How to optimize MySQL?

Mysql The optimization of the

The performance of a database depends on a number of factors at the database level , For example, the design of tables 、 Query statements and database configuration settings . These software architectures lead to hardware level CPU and I/O operation , We must reduce CPU and IO To improve efficiency as much as possible ;

Optimize at the database level ----

1, Consider whether the table structure is reasonable ?---- Three principles of paradigm
Whether the data type is appropriate
2, Whether the correct index is set ?---- The index duplicate field should not have

3, For each table Storage engine Whether it is used properly ?( especially , Select transactional storage engine （ Such as innodb） Or non transactional storage engine （ Such as mysiam） It can be very important for performance and scalability ),

4, Whether the appropriate locking strategy is used ---- Table locks / Row lock so that the database can operate concurrently ;

5, Whether the size of all memory areas used for caching is appropriate ?

This can be adjusted mysql Size of the buffer in (bufferpoolmoren 64M), But not too big ;

Hardware level optimization ---->>

1, disk , It takes a while for the disk to find data , Usually in 10ms about , So theoretically every second 100 Search , Optimizing seek time is to distribute data to multiple disks ;

Or maybe Replacing high-performance disks can reduce disk seek time For example, using a solid-state drive ;
2,cpu Speed , Replace with high performance cpu It can also speed up processing ;
3, Memory bandwidth , When CPU The data required exceeds CPU When caching the data it can hold , Main memory bandwidth will become a bottleneck ;

Hardware level is not in the scope of this discussion

Optimize sql sentence

1, Query statements are often used sql sentence , Key considerations for optimizing queries :

• To make slow queries faster ----->> Check if the index can be added , Set the index for the column in the clause ;
  The more indexes, the better , Consider that indexes also take up disk space ;
• For queries that reference different tables using joins, foreign keys, and so on , have access to explain Statement to determine which indexes are used ;
• Isolate and optimize any part of the query
• Minimize the number of full table scans , Especially for large tables
• The statistical information of the table system can be kept up to date by regularly analyzing the table , Optimize sql Implementation plan of (select etc. )
• If a performance problem cannot be easily solved by a basic rule , You can use EXPLAIN analysis sql sentence And adjust the index 、 Clause 、 Join clauses, etc. to investigate the internal details of a particular query .
• adjustment MySQL be used for Size and properties of the cached memory area . Through effective use Buffer pool 、 Key cache and MySQL The query cache , Repeated queries run faster , Because the results will be retrieved from memory at the second and subsequent times .

Mysql Optimize the details

Usually, the frequency of reading data is higher than that of writing data , So the first one should consider optimization select sentence ;

Data sheet design :
Data type optimization ---->>>

1, Data types that take up less are usually better ( Because more data can be read at a time , This means that it usually takes less to read the same amount of data CPU Processing cycle ;
For example, use mysql Instead of using strings to store dates ;
Store in integers ip Instead of strings ,(mysql There is a function in that can put IP Convert to integer INET_ATON())
2, Simple is good , Avoid using null
3, Avoid using null, stay mysql in nul=null The result is null, However, sometimes the user fails to fill in the information , At this point, we can specify the data as ’’ Empty string instead of null

4, Set the primary key properly
5, Rational use of paradigms and paradigms ( According to the actual situation , Data redundancy can be properly provided )
6, Character set selection
7, Choice of storage engine
8

Optimize select sentence

1, Solve the problem of slow query
First, check the slow query log , Find out the cause of slow query ;

Generally, slow query optimization needs to start from Start with the index ------ Try adding an index to the field you want ;
For the use of Join and foreign key And other functions refer to queries of different tables , Indexing is especially important .

2, Cache commonly used data ;

adjustment MySQL The size and properties of the memory area used for caching . By using buffer pools effectively 、 Key cache and MySQL The query cache , Repeated queries run faster ,

3, Reduce the number of full table scans ;

Try to use triggers cont ,index And so on , Avoid back table queries ;

4, Use regularly analyze table Statement keep statistics up to date ;

where Clause optimization

Remove unnecessary brackets :

((a AND b) AND c OR (((a AND b) AND (c AND d))))
-> (a AND b AND c) OR (a AND b AND c AND d)

1, Index merge optimization

The index merge access method retrieves rows with multiple range scans , And combine the results into one . This access method only merges index scans from a single table , Instead of merging scans across multiple tables . Merge can generate union of its underlying scans 、 Intersection or intersection Union .

Let's look at a table first ----->>

mysql> select * from test ;
+----+----------+------+
| id | name     | age  |
+----+----------+------+
|  2 |  Zhang San 2    | NULL |
|  4 |  Zhang San 4    | NULL |
|  6 |  Li Si      | NULL |
|  7 |  Xiao Qi      | NULL |
|  8 |  Wang Wu      | NULL |
| 10 |  Li Si 10   | NULL |
| 13 |  Zhao 13     | NULL |
| 18 |  Wang Wu 18   | NULL |
+----+----------+------+
8 rows in set (0.00 sec)
# The first table , There are primary keys and indexes name;
mysql> show create table test \G
*************************** 1. row ***************************
       Table: test
Create Table: CREATE TABLE `test` (
  `id` int NOT NULL,
  `name` varchar(8) COLLATE utf8mb4_general_ci DEFAULT NULL,
  `age` int DEFAULT NULL,
  PRIMARY KEY (`id`),
  KEY `nameindex` (`name`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_general_ci
1 row in set (0.00 sec)

#  The other table   Only primary keys 
mysql> show create table test3 \G
*************************** 1. row ***************************
       Table: test3
Create Table: CREATE TABLE `test3` (
  `id` int NOT NULL,
  `name` varchar(8) COLLATE utf8mb4_general_ci DEFAULT NULL,
  `age` int DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_general_ci
1 row in set (0.01 sec)

Next, let's query id Less than 10 and name Is Xiaoqi The data of , How to improve query efficiency ??

The first table ----->>

mysql> explain select * from test where  id <10 and name=" Xiao Qi " \
G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: test
   partitions: NULL
         type: index_merge
possible_keys: PRIMARY,nameindex
          key: nameindex,PRIMARY
      key_len: 39,4
          ref: NULL
         rows: 1
     filtered: 100.00
        Extra: Using intersect(nameindex,PRIMARY); Using where
1 row in set, 1 warning (0.00 sec)

The cases given on the official website —>>

SELECT * FROM tbl_name WHERE key1 = 10 OR key2 = 20;

SELECT * FROM tbl_name
  WHERE (key1 = 10 OR key2 = 20) AND non_key = 30;

SELECT * FROM t1, t2
  WHERE (t1.key1 IN (1,2) OR t1.key2 LIKE 'value%')
  AND t2.key1 = t1.some_col;

SELECT * FROM t1, t2
  WHERE t1.key1 = 1
  AND (t2.key1 = t1.some_col OR t2.key2 = t1.some_col2);