of data maintenance .

1.3 When to use index

• When uniqueness is a characteristic of some kind of data itself , Specify a unique index . Using a unique index ensures the data integrity of the defined column , To improve query speed .
• To sort or group frequently （ That is to say group by or order by operation ） Index on the column of , If there are more than one column to sort , You can build composite indexes on these columns .

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Two 、 Classification of indexes

2.1 Example index

• General index ： General index is MySQL The basic index type in , Allows you to insert duplicate and null values in a column that defines an index
• Unique index requires 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
• Primary key index is a special unique index , No null values are allowed

2.2 Composite index

• Index of multiple field combinations , Only if the left side of these fields is used in the query criteria , Indexes are used . If the intermediate index is not used , Later indexes will also become invalid , When using a composite index, follow the leftmost prefix set

Clustered index selection rules :

• If there is a primary key , A primary key index is a clustered index .
• If there is no primary key , The first unique... Will be used （UNIQUE） Index as clustered index .
• If the table does not have a primary key , Or there is no suitable unique index , be InnoDB It will automatically generate a rowid As a hidden gathering rope
  lead .

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3、 ... and 、 Use of index

3.1 Basic commands for indexing

1. Create index ：

create index  Index name  on  Table name ( Field name ( length ));
alter table  Table name  add index  Index name ( Field name ( length ));

2. Delete index ：

drop index  Index name  on  Table name ;

3. Look at the index :

show index from  Table name 

3.2 Determine whether the index is effective

have access to EXPLAIN Statement to see if the index is in use .
explain select * from Table name where Conditions ( Conditions need to be indexed )

The meaning of each field in the execution plan ：

3.3 Avoid index invalidation

There are several ways , To avoid index failure ：

1. When using composite indexes , Need to follow “ Left most prefix ” principle ;

2. Do nothing on the index column , For example, to calculate 、 function 、 Type conversion , It will cause index invalidation and turn to full table scan ;

3. Try to use overlay index （ Queries that access index columns ）, Reduce select * Overwriting the index can reduce the number of table returns ;

4.MySQL In use is not equal to （!= perhaps <>） Unable to use the index will result in a full table scan ;

5.LIKE Start with a wildcard （%abc）MySQL The index will become invalid and become a full table scan operation ;
for example ：
select * from company where companyName like ‘% Jiangnan leather is long ’;
It can be changed to
select * from company where reverse(companyName) like reverse(‘% Jiangnan leather is long ’);

6. String without single quotation marks will invalidate the index （ An implicit conversion of the index column may have occurred ）;

7. When or The conditions of connection , When the left and right fields have indexes , The index will take effect

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Four 、 Index implementation principle (InnoDB)

stay MySQL In the index structure of , The choice is B+Tree, So what is B+Tree Well ？ Say B+Tree Let's introduce it first B-Tree

B-Tree（B Trees ）,B A tree is a kind of multi fork road scale search tree , Relative to a binary tree ,B Each node of the tree can have multiple branches , That is, multi fork .
At a maximum degree （max-degree） by 5(5 rank ) Of b-tree For example , So this one B Each node of the tree can store up to 4 individual key,5
A pointer to the ：

characteristic ：

• 5 Step B Trees , Each node can store up to 4 individual key, Corresponding 5 A pointer to the .
• Once the node stores key The quantity has arrived 5, Will fission , The intermediate element splits up .
• stay B In the tree , Both non leaf nodes and leaf nodes store data .

B+Tree yes B-Tree Variants , We have a maximum degree （max-degree） by 4（4 rank ） Of b+tree For example , Come and have a look
The structure diagram is shown below ：

In the end, we see ,B+Tree And B-Tree comparison , There are three main differences ：

• All the data will appear in the leaf node .
• Leaf nodes form a one-way linked list .
• Non leaf nodes only serve to index data , The specific data is stored in the leaf node .

MySQL Index data structure for classic B+Tree optimized . In the original B+Tree On the basis of , Add a node pointing to adjacent leaves
Linked list pointer , So we have a sequence pointer B+Tree, Improve the performance of interval access , Conducive to sorting .

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5、 ... and 、 other

5.1 Return to the table for query

First look for data in the secondary index , Find primary key value , Then it is added to the clustered index according to the primary key value , How to get the data , It is called back to table query .

When we execute the following query statement , The specific process is as follows :
1. Because it's based on name Field to query , So first according to name='Arm’ To name Field in the secondary index
look for . But in the secondary index, you can only find Arm The corresponding primary key value 10.

2. Because the data returned by the query is all fields , So at this time , You also need to use the primary key value 10, Find in the clustered index 10 Corresponding records , Finally find 10 The corresponding line row.

3. Finally get the data of this line , Just go back .

5.2 Overlay index

Overlay index means The query uses an index , And the columns that need to be returned , All can be found in this index .

5.3 Prefix index

When the field type is string （varchar,text,longtext etc. ） when , Sometimes you need to index long strings , It will make
The index becomes large , When inquiring , Waste a lot of disk IO, Affecting query efficiency . At this point, you can prefix only part of the string with , build
Vertical index , This can greatly save index space , To improve index efficiency .

create index idx_xxxx on table_name(column(n)) ;

summary

I hope it's lucky