Index - MySQL

Index Overview

Indexes ： Help MySQL Efficient access to data Data structure of ( Orderly ). Out of data , The database system also maintains a data structure that satisfies a specific search algorithm , These data structures are referenced in some way （ Point to ） data , In this way, advanced search algorithms can be implemented on these data structures , This data structure is the index

If we want to implement SQL Statement for ： select * from user where age = 45;

1. No index case
   Without index , You need to scan from the first line , Scan until the last line , We call it Full table scan , Very low performance
2. With an index
   It only takes three scans to find the data , Greatly improve the efficiency of query .

Advantages and disadvantages

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Index structure

MySQL The index of is in Storage engine layer Realized , Different storage engines have different index structures , It mainly includes the following ：

1.Btree Indexes

After inserting the element sorting, if it exceeds , Phase splitting on intermediate elements , Form trees

B-Tree,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, Corresponding 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 .

2. B+tree Indexes

All nodes will appear in the leaf node , And the intermediate element splits upwards

• Green box The framed part , yes Index part , It only plays the role of indexing data , Don't store data .
• The part framed in red , It's the data storage part , Specific data should be stored in its leaf node .

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 .

3. hash Indexes

Hash index is to use a certain hash Algorithm , Convert key values to new hash value , Map to the corresponding slot , Then stored in hash In the table .

characteristic

1. Hash Indexes Can only be used for peer-to-peer comparison (=,in), Range query is not supported （between,>,< ,…）
2. Cannot complete sort operation with index
3. High query efficiency , Usually ( non-existent hash Conflict situation ) It only needs one search , Efficiency is usually higher than B+tree Indexes

Storage engine support
stay MySQL in , Support hash The index is Memory Storage engine . and InnoDB It has adaptive function hash function ,hash The index is
InnoDB The storage engine is based on B+Tree The index is automatically built under specified conditions .

Thinking questions ： Why? InnoDB The storage engine chooses to use B+tree Index structure ?

1. Relative to a binary tree , Fewer levels , High search efficiency ;
2. about B-tree, Whether leaf nodes or non leaf nodes , Data will be saved , This results in fewer key values stored in a page , The pointer decreases , Save a lot of data as well , Can only increase the height of the tree , Resulting in reduced performance ;
3. relative Hash Indexes ,B+tree Support range matching and sorting operation ;

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Index classification

InnoDB In the storage engine , According to the storage form of the index , It can be divided into the following two types ：

Clustered index selection rules :

• If Primary key exists , 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 There is no primary key , Or there is no suitable unique index , be InnoDB Meeting Automatically generate a rowid As a hidden clustered index .

• The data of this row is hung under the leaf node of the clustered index .
• The leaf node of the secondary index is hung with the... Corresponding to the field value Primary key value .

Thinking questions ：
Here are two SQL sentence , The execution efficiency is high ? Why? ?
A. select * from user where id = 10 ;
B. select * from user where name = ‘Arm’ ;
remarks : id Primary key ,name Fields are indexed ;
answer ：
A The execution performance of the statement is higher than B sentence .
because A Statement goes directly to the clustered index , Direct return data . and B The statement needs to query name The secondary index of the field , Then query the clustered index , That is, you need to query back to the table .

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Index creation Syntax

1. Create index

keyword ：create index

create [unique\fulltext] index  Index name  on  Table name  ( Field name 1, Field name 2) ;
//  Indicates the field name to be given to the table 1, Create index 

• unique： Created is unique index
• fulltext： It means to create Full-text index
• No addition Two options indicate that the created is General index

2. Look at the index

show index from table_name ;

View all indexes in the specified table

3. Delete index

drop index index_name on  Table name  ;

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SQL performance optimization

SQL Performance analysis

If you want to optimize performance, you must first know , The execution of those commands is inefficient , Performance analysis is required

MySQL After successful client connection , adopt show [session|global] status The command can provide server status messages
Rest .

• global： Global status information
• session： View the status information of the current conversation

By the following instructions , You can view the INSERT、UPDATE、DELETE、SELECT Frequency of visits ：

show global status like 'Com_______'; # 7 Underscores 

value Value is the number of times the database has executed various commands in the past , According to the execution times of various commands , Make relevant optimization

Slow query log

The slow query log records all execution times that exceed the specified parameters （long_query_time, Company ： second , Default 10 second ） All of the SQL Statement log .

MySQL Slow query log Off by default , We can look at the system variables slow_query_log.

