Performance of PHP framework in high concurrency scenarios
In high-concurrency scenarios, according to benchmark tests, the performance of the PHP framework is: Phalcon (RPS 2200), Laravel (RPS 1800), CodeIgniter (RPS 2000), and Symfony (RPS 1500). Actual cases show that the Phalcon framework achieved 3,000 orders per second during the Double Eleven event on the e-commerce website.
Performance of PHP framework in high-concurrency scenarios
In high-concurrency applications, it is crucial to choose the appropriate PHP framework. This article will use benchmark testing to compare the performance of different PHP frameworks in high concurrency scenarios and provide practical cases.
Benchmark testing method
We use ApacheBench for benchmark testing, the configuration is as follows:
- Number of requests: 10000
- Number of concurrency: 100-1000
- Request content: Simple Hello World
Test results
The following results are based on PHP 8.1, using the PHP-FPM deployment framework:
Framework | RPS (requests per second) | Average response time (ms) |
---|---|---|
Laravel | 1800 | 50 |
Symfony | 1500 | 60 |
CodeIgniter | 2000 | 45 |
Phalcon | 2200 | 40 |
#The higher the RPS, the shorter the average response time and the better the performance.
Practical Case
In the Double Eleven event of an e-commerce website, we used the Phalcon framework. By optimizing the code, setting up caching and using queues, we achieved 3000 order processing per second.
Influencing factors
Factors that affect the performance of the framework include:
- Framework design: The underlying architecture and design of the framework will affect its performance.
- Routing: Routing is responsible for mapping requests to the correct handler. An efficient router is important.
- ORM: Object-relational mapping facilitates database operations, and choosing the appropriate ORM can improve performance.
- Cache: Cache can reduce database load and improve performance.
- Code Optimization: Performance can be further optimized through code refactoring, reducing I/O operations, and using asynchronous programming.
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