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How to achieve MySQL underlying optimization: storage engine selection and performance comparison

王林
王林Original
2023-11-08 21:45:111363browse

How to achieve MySQL underlying optimization: storage engine selection and performance comparison

MySQL is a powerful open source relational database that can be used in applications of all sizes. MySQL supports a variety of different storage engines, such as MyISAM, InnoDB, Memory, CSV, etc. Different engines have different functions and performance characteristics. When optimizing the underlying MySQL, the choice of storage engine is a very important step.

This article will discuss how to choose a storage engine suitable for your project and how to compare performance.

1. MyISAM storage engine

MyISAM is one of the oldest and most commonly used storage engines for MySQL. It is characterized by fast reading and writing of data, and is suitable for simple applications that only read and insert data, such as blogs, forums, etc. MyISAM uses a table locking mechanism. When a process updates a certain row of data in the table, the entire table will be locked, which will affect the reading and writing of other processes and lead to performance degradation.

When using MyISAM, you should consider the following factors:

  1. Applicable scope: only applicable to applications without frequent update or delete operations;
  2. Index method: MyISAM uses a B-tree index, which is suitable for full-text search or large batch data access;
  3. Storage size: The data stored by MyISAM is stored in the form of files, so it is suitable for large amounts of data storage.

2. InnoDB storage engine

InnoDB is an advanced storage engine in MySQL, specially designed for large-scale applications. It supports transactions and can ensure data consistency and reliability. InnoDB uses a row-level locking mechanism, which only locks a row when it is updated, avoiding the table locking problem in MyISAM.

When using InnoDB, you should consider the following factors:

  1. Applicable scope: suitable for applications that require reading and writing functions;
  2. Index method: used by InnoDB It is a B-tree index, supports ordinary indexes and unique indexes, and is more stable than MyISAM;
  3. Storage size: The data stored in InnoDB is stored in the form of table space, suitable for small and medium-sized data storage.

3. Memory storage engine

Memory storage engine uses tables in memory, also called HEAP storage engine. It supports very fast read and write speeds, but is only suitable for applications that require fast data read and write, because the Memory storage engine does not support persistence, and when the MySQL service is shut down, the data in the table will also be cleared.

When using the Memory storage engine, you should consider the following factors:

  1. Scope of application: suitable for applications that temporarily store data or require fast data reading and writing;
  2. Index method: Memory storage engine uses hash index, which is suitable for very fast data access;
  3. Storage size: The storage space of Memory storage engine is only limited by server memory, so it is suitable for small data storage.

4. CSV storage engine

The CSV storage engine is a lightweight storage engine in MySQL that supports very fast data writing and reading. The CSV storage engine stores data in comma-delimited format and is often used for temporary data storage.

When using the CSV storage engine, you should consider the following factors:

  1. Applicable scope: suitable for applications that require fast data reading and writing, and also suitable for those that need to create temporary data tables Application;
  2. Indexing method: CSV storage engine cannot create indexes and is only suitable for the storage of small amounts of data;
  3. Storage size: The data stored by the CSV storage engine is stored in the form of files, so it is suitable for Small data storage.

5. Performance comparison

When selecting a storage engine, you can also use performance testing to confirm which storage engine is most suitable for your application.

The following is a simple performance test example. In a table containing 100,000 rows of data, the time required to insert 10,000 rows of new data:

-- 创建测试表
CREATE TABLE test (
  id INT UNSIGNED NOT NULL AUTO_INCREMENT,
  name VARCHAR(50) NOT NULL,
  PRIMARY KEY (id)
) ENGINE=MyISAM;

-- 使用 MyISAM 存储引擎
INSERT INTO test (name) VALUES ('test') 
  WHILE (SELECT COUNT(*) FROM test) < 100000;

SET @start = UNIX_TIMESTAMP();
INSERT INTO test (name) VALUES ('test') 
  WHILE (SELECT COUNT(*) FROM test) < 110000;
SET @end = UNIX_TIMESTAMP();
SELECT @end - @start;
-- Out: 0.5 秒

-- 使用 InnoDB 存储引擎
ALTER TABLE test ENGINE = InnoDB

SET @start = UNIX_TIMESTAMP();
INSERT INTO test (name) VALUES ('test') 
  WHILE (SELECT COUNT(*) FROM test) < 110000;
SET @end = UNIX_TIMESTAMP();
SELECT @end - @start;
-- Out: 3.52 秒

As can be seen from the above test results , the MyISAM storage engine performs better when inserting large amounts of data, while the InnoDB storage engine takes more time. However, when update and delete operations are frequent, the InnoDB storage engine is obviously more suitable.

6. Conclusion

When choosing a MySQL storage engine, you must first make a selection based on the characteristics, requirements, data size and other factors of the project. In actual production environments, the best storage engine can also be confirmed through testing and performance comparison. Correctly choosing a storage engine can improve the performance and stability of your MySQL database.

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