 View the status of the slow query log 
show  variables like 'slow_query_log' ;

Open slow query log

Need to be in MySQL Configuration file for （/etc/my.cnf） The following information is configured in

#  Turn on MySQL Slow log query switch 
slow_query_log=1
#  Set the time of slow log to 2 second ,SQL Statement execution time exceeds 2 second , It will be regarded as slow query , Log slow queries 
long_query_time=2

You need to restart after setting MySQL database

profile（ Check out time-consuming destinations ）

Turn on profile

show profiles Be able to do SQL Optimization helps us understand where the time is spent .
adopt have_profiling Parameters , Be able to see the present MySQL Do you support profile operation ：

1. View the current MySQL Do you support profile operation

 View the current MySQL Do you support profile operation 
select @@have_profiling ;

2. see profile Open or not

select @@profiling ;

3. Turn on profile

set profiling = 1 ;

View the time consumption of all instructions

When we perform a lot select After statement , Want to know this select After the execution instruction of the statement , You can go through show profiles Command to view all the just executed select Statement execution

grammar ：show profiles ;
Query formulation item ：show profile for query Checked items ;

--  Check each one SQL The time-consuming basic situation of 
show profiles;


--  View the specified SQL The time-consuming situation of each stage of the statement 
show profile for query query_id;


--  View specified query_id Of SQL sentence CPU Usage situation 
show profile cpu for query query_id;

explain（ Implementation plan ）

The first few methods only judge by the length of time SQL Performance of , Can't really reflect SQL Performance of
adopt explain View the day SQL Statement execution plan

grammar ： Directly in select Add the keyword before the statement explain / desc, You can query the execution plan of the current statement

explain select  Field list  from  Table name  where  Conditions  ;

Many columns will be queried

Field	meaning
id	select The serial number of the query , Represents execution in a query select Clause or the order of the operation table (id identical , Execution order from top to bottom ;id Different , The bigger the value is. , Execute first )
select_type（ Reference is of little significance ）	Express SELECT The type of , Common values are SIMPLE（ A simple watch , That is, no table join or subquery is used ）、PRIMARY（ Main query , That is, the outer query ）UNION（UNION The second or subsequent query statement in ）、SUBQUERY（SELECT/WHERE Then it contains sub queries ） etc.
type	Express Connection type , performance The connection type from good to bad is NULL、system、const、eq_ref、ref、range、 index、all
possible_key	Displays the indexes that may be applied to this table , One or more .
key	Actual index used , If NULL, No index is used .
key_len	Represents the number of bytes used in the index , This value is the maximum possible length of the index field , It's not the actual length , Without losing accuracy , The shorter the length, the better .
rows	MySQL The number of rows that you think you must execute the query , stay innodb In the engine's table , Is an estimate , It may not always be accurate .
filtered	Represents the number of rows returned as a percentage of the number of rows to be read , filtered The greater the value, the better .

Use of index

The principle of indexing

The leftmost prefix rule

If you index multiple columns （ Joint index ）, Follow the leftmost prefix rule . The leftmost prefix rule refers to The query starts with the leftmost column of the index , And don't skip columns in the index . If you jump a column , The index will be partially invalidated ( The following field index is invalid ).

The leftmost column must exist , stay select It doesn't matter where in

stay tb_user In the table , There is a joint index , This The federated index involves three fields , The order is ：profession,age,status. For the leftmost prefix, the law refers to , When inquiring , Leftmost column , That is to say profession There must be , Otherwise, all indexes will be invalid . And you can't skip a column in the middle , Otherwise, the field index behind the column will be invalidated .
As long as the leftmost field exists , There is no need to consider the order problem

Range queries （> or < The index on the right will be invalidated ）

In the union index , Range query appears (>,<), The column index on the right side of the range query is invalid .
explain select * from tb_user where profession = ' Software Engineering ' and age > 30 and status= '0';

When range queries use > or < when , Let's go , But the length of the index is 49, It indicates that the query range is on the right status Fields are not indexed .
explain select * from tb_user where profession = ' Software Engineering ' and age >= 30 andstatus = '0';

When range queries use >= or <= when , Let's go , But the length of the index is 54, It means that all fields are indexed .

therefore , When business allows , Use as much as possible similar to >= or <= This kind of range query , Avoid using > or <

Index failure

Operation in index column will be invalid

Do not do... On index columns Operation , Index will fail .

stay tb_user In the table , In addition to the union index described earlier , There is also an index , yes phone Single column index of the field .
A. When according to phone When performing equivalent matching query on fields , The index works .
explain select * from tb_user where phone = '17799990015';

