Home Database Mysql Tutorial Scalability design tips in MySQL

Scalability design tips in MySQL

Jun 15, 2023 pm 09:27 PM
mysql Scalability design skills

MySQL is a popular open source relational database management system that has continued to evolve and develop since its development in the early 1980s. Today, MySQL has become one of the most popular databases for web applications and is the basis for many companies' core business systems. In order to meet the growing data processing needs, MySQL must ensure its scalability and continue to expand outward without affecting performance.

In this article, we will discuss MySQL’s scalability design techniques, including vertical expansion, horizontal expansion, sharding, etc.

Vertical expansion (vertical split)

Vertical expansion is one of the most commonly used scalability techniques in MySQL, which is achieved by adding more hardware resources (such as CPU, memory, storage) to improve system performance. Vertical scaling allows the database to handle larger data volumes faster and to better support concurrent access.

The disadvantages of vertical expansion are mainly cost and performance limitations. Because the cost of hardware is typically higher than another scaling technique (horizontal scaling), this option may not be practical for many small or medium-sized businesses. In addition, due to the architectural limitations of computer hardware, there is always a bottleneck in the performance improvement of vertical expansion.

Horizontal expansion (horizontal splitting)

Horizontal expansion (also known as horizontal slicing or partitioning) is to increase the availability of the database system by distributing data across multiple computer nodes. A method of scalability. Sharding can significantly improve the throughput and availability of the system, allowing the database to handle a large number of queries and requests without reducing performance.

The main methods of horizontal expansion are replication and partitioning. Replication refers to copying data to different servers to ensure that specific services are accessible on multiple nodes and improve system availability and performance. Partitioning distributes data in different databases according to certain rules, and queries different databases according to different rules to improve system performance.

However, there are some problems with horizontal scaling, such as the cost and inefficiency of cross-node data access. In addition, horizontal expansion requires consideration of some issues at the application level, such as how to allocate data, how to merge query results, etc.

Data Partitioning

Before partitioning data, you need to understand the partitioning methods supported by MySQL so that you can choose the partitioning method that suits your business needs. The main partitioning methods supported by MySQL are as follows:

  1. RANGE (range partitioning)

This method is based on the range partitioning of a certain column. Expression to divide data into different partitions.

  1. LIST (list partitioning)

This method is based on the partitioning of a certain column value list, which divides the data in the table according to the value list of the specified column.

  1. HASH (Hash Partition)

Hash partitioning is to allocate the data in the table to a specified number of partitions. The size of each partition is basically the same. You can Avoid uneven distribution of data.

  1. KEY (key partition)

This method is to partition based on a unique key or primary key. MySQL maps key values ​​into specific partitions, thereby dividing the table into multiple logical partitions.

Database Architecture

When designing a MySQL database for horizontal expansion, its architecture needs to have the ability to expand horizontally. Therefore, it is recommended to design the database architecture as centralized. This means that there can be one or more master nodes that support multiple partitions by replicating from nodes to other nodes.

In this architecture, the master node handles write requests and queries, distributes data to slave nodes, and maintains metadata for the entire system. The slave node is only responsible for responding to read requests and will not affect the verification of whether the data has been successfully modified. Using this centralized architecture, horizontal scalability can be achieved through third-party tools such as MySQL Cluster or Galera Cluster.

Optimizing queries

In MySQL, queries are very important operations, and they account for most of the load on the database server. Therefore, optimizing queries is an important step in improving database performance. The following are some tips for query optimization:

  1. Index table

Using index tables can significantly improve query efficiency. An index table is usually a table sorted based on a certain column (or columns) so that queries have fast access to the query columns.

  1. Avoid using SELECT *

Avoid using SELECT * in queries, because it will obtain all columns and rows in the table, resulting in performance degradation.

  1. Merge query

Combining multiple queries into one query statement can significantly improve the execution effect. Multiple queries can be combined into a single query using JOIN, UNION, or other query operators.

Summary

When designing a MySQL database, scalability is crucial. MySQL provides a variety of scalability design techniques, including vertical expansion, horizontal expansion, data partitioning, etc. It’s important to choose a technique that suits your needs. At the same time, the design of the database architecture is also very important. By implementing some query optimization techniques, you can maximize the performance of your MySQL database.

The above is the detailed content of Scalability design tips in MySQL. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
2 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Repo: How To Revive Teammates
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Hello Kitty Island Adventure: How To Get Giant Seeds
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

PHP's big data structure processing skills PHP's big data structure processing skills May 08, 2024 am 10:24 AM

Big data structure processing skills: Chunking: Break down the data set and process it in chunks to reduce memory consumption. Generator: Generate data items one by one without loading the entire data set, suitable for unlimited data sets. Streaming: Read files or query results line by line, suitable for large files or remote data. External storage: For very large data sets, store the data in a database or NoSQL.

How to optimize MySQL query performance in PHP? How to optimize MySQL query performance in PHP? Jun 03, 2024 pm 08:11 PM

MySQL query performance can be optimized by building indexes that reduce lookup time from linear complexity to logarithmic complexity. Use PreparedStatements to prevent SQL injection and improve query performance. Limit query results and reduce the amount of data processed by the server. Optimize join queries, including using appropriate join types, creating indexes, and considering using subqueries. Analyze queries to identify bottlenecks; use caching to reduce database load; optimize PHP code to minimize overhead.

How to use MySQL backup and restore in PHP? How to use MySQL backup and restore in PHP? Jun 03, 2024 pm 12:19 PM

Backing up and restoring a MySQL database in PHP can be achieved by following these steps: Back up the database: Use the mysqldump command to dump the database into a SQL file. Restore database: Use the mysql command to restore the database from SQL files.

How to insert data into a MySQL table using PHP? How to insert data into a MySQL table using PHP? Jun 02, 2024 pm 02:26 PM

How to insert data into MySQL table? Connect to the database: Use mysqli to establish a connection to the database. Prepare the SQL query: Write an INSERT statement to specify the columns and values ​​to be inserted. Execute query: Use the query() method to execute the insertion query. If successful, a confirmation message will be output.

How to fix mysql_native_password not loaded errors on MySQL 8.4 How to fix mysql_native_password not loaded errors on MySQL 8.4 Dec 09, 2024 am 11:42 AM

One of the major changes introduced in MySQL 8.4 (the latest LTS release as of 2024) is that the "MySQL Native Password" plugin is no longer enabled by default. Further, MySQL 9.0 removes this plugin completely. This change affects PHP and other app

How to use MySQL stored procedures in PHP? How to use MySQL stored procedures in PHP? Jun 02, 2024 pm 02:13 PM

To use MySQL stored procedures in PHP: Use PDO or the MySQLi extension to connect to a MySQL database. Prepare the statement to call the stored procedure. Execute the stored procedure. Process the result set (if the stored procedure returns results). Close the database connection.

How to create a MySQL table using PHP? How to create a MySQL table using PHP? Jun 04, 2024 pm 01:57 PM

Creating a MySQL table using PHP requires the following steps: Connect to the database. Create the database if it does not exist. Select a database. Create table. Execute the query. Close the connection.

The difference between oracle database and mysql The difference between oracle database and mysql May 10, 2024 am 01:54 AM

Oracle database and MySQL are both databases based on the relational model, but Oracle is superior in terms of compatibility, scalability, data types and security; while MySQL focuses on speed and flexibility and is more suitable for small to medium-sized data sets. . ① Oracle provides a wide range of data types, ② provides advanced security features, ③ is suitable for enterprise-level applications; ① MySQL supports NoSQL data types, ② has fewer security measures, and ③ is suitable for small to medium-sized applications.

See all articles