Swoole realizes the design and implementation of high-performance order system

With the continuous development of the e-commerce industry, the performance of the order system has become an increasingly important issue. The traditional PHP MySQL architecture can no longer meet the needs of high-concurrency scenarios. Swoole, as a high-performance network framework based on PHP, is used by more and more companies to build high-performance order systems.

This article will introduce how to use Swoole to implement a high-performance order system. This article consists of two parts: First, system design, including order life cycle, MySQL table design, data flow, etc. The second is system implementation, including the construction of Swoole services, coroutines and concurrent programming, asynchronous IO, etc.

1. System design

1. Order life cycle

The life cycle of an order includes four states: unpaid, paid, completed, and canceled. Each status is handled differently, so the order system needs to be optimized for different statuses when designing it.

The unpaid status includes order creation, order placement, payment and other operations. In this state, the system only records order information and does not consider changes or reads of data. The paid status and completed status are handled in a similar way, mainly including changes in order status, inventory deductions, and transaction record recording, etc. In the canceled status, the order needs to be refunded or canceled, and issues such as insufficient inventory need to be resolved.

2. MySQL table design

In order to ensure the high performance of the order system, we need to optimize the data table. Mainly consider the following aspects:

1. Sub-database and sub-table

In order to avoid single-table data being too large and affecting system performance, you can divide orders according to business needs. The table is divided into multiple sub-tables or sub-repositories according to certain rules, such as by order time, or by factors such as customer location.

2. Table structure optimization

In table structure design, we can use the following methods to optimize:

• Choose appropriate data Type reduces data storage space;
• Set indexes appropriately to speed up data query;
• Avoid using a large number of text fields and use foreign key links to solve some related data storage problems.

3. Data flow

In the order system, different data flow methods can affect the performance of the system to a certain extent. We can optimize in the following ways:

1. Message Queue

For high-concurrency order systems, message queue is used to asynchronously send order data to the queue, by Queue processing of order data can effectively relieve system pressure and increase system concurrent processing volume. At the same time, optimization operations such as merging and deduplication of order data can be performed.

2. Asynchronous processing

Using asynchronous processing can effectively improve the processing efficiency of the order system and avoid system performance degradation caused by waiting for IO operations. In actual development, the coroutines and asynchronous IO operations provided by Swoole can be used to implement asynchronous processing.

2. System implementation

1. Construction of Swoole service

With the Server class provided by Swoole, we can easily build a high-performance server that supports asynchronous IO operations. . When building the Swoole service, you need to pay attention to the following points:

1. Set the callback function

In the Swoole service, we need to register the callback function. Client requests, including client connections, data reception, task processing, etc. Each callback function corresponds to different events and needs to be registered according to actual business needs.

2. Set the number of coroutines

In the Swoole service, we can improve system performance by setting the number of coroutines. Coroutines are lightweight threads that can save system resource overhead and improve system concurrent processing capabilities. It needs to be adjusted according to the actual situation of the system.

2. Coroutines and concurrent programming

In the Swoole service, coroutines are a very important programming method. Through the coroutine method, the execution efficiency of the program can be made higher, and some shortcomings of traditional multi-threaded programming can be avoided. In actual programming, you need to pay attention to the following points:

1. Communication between coroutines

When data interaction is required between multiple coroutines, you can use The communication pipeline and message queue provided by Swoole are implemented. When cooperating between multiple coroutines to process tasks, the context switching overhead of the coroutines needs to be considered to avoid performance degradation caused by excessive switching.

2. Coroutine exception handling

In coroutine programming, you need to pay attention to exception handling to avoid the program crashing due to unexpected errors. This can be implemented using the exception mechanism provided by PHP.

3. Asynchronous IO

When processing Swoole data, asynchronous IO needs to be used for performance optimization. For example, operations such as reading files and sending network requests can be implemented using asynchronous IO. When performing asynchronous IO operations, you need to pay attention to callback functions, timeout mechanisms, error handling, etc.

Summary

This article introduces how to use Swoole to realize the design and implementation of a high-performance order system. When designing the system, you need to consider aspects such as order cycle, MySQL table design, and data flow, and choose different optimization solutions for different scenarios. In system implementation, you need to pay attention to the callback function of the Server class, coroutines and concurrent programming, asynchronous IO, etc. By using the Swoole framework, the performance of the system can be greatly improved to meet the needs of a high-concurrency order placing system.

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