From the perspective of MySQL design specifications, how should technical students design a database that adapts to high concurrency?

From the perspective of MySQL design specifications, how should technical students design a database that adapts to high concurrency?

Introduction:
In today's Internet era, the database, as the core of data storage and management, carries a large number of concurrent access and high-speed data processing requirements. As one of the most commonly used relational databases, MySQL has become an important technical test for technical students, how to design a reasonable database structure and standardized operations to adapt to high concurrent access scenarios. This article will share with technical students how to design a database suitable for high concurrency from the perspective of MySQL design specifications.

1. Reasonable planning of database structure

1. Table design:
   Reasonable table design is the key to database performance optimization. When designing tables, the following principles should be followed:
2. The complexity of the table should be reduced as much as possible to avoid too many related tables and redundant fields;
3. The selection of primary keys should take high concurrency into consideration For better read and write performance, it is recommended to use auto-incrementing primary keys;
4. Choose data types reasonably to avoid taking up too much storage space;
5. Use indexes appropriately to improve query efficiency.

Sample code:

CREATE TABLE `user` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `username` varchar(255) NOT NULL,
  `password` varchar(255) NOT NULL,
  `email` varchar(255) NOT NULL,
  PRIMARY KEY (`id`),
  UNIQUE KEY `username` (`username`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

2. Index design:
   Index is an important means of database query and sorting, which can effectively improve the speed of data retrieval. When designing indexes, you should pay attention to the following matters:
3. The selection of indexes should take into account the frequency and complexity of queries to avoid excessive indexing;
4. Combined indexes and prefix indexes can reduce index storage. And improve query efficiency;
5. Avoid using too long index fields, and use functions or calculated columns as indexes;
6. For frequently updated tables, it is necessary to reasonably balance the maintenance cost and query performance of the index .

Sample code:

CREATE TABLE `article` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `title` varchar(255) NOT NULL,
  `content` text NOT NULL,
  `author` varchar(255) NOT NULL,
  PRIMARY KEY (`id`),
  KEY `title` (`title`(10))
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

2. Optimize SQL statements

1. Avoid full table scan in query:
   Full table scan is a performance bottleneck One, it will consume a lot of time and system resources. In query statements, you should avoid using fields without indexes for conditional filtering, and instead locate data through appropriate index fields.

Sample code:

-- 查询用户表中用户名为'admin'的记录
SELECT * FROM `user` WHERE `username` = 'admin';
-- 若`username`字段有索引，则查询效率将大幅提高

2. Reasonable use of JOIN query:
   JOIN query is a way of joint query of multiple tables and is often used to obtain the information of related tables. data. When using JOIN queries, you should pay attention to the following matters:
3. Avoid multiple nested JOINs, and you can split complex queries through subqueries or temporary tables;
4. For JOINs on large tables, Query time and resource consumption can be reduced through reasonable paging and limiting the number of query results.

Sample code:

-- 查询文章表中所有文章的作者
SELECT `article`.`title`, `user`.`username`
FROM `article`
JOIN `user` ON `article`.`author_id` = `user`.`id`;
-- 若`author_id`字段有索引，则查询效率将得到保证

3. Set database parameters reasonably

1. Adjust connection pool parameters:
   Connection pool is important for maintaining database connections component, reasonable adjustment of connection pool parameters can improve database performance. When setting the connection pool parameters, you should pay attention to the following matters:
2. Set the appropriate number of initial connections and the maximum number of connections to avoid excessive connections causing pressure on the database;
3. Set the connection idle time and The maximum number of idle connections controls the effective use of connections;
4. Reasonably select the connection pool technology and database driver to ensure the efficiency and stability of the connection pool.

Sample code:

-- C3P0连接池配置示例
c3p0.acquireIncrement=5
c3p0.initialPoolSize=20
c3p0.maxIdleTime=1800
c3p0.maxPoolSize=100

2. Adjust cache parameters:
   Cache is an effective means to improve database performance and can reduce frequent access to disk IO. When setting cache parameters, you should pay attention to the following matters:
3. Set the query cache size reasonably to avoid excessive memory usage;
4. Set the cache expiration time and refresh mechanism to ensure the cached data Update in time;
5. Use cache preheating and asynchronous loading to improve data hit rate and access speed.

Sample code:

-- Ehcache缓存配置示例
<cache name="articleCache"
       maxElementsInMemory="500"
       eternal="true"
       overflowToDisk="false"
       memoryStoreEvictionPolicy="LFU"
       timeToIdleSeconds="3600"
       timeToLiveSeconds="0"/>

Summary:
Designing a database to adapt to high concurrency is a complex and important task, which requires technical students to comprehensively consider the database structure, SQL statements and Database parameters and many other aspects. By properly planning the database structure, optimizing SQL statements, and adjusting database parameters, MySQL's high concurrency processing capabilities can be effectively improved. I hope this article will be helpful to technical students when designing high-concurrency databases.

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