Building a MySQL storage engine for high-speed reads: faster query response times

Building a MySQL storage engine for high-speed reading: faster query response time

Introduction:
Database is one of the core components of modern applications, and MySQL is the most commonly used relational database one. In applications, query response time is a crucial factor because it directly affects user experience and system performance. In order to improve query response time, developers can take a series of optimization measures, such as using a high-speed read MySQL storage engine. This article will introduce how to build a high-speed read MySQL storage engine to achieve faster query response time.

1. Overview:

MySQL storage engine is the core component of the database management system and is responsible for data storage and retrieval. Commonly used MySQL storage engines include InnoDB, MyISAM, MEMORY, etc. Although these storage engines have good performance in their respective application scenarios, their performance may be limited in high concurrent read scenarios.

In order to solve this problem, we can customize a MySQL storage engine for high-speed reading and improve query response time by optimizing the data access method.

2. Design principle:

The core principle of our storage engine is to store data in memory and use reasonable data structures and algorithms for query operations. Based on this principle, we can build a high-speed reading MySQL storage engine through the following steps:

1. Create a memory storage table:

First, we need to Create an in-memory storage table to store data. For example, we create a table named "my_table" with a storage engine of MEMORY.

CREATE TABLE my_table (
   id INT PRIMARY KEY,
   name VARCHAR(50)
) ENGINE=MEMORY;

2. Writing a storage engine plug-in:

Then, we need to write a storage engine plug-in for storing data into memory. The storage engine plug-in is an extension component of MySQL and can be developed according to customized needs. The following is a simple example:

#include <mysql/plugin.h>

struct st_mysql_storage_engine my_storage_engine =
{
   MYSQL_HANDLERTYPE_STORAGE_ENGINE,
   "my_storage_engine",
   NULL,
   NULL
};

mysql_declare_plugin(my_storage_engine)
{
   MYSQL_STORAGE_ENGINE_PLUGIN,
   &my_storage_engine,
   "my_storage_engine",
   "My Storage Engine",
   "1.0",
   "Your Name",
   "Your License",
   NULL,
   NULL,
   NULL,
   NULL
}
mysql_declare_plugin_end;

3. Implement the operation function of the storage engine:

In the plug-in, we need to implement a series of operation functions, including initialization, creation Table, read data, write data, etc. The specific implementation can be optimized according to business needs.

4. Install and enable the plug-in:

Finally, we need to install the written storage engine plug-in into MySQL and enable the plug-in. Add the following configuration to the MySQL configuration file:

[mysqld]
plugin-load=my_storage_engine.so

Then, restart the MySQL service.

3. Performance test:

In order to verify whether our customized storage engine can provide faster query response time, we can conduct a series of performance tests.

First, we can use MySQL's own tool sysbench to generate a large data set and conduct some benchmark tests. For example, we can use the following command to generate a table containing 10 million rows of data:

sysbench --test=/usr/share/sysbench/oltp_read_only.lua --mysql-db=test --mysql-user=root --mysql-password=123456 prepare

Then, we can use the following command to perform read performance testing and test using the custom storage engine and the default storage engine respectively. Situation:

sysbench --test=/usr/share/sysbench/oltp_read_only.lua --mysql-db=test --mysql-user=root --mysql-password=123456 --oltp-tables-count=1 --oltp-table-size=10000000 --num-threads=10000 --oltp-read-only=on run

By comparing the test results, we can evaluate the performance advantages of the custom storage engine.

Conclusion:

By building a MySQL storage engine for high-speed reading, we can achieve faster query response times in high-concurrency reading scenarios. This is very helpful for improving the performance and user experience of your application. However, custom storage engines need to be optimized according to specific business needs and fully tested for performance.

In short, by in-depth understanding of the principles and usage of the MySQL storage engine, we can build a more efficient storage engine, improve the query response time of the database, and thereby improve the performance of the entire application.

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