B. When according to phone After the function operation of the field , Index failure .
explain select * from tb_user where substring(phone,10,2) = '15';

Strings that are not quoted become invalid

When using string type fields , Without quotes , Index will fail .
Next , We use two sets of examples , Let's look at fields of string type , The difference between single quotation mark and no single quotation mark ：
explain select * from tb_user where profession = ' Software Engineering ' and age = 31 and status = '0';
explain select * from tb_user where profession = ' Software Engineering ' and age = 31 and status = 0;

We will clearly find , If the string is not in single quotation marks , For query results , It doesn't matter , But the database has implicit type conversion , Index will fail .

Fuzzy queries will be invalidated when they appear in the header

If it's just tail blur matching , The index will not fail . If it's a fuzzy head match , Index failure .

Let's mainly take a look at , Fuzzy query ,% Add before keyword , And the influence added after the keyword .

explain select * from tb_user where profession like ' Software %'; It works
explain select * from tb_user where profession like '% engineering '; invalid
explain select * from tb_user where profession like '% work %'; invalid

stay like Fuzzy query , Add the keyword after %, The index can work . And if in the keyword
I added %, The index will fail .

or Only when there is an index in the left and right fields of the connection condition can the index take effect

use or The conditions of separation , If or The columns in the previous condition are indexed , And there's no index in the next column , Then the indexes involved will not be used .

because age No index , So even id、phone There is an index , Indexes will also fail . So you need a needle for age Also index .

then , We can age Field indexing .
After indexing , Let's do the above again SQL sentence , Look at the changes in the implementation plan before and after .

explain select * from tb_user where id = 10 or age = 23;
explain select * from tb_user where phone = '17799990017' or age = 23

because age No index , So even id、phone There is an index , Indexes will also fail . So you need a needle for age Also index .
When or The conditions of connection , When the left and right fields have indexes , The index will take effect .

Data distribution affects

If MySQL Evaluation uses indexes more slowly than full tables , Index is not used .

select * from tb_user where phone >= '17799990005';
select * from tb_user where phone >= '17799990015';

After testing, we found that , same SQL sentence , Only the field values passed in are different , The final implementation plan is also completely different , Why is that ？
Because of MySQL In the query , Will evaluate the efficiency of using the index and the efficiency of full table scanning , If you walk the whole table, scanning is faster , Then abandon the index , Take a full scan . Because the index is used to index a small amount of data , If large quantities of data are returned through index query , It's not as fast as scanning the whole table , At this point, the index will be invalidated .

Next , Let's see is null And is not null Whether the operation takes the index .
Execute the following two statements ：

explain select * from tb_user where profession is null;
explain select * from tb_user where profession is not null;

profession Of null The number of values will affect the query profession Medium null Whether the value is indexed or full table scanned

When inquiring MySQL Will evaluate , Go fast , Or full table scanning is fast , If the full table scan is faster , Then abandon the index and walk the full table scan . therefore ,is null 、is not null Whether to follow the index , We have to analyze the specific situation , It's not fixed .

SQL Tips

SQL Tips , Is an important means to optimize the database , Simply speaking , Is in the SQL Some artificial hints are added to the statement to achieve optimization
The purpose of the operation .

1. use index ： Suggest MySQL Which index to use to complete this query （ It's just advice ,mysql Internal evaluation will be conducted again ）.

explain select * from tb_user use index(idx_user_pro) where profession = ' Software Engineering ';

2. ignore index ： Ignore the specified index .

explain select * from tb_user ignore index(idx_user_pro) where profession = ' Software Engineering ';

3. force index ： Force index .

explain select * from tb_user force index(idx_user_pro) where profession = ' Software Engineering ';

Overlay index

Try to use overlay index , Reduce select *. So what is an 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 .

Prefix index

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

1. grammar ：

create index  Prefix index name  on  Table name ( Field name (n)) ;

by tb_user Tabular email Field , Set the length to 5 Prefix index of .

create index idx_email_5 on tb_user(email(5));

2. Prefix length
   It can be determined according to the selectivity of the index , Selectivity refers to index values that are not repeated （ base ） And the total number of records in the data table , The higher the index selectivity, the higher the query efficiency , The only index selectivity is 1, This is the best index selectivity , Performance is also the best .

select count(distinct email) / count(*) from tb_user ;
select count(distinct substring(email,1,5)) / count(*) from tb_user ;

3. The query process of prefix index